The Cloud and Aerosol Research Group (CARG) of the University of Washington participated in the SAFARI-2000 Dry Season Aircraft campaign with their Convair-580 research aircraft. This campaign covered five countries in southern Africa from 10 August through 18 September 2000. Various types of measurements were obtained on the thirty-one research flights of the Convair-580 in SAFARI-2000, to study their relationships to simultaneous measurements from satellites (particularly Terra), other research aircraft, and SAFARI-2000 ground-based measurements and activities.
The Cloud and Aerosol Research Group (CARG) of the University of Washington participated in the SAFARI-2000 Dry Season Aircraft campaign with their Convair-580 research aircraft. This campaign covered five countries in southern Africa from 10 August through 18 September 2000. Various types of measurements were obtained on the thirty-one research flights of the Convair-580 in SAFARI-2000, to study their relationships to simultaneous measurements from satellites (particularly Terra), other research aircraft, and SAFARI-2000 ground-based measurements and activities.
ABSTRACT: The Cloud and Aerosol Research Group (CARG) of the University of Washington participated in the SAFARI-2000 Dry Season Aircraft campaign with their Convair-580 research aircraft. This campaign covered five countries in southern Africa from 10 August through 18 September 2000. Various types of measurements were obtained on the thirty-one research flights of the Convair-580 in SAFARI-2000, to study their relationships to simultaneous measurements from satellites (particularly Terra), other research aircraft, and SAFARI-2000 ground-based measurements and activities.
The Microwave InfraRed Algorithm (MIRA) is used to produce an imagery data set of daily mean rain rates at 0.1 degree spatial resolution over southern Africa for the period 1993-2001. MIRA combines passive microwave (PMW) from the Special Sensor Microwave/Imager (SSM/I) on board the DMSP F10 and F14 satellites at a resolution of 0.5 degrees and infrared (IR) data from the Meteosat 4, 5, 6, and 7 satellites in 2-hour slots at a resolution of 5 km. This approach accounts for the limitations of both data types in estimating precipitation. Rainfall estimates are produced at the high spatial and temporal frequency of the IR data using rainfall information from the PMW data. An IR/rain rate relationship, variable in space and time, is derived from coincident observations of IR and PMW rain rate (accumulated over a calibration domain) using the probability matching method. The IR/rain rate relationship is then applied to IR imagery at full temporal resolution. The results presented here are the daily means of those derived rain rates at 0.1 degree spatial resolution.The rainfall data sets are flat binary images with no headers. They are compressed band sequential (bsq) files that contain all of the daily images for the given year. Each image is an array of 401 lines, each with 341 binary floating-point numbers, containing rainfall at 0.1 degree resolution for the area 10 to 50 degrees longitude and 0 to -34 degrees latitude. The number of band sequential images in each annual file and the associated dates can be found in the file MIRA_data_dates.csv.
The Microwave InfraRed Algorithm (MIRA) is used to produce an imagery data set of daily mean rain rates at 0.1 degree spatial resolution over southern Africa for the period 1993-2001. MIRA combines passive microwave (PMW) from the Special Sensor Microwave/Imager (SSM/I) on board the DMSP F10 and F14 satellites at a resolution of 0.5 degrees and infrared (IR) data from the Meteosat 4, 5, 6, and 7 satellites in 2-hour slots at a resolution of 5 km. This approach accounts for the limitations of both data types in estimating precipitation. Rainfall estimates are produced at the high spatial and temporal frequency of the IR data using rainfall information from the PMW data. An IR/rain rate relationship, variable in space and time, is derived from coincident observations of IR and PMW rain rate (accumulated over a calibration domain) using the probability matching method. The IR/rain rate relationship is then applied to IR imagery at full temporal resolution. The results presented here are the daily means of those derived rain rates at 0.1 degree spatial resolution.The rainfall data sets are flat binary images with no headers. They are compressed band sequential (bsq) files that contain all of the daily images for the given year. Each image is an array of 401 lines, each with 341 binary floating-point numbers, containing rainfall at 0.1 degree resolution for the area 10 to 50 degrees longitude and 0 to -34 degrees latitude. The number of band sequential images in each annual file and the associated dates can be found in the file MIRA_data_dates.csv.
ABSTRACT: The Microwave InfraRed Algorithm (MIRA) is used to produce an imagery data set of daily mean rain rates at 0.1 degree spatial resolution over southern Africa for the period 1993-2001. MIRA combines passive microwave (PMW) from the Special Sensor Microwave/Imager (SSM/I) on board the DMSP F10 and F14 satellites at a resolution of 0.5 degrees and infrared (IR) data from the Meteosat 4, 5, 6, and 7 satellites in 2-hour slots at a resolution of 5 km. This approach accounts for the limitations of both data types in estimating precipitation. Rainfall estimates are produced at the high spatial and temporal frequency of the IR data using rainfall information from the PMW data. An IR/rain rate relationship, variable in space and time, is derived from coincident observations of IR and PMW rain rate (accumulated over a calibration domain) using the probability matching method. The IR/rain rate relationship is then applied to IR imagery at full temporal resolution. The results presented here are the daily means of those derived rain rates at 0.1 degree spatial resolution.The rainfall data sets are flat binary images with no headers. They are compressed band sequential (bsq) files that contain all of the daily images for the given year. Each image is an array of 401 lines, each with 341 binary floating-point numbers, containing rainfall at 0.1 degree resolution for the area 10 to 50 degrees longitude and 0 to -34 degrees latitude. The number of band sequential images in each annual file and the associated dates can be found in the file MIRA_data_dates.csv.
This data set contains daily rainfall totals (mm) from Mongu, in the Western Province of Zambia. The data were collected with a British standard 5 inch diameter rain gauge in a yard 30 m away from the Meteorological Department building near the Mongu Airport (north of downtown and approximately 20 km from the Kataba Local Forest where the permanent 30 m Mongu tower site is located). Rainfall readings were taken by ZMD staff each morning at 06:00 GMT. These data form the official government rainfall record for Mongu.The data files consist of 3 files, one for each year (July to Jun). Each files contains monthly columns with totals for each day of the month as well as a monthly total. The data files are stored as ASCII text files in comma-separated-value (csv) format.
This data set contains daily rainfall totals (mm) from Mongu, in the Western Province of Zambia. The data were collected with a British standard 5 inch diameter rain gauge in a yard 30 m away from the Meteorological Department building near the Mongu Airport (north of downtown and approximately 20 km from the Kataba Local Forest where the permanent 30 m Mongu tower site is located). Rainfall readings were taken by ZMD staff each morning at 06:00 GMT. These data form the official government rainfall record for Mongu.The data files consist of 3 files, one for each year (July to Jun). Each files contains monthly columns with totals for each day of the month as well as a monthly total. The data files are stored as ASCII text files in comma-separated-value (csv) format.
ABSTRACT: This data set contains daily rainfall totals (mm) from Mongu, in the Western Province of Zambia. The data were collected with a British standard 5 inch diameter rain gauge in a yard 30 m away from the Meteorological Department building near the Mongu Airport (north of downtown and approximately 20 km from the Kataba Local Forest where the permanent 30 m Mongu tower site is located). Rainfall readings were taken by ZMD staff each morning at 06:00 GMT. These data form the official government rainfall record for Mongu.The data files consist of 3 files, one for each year (July to Jun). Each files contains monthly columns with totals for each day of the month as well as a monthly total. The data files are stored as ASCII text files in comma-separated-value (csv) format.
The data set consists of a southern African subset of the ISRIC-WISE global data set of derived soil properties. The World Inventory of Soil Emission Potentials (WISE) database currently contains data for over 4300 soil profiles collected mostly between 1950 and 1995.
The data set consists of a southern African subset of the ISRIC-WISE global data set of derived soil properties. The World Inventory of Soil Emission Potentials (WISE) database currently contains data for over 4300 soil profiles collected mostly between 1950 and 1995.
ABSTRACT: The data set consists of a southern African subset of the ISRIC-WISE global data set of derived soil properties. The World Inventory of Soil Emission Potentials (WISE) database currently contains data for over 4300 soil profiles collected mostly between 1950 and 1995.
This data set consists of a southern African subset of the Global Land One-Kilometer Base Elevation (GLOBE) digital elevation model (DEM) data in both ASCII GRID and binary image file formats.
This data set consists of a southern African subset of the Global Land One-Kilometer Base Elevation (GLOBE) digital elevation model (DEM) data in both ASCII GRID and binary image file formats.
ABSTRACT: This data set consists of a southern African subset of the Global Land One-Kilometer Base Elevation (GLOBE) digital elevation model (DEM) data in both ASCII GRID and binary image file formats.
The recently generated MODIS burned area product over southern Africa for the month of September 2000 was used to calculate regional biomass burning emissions from grassland and woodland fires for a number of trace gases and particulates at 1 km spatial resolution. A dynamic regional fuel load model developed for southern Africa in support of SAFARI 2000 fire emissions modeling is used to compute spatially explicit southern Africa fuel load data.
The recently generated MODIS burned area product over southern Africa for the month of September 2000 was used to calculate regional biomass burning emissions from grassland and woodland fires for a number of trace gases and particulates at 1 km spatial resolution. A dynamic regional fuel load model developed for southern Africa in support of SAFARI 2000 fire emissions modeling is used to compute spatially explicit southern Africa fuel load data.
ABSTRACT: The recently generated MODIS burned area product over southern Africa for the month of September 2000 was used to calculate regional biomass burning emissions from grassland and woodland fires for a number of trace gases and particulates at 1 km spatial resolution. A dynamic regional fuel load model developed for southern Africa in support of SAFARI 2000 fire emissions modeling is used to compute spatially explicit southern Africa fuel load data.
Aerial photography from the NASA ER-2 high-altitude aircraft was collected to provide detailed and spatially extensive documentation over parts of the SAFARI study area. The ER-2 aerial photography consists of 3,046 color-infrared (IR) transparencies collected during the SAFARI 2000 Dry Season Aircraft Campaign in August and September of 2000. ORNL DAAC has archived scanned subsets of the ER-2 aerial photography. In addition, 515 image frames have been scanned from copies of the original level-0 ER-2 aerial photography by the University of the Witwatersrand (Wits), in Pretoria, South Africa. ORNL DAAC has archived subsets of the available imagery from ARC and Wits.
Aerial photography from the NASA ER-2 high-altitude aircraft was collected to provide detailed and spatially extensive documentation over parts of the SAFARI study area. The ER-2 aerial photography consists of 3,046 color-infrared (IR) transparencies collected during the SAFARI 2000 Dry Season Aircraft Campaign in August and September of 2000. ORNL DAAC has archived scanned subsets of the ER-2 aerial photography. In addition, 515 image frames have been scanned from copies of the original level-0 ER-2 aerial photography by the University of the Witwatersrand (Wits), in Pretoria, South Africa. ORNL DAAC has archived subsets of the available imagery from ARC and Wits.
ABSTRACT: Aerial photography from the NASA ER-2 high-altitude aircraft was collected to provide detailed and spatially extensive documentation over parts of the SAFARI study area. The ER-2 aerial photography consists of 3,046 color-infrared (IR) transparencies collected during the SAFARI 2000 Dry Season Aircraft Campaign in August and September of 2000. ORNL DAAC has archived scanned subsets of the ER-2 aerial photography. In addition, 515 image frames have been scanned from copies of the original level-0 ER-2 aerial photography by the University of the Witwatersrand (Wits), in Pretoria, South Africa. ORNL DAAC has archived subsets of the available imagery from ARC and Wits.
Improved vegetation distribution and emission data for Africa south of the equator were developed for the Southern African Regional Science Initiative (SAFARI 2000) and combined with biogenic volatile organic compound (BVOC) emission measurements to estimate BVOC emissions for the southern African region. BVOC emissions were estimated for southern Africa on a monthly basis over a one-year period by combining GIS layers of vegetation, LAI, and climate with a biogenic emissions model, GLOBEIS (Guenther et al, 1993; Guenther, 1999).
Improved vegetation distribution and emission data for Africa south of the equator were developed for the Southern African Regional Science Initiative (SAFARI 2000) and combined with biogenic volatile organic compound (BVOC) emission measurements to estimate BVOC emissions for the southern African region. BVOC emissions were estimated for southern Africa on a monthly basis over a one-year period by combining GIS layers of vegetation, LAI, and climate with a biogenic emissions model, GLOBEIS (Guenther et al, 1993; Guenther, 1999).
ABSTRACT: Improved vegetation distribution and emission data for Africa south of the equator were developed for the Southern African Regional Science Initiative (SAFARI 2000) and combined with biogenic volatile organic compound (BVOC) emission measurements to estimate BVOC emissions for the southern African region. BVOC emissions were estimated for southern Africa on a monthly basis over a one-year period by combining GIS layers of vegetation, LAI, and climate with a biogenic emissions model, GLOBEIS (Guenther et al, 1993; Guenther, 1999).
With modern computer power now capable of making mesoscale model output available in real time in the operational environment, increased attention has been given to utilizing these models in order to improve the forecasting ability of meteorologists. The National Centers for Environmental Prediction (NCEP) has developed a step-mountain eta coordinate model generally known as the ETA Model.This NCEP ETA data assimilation and prediction system (see Mesinger et al., 1988; Black, 1994) has been used by the South African Weather Bureau/Service (SAWS) to provide operational regional forecast guidance since November 1993. SAWS used this model to produce the basic meteorological data for the SAFARI project. The SAWS ETA model is a hydrostatic model with a horizontal grid spacing of approximately 48 km and 38 vertical levels, with layer depths that range from 20 m in the planetary boundary layer to 2 km at 50 mb. There have been several major ETA Model upgrades at SAWS: in March 1996, August 1998, November 1999, and August 2001.
With modern computer power now capable of making mesoscale model output available in real time in the operational environment, increased attention has been given to utilizing these models in order to improve the forecasting ability of meteorologists. The National Centers for Environmental Prediction (NCEP) has developed a step-mountain eta coordinate model generally known as the ETA Model.This NCEP ETA data assimilation and prediction system (see Mesinger et al., 1988; Black, 1994) has been used by the South African Weather Bureau/Service (SAWS) to provide operational regional forecast guidance since November 1993. SAWS used this model to produce the basic meteorological data for the SAFARI project. The SAWS ETA model is a hydrostatic model with a horizontal grid spacing of approximately 48 km and 38 vertical levels, with layer depths that range from 20 m in the planetary boundary layer to 2 km at 50 mb. There have been several major ETA Model upgrades at SAWS: in March 1996, August 1998, November 1999, and August 2001.
ABSTRACT: With modern computer power now capable of making mesoscale model output available in real time in the operational environment, increased attention has been given to utilizing these models in order to improve the forecasting ability of meteorologists. The National Centers for Environmental Prediction (NCEP) has developed a step-mountain eta coordinate model generally known as the ETA Model.This NCEP ETA data assimilation and prediction system (see Mesinger et al., 1988; Black, 1994) has been used by the South African Weather Bureau/Service (SAWS) to provide operational regional forecast guidance since November 1993. SAWS used this model to produce the basic meteorological data for the SAFARI project. The SAWS ETA model is a hydrostatic model with a horizontal grid spacing of approximately 48 km and 38 vertical levels, with layer depths that range from 20 m in the planetary boundary layer to 2 km at 50 mb. There have been several major ETA Model upgrades at SAWS: in March 1996, August 1998, November 1999, and August 2001.
The U.S. Agency for International Development (USAID) Famine Early Warning System (FEWS) has been supporting the production of 10-day Rainfall Estimate (RFE) data for Africa since 1995. The FEWSNET project was established with the goal of reducing the incidence of drought- or flood-induced famine by providing decision makers with timely and accurate information on conditions that may require intervention. RFE data for continental Africa for 1999, 2000, and 2001 were downloaded the from the African Data Dissemination Service (ADDS) site and were subset for southern Africa by the SAFARI 2000 data group. The RFE 1.0 algorithm, implemented from 1995 to 2000, uses an interpolation method to combine Meteosat and Global Telecommunication System (GTS) data, and warm cloud information for the 10-day estimations. The 30-minute geostationary Meteosat-7 satellite infrared data are used to estimate convective rainfall from areas where cloud top temperatures are less than 235K. The RFE 2.0 algorithm, implemented as of January 1, 2001, uses additional techniques to better estimate precipitation while continuing the use of cold cloud duration and station rainfall data.
The U.S. Agency for International Development (USAID) Famine Early Warning System (FEWS) has been supporting the production of 10-day Rainfall Estimate (RFE) data for Africa since 1995. The FEWSNET project was established with the goal of reducing the incidence of drought- or flood-induced famine by providing decision makers with timely and accurate information on conditions that may require intervention. RFE data for continental Africa for 1999, 2000, and 2001 were downloaded the from the African Data Dissemination Service (ADDS) site and were subset for southern Africa by the SAFARI 2000 data group. The RFE 1.0 algorithm, implemented from 1995 to 2000, uses an interpolation method to combine Meteosat and Global Telecommunication System (GTS) data, and warm cloud information for the 10-day estimations. The 30-minute geostationary Meteosat-7 satellite infrared data are used to estimate convective rainfall from areas where cloud top temperatures are less than 235K. The RFE 2.0 algorithm, implemented as of January 1, 2001, uses additional techniques to better estimate precipitation while continuing the use of cold cloud duration and station rainfall data.
ABSTRACT: The U.S. Agency for International Development (USAID) Famine Early Warning System (FEWS) has been supporting the production of 10-day Rainfall Estimate (RFE) data for Africa since 1995. The FEWSNET project was established with the goal of reducing the incidence of drought- or flood-induced famine by providing decision makers with timely and accurate information on conditions that may require intervention. RFE data for continental Africa for 1999, 2000, and 2001 were downloaded the from the African Data Dissemination Service (ADDS) site and were subset for southern Africa by the SAFARI 2000 data group. The RFE 1.0 algorithm, implemented from 1995 to 2000, uses an interpolation method to combine Meteosat and Global Telecommunication System (GTS) data, and warm cloud information for the 10-day estimations. The 30-minute geostationary Meteosat-7 satellite infrared data are used to estimate convective rainfall from areas where cloud top temperatures are less than 235K. The RFE 2.0 algorithm, implemented as of January 1, 2001, uses additional techniques to better estimate precipitation while continuing the use of cold cloud duration and station rainfall data.
As part of the SAFARI 2000), the University of Montana participated in both ground-based and airborne campaigns during the southern African dry season of 2000 to measure trace gas emissions from biofuel production and use and savanna fires, respectively. During the airborne campaign, stable and reactive trace gases were measured over southern Africa with an airborne Fourier transform infrared spectroscopy (AFTIR) onboard the University of Washington Convair-580 research aircraft in August-September of 2000. The measurements included vertical profiles of CO2, CO, H2O, and CH4 up to 5.5 km on 6 occasions above instrumented ground sites and below the TERRA satellite and ER-2 high-flying research aircraft as well as trace gas emissions from ten African savanna fires. These measurements are the first broad characterization of the most abundant trace gases in nascent smoke from African savanna fires (i.e., including oxygen- and nitrogen-containing species).
As part of the SAFARI 2000), the University of Montana participated in both ground-based and airborne campaigns during the southern African dry season of 2000 to measure trace gas emissions from biofuel production and use and savanna fires, respectively. During the airborne campaign, stable and reactive trace gases were measured over southern Africa with an airborne Fourier transform infrared spectroscopy (AFTIR) onboard the University of Washington Convair-580 research aircraft in August-September of 2000. The measurements included vertical profiles of CO2, CO, H2O, and CH4 up to 5.5 km on 6 occasions above instrumented ground sites and below the TERRA satellite and ER-2 high-flying research aircraft as well as trace gas emissions from ten African savanna fires. These measurements are the first broad characterization of the most abundant trace gases in nascent smoke from African savanna fires (i.e., including oxygen- and nitrogen-containing species).
ABSTRACT: As part of the SAFARI 2000), the University of Montana participated in both ground-based and airborne campaigns during the southern African dry season of 2000 to measure trace gas emissions from biofuel production and use and savanna fires, respectively. During the airborne campaign, stable and reactive trace gases were measured over southern Africa with an airborne Fourier transform infrared spectroscopy (AFTIR) onboard the University of Washington Convair-580 research aircraft in August-September of 2000. The measurements included vertical profiles of CO2, CO, H2O, and CH4 up to 5.5 km on 6 occasions above instrumented ground sites and below the TERRA satellite and ER-2 high-flying research aircraft as well as trace gas emissions from ten African savanna fires. These measurements are the first broad characterization of the most abundant trace gases in nascent smoke from African savanna fires (i.e., including oxygen- and nitrogen-containing species).
Data from the Tracing Architecture and Radiation of Canopies (TRAC) instrument were processed to determine the fraction of intercepted photosynthetically active radiation (FPAR) at the EOS Validation Core Site in Kataba Local Forest, approximately 20 km south of Mongu, Zambia. Measurements began in 1999 and continued into 2002, with measurements collected about every month. TRAC contains three pyranometers sensitive to PAR wavelengths, with two sensors upward looking and one downward looking. The TRAC instrument was carried along three parallel transects, each 750 m long and spaced 250 m apart, about 0.7 m off the ground on clear days near midday. The sensors measured PAR at 32 Hz, resulting in a horizontal sampling interval of about 1.7 cm (Privette et al., 2002). Each transect was divided into 25 m segments, and Fpar values, with date/time stamp, are reported for each segment. The length and spacing of the transects were chosen to sample an area large enough to be representative of a 1 km MODIS pixel.  PAR transmittance values were determined from the upward viewing pyranometers on the TRAC instrument. Due to the large gaps in the canopy, incident PAR was estimated from the TRAC data as 95% of the maximum PAR transmittance value for each transect. The FPAR values of all the observations were averaged to give segment-average FPAR, and segment average FPAR values were averaged to give transect-average FPAR.The data file is stored as an ASCII text file, in comma-separated-value (csv) format, with column headers.
Data from the Tracing Architecture and Radiation of Canopies (TRAC) instrument were processed to determine the fraction of intercepted photosynthetically active radiation (FPAR) at the EOS Validation Core Site in Kataba Local Forest, approximately 20 km south of Mongu, Zambia. Measurements began in 1999 and continued into 2002, with measurements collected about every month. TRAC contains three pyranometers sensitive to PAR wavelengths, with two sensors upward looking and one downward looking. The TRAC instrument was carried along three parallel transects, each 750 m long and spaced 250 m apart, about 0.7 m off the ground on clear days near midday. The sensors measured PAR at 32 Hz, resulting in a horizontal sampling interval of about 1.7 cm (Privette et al., 2002). Each transect was divided into 25 m segments, and Fpar values, with date/time stamp, are reported for each segment. The length and spacing of the transects were chosen to sample an area large enough to be representative of a 1 km MODIS pixel.  PAR transmittance values were determined from the upward viewing pyranometers on the TRAC instrument. Due to the large gaps in the canopy, incident PAR was estimated from the TRAC data as 95% of the maximum PAR transmittance value for each transect. The FPAR values of all the observations were averaged to give segment-average FPAR, and segment average FPAR values were averaged to give transect-average FPAR.The data file is stored as an ASCII text file, in comma-separated-value (csv) format, with column headers.
ABSTRACT: Data from the Tracing Architecture and Radiation of Canopies (TRAC) instrument were processed to determine the fraction of intercepted photosynthetically active radiation (FPAR) at the EOS Validation Core Site in Kataba Local Forest, approximately 20 km south of Mongu, Zambia. Measurements began in 1999 and continued into 2002, with measurements collected about every month. TRAC contains three pyranometers sensitive to PAR wavelengths, with two sensors upward looking and one downward looking. The TRAC instrument was carried along three parallel transects, each 750 m long and spaced 250 m apart, about 0.7 m off the ground on clear days near midday. The sensors measured PAR at 32 Hz, resulting in a horizontal sampling interval of about 1.7 cm (Privette et al., 2002). Each transect was divided into 25 m segments, and Fpar values, with date/time stamp, are reported for each segment. The length and spacing of the transects were chosen to sample an area large enough to be representative of a 1 km MODIS pixel.  PAR transmittance values were determined from the upward viewing pyranometers on the TRAC instrument. Due to the large gaps in the canopy, incident PAR was estimated from the TRAC data as 95% of the maximum PAR transmittance value for each transect. The FPAR values of all the observations were averaged to give segment-average FPAR, and segment average FPAR values were averaged to give transect-average FPAR.The data file is stored as an ASCII text file, in comma-separated-value (csv) format, with column headers.
This data set consists of a southern Africa subset of the Global Distribution of Freshwater Wetlands database 1-degree data and is available in ASCII GRID and binary image file formats.
This data set consists of a southern Africa subset of the Global Distribution of Freshwater Wetlands database 1-degree data and is available in ASCII GRID and binary image file formats.
ABSTRACT: This data set consists of a southern Africa subset of the Global Distribution of Freshwater Wetlands database 1-degree data and is available in ASCII GRID and binary image file formats.
Domestic biomass fuels (biofuels) are estimated to be the second largest source of carbon emissions from global biomass burning. Wood and charcoal provide approximately 90% and 10% of domestic energy in tropical Africa, respectively. As part of the Southern Africa Regional Science Initiative (SAFARI 2000), the University of Montana participated in both ground-based and airborne campaigns during the southern African dry season of 2000 to measure trace gas emissions from biofuel production and use and savanna fires, respectively.
Domestic biomass fuels (biofuels) are estimated to be the second largest source of carbon emissions from global biomass burning. Wood and charcoal provide approximately 90% and 10% of domestic energy in tropical Africa, respectively. As part of the Southern Africa Regional Science Initiative (SAFARI 2000), the University of Montana participated in both ground-based and airborne campaigns during the southern African dry season of 2000 to measure trace gas emissions from biofuel production and use and savanna fires, respectively.
ABSTRACT: Domestic biomass fuels (biofuels) are estimated to be the second largest source of carbon emissions from global biomass burning. Wood and charcoal provide approximately 90% and 10% of domestic energy in tropical Africa, respectively. As part of the Southern Africa Regional Science Initiative (SAFARI 2000), the University of Montana participated in both ground-based and airborne campaigns during the southern African dry season of 2000 to measure trace gas emissions from biofuel production and use and savanna fires, respectively.
The Global Burned Area 2000 initiative (GBA2000) was launched by the Global Vegetation Mapping Unit of the Joint Research Centre of the European Commission, in partnership with several other institutions, to develop reliable and quantitative information on the global magnitude and spatial distribution of biomass burning. The objective of GBA2000 was to produce a map of the areas burned globally for the year 2000, using the medium resolution satellite imagery provided by the SPOT-VEGETATION (VGT) system and to derive statistics of area burned per type of vegetation cover. A subset of the global GBA20000 map was prepared for SAFARI 2000 to map the area burned in sub-Saharan Africa during 2000 on a monthly basis using VGT imagery at 1 km spatial resolution. Burned areas were identified with a classification tree, relying only on the near-infrared channel of VGT. The data used in this work are in the S1 daily synthesis format, i.e. the data are radiometrically calibrated, precisely geo-located, and corrected for atmospheric effects.The data are binary image files of area burned, BSQ format in geographic projection.  There is one file for each month of 2000 and one file for all of the year 2000. There is also a comma-delimited ASCII text file that provides geographic coordinates (latitude and longitude) of the center of each pixel indicated as a burned area for all of 2000.
The Global Burned Area 2000 initiative (GBA2000) was launched by the Global Vegetation Mapping Unit of the Joint Research Centre of the European Commission, in partnership with several other institutions, to develop reliable and quantitative information on the global magnitude and spatial distribution of biomass burning. The objective of GBA2000 was to produce a map of the areas burned globally for the year 2000, using the medium resolution satellite imagery provided by the SPOT-VEGETATION (VGT) system and to derive statistics of area burned per type of vegetation cover. A subset of the global GBA20000 map was prepared for SAFARI 2000 to map the area burned in sub-Saharan Africa during 2000 on a monthly basis using VGT imagery at 1 km spatial resolution. Burned areas were identified with a classification tree, relying only on the near-infrared channel of VGT. The data used in this work are in the S1 daily synthesis format, i.e. the data are radiometrically calibrated, precisely geo-located, and corrected for atmospheric effects.The data are binary image files of area burned, BSQ format in geographic projection.  There is one file for each month of 2000 and one file for all of the year 2000. There is also a comma-delimited ASCII text file that provides geographic coordinates (latitude and longitude) of the center of each pixel indicated as a burned area for all of 2000.
ABSTRACT: The Global Burned Area 2000 initiative (GBA2000) was launched by the Global Vegetation Mapping Unit of the Joint Research Centre of the European Commission, in partnership with several other institutions, to develop reliable and quantitative information on the global magnitude and spatial distribution of biomass burning. The objective of GBA2000 was to produce a map of the areas burned globally for the year 2000, using the medium resolution satellite imagery provided by the SPOT-VEGETATION (VGT) system and to derive statistics of area burned per type of vegetation cover. A subset of the global GBA20000 map was prepared for SAFARI 2000 to map the area burned in sub-Saharan Africa during 2000 on a monthly basis using VGT imagery at 1 km spatial resolution. Burned areas were identified with a classification tree, relying only on the near-infrared channel of VGT. The data used in this work are in the S1 daily synthesis format, i.e. the data are radiometrically calibrated, precisely geo-located, and corrected for atmospheric effects.The data are binary image files of area burned, BSQ format in geographic projection.  There is one file for each month of 2000 and one file for all of the year 2000. There is also a comma-delimited ASCII text file that provides geographic coordinates (latitude and longitude) of the center of each pixel indicated as a burned area for all of 2000.
This data set consists of a southern African subset of the Global Historical Climatology Network (GHCN) Version 1 database. All stations with the following bounding coordinates are included in this subset: 5W - 60E and 5N - 35S. There are three files available, one each for precipitation, temperature, and pressure data. Within this subset the oldest data date from 1874 and the most recent from 1990.
This data set consists of a southern African subset of the Global Historical Climatology Network (GHCN) Version 1 database. All stations with the following bounding coordinates are included in this subset: 5W - 60E and 5N - 35S. There are three files available, one each for precipitation, temperature, and pressure data. Within this subset the oldest data date from 1874 and the most recent from 1990.
ABSTRACT: This data set consists of a southern African subset of the Global Historical Climatology Network (GHCN) Version 1 database. All stations with the following bounding coordinates are included in this subset: 5W - 60E and 5N - 35S. There are three files available, one each for precipitation, temperature, and pressure data. Within this subset the oldest data date from 1874 and the most recent from 1990.
This data set consists of a southern Africa subset of the Global Historical Climatology Network (GHCN) Version 2 database.  All stations with the following bounding coordinates are included in this subset:  5W - 60E and 5N - 35S.
This data set consists of a southern Africa subset of the Global Historical Climatology Network (GHCN) Version 2 database.  All stations with the following bounding coordinates are included in this subset:  5W - 60E and 5N - 35S.
ABSTRACT: This data set consists of a southern Africa subset of the Global Historical Climatology Network (GHCN) Version 2 database.  All stations with the following bounding coordinates are included in this subset:  5W - 60E and 5N - 35S.
The Global Precipitation Climatology Project (GPCP) is an international project designed to provide improved long-record estimates of precipitation over the globe. The general approach is to combine the precipitation information available from several sources into a final merged product that takes advantage of the strengths of each data type. The GPCP has promoted the development of an analysis procedure for blending the various estimates together to produce the necessary global gridded precipitation fields. The currently operational procedure is based on Huffman et al. (1995) and has been used to produce the GPCP Version 2 Combined Precipitation Data Set, covering the period January 1979 through the present. The primary product in the Version 2 data set is a combined observation-only data set, that is, a gridded analysis based on gauge measurements and satellite estimates of rainfall.
The Global Precipitation Climatology Project (GPCP) is an international project designed to provide improved long-record estimates of precipitation over the globe. The general approach is to combine the precipitation information available from several sources into a final merged product that takes advantage of the strengths of each data type. The GPCP has promoted the development of an analysis procedure for blending the various estimates together to produce the necessary global gridded precipitation fields. The currently operational procedure is based on Huffman et al. (1995) and has been used to produce the GPCP Version 2 Combined Precipitation Data Set, covering the period January 1979 through the present. The primary product in the Version 2 data set is a combined observation-only data set, that is, a gridded analysis based on gauge measurements and satellite estimates of rainfall.
ABSTRACT: The Global Precipitation Climatology Project (GPCP) is an international project designed to provide improved long-record estimates of precipitation over the globe. The general approach is to combine the precipitation information available from several sources into a final merged product that takes advantage of the strengths of each data type. The GPCP has promoted the development of an analysis procedure for blending the various estimates together to produce the necessary global gridded precipitation fields. The currently operational procedure is based on Huffman et al. (1995) and has been used to produce the GPCP Version 2 Combined Precipitation Data Set, covering the period January 1979 through the present. The primary product in the Version 2 data set is a combined observation-only data set, that is, a gridded analysis based on gauge measurements and satellite estimates of rainfall.
Kruger National Park (KNP) was established in 1898 to protect wildlife on nearly 2 million hectares of the South African Lowveld. Savanna fires are common in the South African Lowveld during the dry season. The two primary sources of fire ignition, historically and currently, are human activity and lightning. This data set contains a record of all fires observed in the Kruger National Park for each of the 10 fire years from 1992 to 2001. The data were compiled from various sources, including old fire records in hardcopy and vector form, as well as satellite imagery.
Kruger National Park (KNP) was established in 1898 to protect wildlife on nearly 2 million hectares of the South African Lowveld. Savanna fires are common in the South African Lowveld during the dry season. The two primary sources of fire ignition, historically and currently, are human activity and lightning. This data set contains a record of all fires observed in the Kruger National Park for each of the 10 fire years from 1992 to 2001. The data were compiled from various sources, including old fire records in hardcopy and vector form, as well as satellite imagery.
ABSTRACT: Kruger National Park (KNP) was established in 1898 to protect wildlife on nearly 2 million hectares of the South African Lowveld. Savanna fires are common in the South African Lowveld during the dry season. The two primary sources of fire ignition, historically and currently, are human activity and lightning. This data set contains a record of all fires observed in the Kruger National Park for each of the 10 fire years from 1992 to 2001. The data were compiled from various sources, including old fire records in hardcopy and vector form, as well as satellite imagery.
This southern African subset of the Global Hydrographic data set (GGHYDRO) Release 2.2 is organized into 19 files containing terrain type, stream frequency counts, major drainage basins, main features of the cryosphere surface, and ice/water runoff per year for the entire Earth's surface at a spatial resolution of 1-degree longitude by 1-degree latitude. The data are provided in both ASCII GRID and binary image file formats.
This southern African subset of the Global Hydrographic data set (GGHYDRO) Release 2.2 is organized into 19 files containing terrain type, stream frequency counts, major drainage basins, main features of the cryosphere surface, and ice/water runoff per year for the entire Earth's surface at a spatial resolution of 1-degree longitude by 1-degree latitude. The data are provided in both ASCII GRID and binary image file formats.
ABSTRACT: This southern African subset of the Global Hydrographic data set (GGHYDRO) Release 2.2 is organized into 19 files containing terrain type, stream frequency counts, major drainage basins, main features of the cryosphere surface, and ice/water runoff per year for the entire Earth's surface at a spatial resolution of 1-degree longitude by 1-degree latitude. The data are provided in both ASCII GRID and binary image file formats.
As part of the 3rd Intensive Campaign of SAFARI 2000, the South African Weather Bureau Aerocommander, JRA, flew 19 missions, for a total of 28 separate flights conducted between August 15th and September 7th, 2000.  JRA worked closely with the other Aerocommander, JRA, and was dedicated to the measurement of trace gas and aerosol properties.  A suite of trace analyzers (for O3, SO2, CO and NO), laser aerosol probes and atmospheric probes were present for all flights.  Other instruments and sampling units present for some of the flights included, a nephelometer (Elias), CO flasks (Novelli) for MOPITT validation purposes, and VOC canisters for the collection and characterization of volatile organic compounds present over various land surface types.
As part of the 3rd Intensive Campaign of SAFARI 2000, the South African Weather Bureau Aerocommander, JRA, flew 19 missions, for a total of 28 separate flights conducted between August 15th and September 7th, 2000.  JRA worked closely with the other Aerocommander, JRA, and was dedicated to the measurement of trace gas and aerosol properties.  A suite of trace analyzers (for O3, SO2, CO and NO), laser aerosol probes and atmospheric probes were present for all flights.  Other instruments and sampling units present for some of the flights included, a nephelometer (Elias), CO flasks (Novelli) for MOPITT validation purposes, and VOC canisters for the collection and characterization of volatile organic compounds present over various land surface types.
ABSTRACT: As part of the 3rd Intensive Campaign of SAFARI 2000, the South African Weather Bureau Aerocommander, JRA, flew 19 missions, for a total of 28 separate flights conducted between August 15th and September 7th, 2000.  JRA worked closely with the other Aerocommander, JRA, and was dedicated to the measurement of trace gas and aerosol properties.  A suite of trace analyzers (for O3, SO2, CO and NO), laser aerosol probes and atmospheric probes were present for all flights.  Other instruments and sampling units present for some of the flights included, a nephelometer (Elias), CO flasks (Novelli) for MOPITT validation purposes, and VOC canisters for the collection and characterization of volatile organic compounds present over various land surface types.
As part of the 3rd Intensive Campaign of SAFARI 2000, the South African Weather Bureau Aerocommander, JRB, flew 19 missions, for a total of 28 separate flights conducted between August 15th and September 7th, 2000.  JRB worked closely with the other Aerocommander, JRA, and was dedicated to the measurement of trace gas and aerosol properties.  A suite of trace analyzers (for O3, SO2, CO and NO), laser aerosol probes and atmospheric probes were present for all flights.  Other instruments and sampling units present for some of the flights included, a nephelometer (Elias), CO flasks (Novelli) for MOPITT validation purposes, and VOC canisters for the collection and characterization of volatile organic compounds present over various land surface types.
As part of the 3rd Intensive Campaign of SAFARI 2000, the South African Weather Bureau Aerocommander, JRB, flew 19 missions, for a total of 28 separate flights conducted between August 15th and September 7th, 2000.  JRB worked closely with the other Aerocommander, JRA, and was dedicated to the measurement of trace gas and aerosol properties.  A suite of trace analyzers (for O3, SO2, CO and NO), laser aerosol probes and atmospheric probes were present for all flights.  Other instruments and sampling units present for some of the flights included, a nephelometer (Elias), CO flasks (Novelli) for MOPITT validation purposes, and VOC canisters for the collection and characterization of volatile organic compounds present over various land surface types.
ABSTRACT: As part of the 3rd Intensive Campaign of SAFARI 2000, the South African Weather Bureau Aerocommander, JRB, flew 19 missions, for a total of 28 separate flights conducted between August 15th and September 7th, 2000.  JRB worked closely with the other Aerocommander, JRA, and was dedicated to the measurement of trace gas and aerosol properties.  A suite of trace analyzers (for O3, SO2, CO and NO), laser aerosol probes and atmospheric probes were present for all flights.  Other instruments and sampling units present for some of the flights included, a nephelometer (Elias), CO flasks (Novelli) for MOPITT validation purposes, and VOC canisters for the collection and characterization of volatile organic compounds present over various land surface types.
Short-term measurements of carbon dioxide, water, and energy fluxes were collected at four locations along a mean annual precipitation gradient in southern Africa during the SAFARI 2000 wet (growing) season campaign of 2000. The purpose of this research was to determine how observed vegetation-atmosphere exchange properties are functionally related to long-term climatic conditions.
Short-term measurements of carbon dioxide, water, and energy fluxes were collected at four locations along a mean annual precipitation gradient in southern Africa during the SAFARI 2000 wet (growing) season campaign of 2000. The purpose of this research was to determine how observed vegetation-atmosphere exchange properties are functionally related to long-term climatic conditions.
ABSTRACT: Short-term measurements of carbon dioxide, water, and energy fluxes were collected at four locations along a mean annual precipitation gradient in southern Africa during the SAFARI 2000 wet (growing) season campaign of 2000. The purpose of this research was to determine how observed vegetation-atmosphere exchange properties are functionally related to long-term climatic conditions.
The Multi-angle Imaging SpectroRadiometer (MISR) Validation team was deployed to the Sua Pan salt playa in the Magkadigkadi region of Botswana during the SAFARI 2000 Dry Season Aircraft Campaign to collect various data sets for validating the MISR LAI/FPAR algorithm. Ground measurements of leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR) were made using the LAI-2000 plant canopy analyzer and Sunfleck PAR ceptometer, respectively, during focused periods from August 20 to August 28, 2000 at a dry grassland site adjacent to the Sua Pan. The 1 km by 1 km sampling grid was a homogeneous, relatively dense grassland, with a height of 20-100 cm and two prevalent grass types, Odyssea paucinervis and Sporobolus spicatus. Associated reflectance measurements were made with the PARABOLA and ASD instruments (Helmlinger et al., 2004a; 2004b).The data files contain measurements of LAI and PAR reflectance and transmission and a description of sky conditions during the sampling periods. With one exception, all measurements were made under clear sky conditions.  PAR data were measured only on the transect scale while LAI are provided at both pixel and transect scales. PAR readings were performed at 93 transect sample points, and LAI readings were performed at 135 (93 transect and 42 subgrid) sample points. Each file also contains mean LAI and PAR values. The data files are ASCII tables, in comma-separated-value format.
The Multi-angle Imaging SpectroRadiometer (MISR) Validation team was deployed to the Sua Pan salt playa in the Magkadigkadi region of Botswana during the SAFARI 2000 Dry Season Aircraft Campaign to collect various data sets for validating the MISR LAI/FPAR algorithm. Ground measurements of leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR) were made using the LAI-2000 plant canopy analyzer and Sunfleck PAR ceptometer, respectively, during focused periods from August 20 to August 28, 2000 at a dry grassland site adjacent to the Sua Pan. The 1 km by 1 km sampling grid was a homogeneous, relatively dense grassland, with a height of 20-100 cm and two prevalent grass types, Odyssea paucinervis and Sporobolus spicatus. Associated reflectance measurements were made with the PARABOLA and ASD instruments (Helmlinger et al., 2004a; 2004b).The data files contain measurements of LAI and PAR reflectance and transmission and a description of sky conditions during the sampling periods. With one exception, all measurements were made under clear sky conditions.  PAR data were measured only on the transect scale while LAI are provided at both pixel and transect scales. PAR readings were performed at 93 transect sample points, and LAI readings were performed at 135 (93 transect and 42 subgrid) sample points. Each file also contains mean LAI and PAR values. The data files are ASCII tables, in comma-separated-value format.
ABSTRACT: The Multi-angle Imaging SpectroRadiometer (MISR) Validation team was deployed to the Sua Pan salt playa in the Magkadigkadi region of Botswana during the SAFARI 2000 Dry Season Aircraft Campaign to collect various data sets for validating the MISR LAI/FPAR algorithm. Ground measurements of leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR) were made using the LAI-2000 plant canopy analyzer and Sunfleck PAR ceptometer, respectively, during focused periods from August 20 to August 28, 2000 at a dry grassland site adjacent to the Sua Pan. The 1 km by 1 km sampling grid was a homogeneous, relatively dense grassland, with a height of 20-100 cm and two prevalent grass types, Odyssea paucinervis and Sporobolus spicatus. Associated reflectance measurements were made with the PARABOLA and ASD instruments (Helmlinger et al., 2004a; 2004b).The data files contain measurements of LAI and PAR reflectance and transmission and a description of sky conditions during the sampling periods. With one exception, all measurements were made under clear sky conditions.  PAR data were measured only on the transect scale while LAI are provided at both pixel and transect scales. PAR readings were performed at 93 transect sample points, and LAI readings were performed at 135 (93 transect and 42 subgrid) sample points. Each file also contains mean LAI and PAR values. The data files are ASCII tables, in comma-separated-value format.
The Boston University team collected several data sets along the Kalahari Transect during the SAFARI 2000 wet season field campaign from March 3rd to March 18th, 2000, to support the validation of the MODIS LAI/FPAR algorithm. Ground measurements of LAI, FPAR, leaf hemispherical reflectance, leaf hemispherical transmittance, and canopy transmittance were made using a LAI-2000 plant canopy analyzer, an AccuPAR ceptometer, a LiCor 1800-12S External Integrating Sphere (LI-1800) portable spectroradiometer, and an ASD handheld spectroradiometer. LAI data are provided in this data set. LAI was intensively measured at 4 different sites in Botswana -- Pandamatenga, Maun, Okwa River, and Tshane (from north to south) -- where vegetation types range from moist closed woodlands to arid sparsely-shrub-covered grasslands.
The Boston University team collected several data sets along the Kalahari Transect during the SAFARI 2000 wet season field campaign from March 3rd to March 18th, 2000, to support the validation of the MODIS LAI/FPAR algorithm. Ground measurements of LAI, FPAR, leaf hemispherical reflectance, leaf hemispherical transmittance, and canopy transmittance were made using a LAI-2000 plant canopy analyzer, an AccuPAR ceptometer, a LiCor 1800-12S External Integrating Sphere (LI-1800) portable spectroradiometer, and an ASD handheld spectroradiometer. LAI data are provided in this data set. LAI was intensively measured at 4 different sites in Botswana -- Pandamatenga, Maun, Okwa River, and Tshane (from north to south) -- where vegetation types range from moist closed woodlands to arid sparsely-shrub-covered grasslands.
ABSTRACT: The Boston University team collected several data sets along the Kalahari Transect during the SAFARI 2000 wet season field campaign from March 3rd to March 18th, 2000, to support the validation of the MODIS LAI/FPAR algorithm. Ground measurements of LAI, FPAR, leaf hemispherical reflectance, leaf hemispherical transmittance, and canopy transmittance were made using a LAI-2000 plant canopy analyzer, an AccuPAR ceptometer, a LiCor 1800-12S External Integrating Sphere (LI-1800) portable spectroradiometer, and an ASD handheld spectroradiometer. LAI data are provided in this data set. LAI was intensively measured at 4 different sites in Botswana -- Pandamatenga, Maun, Okwa River, and Tshane (from north to south) -- where vegetation types range from moist closed woodlands to arid sparsely-shrub-covered grasslands.
The UMD 1-degree Global Land Cover product was produced by researchers at the Laboratory for Global Remote Sensing Studies (LGRSS) at UMD.  The product is based on Advanced Very High Resolution Radiometer (AVHRR) maximum monthly composites for 1987 of Normalized Difference Vegetation Index (NDVI) values at approximately 8-km resolution, averaged to one-by-one degree resolution. This coarse-resolution data set was used as the basis for a supervised classification of eleven cover types that broadly represent the major biomes of the world.
The UMD 1-degree Global Land Cover product was produced by researchers at the Laboratory for Global Remote Sensing Studies (LGRSS) at UMD.  The product is based on Advanced Very High Resolution Radiometer (AVHRR) maximum monthly composites for 1987 of Normalized Difference Vegetation Index (NDVI) values at approximately 8-km resolution, averaged to one-by-one degree resolution. This coarse-resolution data set was used as the basis for a supervised classification of eleven cover types that broadly represent the major biomes of the world.
ABSTRACT: The UMD 1-degree Global Land Cover product was produced by researchers at the Laboratory for Global Remote Sensing Studies (LGRSS) at UMD.  The product is based on Advanced Very High Resolution Radiometer (AVHRR) maximum monthly composites for 1987 of Normalized Difference Vegetation Index (NDVI) values at approximately 8-km resolution, averaged to one-by-one degree resolution. This coarse-resolution data set was used as the basis for a supervised classification of eleven cover types that broadly represent the major biomes of the world.
This data set consists of a southern African subset of the 1-km Global Land Cover Data Set Derived from AVHRR developed at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland. Both ASCII data and binary image files are available.
This data set consists of a southern African subset of the 1-km Global Land Cover Data Set Derived from AVHRR developed at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland. Both ASCII data and binary image files are available.
ABSTRACT: This data set consists of a southern African subset of the 1-km Global Land Cover Data Set Derived from AVHRR developed at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland. Both ASCII data and binary image files are available.
This data set consists of a southern African subset of the University of Maryland (UMD) 8-km Global Land Cover product in ASCII GRID and binary image files formats.
This data set consists of a southern African subset of the University of Maryland (UMD) 8-km Global Land Cover product in ASCII GRID and binary image files formats.
ABSTRACT: This data set consists of a southern African subset of the University of Maryland (UMD) 8-km Global Land Cover product in ASCII GRID and binary image files formats.
This data set contains Global Positioning System (GPS) imprinted landscape photographs at 100-m intervals along the Large Grid Transects at Kalahari Transect sites in Botswana and at measurement sites in Kataba Forest, Mongu, Zambia, and in the vicinity of the Skukuza flux tower site in Kruger National Park, South Africa. The Kalahari sites visited were Pandamatenga, Maun, Okwa Valley, and Tshane. There are about 30 pictures per site.  In a related study, vegetation cover and composition were measured at various locations along the Kalahari Transect and trends in major vegetative cover, including species types and richness, were recorded (Ringrose and Matheson, 2004). The photographs are intended to aid in the interpretation of other data sets, and can be used to suggest canopy height, gap fraction, grass, soil, and sky conditions. The photographs are provided as JPEG images.
This data set contains Global Positioning System (GPS) imprinted landscape photographs at 100-m intervals along the Large Grid Transects at Kalahari Transect sites in Botswana and at measurement sites in Kataba Forest, Mongu, Zambia, and in the vicinity of the Skukuza flux tower site in Kruger National Park, South Africa. The Kalahari sites visited were Pandamatenga, Maun, Okwa Valley, and Tshane. There are about 30 pictures per site.  In a related study, vegetation cover and composition were measured at various locations along the Kalahari Transect and trends in major vegetative cover, including species types and richness, were recorded (Ringrose and Matheson, 2004). The photographs are intended to aid in the interpretation of other data sets, and can be used to suggest canopy height, gap fraction, grass, soil, and sky conditions. The photographs are provided as JPEG images.
ABSTRACT: This data set contains Global Positioning System (GPS) imprinted landscape photographs at 100-m intervals along the Large Grid Transects at Kalahari Transect sites in Botswana and at measurement sites in Kataba Forest, Mongu, Zambia, and in the vicinity of the Skukuza flux tower site in Kruger National Park, South Africa. The Kalahari sites visited were Pandamatenga, Maun, Okwa Valley, and Tshane. There are about 30 pictures per site.  In a related study, vegetation cover and composition were measured at various locations along the Kalahari Transect and trends in major vegetative cover, including species types and richness, were recorded (Ringrose and Matheson, 2004). The photographs are intended to aid in the interpretation of other data sets, and can be used to suggest canopy height, gap fraction, grass, soil, and sky conditions. The photographs are provided as JPEG images.
Data from the Tracing Radiation and Architecture of Canopies (TRAC) instrument were collected at five sites along the International Geosphere-Biosphere Programme (IGBP) Kalahari Transect, including Mongu in Zambia and Pandamatenga, Maun, Okwa River Crossing, and Tshane in Botswana, during the 2000 wet season field campaign (March-April) of SAFARI 2000. At the Mongu site, TRAC measurements began in August of 1999 and continued beyond the 2000 wet season field campaign, about every month for the rest of 2000. The TRAC instrument contains pyranometers that are sensitive to photosynthetically active radiation (PAR) at 400-700 nm. The TRAC measures the PAR flux transmitted through the overstory canopy continuously at 32 Hz. The parameters derived from the TRAC instrument include estimates of plant or leaf area index (PAI, LAI), overstory gap fraction, and clumping index.
Data from the Tracing Radiation and Architecture of Canopies (TRAC) instrument were collected at five sites along the International Geosphere-Biosphere Programme (IGBP) Kalahari Transect, including Mongu in Zambia and Pandamatenga, Maun, Okwa River Crossing, and Tshane in Botswana, during the 2000 wet season field campaign (March-April) of SAFARI 2000. At the Mongu site, TRAC measurements began in August of 1999 and continued beyond the 2000 wet season field campaign, about every month for the rest of 2000. The TRAC instrument contains pyranometers that are sensitive to photosynthetically active radiation (PAR) at 400-700 nm. The TRAC measures the PAR flux transmitted through the overstory canopy continuously at 32 Hz. The parameters derived from the TRAC instrument include estimates of plant or leaf area index (PAI, LAI), overstory gap fraction, and clumping index.
ABSTRACT: Data from the Tracing Radiation and Architecture of Canopies (TRAC) instrument were collected at five sites along the International Geosphere-Biosphere Programme (IGBP) Kalahari Transect, including Mongu in Zambia and Pandamatenga, Maun, Okwa River Crossing, and Tshane in Botswana, during the 2000 wet season field campaign (March-April) of SAFARI 2000. At the Mongu site, TRAC measurements began in August of 1999 and continued beyond the 2000 wet season field campaign, about every month for the rest of 2000. The TRAC instrument contains pyranometers that are sensitive to photosynthetically active radiation (PAR) at 400-700 nm. The TRAC measures the PAR flux transmitted through the overstory canopy continuously at 32 Hz. The parameters derived from the TRAC instrument include estimates of plant or leaf area index (PAI, LAI), overstory gap fraction, and clumping index.
Data from the LAI-2000 instrument were processed to determine the leaf area index (LAI) at the EOS Validation Core Site in Kataba Local Forest, approximately 20 km south of Mongu, Zambia. Measurements began in 2000 and continued into 2002, with measurements collected about every month throughout the growing season to examine the phenology of LAI for the site. The LAI-2000 measures the intensity of blue light in five upward-looking concentric conical rings. Measurements are made under the forest canopy and compared with open-sky measurements to determine transmittance for each of the five viewing angles. The sensor head was placed at ground level while the sensors measured light levels in conical scans. Effective leaf area was calculated from the transmittance in the different view angles based on the assumption of a random distribution of leaves (Welles and Norman, 1991).The LAI-2000 was carried along three parallel transects, each 750 m long and spaced 250 m apart. Each transect was divided into 25 m segments, and measurements were collected at the endpoints of each segment. Data from all transects were combined to provide site-average LAI for each sampling date. The length and spacing of the transects were chosen to sample an area large enough to be representative of a 1 km MODIS pixel. Ground observations of LAI from this study compared with MODIS LAI products were found to be in close agreement.The data are stored in an ASCII text file, in comma-separated-value (csv) format, with column headers.
Data from the LAI-2000 instrument were processed to determine the leaf area index (LAI) at the EOS Validation Core Site in Kataba Local Forest, approximately 20 km south of Mongu, Zambia. Measurements began in 2000 and continued into 2002, with measurements collected about every month throughout the growing season to examine the phenology of LAI for the site. The LAI-2000 measures the intensity of blue light in five upward-looking concentric conical rings. Measurements are made under the forest canopy and compared with open-sky measurements to determine transmittance for each of the five viewing angles. The sensor head was placed at ground level while the sensors measured light levels in conical scans. Effective leaf area was calculated from the transmittance in the different view angles based on the assumption of a random distribution of leaves (Welles and Norman, 1991).The LAI-2000 was carried along three parallel transects, each 750 m long and spaced 250 m apart. Each transect was divided into 25 m segments, and measurements were collected at the endpoints of each segment. Data from all transects were combined to provide site-average LAI for each sampling date. The length and spacing of the transects were chosen to sample an area large enough to be representative of a 1 km MODIS pixel. Ground observations of LAI from this study compared with MODIS LAI products were found to be in close agreement.The data are stored in an ASCII text file, in comma-separated-value (csv) format, with column headers.
ABSTRACT: Data from the LAI-2000 instrument were processed to determine the leaf area index (LAI) at the EOS Validation Core Site in Kataba Local Forest, approximately 20 km south of Mongu, Zambia. Measurements began in 2000 and continued into 2002, with measurements collected about every month throughout the growing season to examine the phenology of LAI for the site. The LAI-2000 measures the intensity of blue light in five upward-looking concentric conical rings. Measurements are made under the forest canopy and compared with open-sky measurements to determine transmittance for each of the five viewing angles. The sensor head was placed at ground level while the sensors measured light levels in conical scans. Effective leaf area was calculated from the transmittance in the different view angles based on the assumption of a random distribution of leaves (Welles and Norman, 1991).The LAI-2000 was carried along three parallel transects, each 750 m long and spaced 250 m apart. Each transect was divided into 25 m segments, and measurements were collected at the endpoints of each segment. Data from all transects were combined to provide site-average LAI for each sampling date. The length and spacing of the transects were chosen to sample an area large enough to be representative of a 1 km MODIS pixel. Ground observations of LAI from this study compared with MODIS LAI products were found to be in close agreement.The data are stored in an ASCII text file, in comma-separated-value (csv) format, with column headers.
Data presented in this data set were collected during an intensive field campaign in Botswana between February 28 and March 18, 2000 along the Kalahari Transect as part of the SAFARI 2000 wet season field campaign. The sites visited were Pandamatenga, Maun, Okwa River Crossing, and Tshane (north to south). Individual leaf blade measurements were made on replicate samples from selected dominant and subdominant tree species using an optical lens and graticule. Leaves used in the study had recently-matured new growth and were fully exposed to the sun for a significant part of the day. The data set comprises individual leaf blade dimensions along the length and width of each leaf by tree species as well as the mean of the replicate leaf length and width samples. The data are in comma-delimited ASCII format (kt_leaf_dimensions.csv).
Data presented in this data set were collected during an intensive field campaign in Botswana between February 28 and March 18, 2000 along the Kalahari Transect as part of the SAFARI 2000 wet season field campaign. The sites visited were Pandamatenga, Maun, Okwa River Crossing, and Tshane (north to south). Individual leaf blade measurements were made on replicate samples from selected dominant and subdominant tree species using an optical lens and graticule. Leaves used in the study had recently-matured new growth and were fully exposed to the sun for a significant part of the day. The data set comprises individual leaf blade dimensions along the length and width of each leaf by tree species as well as the mean of the replicate leaf length and width samples. The data are in comma-delimited ASCII format (kt_leaf_dimensions.csv).
ABSTRACT: Data presented in this data set were collected during an intensive field campaign in Botswana between February 28 and March 18, 2000 along the Kalahari Transect as part of the SAFARI 2000 wet season field campaign. The sites visited were Pandamatenga, Maun, Okwa River Crossing, and Tshane (north to south). Individual leaf blade measurements were made on replicate samples from selected dominant and subdominant tree species using an optical lens and graticule. Leaves used in the study had recently-matured new growth and were fully exposed to the sun for a significant part of the day. The data set comprises individual leaf blade dimensions along the length and width of each leaf by tree species as well as the mean of the replicate leaf length and width samples. The data are in comma-delimited ASCII format (kt_leaf_dimensions.csv).
The Boston University team collected several data sets along the Kalahari Transect during the SAFARI 2000 wet season field campaign between March 3 and March 18, 2000, to support the validation of the MODIS LAI/FPAR algorithm. Ground measurements of LAI, FPAR, leaf hemispherical reflectance and transmittance, and canopy transmittance were made using a LAI-2000 plant canopy analyzer, an AccuPAR ceptometer, a LiCor 1800-12S External Integrating Sphere (LI-1800) portable spectroradiometer, and an ASD handheld spectroradiometer. Leaf spectral data are provided in this data set. Leaf spectral measurements were made on samples from dominant tree, shrub, and grass species at 5 different Kalahari Transect sites - Mongu in Zambia and Pandamatenga, Maun, Okwa River, and Tshane in Botswana (from north to south)- where vegetation ranges from moist closed woodlands to arid sparsely-shrub-covered grasslands.
The Boston University team collected several data sets along the Kalahari Transect during the SAFARI 2000 wet season field campaign between March 3 and March 18, 2000, to support the validation of the MODIS LAI/FPAR algorithm. Ground measurements of LAI, FPAR, leaf hemispherical reflectance and transmittance, and canopy transmittance were made using a LAI-2000 plant canopy analyzer, an AccuPAR ceptometer, a LiCor 1800-12S External Integrating Sphere (LI-1800) portable spectroradiometer, and an ASD handheld spectroradiometer. Leaf spectral data are provided in this data set. Leaf spectral measurements were made on samples from dominant tree, shrub, and grass species at 5 different Kalahari Transect sites - Mongu in Zambia and Pandamatenga, Maun, Okwa River, and Tshane in Botswana (from north to south)- where vegetation ranges from moist closed woodlands to arid sparsely-shrub-covered grasslands.
ABSTRACT: The Boston University team collected several data sets along the Kalahari Transect during the SAFARI 2000 wet season field campaign between March 3 and March 18, 2000, to support the validation of the MODIS LAI/FPAR algorithm. Ground measurements of LAI, FPAR, leaf hemispherical reflectance and transmittance, and canopy transmittance were made using a LAI-2000 plant canopy analyzer, an AccuPAR ceptometer, a LiCor 1800-12S External Integrating Sphere (LI-1800) portable spectroradiometer, and an ASD handheld spectroradiometer. Leaf spectral data are provided in this data set. Leaf spectral measurements were made on samples from dominant tree, shrub, and grass species at 5 different Kalahari Transect sites - Mongu in Zambia and Pandamatenga, Maun, Okwa River, and Tshane in Botswana (from north to south)- where vegetation ranges from moist closed woodlands to arid sparsely-shrub-covered grasslands.
Biogenic volatile organic compounds (VOCs) comprise a significant proportion of trace gases in the atmospheric environment and play an important role in the formation of secondary air pollutants. Emissions of monoterpenes from vegetation were studied at adjacent sites in Botswana as part of the SAFARI 2000 (Southern African Regional Science Initiative). Using a LI-COR leaf cuvette, VOC emissions were measured from the dominant tree species (Colophospermum mopane) and other vegetation near Maun, Botswana.
Biogenic volatile organic compounds (VOCs) comprise a significant proportion of trace gases in the atmospheric environment and play an important role in the formation of secondary air pollutants. Emissions of monoterpenes from vegetation were studied at adjacent sites in Botswana as part of the SAFARI 2000 (Southern African Regional Science Initiative). Using a LI-COR leaf cuvette, VOC emissions were measured from the dominant tree species (Colophospermum mopane) and other vegetation near Maun, Botswana.
ABSTRACT: Biogenic volatile organic compounds (VOCs) comprise a significant proportion of trace gases in the atmospheric environment and play an important role in the formation of secondary air pollutants. Emissions of monoterpenes from vegetation were studied at adjacent sites in Botswana as part of the SAFARI 2000 (Southern African Regional Science Initiative). Using a LI-COR leaf cuvette, VOC emissions were measured from the dominant tree species (Colophospermum mopane) and other vegetation near Maun, Botswana.
The MODIS (Moderate Resolution Imaging Spectroradiometer) Atmosphere Group develops remote sensing algorithms for deriving sets of atmospheric parameters from MODIS radiance data. These parameters can be integrated into conceptual and predictive global models. MODIS Atmosphere Products Subset Statistics (MAPSS) are generated over important locations around the world, as one of the ways to increase the scope of application of the MODIS atmospheric parameters. This MAPSS data set contains daily time series of the MODIS MOD04_L2 aerosol product over seventeen (17) AERONET sunphotometer measurement sites in southern Africa for the period February 26, 2000, through December 31, 2001. The process of generating the statistics involves identifying these locations on the MODIS MOD04_L2 product, extracting the values of the pixel corresponding to each coordinate point as well as surrounding pixels falling within a 50 x 50 km box centered on the coordinate point. The data files are stored as ASCII tables in comma-separated-value (.csv) format. There is one file per site per year for each of the following variables: cloud fraction (land); cloud fraction (ocean); particle effective radius (ocean); optical depth (land and ocean); optical depth (land, corrected); optical depth (ocean, effective average); and optical depth ratio (small ocean).
The MODIS (Moderate Resolution Imaging Spectroradiometer) Atmosphere Group develops remote sensing algorithms for deriving sets of atmospheric parameters from MODIS radiance data. These parameters can be integrated into conceptual and predictive global models. MODIS Atmosphere Products Subset Statistics (MAPSS) are generated over important locations around the world, as one of the ways to increase the scope of application of the MODIS atmospheric parameters. This MAPSS data set contains daily time series of the MODIS MOD04_L2 aerosol product over seventeen (17) AERONET sunphotometer measurement sites in southern Africa for the period February 26, 2000, through December 31, 2001. The process of generating the statistics involves identifying these locations on the MODIS MOD04_L2 product, extracting the values of the pixel corresponding to each coordinate point as well as surrounding pixels falling within a 50 x 50 km box centered on the coordinate point. The data files are stored as ASCII tables in comma-separated-value (.csv) format. There is one file per site per year for each of the following variables: cloud fraction (land); cloud fraction (ocean); particle effective radius (ocean); optical depth (land and ocean); optical depth (land, corrected); optical depth (ocean, effective average); and optical depth ratio (small ocean).
ABSTRACT: The MODIS (Moderate Resolution Imaging Spectroradiometer) Atmosphere Group develops remote sensing algorithms for deriving sets of atmospheric parameters from MODIS radiance data. These parameters can be integrated into conceptual and predictive global models. MODIS Atmosphere Products Subset Statistics (MAPSS) are generated over important locations around the world, as one of the ways to increase the scope of application of the MODIS atmospheric parameters. This MAPSS data set contains daily time series of the MODIS MOD04_L2 aerosol product over seventeen (17) AERONET sunphotometer measurement sites in southern Africa for the period February 26, 2000, through December 31, 2001. The process of generating the statistics involves identifying these locations on the MODIS MOD04_L2 product, extracting the values of the pixel corresponding to each coordinate point as well as surrounding pixels falling within a 50 x 50 km box centered on the coordinate point. The data files are stored as ASCII tables in comma-separated-value (.csv) format. There is one file per site per year for each of the following variables: cloud fraction (land); cloud fraction (ocean); particle effective radius (ocean); optical depth (land and ocean); optical depth (land, corrected); optical depth (ocean, effective average); and optical depth ratio (small ocean).
The MODIS (Moderate Resolution Imaging Spectroradiometer) Atmosphere Group develops remote sensing algorithms for deriving sets of atmospheric parameters from MODIS radiance data. These parameters can be integrated into conceptual and predictive global models. MODIS Atmosphere Products Subset Statistics (MAPSS) are generated over important locations around the world, as one of the ways to increase the scope of application of the MODIS atmospheric parameters. This MAPSS data set contains daily time series of the MODIS MOD05_L2 water vapor product over seventeen (17) AERONET sunphotometer measurement sites in southern Africa for the period February 24, 2000, through March 4, 2002. The process of generating the statistics involves identifying these locations on the MODIS MOD05_L2 product, extracting the values of the pixel corresponding to each coordinate point as well as surrounding pixels falling within a 50 x 50 km box centered on the coordinate point. The data product consists of column water-vapor amounts. During the daytime, a near-infrared algorithm is applied over clear land areas of the globe and above clouds over both land and ocean. Over clear ocean areas, water-vapor estimates are provided over the extended glint area. An infrared algorithm for deriving atmospheric profiles is also applied both day and night for Level 2. The data files are stored as ASCII tables in comma-separated-value (.csv) format. There is one file per site per year for each of the following two variables: total column precipitable water vapor (infrared retrieved) and total column precipitable water vapor (near-infrared retrieved).
The MODIS (Moderate Resolution Imaging Spectroradiometer) Atmosphere Group develops remote sensing algorithms for deriving sets of atmospheric parameters from MODIS radiance data. These parameters can be integrated into conceptual and predictive global models. MODIS Atmosphere Products Subset Statistics (MAPSS) are generated over important locations around the world, as one of the ways to increase the scope of application of the MODIS atmospheric parameters. This MAPSS data set contains daily time series of the MODIS MOD05_L2 water vapor product over seventeen (17) AERONET sunphotometer measurement sites in southern Africa for the period February 24, 2000, through March 4, 2002. The process of generating the statistics involves identifying these locations on the MODIS MOD05_L2 product, extracting the values of the pixel corresponding to each coordinate point as well as surrounding pixels falling within a 50 x 50 km box centered on the coordinate point. The data product consists of column water-vapor amounts. During the daytime, a near-infrared algorithm is applied over clear land areas of the globe and above clouds over both land and ocean. Over clear ocean areas, water-vapor estimates are provided over the extended glint area. An infrared algorithm for deriving atmospheric profiles is also applied both day and night for Level 2. The data files are stored as ASCII tables in comma-separated-value (.csv) format. There is one file per site per year for each of the following two variables: total column precipitable water vapor (infrared retrieved) and total column precipitable water vapor (near-infrared retrieved).
ABSTRACT: The MODIS (Moderate Resolution Imaging Spectroradiometer) Atmosphere Group develops remote sensing algorithms for deriving sets of atmospheric parameters from MODIS radiance data. These parameters can be integrated into conceptual and predictive global models. MODIS Atmosphere Products Subset Statistics (MAPSS) are generated over important locations around the world, as one of the ways to increase the scope of application of the MODIS atmospheric parameters. This MAPSS data set contains daily time series of the MODIS MOD05_L2 water vapor product over seventeen (17) AERONET sunphotometer measurement sites in southern Africa for the period February 24, 2000, through March 4, 2002. The process of generating the statistics involves identifying these locations on the MODIS MOD05_L2 product, extracting the values of the pixel corresponding to each coordinate point as well as surrounding pixels falling within a 50 x 50 km box centered on the coordinate point. The data product consists of column water-vapor amounts. During the daytime, a near-infrared algorithm is applied over clear land areas of the globe and above clouds over both land and ocean. Over clear ocean areas, water-vapor estimates are provided over the extended glint area. An infrared algorithm for deriving atmospheric profiles is also applied both day and night for Level 2. The data files are stored as ASCII tables in comma-separated-value (.csv) format. There is one file per site per year for each of the following two variables: total column precipitable water vapor (infrared retrieved) and total column precipitable water vapor (near-infrared retrieved).
This data set is a subset of Cramer and Leeman's (1999) global mean monthly climatology . The subset is for the area of southern Africa within the following bounds: 5 N to 35 S and 5 E to 60 E. The data are available in ASCII grid and binary image formats.
This data set is a subset of Cramer and Leeman's (1999) global mean monthly climatology . The subset is for the area of southern Africa within the following bounds: 5 N to 35 S and 5 E to 60 E. The data are available in ASCII grid and binary image formats.
ABSTRACT: This data set is a subset of Cramer and Leeman's (1999) global mean monthly climatology . The subset is for the area of southern Africa within the following bounds: 5 N to 35 S and 5 E to 60 E. The data are available in ASCII grid and binary image formats.
To investigate potential contributions of savanna ecosystems to the Earth's carbon balance, an eddy covariance system was used to measure the seasonal variation in carbon dioxide, water vapor, and energy flux at the Maun micrometerological tower site in a broadleaf semi-arid savanna in Southern Africa, approximately 20 km east of Maun in northeastern Botswana.
To investigate potential contributions of savanna ecosystems to the Earth's carbon balance, an eddy covariance system was used to measure the seasonal variation in carbon dioxide, water vapor, and energy flux at the Maun micrometerological tower site in a broadleaf semi-arid savanna in Southern Africa, approximately 20 km east of Maun in northeastern Botswana.
ABSTRACT: To investigate potential contributions of savanna ecosystems to the Earth's carbon balance, an eddy covariance system was used to measure the seasonal variation in carbon dioxide, water vapor, and energy flux at the Maun micrometerological tower site in a broadleaf semi-arid savanna in Southern Africa, approximately 20 km east of Maun in northeastern Botswana.
An eddy covariance system mounted on a tower near the Skukuza Camp in Kruger National Park, South Africa, has been operating continuously since early 2000. Meteorological measurements started in February 2000, and the first flux measurements were made in April 2000. The site is unique in that the micrometeorological instruments are positioned on a tower located between two distinct savanna types, a broad-leafed Combretum savanna and a fine-leafed Acacia savanna. Measurements on the main eddy covariance tower include net ecosystem exchange of CO2, water, and energy, and measurements of a range of meteorological variables with 30-minute averaging period.
An eddy covariance system mounted on a tower near the Skukuza Camp in Kruger National Park, South Africa, has been operating continuously since early 2000. Meteorological measurements started in February 2000, and the first flux measurements were made in April 2000. The site is unique in that the micrometeorological instruments are positioned on a tower located between two distinct savanna types, a broad-leafed Combretum savanna and a fine-leafed Acacia savanna. Measurements on the main eddy covariance tower include net ecosystem exchange of CO2, water, and energy, and measurements of a range of meteorological variables with 30-minute averaging period.
ABSTRACT: An eddy covariance system mounted on a tower near the Skukuza Camp in Kruger National Park, South Africa, has been operating continuously since early 2000. Meteorological measurements started in February 2000, and the first flux measurements were made in April 2000. The site is unique in that the micrometeorological instruments are positioned on a tower located between two distinct savanna types, a broad-leafed Combretum savanna and a fine-leafed Acacia savanna. Measurements on the main eddy covariance tower include net ecosystem exchange of CO2, water, and energy, and measurements of a range of meteorological variables with 30-minute averaging period.
Two Micro-Pulse Lidar (MPL) systems were deployed to Africa for the SAFARI 2000 experiment. One MPL was set up in Mongu, Zambia, and the other was set up in Skukuza, South Africa. The primary focus of MPL work during SAFARI was to study the vertical distribution and optical properties of smoke from biomass burning in the region.
Two Micro-Pulse Lidar (MPL) systems were deployed to Africa for the SAFARI 2000 experiment. One MPL was set up in Mongu, Zambia, and the other was set up in Skukuza, South Africa. The primary focus of MPL work during SAFARI was to study the vertical distribution and optical properties of smoke from biomass burning in the region.
ABSTRACT: Two Micro-Pulse Lidar (MPL) systems were deployed to Africa for the SAFARI 2000 experiment. One MPL was set up in Mongu, Zambia, and the other was set up in Skukuza, South Africa. The primary focus of MPL work during SAFARI was to study the vertical distribution and optical properties of smoke from biomass burning in the region.
MISR (Multi-angle Imaging SpectroRadiometer) views the sunlit Earth simultaneously at nine widely spaced and collects global images with high spatial detail in four colors at every angle. These images are carefully calibrated to provide accurate measures of the brightness, contrast, and color of reflected sunlight. The change in reflection at different view angles affords the means to distinguish different types of atmospheric particles (aerosols), cloud forms, and land surface covers. Combined with stereoscopic techniques, this enables construction of 3-dimensional models and more accurate estimates of the total amount of sunlight reflected by Earth's diverse environments.MISR was built for NASA by the Jet Propulsion Laboratory. It is part of NASA's Terra spacecraft, launched into a polar orbit around the Earth on December 18, 1999.The Southern African Fire Atmosphere Research Initiative (SAFARI) 2000 field campaign focused on the smoke and gases released into the environment of southern Africa by industrial, biological, and man-made sources such as biomass burning. The area of study and MISR path numbers include Botswana, Lesotho, Malawi, Mozambique, Namibia, South Africa, Swaziland, Zambia, and Zimbabwe. These MISR data cover the period August 12 through September 28, 2000.
MISR (Multi-angle Imaging SpectroRadiometer) views the sunlit Earth simultaneously at nine widely spaced and collects global images with high spatial detail in four colors at every angle. These images are carefully calibrated to provide accurate measures of the brightness, contrast, and color of reflected sunlight. The change in reflection at different view angles affords the means to distinguish different types of atmospheric particles (aerosols), cloud forms, and land surface covers. Combined with stereoscopic techniques, this enables construction of 3-dimensional models and more accurate estimates of the total amount of sunlight reflected by Earth's diverse environments.MISR was built for NASA by the Jet Propulsion Laboratory. It is part of NASA's Terra spacecraft, launched into a polar orbit around the Earth on December 18, 1999.The Southern African Fire Atmosphere Research Initiative (SAFARI) 2000 field campaign focused on the smoke and gases released into the environment of southern Africa by industrial, biological, and man-made sources such as biomass burning. The area of study and MISR path numbers include Botswana, Lesotho, Malawi, Mozambique, Namibia, South Africa, Swaziland, Zambia, and Zimbabwe. These MISR data cover the period August 12 through September 28, 2000.
ABSTRACT: MISR (Multi-angle Imaging SpectroRadiometer) views the sunlit Earth simultaneously at nine widely spaced and collects global images with high spatial detail in four colors at every angle. These images are carefully calibrated to provide accurate measures of the brightness, contrast, and color of reflected sunlight. The change in reflection at different view angles affords the means to distinguish different types of atmospheric particles (aerosols), cloud forms, and land surface covers. Combined with stereoscopic techniques, this enables construction of 3-dimensional models and more accurate estimates of the total amount of sunlight reflected by Earth's diverse environments.MISR was built for NASA by the Jet Propulsion Laboratory. It is part of NASA's Terra spacecraft, launched into a polar orbit around the Earth on December 18, 1999.The Southern African Fire Atmosphere Research Initiative (SAFARI) 2000 field campaign focused on the smoke and gases released into the environment of southern Africa by industrial, biological, and man-made sources such as biomass burning. The area of study and MISR path numbers include Botswana, Lesotho, Malawi, Mozambique, Namibia, South Africa, Swaziland, Zambia, and Zimbabwe. These MISR data cover the period August 12 through September 28, 2000.
This data set contains global, spatially explicit (1 km2 grid cells) and temporally explicit (semi-monthly) modeled output of fuel loads over southern Africa. The fuel types considered in the data set are litter (dead tree leaves), dead grass, green grass, and small-diameter twigs. The Production Efficiency Model (PEM) was used to produce the estimated fuel loads for southern Africa for the 1999-2000 growing seasons.
This data set contains global, spatially explicit (1 km2 grid cells) and temporally explicit (semi-monthly) modeled output of fuel loads over southern Africa. The fuel types considered in the data set are litter (dead tree leaves), dead grass, green grass, and small-diameter twigs. The Production Efficiency Model (PEM) was used to produce the estimated fuel loads for southern Africa for the 1999-2000 growing seasons.
ABSTRACT: This data set contains global, spatially explicit (1 km2 grid cells) and temporally explicit (semi-monthly) modeled output of fuel loads over southern Africa. The fuel types considered in the data set are litter (dead tree leaves), dead grass, green grass, and small-diameter twigs. The Production Efficiency Model (PEM) was used to produce the estimated fuel loads for southern Africa for the 1999-2000 growing seasons.
The ETA Forecast Trajectory Model was used to produce forecasts of air-parcel trajectories twice a day at three pressure levels over seven sites in Southern Africa for the period August 14, 2000 to September 23, 2000. These sites are Durban, Middleburg, Pietersburg, and Springbok, South Africa; Maun, Botswana; Mongu, Zambia; and Windhoek, Namibia. The twice daily three-dimensional wind field (at 0000 and 1200 UTC) was used as input to the trajectory model. By integrating the vertical motion of the air parcels over a period of time, the trajectory model was able to forecast the net vertical displacement of air parcels during 12-hour periods. The resulting trajectory plots represent the three-dimensional transport of air in time and can be used to examine what is happening in the low-to-mid troposphere during flight and ground-based observations. These levels are most significant in terms of the thermodynamic structure of the troposphere, especially the stable layers and accumulation of material between and below them, as well containing the major levels of subsidence over the subcontinent. The trajectory model output and  thermodynamic profiles of the troposphere were used to position aircraft for sampling trace gases, aerosols and other species during the SAFARI 2000 field campaign and to predict regions of high aerosol and trace gas concentrations downwind.The model output data are daily forward and backward trajectory plots at 850 hPa, 700 hPa, and 500 hPa pressure levels for each location. The plots are provided as JPEG images with coordinate, date, and time stamps.
The ETA Forecast Trajectory Model was used to produce forecasts of air-parcel trajectories twice a day at three pressure levels over seven sites in Southern Africa for the period August 14, 2000 to September 23, 2000. These sites are Durban, Middleburg, Pietersburg, and Springbok, South Africa; Maun, Botswana; Mongu, Zambia; and Windhoek, Namibia. The twice daily three-dimensional wind field (at 0000 and 1200 UTC) was used as input to the trajectory model. By integrating the vertical motion of the air parcels over a period of time, the trajectory model was able to forecast the net vertical displacement of air parcels during 12-hour periods. The resulting trajectory plots represent the three-dimensional transport of air in time and can be used to examine what is happening in the low-to-mid troposphere during flight and ground-based observations. These levels are most significant in terms of the thermodynamic structure of the troposphere, especially the stable layers and accumulation of material between and below them, as well containing the major levels of subsidence over the subcontinent. The trajectory model output and  thermodynamic profiles of the troposphere were used to position aircraft for sampling trace gases, aerosols and other species during the SAFARI 2000 field campaign and to predict regions of high aerosol and trace gas concentrations downwind.The model output data are daily forward and backward trajectory plots at 850 hPa, 700 hPa, and 500 hPa pressure levels for each location. The plots are provided as JPEG images with coordinate, date, and time stamps.
ABSTRACT: The ETA Forecast Trajectory Model was used to produce forecasts of air-parcel trajectories twice a day at three pressure levels over seven sites in Southern Africa for the period August 14, 2000 to September 23, 2000. These sites are Durban, Middleburg, Pietersburg, and Springbok, South Africa; Maun, Botswana; Mongu, Zambia; and Windhoek, Namibia. The twice daily three-dimensional wind field (at 0000 and 1200 UTC) was used as input to the trajectory model. By integrating the vertical motion of the air parcels over a period of time, the trajectory model was able to forecast the net vertical displacement of air parcels during 12-hour periods. The resulting trajectory plots represent the three-dimensional transport of air in time and can be used to examine what is happening in the low-to-mid troposphere during flight and ground-based observations. These levels are most significant in terms of the thermodynamic structure of the troposphere, especially the stable layers and accumulation of material between and below them, as well containing the major levels of subsidence over the subcontinent. The trajectory model output and  thermodynamic profiles of the troposphere were used to position aircraft for sampling trace gases, aerosols and other species during the SAFARI 2000 field campaign and to predict regions of high aerosol and trace gas concentrations downwind.The model output data are daily forward and backward trajectory plots at 850 hPa, 700 hPa, and 500 hPa pressure levels for each location. The plots are provided as JPEG images with coordinate, date, and time stamps.
The SAFARI 2000 project was selected as the first regional test for a prototype regional 500 m MODIS burned area product. The MODIS burned area product maps the 500 m location and approximate day of burning using a change detection algorithm based on a bi-directional reflectance model-based expectation method applied to the MODIS near-infrared and shortwave infrared bands (Roy et al., 2002). The algorithm was applied to recently reprocessed 500 m daily MODIS land surface reflectance data to produce burned area data sets for all of southern Africa for 2000 forward. This archived data set contains MODIS 500 m burned area products for two dry season months (July and September 2000).Burned area products are spatially explicit data sets that describe the approximate day of burning at 500 m resolution for all of southern Africa south of the Equator, including Madagascar. The burned area maps are compressed GeoTiff files. Several text files are included in the compressed files to aid ENVI (Research Systems, Inc.) users, including ENVI header files and ENVI density slice files. The data set also includes a projection parameters file.The MODIS burned area data set was validated using a methodology based upon the interpretation of multitemporal Landsat Enhanced Thematic Mapper plus (ETM+) data as described in Roy et al. (in press).
The SAFARI 2000 project was selected as the first regional test for a prototype regional 500 m MODIS burned area product. The MODIS burned area product maps the 500 m location and approximate day of burning using a change detection algorithm based on a bi-directional reflectance model-based expectation method applied to the MODIS near-infrared and shortwave infrared bands (Roy et al., 2002). The algorithm was applied to recently reprocessed 500 m daily MODIS land surface reflectance data to produce burned area data sets for all of southern Africa for 2000 forward. This archived data set contains MODIS 500 m burned area products for two dry season months (July and September 2000).Burned area products are spatially explicit data sets that describe the approximate day of burning at 500 m resolution for all of southern Africa south of the Equator, including Madagascar. The burned area maps are compressed GeoTiff files. Several text files are included in the compressed files to aid ENVI (Research Systems, Inc.) users, including ENVI header files and ENVI density slice files. The data set also includes a projection parameters file.The MODIS burned area data set was validated using a methodology based upon the interpretation of multitemporal Landsat Enhanced Thematic Mapper plus (ETM+) data as described in Roy et al. (in press).
ABSTRACT: The SAFARI 2000 project was selected as the first regional test for a prototype regional 500 m MODIS burned area product. The MODIS burned area product maps the 500 m location and approximate day of burning using a change detection algorithm based on a bi-directional reflectance model-based expectation method applied to the MODIS near-infrared and shortwave infrared bands (Roy et al., 2002). The algorithm was applied to recently reprocessed 500 m daily MODIS land surface reflectance data to produce burned area data sets for all of southern Africa for 2000 forward. This archived data set contains MODIS 500 m burned area products for two dry season months (July and September 2000).Burned area products are spatially explicit data sets that describe the approximate day of burning at 500 m resolution for all of southern Africa south of the Equator, including Madagascar. The burned area maps are compressed GeoTiff files. Several text files are included in the compressed files to aid ENVI (Research Systems, Inc.) users, including ENVI header files and ENVI density slice files. The data set also includes a projection parameters file.The MODIS burned area data set was validated using a methodology based upon the interpretation of multitemporal Landsat Enhanced Thematic Mapper plus (ETM+) data as described in Roy et al. (in press).
The Filled Land Surface Albedo Product for Southern Africa, which is generated from MOD43B3 Product (the official Terra/MODIS-derived Land Surface Albedo - http://geography.bu.edu/brdf/userguide/albedo.html ), is a subset of the global data set of spatially complete albedo maps computed for both white-sky and black-sky at 10 wavelengths (0.47mm, 0.55mm, 0.67mm, 0.86mm, 1.24mm, 1.64mm, 2.1mm, and broadband 0.3-0.7mm, 0.3-5.0mm, and 0.7-5.0mm). An exception is that no 2.1mm data for black-sky is being archived at this time. The data spatial extent is from approximately 5 degrees N to -30 degrees S latitude and 5 minutes E to 60 degrees E longitude and covers 7 sixteen day periods starting on July 11 through October 15, 2000.Map Products, containing spatially complete land surface albedo data, are generated at 1-minute resolution on an equal-angle grid. The maps are stored in separate HDF files for each wavelength, each 16-day period and each albedo type (white- and black-sky). Data belonging to black sky and white sky albedo have been zipped separately. This format allows the user to have flexibility to download and store only the data absolutely needed.The One-Minute Land Ecosystem Classification Product is a global (static map) data set of the International Geosphere-Biosphere Programme (IGBP) classification scheme stored on an equal-angle rectangular grid at 1-minute resolution. The dataset is generated from the official MODIS land ecosystem classification dataset, MOD12Q1 for year 2000, day 289 data (October 15, 2000). This dataset is used in generating the spatially complete albedo maps, but is also a stand-alone product designed for use by the user community. The Land Ecosystem Classification Map File product file is stored in Hierarchical Data Format (HDF).
The Filled Land Surface Albedo Product for Southern Africa, which is generated from MOD43B3 Product (the official Terra/MODIS-derived Land Surface Albedo - http://geography.bu.edu/brdf/userguide/albedo.html ), is a subset of the global data set of spatially complete albedo maps computed for both white-sky and black-sky at 10 wavelengths (0.47mm, 0.55mm, 0.67mm, 0.86mm, 1.24mm, 1.64mm, 2.1mm, and broadband 0.3-0.7mm, 0.3-5.0mm, and 0.7-5.0mm). An exception is that no 2.1mm data for black-sky is being archived at this time. The data spatial extent is from approximately 5 degrees N to -30 degrees S latitude and 5 minutes E to 60 degrees E longitude and covers 7 sixteen day periods starting on July 11 through October 15, 2000.Map Products, containing spatially complete land surface albedo data, are generated at 1-minute resolution on an equal-angle grid. The maps are stored in separate HDF files for each wavelength, each 16-day period and each albedo type (white- and black-sky). Data belonging to black sky and white sky albedo have been zipped separately. This format allows the user to have flexibility to download and store only the data absolutely needed.The One-Minute Land Ecosystem Classification Product is a global (static map) data set of the International Geosphere-Biosphere Programme (IGBP) classification scheme stored on an equal-angle rectangular grid at 1-minute resolution. The dataset is generated from the official MODIS land ecosystem classification dataset, MOD12Q1 for year 2000, day 289 data (October 15, 2000). This dataset is used in generating the spatially complete albedo maps, but is also a stand-alone product designed for use by the user community. The Land Ecosystem Classification Map File product file is stored in Hierarchical Data Format (HDF).
ABSTRACT: The Filled Land Surface Albedo Product for Southern Africa, which is generated from MOD43B3 Product (the official Terra/MODIS-derived Land Surface Albedo - http://geography.bu.edu/brdf/userguide/albedo.html ), is a subset of the global data set of spatially complete albedo maps computed for both white-sky and black-sky at 10 wavelengths (0.47mm, 0.55mm, 0.67mm, 0.86mm, 1.24mm, 1.64mm, 2.1mm, and broadband 0.3-0.7mm, 0.3-5.0mm, and 0.7-5.0mm). An exception is that no 2.1mm data for black-sky is being archived at this time. The data spatial extent is from approximately 5 degrees N to -30 degrees S latitude and 5 minutes E to 60 degrees E longitude and covers 7 sixteen day periods starting on July 11 through October 15, 2000.Map Products, containing spatially complete land surface albedo data, are generated at 1-minute resolution on an equal-angle grid. The maps are stored in separate HDF files for each wavelength, each 16-day period and each albedo type (white- and black-sky). Data belonging to black sky and white sky albedo have been zipped separately. This format allows the user to have flexibility to download and store only the data absolutely needed.The One-Minute Land Ecosystem Classification Product is a global (static map) data set of the International Geosphere-Biosphere Programme (IGBP) classification scheme stored on an equal-angle rectangular grid at 1-minute resolution. The dataset is generated from the official MODIS land ecosystem classification dataset, MOD12Q1 for year 2000, day 289 data (October 15, 2000). This dataset is used in generating the spatially complete albedo maps, but is also a stand-alone product designed for use by the user community. The Land Ecosystem Classification Map File product file is stored in Hierarchical Data Format (HDF).
The subset of the MODIS MOD04_L2 aerosol product provided in this data set represents the swaths that coincide with known times of the South African Weather Bureau/Service (SAWS) Aerocommanders JRA and JRB research aircraft missions to support aerosol research and validation activities for the SAFARI 2000 region. The MODIS aerosol product monitors the ambient aerosol optical thickness over the oceans globally and over a portion of the continents. Further, the aerosol size distribution is derived over the oceans, and the aerosol type is derived over the continents. Daily Level 2 data are produced at the spatial resolution of a 10 x 10 1 km (at nadir) pixel array. The daily data files cover the period August 21, 2000, through September 26, 2000. For some data collection dates, there are two or more data files.The MOD04_L2 swath data files included in this data set are from the GSFC DAAC (V4.1.0, Collection 004). The MODIS Level 2 data files were converted from Hierarchical Data Format (HDF) to granule tables (GRANT) format. The GRANT format provides the extracted Scientific Data Set (SDS) in ASCII table form where each pixel (x,y) is represented as a row of data with georeferencing information and each SDS is provided as a separate column in the table. The ASCII tables are in comma-delimited format.
The subset of the MODIS MOD04_L2 aerosol product provided in this data set represents the swaths that coincide with known times of the South African Weather Bureau/Service (SAWS) Aerocommanders JRA and JRB research aircraft missions to support aerosol research and validation activities for the SAFARI 2000 region. The MODIS aerosol product monitors the ambient aerosol optical thickness over the oceans globally and over a portion of the continents. Further, the aerosol size distribution is derived over the oceans, and the aerosol type is derived over the continents. Daily Level 2 data are produced at the spatial resolution of a 10 x 10 1 km (at nadir) pixel array. The daily data files cover the period August 21, 2000, through September 26, 2000. For some data collection dates, there are two or more data files.The MOD04_L2 swath data files included in this data set are from the GSFC DAAC (V4.1.0, Collection 004). The MODIS Level 2 data files were converted from Hierarchical Data Format (HDF) to granule tables (GRANT) format. The GRANT format provides the extracted Scientific Data Set (SDS) in ASCII table form where each pixel (x,y) is represented as a row of data with georeferencing information and each SDS is provided as a separate column in the table. The ASCII tables are in comma-delimited format.
ABSTRACT: The subset of the MODIS MOD04_L2 aerosol product provided in this data set represents the swaths that coincide with known times of the South African Weather Bureau/Service (SAWS) Aerocommanders JRA and JRB research aircraft missions to support aerosol research and validation activities for the SAFARI 2000 region. The MODIS aerosol product monitors the ambient aerosol optical thickness over the oceans globally and over a portion of the continents. Further, the aerosol size distribution is derived over the oceans, and the aerosol type is derived over the continents. Daily Level 2 data are produced at the spatial resolution of a 10 x 10 1 km (at nadir) pixel array. The daily data files cover the period August 21, 2000, through September 26, 2000. For some data collection dates, there are two or more data files.The MOD04_L2 swath data files included in this data set are from the GSFC DAAC (V4.1.0, Collection 004). The MODIS Level 2 data files were converted from Hierarchical Data Format (HDF) to granule tables (GRANT) format. The GRANT format provides the extracted Scientific Data Set (SDS) in ASCII table form where each pixel (x,y) is represented as a row of data with georeferencing information and each SDS is provided as a separate column in the table. The ASCII tables are in comma-delimited format.
The MODIS precipitable water product consists of vertical column water-vapor amounts in centimeters (cm) at 1 km spatial resolution. The SAFARI 2000 product, provided in flat binary data files, is a subset of the official MODIS Level 2 MOD05 product in EOS Hierarchical Data Format (HDF) format. Specifically, the SAFARI product contains data from daytime-only MODIS granules over southern Africa for the period August 21, 2000, through September 20, 2000. A granule is the data collected over the full MODIS swath in a five-minute period. Further, the SAFARI product contains values generated by the MODIS near-infrared algorithm applied over clear land areas only (determined via the QA bit field). All values were derived from MODIS on the morning-pass Terra satellite. The product is very sensitive to boundary-layer water vapor since it is derived from attenuation of reflected solar light from the surface. This data product is essential to understanding the hydrological cycle, aerosol properties, aerosol-cloud interactions, energy budget, and climate.The MOD05 water vapor data files were converted from their original HDF format to flat binary files for this SAFARI 2000 data set. The conversion was performed using code developed in the Interactive Data Language (IDL) Version 5.5. The following Scientific Data Sets (SDS) are provided in this data set: Latitude; Longitude; Sensor_Zenith; and Water_Vapor_Near_Infrared.
The MODIS precipitable water product consists of vertical column water-vapor amounts in centimeters (cm) at 1 km spatial resolution. The SAFARI 2000 product, provided in flat binary data files, is a subset of the official MODIS Level 2 MOD05 product in EOS Hierarchical Data Format (HDF) format. Specifically, the SAFARI product contains data from daytime-only MODIS granules over southern Africa for the period August 21, 2000, through September 20, 2000. A granule is the data collected over the full MODIS swath in a five-minute period. Further, the SAFARI product contains values generated by the MODIS near-infrared algorithm applied over clear land areas only (determined via the QA bit field). All values were derived from MODIS on the morning-pass Terra satellite. The product is very sensitive to boundary-layer water vapor since it is derived from attenuation of reflected solar light from the surface. This data product is essential to understanding the hydrological cycle, aerosol properties, aerosol-cloud interactions, energy budget, and climate.The MOD05 water vapor data files were converted from their original HDF format to flat binary files for this SAFARI 2000 data set. The conversion was performed using code developed in the Interactive Data Language (IDL) Version 5.5. The following Scientific Data Sets (SDS) are provided in this data set: Latitude; Longitude; Sensor_Zenith; and Water_Vapor_Near_Infrared.
ABSTRACT: The MODIS precipitable water product consists of vertical column water-vapor amounts in centimeters (cm) at 1 km spatial resolution. The SAFARI 2000 product, provided in flat binary data files, is a subset of the official MODIS Level 2 MOD05 product in EOS Hierarchical Data Format (HDF) format. Specifically, the SAFARI product contains data from daytime-only MODIS granules over southern Africa for the period August 21, 2000, through September 20, 2000. A granule is the data collected over the full MODIS swath in a five-minute period. Further, the SAFARI product contains values generated by the MODIS near-infrared algorithm applied over clear land areas only (determined via the QA bit field). All values were derived from MODIS on the morning-pass Terra satellite. The product is very sensitive to boundary-layer water vapor since it is derived from attenuation of reflected solar light from the surface. This data product is essential to understanding the hydrological cycle, aerosol properties, aerosol-cloud interactions, energy budget, and climate.The MOD05 water vapor data files were converted from their original HDF format to flat binary files for this SAFARI 2000 data set. The conversion was performed using code developed in the Interactive Data Language (IDL) Version 5.5. The following Scientific Data Sets (SDS) are provided in this data set: Latitude; Longitude; Sensor_Zenith; and Water_Vapor_Near_Infrared.
A physically-based model, Energy: Surface Towards Atmosphere (ESTA), was used to model and map the energy and water balances of a heterogeneous land surface in a savanna environment on the southern fringe of the Okavango Delta, near Maun, Botswana. ESTA is governed by remotely sensed values of surface temperature, reflection, and vegetation density. Surface reflectance data from the MODIS sensor aboard the Terra satellite were obtained for the Okavango Delta region for September of 2001.
A physically-based model, Energy: Surface Towards Atmosphere (ESTA), was used to model and map the energy and water balances of a heterogeneous land surface in a savanna environment on the southern fringe of the Okavango Delta, near Maun, Botswana. ESTA is governed by remotely sensed values of surface temperature, reflection, and vegetation density. Surface reflectance data from the MODIS sensor aboard the Terra satellite were obtained for the Okavango Delta region for September of 2001.
ABSTRACT: A physically-based model, Energy: Surface Towards Atmosphere (ESTA), was used to model and map the energy and water balances of a heterogeneous land surface in a savanna environment on the southern fringe of the Okavango Delta, near Maun, Botswana. ESTA is governed by remotely sensed values of surface temperature, reflection, and vegetation density. Surface reflectance data from the MODIS sensor aboard the Terra satellite were obtained for the Okavango Delta region for September of 2001.
This is a data set of mean monthly surface climate data over Southern Africa for nearly all of the twentieth century. The data set is gridded at 0.5-degree latitude/longitude resolution and includes seven variables: precipitation, mean temperature, diurnal temperature range, wet-day frequency, vapour pressure, cloud cover, and ground-frost frequency.
This is a data set of mean monthly surface climate data over Southern Africa for nearly all of the twentieth century. The data set is gridded at 0.5-degree latitude/longitude resolution and includes seven variables: precipitation, mean temperature, diurnal temperature range, wet-day frequency, vapour pressure, cloud cover, and ground-frost frequency.
ABSTRACT: This is a data set of mean monthly surface climate data over Southern Africa for nearly all of the twentieth century. The data set is gridded at 0.5-degree latitude/longitude resolution and includes seven variables: precipitation, mean temperature, diurnal temperature range, wet-day frequency, vapour pressure, cloud cover, and ground-frost frequency.
The MOPITT (Measurements Of Pollution In The Troposphere) instrument on the NASA Terra Satellite makes measurements of infrared radiation originating from the surface of the planet and isolates the energy being radiated from carbon monoxide (CO). By using appropriate data analysis techniques, concentration profiles of CO (Level-2 (L2) data) can be obtained on a global basis at a reasonably high horizontal (~22km) and vertical resolution (~3km).The MOPITT Level-3 (L3) data products provided in this data set are a subset of the daily averages from the L2 data. This subset was produced by overlaying a global 1x1-degree grid onto the L2 data, and then clipping the data to this southern Africa subset which originates at 5 degrees longitude and -35 degrees latitude and extends to 60 degrees longitude and 35 degrees latitude. Data are reported for 2 heights, 700 and 350 hPa, from daytime swaths for the period August 1-September 30, 2000, the SAFARI 2000 Dry Season Campaign.
The MOPITT (Measurements Of Pollution In The Troposphere) instrument on the NASA Terra Satellite makes measurements of infrared radiation originating from the surface of the planet and isolates the energy being radiated from carbon monoxide (CO). By using appropriate data analysis techniques, concentration profiles of CO (Level-2 (L2) data) can be obtained on a global basis at a reasonably high horizontal (~22km) and vertical resolution (~3km).The MOPITT Level-3 (L3) data products provided in this data set are a subset of the daily averages from the L2 data. This subset was produced by overlaying a global 1x1-degree grid onto the L2 data, and then clipping the data to this southern Africa subset which originates at 5 degrees longitude and -35 degrees latitude and extends to 60 degrees longitude and 35 degrees latitude. Data are reported for 2 heights, 700 and 350 hPa, from daytime swaths for the period August 1-September 30, 2000, the SAFARI 2000 Dry Season Campaign.
ABSTRACT: The MOPITT (Measurements Of Pollution In The Troposphere) instrument on the NASA Terra Satellite makes measurements of infrared radiation originating from the surface of the planet and isolates the energy being radiated from carbon monoxide (CO). By using appropriate data analysis techniques, concentration profiles of CO (Level-2 (L2) data) can be obtained on a global basis at a reasonably high horizontal (~22km) and vertical resolution (~3km).The MOPITT Level-3 (L3) data products provided in this data set are a subset of the daily averages from the L2 data. This subset was produced by overlaying a global 1x1-degree grid onto the L2 data, and then clipping the data to this southern Africa subset which originates at 5 degrees longitude and -35 degrees latitude and extends to 60 degrees longitude and 35 degrees latitude. Data are reported for 2 heights, 700 and 350 hPa, from daytime swaths for the period August 1-September 30, 2000, the SAFARI 2000 Dry Season Campaign.
The National Botanical Institute (NBI) has mapped woody plant species distribution to provide estimates of individual species contribution to peak leaf area index for designated vegetation types in southern Africa (Rutherford et al., 2000). The target was to account for 80% of the woody vegetation leaf area in terms of named species, for 80% of the surface area of Africa south of the equator. The data sources include published and unpublished species lists for vegetation types and individual sample plots, with the species contribution estimated by local experts in terms of dominants and subdominants. Source maps include: Low and Rebelo (1998); Giess (1971); Wild and Barbosa (1968); Barbosa (1970); and White (1983). Each source map delineates a wide variety of land cover categories that differ from region to region. Because vegetation discontinuities exist along some of the regional borders and a perfectly continuous regional map could not be achieved within the timeframe and budget of the project, the final map is made up of six independent sub-regional maps. A cross-referenced database of woody plant species, in order of species dominance, associated with all mapped units is provided.The data set contains six GIS shapefile archives, each containing a shape file for a given region in southern Africa on a 5 x 5 degree grid. An accompanying ASCII file contains the species list associated with the map files. The regional NBI Vegetation Map (a compilation of the 6 independent sub-regional coverages) is provided as a JPEG image.
The National Botanical Institute (NBI) has mapped woody plant species distribution to provide estimates of individual species contribution to peak leaf area index for designated vegetation types in southern Africa (Rutherford et al., 2000). The target was to account for 80% of the woody vegetation leaf area in terms of named species, for 80% of the surface area of Africa south of the equator. The data sources include published and unpublished species lists for vegetation types and individual sample plots, with the species contribution estimated by local experts in terms of dominants and subdominants. Source maps include: Low and Rebelo (1998); Giess (1971); Wild and Barbosa (1968); Barbosa (1970); and White (1983). Each source map delineates a wide variety of land cover categories that differ from region to region. Because vegetation discontinuities exist along some of the regional borders and a perfectly continuous regional map could not be achieved within the timeframe and budget of the project, the final map is made up of six independent sub-regional maps. A cross-referenced database of woody plant species, in order of species dominance, associated with all mapped units is provided.The data set contains six GIS shapefile archives, each containing a shape file for a given region in southern Africa on a 5 x 5 degree grid. An accompanying ASCII file contains the species list associated with the map files. The regional NBI Vegetation Map (a compilation of the 6 independent sub-regional coverages) is provided as a JPEG image.
ABSTRACT: The National Botanical Institute (NBI) has mapped woody plant species distribution to provide estimates of individual species contribution to peak leaf area index for designated vegetation types in southern Africa (Rutherford et al., 2000). The target was to account for 80% of the woody vegetation leaf area in terms of named species, for 80% of the surface area of Africa south of the equator. The data sources include published and unpublished species lists for vegetation types and individual sample plots, with the species contribution estimated by local experts in terms of dominants and subdominants. Source maps include: Low and Rebelo (1998); Giess (1971); Wild and Barbosa (1968); Barbosa (1970); and White (1983). Each source map delineates a wide variety of land cover categories that differ from region to region. Because vegetation discontinuities exist along some of the regional borders and a perfectly continuous regional map could not be achieved within the timeframe and budget of the project, the final map is made up of six independent sub-regional maps. A cross-referenced database of woody plant species, in order of species dominance, associated with all mapped units is provided.The data set contains six GIS shapefile archives, each containing a shape file for a given region in southern Africa on a 5 x 5 degree grid. An accompanying ASCII file contains the species list associated with the map files. The regional NBI Vegetation Map (a compilation of the 6 independent sub-regional coverages) is provided as a JPEG image.
This data set contains a subset of the Worldwide Organic Soil Carbon and Nitrogen (Zinke et al. 1986) data set for southern Africa. The data were obtained from soil surveys by Zinke and soil survey literature. The main samples for laboratory analyses were collected at uniform soil increments and included bulk density determinations.&
This data set contains a subset of the Worldwide Organic Soil Carbon and Nitrogen (Zinke et al. 1986) data set for southern Africa. The data were obtained from soil surveys by Zinke and soil survey literature. The main samples for laboratory analyses were collected at uniform soil increments and included bulk density determinations.&
ABSTRACT: This data set contains a subset of the Worldwide Organic Soil Carbon and Nitrogen (Zinke et al. 1986) data set for southern Africa. The data were obtained from soil surveys by Zinke and soil survey literature. The main samples for laboratory analyses were collected at uniform soil increments and included bulk density determinations.&
This data set was collected during February-March 2000 wet season and September 2000 dry season field campaigns of SAFARI 2000. Mongu in Zambia and Pandematenga (aka Kasane) and Tshane in Botswana were visited during the wet season campaign. Dry season data are for Mongu only. Hemispherical photographs, from which Plant Area Index (PAI) estimates are derived, were obtained at the field sites to characterize vegetation structural changes along the Kalahari Transect. The photographs are classified into sky and vegetation (trunk, green and senescent leaves, and branches) using an unsupervised classification scheme.
This data set was collected during February-March 2000 wet season and September 2000 dry season field campaigns of SAFARI 2000. Mongu in Zambia and Pandematenga (aka Kasane) and Tshane in Botswana were visited during the wet season campaign. Dry season data are for Mongu only. Hemispherical photographs, from which Plant Area Index (PAI) estimates are derived, were obtained at the field sites to characterize vegetation structural changes along the Kalahari Transect. The photographs are classified into sky and vegetation (trunk, green and senescent leaves, and branches) using an unsupervised classification scheme.
ABSTRACT: This data set was collected during February-March 2000 wet season and September 2000 dry season field campaigns of SAFARI 2000. Mongu in Zambia and Pandematenga (aka Kasane) and Tshane in Botswana were visited during the wet season campaign. Dry season data are for Mongu only. Hemispherical photographs, from which Plant Area Index (PAI) estimates are derived, were obtained at the field sites to characterize vegetation structural changes along the Kalahari Transect. The photographs are classified into sky and vegetation (trunk, green and senescent leaves, and branches) using an unsupervised classification scheme.
Ceptometer data from a Decagon AccuPAR (Model PAR-80) were collected at four sites in Botswana during the SAFARI 2000 Kalahari Transect Wet Season Campaign (March, 2000). These sites include Maun, Pandamentanga, Ghanzi/Okwa River Crossing, and Tshane. The measurements were taken near stake flags placed at 25 m intervals along three parallel 750 m transects located 250 m apart. The ceptometer contains 80 photosynthetically active radiation (PAR) sensors fixed at 1 cm intervals along a wand and connected to a control box. The sampling protocol followed in general was to first measure above canopy incident PAR, then canopy reflected PAR, then above canopy incident PAR again, and finally, canopy transmitted PAR. The data can be used to compute fraction of photosynthetically active radiation (FPAR), intercepted PAR, leaf area index (LAI), and gap fraction. These data currently exist in raw format, but can be processed using manufacturer-provided software to estimate the derived products.The data are stored as ASCII files, in csv format, organized by site, with one file per transect. Incident, transmitted, and reflected PAR radiation values for a transect and site are in the same file. The type of measurement for each data point is known due to comments in the data files. For the Maun and Pandamatenga sites, there is an additional file containing above canopy PAR irradiance. The PAR data units are micromols m-2 s-1, and the time is in Local Time. There is also a readme file, in txt format, for each site.
Ceptometer data from a Decagon AccuPAR (Model PAR-80) were collected at four sites in Botswana during the SAFARI 2000 Kalahari Transect Wet Season Campaign (March, 2000). These sites include Maun, Pandamentanga, Ghanzi/Okwa River Crossing, and Tshane. The measurements were taken near stake flags placed at 25 m intervals along three parallel 750 m transects located 250 m apart. The ceptometer contains 80 photosynthetically active radiation (PAR) sensors fixed at 1 cm intervals along a wand and connected to a control box. The sampling protocol followed in general was to first measure above canopy incident PAR, then canopy reflected PAR, then above canopy incident PAR again, and finally, canopy transmitted PAR. The data can be used to compute fraction of photosynthetically active radiation (FPAR), intercepted PAR, leaf area index (LAI), and gap fraction. These data currently exist in raw format, but can be processed using manufacturer-provided software to estimate the derived products.The data are stored as ASCII files, in csv format, organized by site, with one file per transect. Incident, transmitted, and reflected PAR radiation values for a transect and site are in the same file. The type of measurement for each data point is known due to comments in the data files. For the Maun and Pandamatenga sites, there is an additional file containing above canopy PAR irradiance. The PAR data units are micromols m-2 s-1, and the time is in Local Time. There is also a readme file, in txt format, for each site.
ABSTRACT: Ceptometer data from a Decagon AccuPAR (Model PAR-80) were collected at four sites in Botswana during the SAFARI 2000 Kalahari Transect Wet Season Campaign (March, 2000). These sites include Maun, Pandamentanga, Ghanzi/Okwa River Crossing, and Tshane. The measurements were taken near stake flags placed at 25 m intervals along three parallel 750 m transects located 250 m apart. The ceptometer contains 80 photosynthetically active radiation (PAR) sensors fixed at 1 cm intervals along a wand and connected to a control box. The sampling protocol followed in general was to first measure above canopy incident PAR, then canopy reflected PAR, then above canopy incident PAR again, and finally, canopy transmitted PAR. The data can be used to compute fraction of photosynthetically active radiation (FPAR), intercepted PAR, leaf area index (LAI), and gap fraction. These data currently exist in raw format, but can be processed using manufacturer-provided software to estimate the derived products.The data are stored as ASCII files, in csv format, organized by site, with one file per transect. Incident, transmitted, and reflected PAR radiation values for a transect and site are in the same file. The type of measurement for each data point is known due to comments in the data files. For the Maun and Pandamatenga sites, there is an additional file containing above canopy PAR irradiance. The PAR data units are micromols m-2 s-1, and the time is in Local Time. There is also a readme file, in txt format, for each site.
SAFARI 2000 provided an opportunity to study aerosol particles produced by savanna burning. We used analytical transmission electron microscopy (TEM), including energy-dispersive X-ray spectrometry (EDS) and electron energy-loss spectroscopy (EELS), to study aerosol particles from several smoke and haze samples and from a set of cloud samples. These aerosol particle samples were collected using the University of Washington Convair CV-580 research aircraft (Posfai et al., 2003).
SAFARI 2000 provided an opportunity to study aerosol particles produced by savanna burning. We used analytical transmission electron microscopy (TEM), including energy-dispersive X-ray spectrometry (EDS) and electron energy-loss spectroscopy (EELS), to study aerosol particles from several smoke and haze samples and from a set of cloud samples. These aerosol particle samples were collected using the University of Washington Convair CV-580 research aircraft (Posfai et al., 2003).
ABSTRACT: SAFARI 2000 provided an opportunity to study aerosol particles produced by savanna burning. We used analytical transmission electron microscopy (TEM), including energy-dispersive X-ray spectrometry (EDS) and electron energy-loss spectroscopy (EELS), to study aerosol particles from several smoke and haze samples and from a set of cloud samples. These aerosol particle samples were collected using the University of Washington Convair CV-580 research aircraft (Posfai et al., 2003).
This data set contains measurements of the concentration and stable carbon (13C/12C) and nitrogen (15N/14N) isotope ratios of plant (leaves, roots and fungi) and soil samples from southern Africa. The study sites in Zambia, Botswana, Namibia, and South Africa are located along the Kalahari Transect precipitation gradient. Some of the sites were relatively undisturbed while others had different intensities of cultivation, domestic grazing, and fires. The data were collected to detect patterns of N cycling along precipitation and grazing gradients, including N2 fixation by legumes. Data from different multiple projects are included. The plants and soils were sampled mainly in the wet season of years 1995, 1999, and 2000, with most of the data collected during the SAFARI 2000 Kalahari Wet Season Field Campaign in February and March of 2000. Some grass samples were collected in the dry season of year 2000 (from Mongu-dambo and Sua Pan grassland sites). Soil and plant samples were analyzed in a laboratory for %C, %N, d13C, and d15N with an Optima isotope ratio mass spectrometer coupled to an elemental analyzer. The stable isotope ratios are expressed using standard delta notation in units per mil. The isotope ratios are expressed relative to the international standard PDB (Pee Dee Belemnite) for carbon and atmospheric N2 for nitrogen samples. The carbon and nitrogen contents are expressed in percentage weight of the dry sample.The data files contain numerical and character fields of varying length separated by commas (.csv format).
This data set contains measurements of the concentration and stable carbon (13C/12C) and nitrogen (15N/14N) isotope ratios of plant (leaves, roots and fungi) and soil samples from southern Africa. The study sites in Zambia, Botswana, Namibia, and South Africa are located along the Kalahari Transect precipitation gradient. Some of the sites were relatively undisturbed while others had different intensities of cultivation, domestic grazing, and fires. The data were collected to detect patterns of N cycling along precipitation and grazing gradients, including N2 fixation by legumes. Data from different multiple projects are included. The plants and soils were sampled mainly in the wet season of years 1995, 1999, and 2000, with most of the data collected during the SAFARI 2000 Kalahari Wet Season Field Campaign in February and March of 2000. Some grass samples were collected in the dry season of year 2000 (from Mongu-dambo and Sua Pan grassland sites). Soil and plant samples were analyzed in a laboratory for %C, %N, d13C, and d15N with an Optima isotope ratio mass spectrometer coupled to an elemental analyzer. The stable isotope ratios are expressed using standard delta notation in units per mil. The isotope ratios are expressed relative to the international standard PDB (Pee Dee Belemnite) for carbon and atmospheric N2 for nitrogen samples. The carbon and nitrogen contents are expressed in percentage weight of the dry sample.The data files contain numerical and character fields of varying length separated by commas (.csv format).
ABSTRACT: This data set contains measurements of the concentration and stable carbon (13C/12C) and nitrogen (15N/14N) isotope ratios of plant (leaves, roots and fungi) and soil samples from southern Africa. The study sites in Zambia, Botswana, Namibia, and South Africa are located along the Kalahari Transect precipitation gradient. Some of the sites were relatively undisturbed while others had different intensities of cultivation, domestic grazing, and fires. The data were collected to detect patterns of N cycling along precipitation and grazing gradients, including N2 fixation by legumes. Data from different multiple projects are included. The plants and soils were sampled mainly in the wet season of years 1995, 1999, and 2000, with most of the data collected during the SAFARI 2000 Kalahari Wet Season Field Campaign in February and March of 2000. Some grass samples were collected in the dry season of year 2000 (from Mongu-dambo and Sua Pan grassland sites). Soil and plant samples were analyzed in a laboratory for %C, %N, d13C, and d15N with an Optima isotope ratio mass spectrometer coupled to an elemental analyzer. The stable isotope ratios are expressed using standard delta notation in units per mil. The isotope ratios are expressed relative to the international standard PDB (Pee Dee Belemnite) for carbon and atmospheric N2 for nitrogen samples. The carbon and nitrogen contents are expressed in percentage weight of the dry sample.The data files contain numerical and character fields of varying length separated by commas (.csv format).
This data set consists of a southern African subset of the 5-min resolution Global Potential Vegetation data set developed by Navin Ramankutty and Jon Foley at the University of Wisconsin. Data are available in both ASCII GRID and binary image file formats.
This data set consists of a southern African subset of the 5-min resolution Global Potential Vegetation data set developed by Navin Ramankutty and Jon Foley at the University of Wisconsin. Data are available in both ASCII GRID and binary image file formats.
ABSTRACT: This data set consists of a southern African subset of the 5-min resolution Global Potential Vegetation data set developed by Navin Ramankutty and Jon Foley at the University of Wisconsin. Data are available in both ASCII GRID and binary image file formats.
The main goal of this study was to analyze the possibility of estimating combustion completeness based on fire-induced spectral reflectance changes of surface features by the development of relationships between combustion completeness and pre-fire to post-fire spectral reflectance changes, in the green, red, and near-infrared spectral domains (equivalent to Landsat ETM+ channels 2, 3, and 4).
The main goal of this study was to analyze the possibility of estimating combustion completeness based on fire-induced spectral reflectance changes of surface features by the development of relationships between combustion completeness and pre-fire to post-fire spectral reflectance changes, in the green, red, and near-infrared spectral domains (equivalent to Landsat ETM+ channels 2, 3, and 4).
ABSTRACT: The main goal of this study was to analyze the possibility of estimating combustion completeness based on fire-induced spectral reflectance changes of surface features by the development of relationships between combustion completeness and pre-fire to post-fire spectral reflectance changes, in the green, red, and near-infrared spectral domains (equivalent to Landsat ETM+ channels 2, 3, and 4).
The goal of this study was to understand the change in reflectance caused by the action of fire and the heterogeneity of fire effects (i.e., the fraction of the observation that burned and the combustion completeness of that observation). A spectral mixture model and field and satellite observations were used to compare changes in Landsat reflectance associated with fire and combustion completeness derived from field measurements at prescribed fire sites in South Africa and to substantiate and illustrate the model findings. The data are stored in a single ASCII file in comma-separate-value format (.csv).
The goal of this study was to understand the change in reflectance caused by the action of fire and the heterogeneity of fire effects (i.e., the fraction of the observation that burned and the combustion completeness of that observation). A spectral mixture model and field and satellite observations were used to compare changes in Landsat reflectance associated with fire and combustion completeness derived from field measurements at prescribed fire sites in South Africa and to substantiate and illustrate the model findings. The data are stored in a single ASCII file in comma-separate-value format (.csv).
ABSTRACT: The goal of this study was to understand the change in reflectance caused by the action of fire and the heterogeneity of fire effects (i.e., the fraction of the observation that burned and the combustion completeness of that observation). A spectral mixture model and field and satellite observations were used to compare changes in Landsat reflectance associated with fire and combustion completeness derived from field measurements at prescribed fire sites in South Africa and to substantiate and illustrate the model findings. The data are stored in a single ASCII file in comma-separate-value format (.csv).
This data set consists of a southern African subset of the Climate, People, and Environment Program (CPEP) Global River Discharge Data Set. The CPEP global river discharge data set is a compilation of monthly mean discharge data for over 2600 sites worldwide. The period of record is variable, from 3 years to greater than 100.
This data set consists of a southern African subset of the Climate, People, and Environment Program (CPEP) Global River Discharge Data Set. The CPEP global river discharge data set is a compilation of monthly mean discharge data for over 2600 sites worldwide. The period of record is variable, from 3 years to greater than 100.
ABSTRACT: This data set consists of a southern African subset of the Climate, People, and Environment Program (CPEP) Global River Discharge Data Set. The CPEP global river discharge data set is a compilation of monthly mean discharge data for over 2600 sites worldwide. The period of record is variable, from 3 years to greater than 100.
This data set contains Sea-viewing Wide Field-of-view Sensor (SeaWiFS) imagery for the eight core study sites of Mongu, Etosha, Kasangu, Skukuza, Mutoko, Mzola, Nampula, and Ndola. There are two main sets of local area coverage (LAC) data: Level-1 and Level-2 200-km x 200-km image subsets for seven of the sites and 400-km x 400-km image subsets for the Etosha site. The data are provided in HDF format files.
This data set contains Sea-viewing Wide Field-of-view Sensor (SeaWiFS) imagery for the eight core study sites of Mongu, Etosha, Kasangu, Skukuza, Mutoko, Mzola, Nampula, and Ndola. There are two main sets of local area coverage (LAC) data: Level-1 and Level-2 200-km x 200-km image subsets for seven of the sites and 400-km x 400-km image subsets for the Etosha site. The data are provided in HDF format files.
ABSTRACT: This data set contains Sea-viewing Wide Field-of-view Sensor (SeaWiFS) imagery for the eight core study sites of Mongu, Etosha, Kasangu, Skukuza, Mutoko, Mzola, Nampula, and Ndola. There are two main sets of local area coverage (LAC) data: Level-1 and Level-2 200-km x 200-km image subsets for seven of the sites and 400-km x 400-km image subsets for the Etosha site. The data are provided in HDF format files.
This data set contains Sea-viewing Wide Field-of-view Sensor (SeaWiFS) imagery for the southern African region. These images are Level-1a swaths of the southern African region selected from global area coverage (GAC) at 4.5-km resolution. The data are provided in HDF format files.
This data set contains Sea-viewing Wide Field-of-view Sensor (SeaWiFS) imagery for the southern African region. These images are Level-1a swaths of the southern African region selected from global area coverage (GAC) at 4.5-km resolution. The data are provided in HDF format files.
ABSTRACT: This data set contains Sea-viewing Wide Field-of-view Sensor (SeaWiFS) imagery for the southern African region. These images are Level-1a swaths of the southern African region selected from global area coverage (GAC) at 4.5-km resolution. The data are provided in HDF format files.
SAFARI Subset - GRIDDED SURFACES of SELECTED SOIL CHARACTERISTICS (IGBP-DIS). The data-surfaces pre-generated by SoilData, at a resolution fo 5x5 arc-minutes, in ASCII GRID format for ARC INFO and for the soil depth interval 0-100 cm.
SAFARI Subset - GRIDDED SURFACES of SELECTED SOIL CHARACTERISTICS (IGBP-DIS). The data-surfaces pre-generated by SoilData, at a resolution fo 5x5 arc-minutes, in ASCII GRID format for ARC INFO and for the soil depth interval 0-100 cm.
ABSTRACT: SAFARI Subset - GRIDDED SURFACES of SELECTED SOIL CHARACTERISTICS (IGBP-DIS). The data-surfaces pre-generated by SoilData, at a resolution fo 5x5 arc-minutes, in ASCII GRID format for ARC INFO and for the soil depth interval 0-100 cm.
Ozonesonde launches were made by the Southern Hemisphere ADditional OZonesondes (SHADOZ) group as part of the SAFARI 2000 Dry Season Campaign in September 2000 (Thompson et al., 2002). Ozonesondes are balloon-borne instruments measuring profile ozone, as well as temperature and pressure from an attached radiosonde, up to 35 km in height (around 5 hPa in pressure coordinates) capturing the troposphere and lower stratospheric portion of the atmosphere. During the campaign, ozonesondes were launched daily during the height of the burning season and in a region of active biomass burning activity.
Ozonesonde launches were made by the Southern Hemisphere ADditional OZonesondes (SHADOZ) group as part of the SAFARI 2000 Dry Season Campaign in September 2000 (Thompson et al., 2002). Ozonesondes are balloon-borne instruments measuring profile ozone, as well as temperature and pressure from an attached radiosonde, up to 35 km in height (around 5 hPa in pressure coordinates) capturing the troposphere and lower stratospheric portion of the atmosphere. During the campaign, ozonesondes were launched daily during the height of the burning season and in a region of active biomass burning activity.
ABSTRACT: Ozonesonde launches were made by the Southern Hemisphere ADditional OZonesondes (SHADOZ) group as part of the SAFARI 2000 Dry Season Campaign in September 2000 (Thompson et al., 2002). Ozonesondes are balloon-borne instruments measuring profile ozone, as well as temperature and pressure from an attached radiosonde, up to 35 km in height (around 5 hPa in pressure coordinates) capturing the troposphere and lower stratospheric portion of the atmosphere. During the campaign, ozonesondes were launched daily during the height of the burning season and in a region of active biomass burning activity.
This is a southern African subset of the ISRIC-WISE International soil profile data set.
This is a southern African subset of the ISRIC-WISE International soil profile data set.
ABSTRACT: This is a southern African subset of the ISRIC-WISE International soil profile data set.
Soil moisture and temperature profile sensors were deployed at flux tower sites in Mongu, Zambia and Skukuza, South Africa. In addition, thermal infrared sensors were deployed to monitor surface temperature at the sites, and soil samples were collected for physical property analysis. A heat-flux plate was also installed at 10 cm depth at the Mongu site. The data cover the period variously from August, 1999 to December, 2001.At the Mongu site, three profiles of soil moisture and temperature were obtained to a maximum depth of 125 cm. These profiles were located approximately 30 meters north of the Mongu flux tower, within the Kataba Local Forest. Surface radiometric temperature was measured by thermal infrared sensors deployed on top of the 30-meter tower and on a tree.  At the Skukuza site, two profiles of soil moisture and temperature were obtained to a maximum depth of 40 cm in a Combretum stand. The radiometric temperature of the tree crown and the background surface were monitored by infrared thermocouple sensors deployed on a pole at 2.5 m and 5 m heights. Soil samples were collected at different depths in the vicinity of the soil profiles at each site and were analyzed at CSIR in Pretoria to determine bulk density, texture, and particle size distribution. The data files are stored as ASCII text files, in comma-separated-value (.csv) format. Associated with each data file is a metadata (.txt ) file. Among other information, the metadata files indicate periods of missing data.
Soil moisture and temperature profile sensors were deployed at flux tower sites in Mongu, Zambia and Skukuza, South Africa. In addition, thermal infrared sensors were deployed to monitor surface temperature at the sites, and soil samples were collected for physical property analysis. A heat-flux plate was also installed at 10 cm depth at the Mongu site. The data cover the period variously from August, 1999 to December, 2001.At the Mongu site, three profiles of soil moisture and temperature were obtained to a maximum depth of 125 cm. These profiles were located approximately 30 meters north of the Mongu flux tower, within the Kataba Local Forest. Surface radiometric temperature was measured by thermal infrared sensors deployed on top of the 30-meter tower and on a tree.  At the Skukuza site, two profiles of soil moisture and temperature were obtained to a maximum depth of 40 cm in a Combretum stand. The radiometric temperature of the tree crown and the background surface were monitored by infrared thermocouple sensors deployed on a pole at 2.5 m and 5 m heights. Soil samples were collected at different depths in the vicinity of the soil profiles at each site and were analyzed at CSIR in Pretoria to determine bulk density, texture, and particle size distribution. The data files are stored as ASCII text files, in comma-separated-value (.csv) format. Associated with each data file is a metadata (.txt ) file. Among other information, the metadata files indicate periods of missing data.
ABSTRACT: Soil moisture and temperature profile sensors were deployed at flux tower sites in Mongu, Zambia and Skukuza, South Africa. In addition, thermal infrared sensors were deployed to monitor surface temperature at the sites, and soil samples were collected for physical property analysis. A heat-flux plate was also installed at 10 cm depth at the Mongu site. The data cover the period variously from August, 1999 to December, 2001.At the Mongu site, three profiles of soil moisture and temperature were obtained to a maximum depth of 125 cm. These profiles were located approximately 30 meters north of the Mongu flux tower, within the Kataba Local Forest. Surface radiometric temperature was measured by thermal infrared sensors deployed on top of the 30-meter tower and on a tree.  At the Skukuza site, two profiles of soil moisture and temperature were obtained to a maximum depth of 40 cm in a Combretum stand. The radiometric temperature of the tree crown and the background surface were monitored by infrared thermocouple sensors deployed on a pole at 2.5 m and 5 m heights. Soil samples were collected at different depths in the vicinity of the soil profiles at each site and were analyzed at CSIR in Pretoria to determine bulk density, texture, and particle size distribution. The data files are stored as ASCII text files, in comma-separated-value (.csv) format. Associated with each data file is a metadata (.txt ) file. Among other information, the metadata files indicate periods of missing data.
A SAFARI 2000 data set of soil types is available at 0.5-degree latitude by 0.5-degree longitude resolution. There are 106 soil units, based on Zobler's (1986) assessment of the FAO/UNESCO Soil Map of the World. This data set is a conversion of the Zobler 1-degree resolution version to a 0.5-degree resolution. The resolution of the data set was not actually increased. Rather, the 1-degree squares were divided into four 0.5-degree squares with the necessary adjustment of continental boundaries and islands.
A SAFARI 2000 data set of soil types is available at 0.5-degree latitude by 0.5-degree longitude resolution. There are 106 soil units, based on Zobler's (1986) assessment of the FAO/UNESCO Soil Map of the World. This data set is a conversion of the Zobler 1-degree resolution version to a 0.5-degree resolution. The resolution of the data set was not actually increased. Rather, the 1-degree squares were divided into four 0.5-degree squares with the necessary adjustment of continental boundaries and islands.
ABSTRACT: A SAFARI 2000 data set of soil types is available at 0.5-degree latitude by 0.5-degree longitude resolution. There are 106 soil units, based on Zobler's (1986) assessment of the FAO/UNESCO Soil Map of the World. This data set is a conversion of the Zobler 1-degree resolution version to a 0.5-degree resolution. The resolution of the data set was not actually increased. Rather, the 1-degree squares were divided into four 0.5-degree squares with the necessary adjustment of continental boundaries and islands.
The Solar Spectral Flux Radiometer (SSFR) was deployed on the University of Washington CV-580 during the dry season component of the Southern African Regional Science Initiative, August 1 - September 20, 2000. The SSFR made simultaneous measurements of both downwelling and upwelling net solar spectral irradiance at varying flight levels.  Data have been provided for twenty flights in netcdf format for the period August 17 - September 16, 2000.For a complete detailed guide to the extensive measurements obtained aboard the UW Convair-580 aircraft in support of SAFARI 2000, see the UW Technical Report for the SAFARI 2000 Project.
The Solar Spectral Flux Radiometer (SSFR) was deployed on the University of Washington CV-580 during the dry season component of the Southern African Regional Science Initiative, August 1 - September 20, 2000. The SSFR made simultaneous measurements of both downwelling and upwelling net solar spectral irradiance at varying flight levels.  Data have been provided for twenty flights in netcdf format for the period August 17 - September 16, 2000.For a complete detailed guide to the extensive measurements obtained aboard the UW Convair-580 aircraft in support of SAFARI 2000, see the UW Technical Report for the SAFARI 2000 Project.
ABSTRACT: The Solar Spectral Flux Radiometer (SSFR) was deployed on the University of Washington CV-580 during the dry season component of the Southern African Regional Science Initiative, August 1 - September 20, 2000. The SSFR made simultaneous measurements of both downwelling and upwelling net solar spectral irradiance at varying flight levels.  Data have been provided for twenty flights in netcdf format for the period August 17 - September 16, 2000.For a complete detailed guide to the extensive measurements obtained aboard the UW Convair-580 aircraft in support of SAFARI 2000, see the UW Technical Report for the SAFARI 2000 Project.
The GPROF 6.0 Pentads data set contains 5-day (pentad) averages of the GPROF 6.0 Gridded Orbits. The GPROF(Goddard Profiling Algorithm) data set contains a suite of 9 products providing instantaneous, gridded values of precipitation totals for each granule of the SSM/I (Special Sensor Microwave/Imager) data over the roughly 14-year period July 1987 through the present. Even though there have been at least two satellites for the entire period, sampling is sufficiently sparse that the data are averaged for pentads, then the pentads are smoothed with a 1-2-3-2-1 time-weighting. The last two pentads are unevenly weighted since the last (or last two) pentads in the average are not yet available. Consequently, the last two pentads must be recomputed when the next pentad becomes available.The data set prepared for SAFARI cover the years 1999, 2000, and 2001.The main refereed citations for the data set are Kummerow et al. (1996)and Olson et al. (1999)
The GPROF 6.0 Pentads data set contains 5-day (pentad) averages of the GPROF 6.0 Gridded Orbits. The GPROF(Goddard Profiling Algorithm) data set contains a suite of 9 products providing instantaneous, gridded values of precipitation totals for each granule of the SSM/I (Special Sensor Microwave/Imager) data over the roughly 14-year period July 1987 through the present. Even though there have been at least two satellites for the entire period, sampling is sufficiently sparse that the data are averaged for pentads, then the pentads are smoothed with a 1-2-3-2-1 time-weighting. The last two pentads are unevenly weighted since the last (or last two) pentads in the average are not yet available. Consequently, the last two pentads must be recomputed when the next pentad becomes available.The data set prepared for SAFARI cover the years 1999, 2000, and 2001.The main refereed citations for the data set are Kummerow et al. (1996)and Olson et al. (1999)
ABSTRACT: The GPROF 6.0 Pentads data set contains 5-day (pentad) averages of the GPROF 6.0 Gridded Orbits. The GPROF(Goddard Profiling Algorithm) data set contains a suite of 9 products providing instantaneous, gridded values of precipitation totals for each granule of the SSM/I (Special Sensor Microwave/Imager) data over the roughly 14-year period July 1987 through the present. Even though there have been at least two satellites for the entire period, sampling is sufficiently sparse that the data are averaged for pentads, then the pentads are smoothed with a 1-2-3-2-1 time-weighting. The last two pentads are unevenly weighted since the last (or last two) pentads in the average are not yet available. Consequently, the last two pentads must be recomputed when the next pentad becomes available.The data set prepared for SAFARI cover the years 1999, 2000, and 2001.The main refereed citations for the data set are Kummerow et al. (1996)and Olson et al. (1999)
This data set provides species distribution, basal area, height, and crown cover of woody stems at 10 sites along the Kalahari Transect where a large gradient in both the mean and variation of annual rainfall results in dramatic changes in vegetation structure. Some of the data were collected during earlier Kalahari Transect projects in 1995 and 1997 at Vastrap, South Africa; Sandveld and Sachinga, Namibia; and Maziba, Senanga, and Lukulu, Zambia. The rest of the data were collected at Mongu, Zambia; and Pandamatenga, Maun, and Tshane, Botswana during the February-March 2000 wet season field campaign of SAFARI 2000. Stem maps were generated at each site using a variable-width belt-transect approach. Tree location, species, diameter, height, and major and minor axis of crown dimensions were measured for each individual taller than 1.5 meters. For multi-stemmed individuals, the diameter of each stem was recorded separately. Canopy area was calculated to be an ellipse defined by the two major axes of measurement. Canopy height was estimated using a clinometer. Biomass was calculated following Goodman (1990) as modified by Dowty (1999).There are two ASCII data files, in comma-delimited format. The stem map file contains records of living, dead, and cut stem allometry, canopy geometry, and biomass at the SAFARI sites. The species list file provides plant family, genus, and species names, numerical codes that correspond to the stem map file, and species common names in English and AFRICAANS.
This data set provides species distribution, basal area, height, and crown cover of woody stems at 10 sites along the Kalahari Transect where a large gradient in both the mean and variation of annual rainfall results in dramatic changes in vegetation structure. Some of the data were collected during earlier Kalahari Transect projects in 1995 and 1997 at Vastrap, South Africa; Sandveld and Sachinga, Namibia; and Maziba, Senanga, and Lukulu, Zambia. The rest of the data were collected at Mongu, Zambia; and Pandamatenga, Maun, and Tshane, Botswana during the February-March 2000 wet season field campaign of SAFARI 2000. Stem maps were generated at each site using a variable-width belt-transect approach. Tree location, species, diameter, height, and major and minor axis of crown dimensions were measured for each individual taller than 1.5 meters. For multi-stemmed individuals, the diameter of each stem was recorded separately. Canopy area was calculated to be an ellipse defined by the two major axes of measurement. Canopy height was estimated using a clinometer. Biomass was calculated following Goodman (1990) as modified by Dowty (1999).There are two ASCII data files, in comma-delimited format. The stem map file contains records of living, dead, and cut stem allometry, canopy geometry, and biomass at the SAFARI sites. The species list file provides plant family, genus, and species names, numerical codes that correspond to the stem map file, and species common names in English and AFRICAANS.
ABSTRACT: This data set provides species distribution, basal area, height, and crown cover of woody stems at 10 sites along the Kalahari Transect where a large gradient in both the mean and variation of annual rainfall results in dramatic changes in vegetation structure. Some of the data were collected during earlier Kalahari Transect projects in 1995 and 1997 at Vastrap, South Africa; Sandveld and Sachinga, Namibia; and Maziba, Senanga, and Lukulu, Zambia. The rest of the data were collected at Mongu, Zambia; and Pandamatenga, Maun, and Tshane, Botswana during the February-March 2000 wet season field campaign of SAFARI 2000. Stem maps were generated at each site using a variable-width belt-transect approach. Tree location, species, diameter, height, and major and minor axis of crown dimensions were measured for each individual taller than 1.5 meters. For multi-stemmed individuals, the diameter of each stem was recorded separately. Canopy area was calculated to be an ellipse defined by the two major axes of measurement. Canopy height was estimated using a clinometer. Biomass was calculated following Goodman (1990) as modified by Dowty (1999).There are two ASCII data files, in comma-delimited format. The stem map file contains records of living, dead, and cut stem allometry, canopy geometry, and biomass at the SAFARI sites. The species list file provides plant family, genus, and species names, numerical codes that correspond to the stem map file, and species common names in English and AFRICAANS.
Top-of-the-canopy broadband albedo and radiation fluxes are calculated from measurements at the Mongu and Skukuza flux tower sites in southern Africa from March 2000 through December 2002. Data were collected by instrumentation deployed at the top of the 30 m tower in the Kataba Local Forest near Mongu, Zambia, and atop the 20 m tower at the Skukuza tower site in Kruger National Park, South Africa.  At the Mongu site, Kipp and Zonen albedometers housing both upward- and downward-looking pyranometers were outfitted with clear and red domes to collect broadband albedo and radiation fluxes in the shortwave (SW) and near-infrared  (NIR) wavebands, respectively. The data are mean values provided at 15-minute intervals for 2000-2002. At the Skukuza tower, Kipp and Zonen albedometers (also outfitted with clear and red domes) collected broadband albedo and radiation fluxes in the SW and NIR wavebands. In addition, a pyrgeometer was used to collect longwave radiation flux in thermal infrared (TIR) wavebands. The data at Skukuza are mean values provided at 30-minute intervals for 2000-2002, except for the TIR data, which are provided for 2001 and 2002 only. For both sites, photosynthetically active radiation can be calculated from measurements.The data are provided in comma-delimited ASCII files, with column headers. The SW and NIR data for both sites are provided in one file per year per site for 2000-2002. The Skukuza longwave data are provided separately, and for years 2001 and 2002 only.
Top-of-the-canopy broadband albedo and radiation fluxes are calculated from measurements at the Mongu and Skukuza flux tower sites in southern Africa from March 2000 through December 2002. Data were collected by instrumentation deployed at the top of the 30 m tower in the Kataba Local Forest near Mongu, Zambia, and atop the 20 m tower at the Skukuza tower site in Kruger National Park, South Africa.  At the Mongu site, Kipp and Zonen albedometers housing both upward- and downward-looking pyranometers were outfitted with clear and red domes to collect broadband albedo and radiation fluxes in the shortwave (SW) and near-infrared  (NIR) wavebands, respectively. The data are mean values provided at 15-minute intervals for 2000-2002. At the Skukuza tower, Kipp and Zonen albedometers (also outfitted with clear and red domes) collected broadband albedo and radiation fluxes in the SW and NIR wavebands. In addition, a pyrgeometer was used to collect longwave radiation flux in thermal infrared (TIR) wavebands. The data at Skukuza are mean values provided at 30-minute intervals for 2000-2002, except for the TIR data, which are provided for 2001 and 2002 only. For both sites, photosynthetically active radiation can be calculated from measurements.The data are provided in comma-delimited ASCII files, with column headers. The SW and NIR data for both sites are provided in one file per year per site for 2000-2002. The Skukuza longwave data are provided separately, and for years 2001 and 2002 only.
ABSTRACT: Top-of-the-canopy broadband albedo and radiation fluxes are calculated from measurements at the Mongu and Skukuza flux tower sites in southern Africa from March 2000 through December 2002. Data were collected by instrumentation deployed at the top of the 30 m tower in the Kataba Local Forest near Mongu, Zambia, and atop the 20 m tower at the Skukuza tower site in Kruger National Park, South Africa.  At the Mongu site, Kipp and Zonen albedometers housing both upward- and downward-looking pyranometers were outfitted with clear and red domes to collect broadband albedo and radiation fluxes in the shortwave (SW) and near-infrared  (NIR) wavebands, respectively. The data are mean values provided at 15-minute intervals for 2000-2002. At the Skukuza tower, Kipp and Zonen albedometers (also outfitted with clear and red domes) collected broadband albedo and radiation fluxes in the SW and NIR wavebands. In addition, a pyrgeometer was used to collect longwave radiation flux in thermal infrared (TIR) wavebands. The data at Skukuza are mean values provided at 30-minute intervals for 2000-2002, except for the TIR data, which are provided for 2001 and 2002 only. For both sites, photosynthetically active radiation can be calculated from measurements.The data are provided in comma-delimited ASCII files, with column headers. The SW and NIR data for both sites are provided in one file per year per site for 2000-2002. The Skukuza longwave data are provided separately, and for years 2001 and 2002 only.
Surface-sensing Measurements for Radiative Transfer (SMART) and Chemical, Optical, and Microphysical Measurements of In-situ Troposphere (COMMIT) consist of a suite of instruments that measure (both in-situ and by remote sensing) parameters that help to characterize, as completely as possible, constituents of the atmosphere at a given location. SMART and COMMIT are mobile systems that can be deployed to locations that exhibit interesting atmospheric phenomena. This allows investigators to participate in coordinated measurement campaigns, such as SAFARI 2000.The SMART instruments were deployed to the Skukuza Airport from August 15 to September 17, 2000 to take part in the SAFARI 2000 Dry Season Aircraft Campaign. The SMART-COMMIT mission is designed to pursue the following goals: Earth Observing System (EOS) validation; innovative investigations; and long-term atmospheric monitoring. The results reported in this data set are for the following instruments deployed and measurements recorded at the Skukuza Airport site within the Kruger National Park: several broadband radiometers, for global, diffuse, direct downward solar irradiance and global infrared downward irradiance; meteorological sensors, for surface air temperature, pressure, relative humidity, and wind; and a Solar Spectral Flux Radiometer (NASA Ames) for spectral solar downward irradiance.
Surface-sensing Measurements for Radiative Transfer (SMART) and Chemical, Optical, and Microphysical Measurements of In-situ Troposphere (COMMIT) consist of a suite of instruments that measure (both in-situ and by remote sensing) parameters that help to characterize, as completely as possible, constituents of the atmosphere at a given location. SMART and COMMIT are mobile systems that can be deployed to locations that exhibit interesting atmospheric phenomena. This allows investigators to participate in coordinated measurement campaigns, such as SAFARI 2000.The SMART instruments were deployed to the Skukuza Airport from August 15 to September 17, 2000 to take part in the SAFARI 2000 Dry Season Aircraft Campaign. The SMART-COMMIT mission is designed to pursue the following goals: Earth Observing System (EOS) validation; innovative investigations; and long-term atmospheric monitoring. The results reported in this data set are for the following instruments deployed and measurements recorded at the Skukuza Airport site within the Kruger National Park: several broadband radiometers, for global, diffuse, direct downward solar irradiance and global infrared downward irradiance; meteorological sensors, for surface air temperature, pressure, relative humidity, and wind; and a Solar Spectral Flux Radiometer (NASA Ames) for spectral solar downward irradiance.
ABSTRACT: Surface-sensing Measurements for Radiative Transfer (SMART) and Chemical, Optical, and Microphysical Measurements of In-situ Troposphere (COMMIT) consist of a suite of instruments that measure (both in-situ and by remote sensing) parameters that help to characterize, as completely as possible, constituents of the atmosphere at a given location. SMART and COMMIT are mobile systems that can be deployed to locations that exhibit interesting atmospheric phenomena. This allows investigators to participate in coordinated measurement campaigns, such as SAFARI 2000.The SMART instruments were deployed to the Skukuza Airport from August 15 to September 17, 2000 to take part in the SAFARI 2000 Dry Season Aircraft Campaign. The SMART-COMMIT mission is designed to pursue the following goals: Earth Observing System (EOS) validation; innovative investigations; and long-term atmospheric monitoring. The results reported in this data set are for the following instruments deployed and measurements recorded at the Skukuza Airport site within the Kruger National Park: several broadband radiometers, for global, diffuse, direct downward solar irradiance and global infrared downward irradiance; meteorological sensors, for surface air temperature, pressure, relative humidity, and wind; and a Solar Spectral Flux Radiometer (NASA Ames) for spectral solar downward irradiance.
This data set contains the top-of-canopy irradiance in the shortwave (0.3-2.8 micron) and photosynthetically active radiation (PAR; 0.4-0.7 micron) wavebands collected with an Eppley Precision Spectral Pyranometer (PSP) and a Skye SKE510 pyranometer, respectively. The instruments were deployed at the top of the 30-m tower in the Kataba Local Forest approximately 20 km south of Mongu in Western Province, Zambia. The data include the hourly mean and maximum values from 0500-1600 GMT (7 a.m. - 6 p.m. local time) and cover the period from September 4, 2000 to December 31, 2002. The data were obtained primarily for EOS validation and energy budget modeling.The Skye SKE510 uses a blue enhanced planar diffused silicon detector and has a fairly even response from 400 to 700 nm. The Eppley PSP is a World Meteorological Organization First Class Radiometer designed for the measurement of sun and sky radiation, totally or in defined broad wavelength bands. It comprises a circular multi-junction wire-wound thermopile. A data logger sampled the sensors at 60-second intervals and recorded the maximum and mean values every 60 minutes throughout the day.The data are contained within a single ASCII text file, in comma-separated-value format, with associated date, time, and QA information.
This data set contains the top-of-canopy irradiance in the shortwave (0.3-2.8 micron) and photosynthetically active radiation (PAR; 0.4-0.7 micron) wavebands collected with an Eppley Precision Spectral Pyranometer (PSP) and a Skye SKE510 pyranometer, respectively. The instruments were deployed at the top of the 30-m tower in the Kataba Local Forest approximately 20 km south of Mongu in Western Province, Zambia. The data include the hourly mean and maximum values from 0500-1600 GMT (7 a.m. - 6 p.m. local time) and cover the period from September 4, 2000 to December 31, 2002. The data were obtained primarily for EOS validation and energy budget modeling.The Skye SKE510 uses a blue enhanced planar diffused silicon detector and has a fairly even response from 400 to 700 nm. The Eppley PSP is a World Meteorological Organization First Class Radiometer designed for the measurement of sun and sky radiation, totally or in defined broad wavelength bands. It comprises a circular multi-junction wire-wound thermopile. A data logger sampled the sensors at 60-second intervals and recorded the maximum and mean values every 60 minutes throughout the day.The data are contained within a single ASCII text file, in comma-separated-value format, with associated date, time, and QA information.
ABSTRACT: This data set contains the top-of-canopy irradiance in the shortwave (0.3-2.8 micron) and photosynthetically active radiation (PAR; 0.4-0.7 micron) wavebands collected with an Eppley Precision Spectral Pyranometer (PSP) and a Skye SKE510 pyranometer, respectively. The instruments were deployed at the top of the 30-m tower in the Kataba Local Forest approximately 20 km south of Mongu in Western Province, Zambia. The data include the hourly mean and maximum values from 0500-1600 GMT (7 a.m. - 6 p.m. local time) and cover the period from September 4, 2000 to December 31, 2002. The data were obtained primarily for EOS validation and energy budget modeling.The Skye SKE510 uses a blue enhanced planar diffused silicon detector and has a fairly even response from 400 to 700 nm. The Eppley PSP is a World Meteorological Organization First Class Radiometer designed for the measurement of sun and sky radiation, totally or in defined broad wavelength bands. It comprises a circular multi-junction wire-wound thermopile. A data logger sampled the sensors at 60-second intervals and recorded the maximum and mean values every 60 minutes throughout the day.The data are contained within a single ASCII text file, in comma-separated-value format, with associated date, time, and QA information.
The Multi-angle Imaging SpectroRadiometer (MISR) Validation team was deployed to Sua Pan, a salt playa in the Magkadigkadi region of Botswana, from August 18 to September 4, 2000, during the SAFARI 2000 Dry Season Aircraft Campaign. The experiment was designed to collect data necessary for multi-angle top-of-atmosphere radiance predictions in order to provide a vicarious calibration of the MISR instrument aboard the Terra satellite. Reported here are ground-based reflectance measurements collected using an Analytical Spectral Devices (ASD) spectroradiometer at Sua Pan and adjacent grassland targets. The grasslands provided large homogeneous areas for comparison of scale between ground measurements and remote sensing results.Data files contain numeric values that represent mean reflectance over space (grassland) or wavelength range (pan), stored as ASCII files, one file per site, in comma-separated-value (.csv) format, with column headers. The Sua Pan data, collected over a 1 km x 2 km area, are presented as rows of mean reflectance (every 10 nm) for 20 points, where the mean represents the average local reflectance spectra collected within 150 m of the given latitude and longitude. The grassland data cover a 1 km2 area and are provided every nm from 1 to 2500. Each row of data contains a mean and standard deviation at a given wavelength, where the mean represents the average of 570 measurements taken over the 1 km2 area.Related data sets from Sua Pan provide ground measurements of BRDF, and LAI and FPAR (Helmlinger et al., 2004 and Buermann and Helmlinger, 2004, respectively).
The Multi-angle Imaging SpectroRadiometer (MISR) Validation team was deployed to Sua Pan, a salt playa in the Magkadigkadi region of Botswana, from August 18 to September 4, 2000, during the SAFARI 2000 Dry Season Aircraft Campaign. The experiment was designed to collect data necessary for multi-angle top-of-atmosphere radiance predictions in order to provide a vicarious calibration of the MISR instrument aboard the Terra satellite. Reported here are ground-based reflectance measurements collected using an Analytical Spectral Devices (ASD) spectroradiometer at Sua Pan and adjacent grassland targets. The grasslands provided large homogeneous areas for comparison of scale between ground measurements and remote sensing results.Data files contain numeric values that represent mean reflectance over space (grassland) or wavelength range (pan), stored as ASCII files, one file per site, in comma-separated-value (.csv) format, with column headers. The Sua Pan data, collected over a 1 km x 2 km area, are presented as rows of mean reflectance (every 10 nm) for 20 points, where the mean represents the average local reflectance spectra collected within 150 m of the given latitude and longitude. The grassland data cover a 1 km2 area and are provided every nm from 1 to 2500. Each row of data contains a mean and standard deviation at a given wavelength, where the mean represents the average of 570 measurements taken over the 1 km2 area.Related data sets from Sua Pan provide ground measurements of BRDF, and LAI and FPAR (Helmlinger et al., 2004 and Buermann and Helmlinger, 2004, respectively).
ABSTRACT: The Multi-angle Imaging SpectroRadiometer (MISR) Validation team was deployed to Sua Pan, a salt playa in the Magkadigkadi region of Botswana, from August 18 to September 4, 2000, during the SAFARI 2000 Dry Season Aircraft Campaign. The experiment was designed to collect data necessary for multi-angle top-of-atmosphere radiance predictions in order to provide a vicarious calibration of the MISR instrument aboard the Terra satellite. Reported here are ground-based reflectance measurements collected using an Analytical Spectral Devices (ASD) spectroradiometer at Sua Pan and adjacent grassland targets. The grasslands provided large homogeneous areas for comparison of scale between ground measurements and remote sensing results.Data files contain numeric values that represent mean reflectance over space (grassland) or wavelength range (pan), stored as ASCII files, one file per site, in comma-separated-value (.csv) format, with column headers. The Sua Pan data, collected over a 1 km x 2 km area, are presented as rows of mean reflectance (every 10 nm) for 20 points, where the mean represents the average local reflectance spectra collected within 150 m of the given latitude and longitude. The grassland data cover a 1 km2 area and are provided every nm from 1 to 2500. Each row of data contains a mean and standard deviation at a given wavelength, where the mean represents the average of 570 measurements taken over the 1 km2 area.Related data sets from Sua Pan provide ground measurements of BRDF, and LAI and FPAR (Helmlinger et al., 2004 and Buermann and Helmlinger, 2004, respectively).
Daily Aerosol Index (AI) data from Earth Probe (EP) Total Ozone Mapping Spectrometer (TOMS) for the period of August 12-September 25, 2000 were processed and provided by the Atmospheric Chemistry and Dynamics Branch at NASA/GSFC for the SAFARI 2000 Dry Season Aircraft Campaign.The TOMS AI is formed directly from measured TOMS radiances in two channels. It is a measure of how much the wavelength dependence of backscattered UV radiation from an atmosphere containing aerosols (Mie scattering, Rayleigh scattering, and absorption) differs from that of a pure molecular atmosphere (pure Rayleigh scattering). Quantitatively, the AI is defined at http://toms.gsfc.nasa.gov/aerosols/AI_definition/ai_ep_definition.pdf. Positive values represent absorbing aerosols (dust and smoke); negative values represent non-absorbing aerosols. The identification is not perfect because of geophysical reasons (e.g., when aerosols are too low to the ground).The data from TOMS records have been used increasingly to understand the behavior of aerosols within the atmosphere. The TOMS is the first instrument to allow observation of aerosols as the particles cross the land/sea boundary. Using these data it is possible to observe a wide range of phenomena such as desert dust storms, forest fires, and biomass burning.The TOMS AI data are a daily gridded Level-3 product (ASCII .dat format) that covers the area of 40 deg. S to the Equator and 40 deg. W to 80 deg. E. There is also a JPEG image of each data file.
Daily Aerosol Index (AI) data from Earth Probe (EP) Total Ozone Mapping Spectrometer (TOMS) for the period of August 12-September 25, 2000 were processed and provided by the Atmospheric Chemistry and Dynamics Branch at NASA/GSFC for the SAFARI 2000 Dry Season Aircraft Campaign.The TOMS AI is formed directly from measured TOMS radiances in two channels. It is a measure of how much the wavelength dependence of backscattered UV radiation from an atmosphere containing aerosols (Mie scattering, Rayleigh scattering, and absorption) differs from that of a pure molecular atmosphere (pure Rayleigh scattering). Quantitatively, the AI is defined at http://toms.gsfc.nasa.gov/aerosols/AI_definition/ai_ep_definition.pdf. Positive values represent absorbing aerosols (dust and smoke); negative values represent non-absorbing aerosols. The identification is not perfect because of geophysical reasons (e.g., when aerosols are too low to the ground).The data from TOMS records have been used increasingly to understand the behavior of aerosols within the atmosphere. The TOMS is the first instrument to allow observation of aerosols as the particles cross the land/sea boundary. Using these data it is possible to observe a wide range of phenomena such as desert dust storms, forest fires, and biomass burning.The TOMS AI data are a daily gridded Level-3 product (ASCII .dat format) that covers the area of 40 deg. S to the Equator and 40 deg. W to 80 deg. E. There is also a JPEG image of each data file.
ABSTRACT: Daily Aerosol Index (AI) data from Earth Probe (EP) Total Ozone Mapping Spectrometer (TOMS) for the period of August 12-September 25, 2000 were processed and provided by the Atmospheric Chemistry and Dynamics Branch at NASA/GSFC for the SAFARI 2000 Dry Season Aircraft Campaign.The TOMS AI is formed directly from measured TOMS radiances in two channels. It is a measure of how much the wavelength dependence of backscattered UV radiation from an atmosphere containing aerosols (Mie scattering, Rayleigh scattering, and absorption) differs from that of a pure molecular atmosphere (pure Rayleigh scattering). Quantitatively, the AI is defined at http://toms.gsfc.nasa.gov/aerosols/AI_definition/ai_ep_definition.pdf. Positive values represent absorbing aerosols (dust and smoke); negative values represent non-absorbing aerosols. The identification is not perfect because of geophysical reasons (e.g., when aerosols are too low to the ground).The data from TOMS records have been used increasingly to understand the behavior of aerosols within the atmosphere. The TOMS is the first instrument to allow observation of aerosols as the particles cross the land/sea boundary. Using these data it is possible to observe a wide range of phenomena such as desert dust storms, forest fires, and biomass burning.The TOMS AI data are a daily gridded Level-3 product (ASCII .dat format) that covers the area of 40 deg. S to the Equator and 40 deg. W to 80 deg. E. There is also a JPEG image of each data file.
Tropical Tropospheric Ozone (TTO) data from Earth Probe (EP) Total Ozone Mapping Spectrometer (TOMS) for the period of August 8-September 29, 2000 were processed and provided by the Atmospheric Chemistry and Dynamics Branch at NASA/GSFC for the SAFARI 2000 Dry Season Aircraft Campaign.The TTO measurement is derived from TOMS total ozone (Thompson and Hudson, 1999; Thompson et al., 2001) using the modified-residual method to separate stratospheric ozone from tropospheric ozone. The tropospheric ozone column thickness is reported in Dobson Units (DU).EP TOMS is currently the only NASA spacecraft on orbit specializing in ozone retrieval. EP TOMS was launched in 1996 into an orbit 500 km rather than the 950 km that was originally planned. The Earth Probe satellite was boosted to 740 km in 1997 when the ADEOS satellite failed. The lower orbit of EP TOMS decreased the size of the footprint of each measurement, which increased the resolution and also increased the ability to make measurements over cloudless scenes. This orbit was chosen to improve the ability of the TOMS instrument to make measurements of UV-absorbing aerosols in the troposphere and enhanced the capability of converting the TOMS aerosol measurements into geophysical quantities such as optical depth. Tropospheric aerosols play a major role in the Earth's climate and the capability to measure them from a TOMS instrument had recently been developed using data from Nimbus-7 and Meteor-3 TOMS.The TOMS Tropospheric Ozone data are 9-day averaged, gridded (1-degree by 2-degree) ASCII products. There is also a GIF image of each data file.
Tropical Tropospheric Ozone (TTO) data from Earth Probe (EP) Total Ozone Mapping Spectrometer (TOMS) for the period of August 8-September 29, 2000 were processed and provided by the Atmospheric Chemistry and Dynamics Branch at NASA/GSFC for the SAFARI 2000 Dry Season Aircraft Campaign.The TTO measurement is derived from TOMS total ozone (Thompson and Hudson, 1999; Thompson et al., 2001) using the modified-residual method to separate stratospheric ozone from tropospheric ozone. The tropospheric ozone column thickness is reported in Dobson Units (DU).EP TOMS is currently the only NASA spacecraft on orbit specializing in ozone retrieval. EP TOMS was launched in 1996 into an orbit 500 km rather than the 950 km that was originally planned. The Earth Probe satellite was boosted to 740 km in 1997 when the ADEOS satellite failed. The lower orbit of EP TOMS decreased the size of the footprint of each measurement, which increased the resolution and also increased the ability to make measurements over cloudless scenes. This orbit was chosen to improve the ability of the TOMS instrument to make measurements of UV-absorbing aerosols in the troposphere and enhanced the capability of converting the TOMS aerosol measurements into geophysical quantities such as optical depth. Tropospheric aerosols play a major role in the Earth's climate and the capability to measure them from a TOMS instrument had recently been developed using data from Nimbus-7 and Meteor-3 TOMS.The TOMS Tropospheric Ozone data are 9-day averaged, gridded (1-degree by 2-degree) ASCII products. There is also a GIF image of each data file.
ABSTRACT: Tropical Tropospheric Ozone (TTO) data from Earth Probe (EP) Total Ozone Mapping Spectrometer (TOMS) for the period of August 8-September 29, 2000 were processed and provided by the Atmospheric Chemistry and Dynamics Branch at NASA/GSFC for the SAFARI 2000 Dry Season Aircraft Campaign.The TTO measurement is derived from TOMS total ozone (Thompson and Hudson, 1999; Thompson et al., 2001) using the modified-residual method to separate stratospheric ozone from tropospheric ozone. The tropospheric ozone column thickness is reported in Dobson Units (DU).EP TOMS is currently the only NASA spacecraft on orbit specializing in ozone retrieval. EP TOMS was launched in 1996 into an orbit 500 km rather than the 950 km that was originally planned. The Earth Probe satellite was boosted to 740 km in 1997 when the ADEOS satellite failed. The lower orbit of EP TOMS decreased the size of the footprint of each measurement, which increased the resolution and also increased the ability to make measurements over cloudless scenes. This orbit was chosen to improve the ability of the TOMS instrument to make measurements of UV-absorbing aerosols in the troposphere and enhanced the capability of converting the TOMS aerosol measurements into geophysical quantities such as optical depth. Tropospheric aerosols play a major role in the Earth's climate and the capability to measure them from a TOMS instrument had recently been developed using data from Nimbus-7 and Meteor-3 TOMS.The TOMS Tropospheric Ozone data are 9-day averaged, gridded (1-degree by 2-degree) ASCII products. There is also a GIF image of each data file.
NOAA's TIROS (Television Infrared Observation Satellite) Operational Vertical Sounder (TOVS) is a suite of three sensors: the Microwave Sounding Unit (MSU), the High resolution Infrared Radiation Sounder (HIRS), and the Stratospheric Sounding Unit (SSU) aboard the NOAA series of polar-orbiting operational meteorological satellites. TOVS-derived data provide a means to investigate long-term climate change and interannual variability and study local and periodic phenomena such as El Nino and stratospheric warmings. A set of the derived meteorological parameters for southern Africa have been selected by SAFARI 2000.
NOAA's TIROS (Television Infrared Observation Satellite) Operational Vertical Sounder (TOVS) is a suite of three sensors: the Microwave Sounding Unit (MSU), the High resolution Infrared Radiation Sounder (HIRS), and the Stratospheric Sounding Unit (SSU) aboard the NOAA series of polar-orbiting operational meteorological satellites. TOVS-derived data provide a means to investigate long-term climate change and interannual variability and study local and periodic phenomena such as El Nino and stratospheric warmings. A set of the derived meteorological parameters for southern Africa have been selected by SAFARI 2000.
ABSTRACT: NOAA's TIROS (Television Infrared Observation Satellite) Operational Vertical Sounder (TOVS) is a suite of three sensors: the Microwave Sounding Unit (MSU), the High resolution Infrared Radiation Sounder (HIRS), and the Stratospheric Sounding Unit (SSU) aboard the NOAA series of polar-orbiting operational meteorological satellites. TOVS-derived data provide a means to investigate long-term climate change and interannual variability and study local and periodic phenomena such as El Nino and stratospheric warmings. A set of the derived meteorological parameters for southern Africa have been selected by SAFARI 2000.
This data set consists of a southern African subset of the 1-km Global Tree Cover Data Set developed at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland. Data are available in both ASCII GRID and binary image files formats.
This data set consists of a southern African subset of the 1-km Global Tree Cover Data Set developed at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland. Data are available in both ASCII GRID and binary image files formats.
ABSTRACT: This data set consists of a southern African subset of the 1-km Global Tree Cover Data Set developed at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland. Data are available in both ASCII GRID and binary image files formats.
This data set contains tree ring data from three sites located about 25 km of the meteorological station at Mongu, Zambia. Data from about 50 individual trees are reported. In addition, chronologies (or site mean curves) that better represent common influences (e.g., in this study, the climatic signal) were developed for each site based on the individual data (Trouet, 2004; Trouet et al., 2001). The series covers a maximum of 46 years, although most series do not extend longer than 30 years. The data were collected during the SAFARI 2000 Dry Season Field Campaign of August 2000.Ten to 23 samples were taken at each site. Brachystegia bakeriana was sampled at site 1, and Brachystegia spiciformis at sites 2 and 3. The vegetation at all sites underwent primitive harvesting for subsistence earlier the same year, thus samples could be taken from freshly cut trees and no living trees were cut. At all sites, samples consisted of full stem discs. Where possible, samples were taken at breast height (1.3 m) or slightly lower. Growth ring widths were measured to the nearest 0.01 mm using LINTAB equipment and TSAP software (Rinn and Jakel, 1997). Four radii per sample disc were measured. Cross-dating and response function analyses were performed by routine dendrochronological techniques. There are two files for each site, one containing integer values representing tree ring widths (raw data), and the other containing standardized values (chronologies), for each year. The data are stored as ASCII table files in comma-separated-value (.csv) format, with column headers.
This data set contains tree ring data from three sites located about 25 km of the meteorological station at Mongu, Zambia. Data from about 50 individual trees are reported. In addition, chronologies (or site mean curves) that better represent common influences (e.g., in this study, the climatic signal) were developed for each site based on the individual data (Trouet, 2004; Trouet et al., 2001). The series covers a maximum of 46 years, although most series do not extend longer than 30 years. The data were collected during the SAFARI 2000 Dry Season Field Campaign of August 2000.Ten to 23 samples were taken at each site. Brachystegia bakeriana was sampled at site 1, and Brachystegia spiciformis at sites 2 and 3. The vegetation at all sites underwent primitive harvesting for subsistence earlier the same year, thus samples could be taken from freshly cut trees and no living trees were cut. At all sites, samples consisted of full stem discs. Where possible, samples were taken at breast height (1.3 m) or slightly lower. Growth ring widths were measured to the nearest 0.01 mm using LINTAB equipment and TSAP software (Rinn and Jakel, 1997). Four radii per sample disc were measured. Cross-dating and response function analyses were performed by routine dendrochronological techniques. There are two files for each site, one containing integer values representing tree ring widths (raw data), and the other containing standardized values (chronologies), for each year. The data are stored as ASCII table files in comma-separated-value (.csv) format, with column headers.
ABSTRACT: This data set contains tree ring data from three sites located about 25 km of the meteorological station at Mongu, Zambia. Data from about 50 individual trees are reported. In addition, chronologies (or site mean curves) that better represent common influences (e.g., in this study, the climatic signal) were developed for each site based on the individual data (Trouet, 2004; Trouet et al., 2001). The series covers a maximum of 46 years, although most series do not extend longer than 30 years. The data were collected during the SAFARI 2000 Dry Season Field Campaign of August 2000.Ten to 23 samples were taken at each site. Brachystegia bakeriana was sampled at site 1, and Brachystegia spiciformis at sites 2 and 3. The vegetation at all sites underwent primitive harvesting for subsistence earlier the same year, thus samples could be taken from freshly cut trees and no living trees were cut. At all sites, samples consisted of full stem discs. Where possible, samples were taken at breast height (1.3 m) or slightly lower. Growth ring widths were measured to the nearest 0.01 mm using LINTAB equipment and TSAP software (Rinn and Jakel, 1997). Four radii per sample disc were measured. Cross-dating and response function analyses were performed by routine dendrochronological techniques. There are two files for each site, one containing integer values representing tree ring widths (raw data), and the other containing standardized values (chronologies), for each year. The data are stored as ASCII table files in comma-separated-value (.csv) format, with column headers.
The purpose of the Tropical Rainfall Measuring Mission (TRMM) and TRMM Product 3B-43 is to provide a monthly, best-estimate precipitation rate and root-mean-square (RMS) precipitation error. These gridded estimates are on a one-calendar month temporal resolution and a 1-degree by 1-degree spatial resolution for the global band extending from 40 degrees south to 40 degrees north in latitude.
The purpose of the Tropical Rainfall Measuring Mission (TRMM) and TRMM Product 3B-43 is to provide a monthly, best-estimate precipitation rate and root-mean-square (RMS) precipitation error. These gridded estimates are on a one-calendar month temporal resolution and a 1-degree by 1-degree spatial resolution for the global band extending from 40 degrees south to 40 degrees north in latitude.
ABSTRACT: The purpose of the Tropical Rainfall Measuring Mission (TRMM) and TRMM Product 3B-43 is to provide a monthly, best-estimate precipitation rate and root-mean-square (RMS) precipitation error. These gridded estimates are on a one-calendar month temporal resolution and a 1-degree by 1-degree spatial resolution for the global band extending from 40 degrees south to 40 degrees north in latitude.
Vaisala RS80 sondes were deployed from Skukuza Airport, South Africa, to collect atmospheric sounding profiles of temperature and moisture data from the surface to 30 km. These sonde launches were coordinated to augment the regional sounding network in the region during the SAFARI 2000 Dry Season Campaigns of 1999 and 2000. The radiosondes were launched from Skukuza Airport between August 14-September 3, 1999, and between August 24-September 23, 2000.  The radiosonde instrument package RS80 measured the following meteorological parameters: pressure in hecto-Pascals (P), ambient temperature in degrees Celsius (T), and relative humidity in percentage (RH). A hydrostatic equation was applied to the recorded data, after error-checking, to calculate the output parameters: height above sea level in meters, dew point temperature in degrees Celsius, and q (g/kg) which is specific humidity in grams per kilogram.
Vaisala RS80 sondes were deployed from Skukuza Airport, South Africa, to collect atmospheric sounding profiles of temperature and moisture data from the surface to 30 km. These sonde launches were coordinated to augment the regional sounding network in the region during the SAFARI 2000 Dry Season Campaigns of 1999 and 2000. The radiosondes were launched from Skukuza Airport between August 14-September 3, 1999, and between August 24-September 23, 2000.  The radiosonde instrument package RS80 measured the following meteorological parameters: pressure in hecto-Pascals (P), ambient temperature in degrees Celsius (T), and relative humidity in percentage (RH). A hydrostatic equation was applied to the recorded data, after error-checking, to calculate the output parameters: height above sea level in meters, dew point temperature in degrees Celsius, and q (g/kg) which is specific humidity in grams per kilogram.
ABSTRACT: Vaisala RS80 sondes were deployed from Skukuza Airport, South Africa, to collect atmospheric sounding profiles of temperature and moisture data from the surface to 30 km. These sonde launches were coordinated to augment the regional sounding network in the region during the SAFARI 2000 Dry Season Campaigns of 1999 and 2000. The radiosondes were launched from Skukuza Airport between August 14-September 3, 1999, and between August 24-September 23, 2000.  The radiosonde instrument package RS80 measured the following meteorological parameters: pressure in hecto-Pascals (P), ambient temperature in degrees Celsius (T), and relative humidity in percentage (RH). A hydrostatic equation was applied to the recorded data, after error-checking, to calculate the output parameters: height above sea level in meters, dew point temperature in degrees Celsius, and q (g/kg) which is specific humidity in grams per kilogram.
The University of Wyoming has a series of balloonborne radiosonde measurements from all around the world, from the surface to 30 km.  This data set contains upper air meteorological profiles from 594 radiosonde launches deployed from sites in South Africa.  These sonde launches were made to augment the regional sounding network in the region during the SAFARI 2000 Dry Season Campaign of 2000.Vaisala RS80 sondes were launched from nine sites in South Africa between August 1, 2000 and September 30, 2000. The launch sites were Pietersburg (changed to Polokwane after 2000), Pretoria (Irene), Bethlehem, Springbok, De Aar, Durban, Cape Town, Port Elizabeth, and Gough Island. The parameters measured by the radiosonde instruments include: pressure, air temperature, relative humidity, wind speed, and wind direction.
The University of Wyoming has a series of balloonborne radiosonde measurements from all around the world, from the surface to 30 km.  This data set contains upper air meteorological profiles from 594 radiosonde launches deployed from sites in South Africa.  These sonde launches were made to augment the regional sounding network in the region during the SAFARI 2000 Dry Season Campaign of 2000.Vaisala RS80 sondes were launched from nine sites in South Africa between August 1, 2000 and September 30, 2000. The launch sites were Pietersburg (changed to Polokwane after 2000), Pretoria (Irene), Bethlehem, Springbok, De Aar, Durban, Cape Town, Port Elizabeth, and Gough Island. The parameters measured by the radiosonde instruments include: pressure, air temperature, relative humidity, wind speed, and wind direction.
ABSTRACT: The University of Wyoming has a series of balloonborne radiosonde measurements from all around the world, from the surface to 30 km.  This data set contains upper air meteorological profiles from 594 radiosonde launches deployed from sites in South Africa.  These sonde launches were made to augment the regional sounding network in the region during the SAFARI 2000 Dry Season Campaign of 2000.Vaisala RS80 sondes were launched from nine sites in South Africa between August 1, 2000 and September 30, 2000. The launch sites were Pietersburg (changed to Polokwane after 2000), Pretoria (Irene), Bethlehem, Springbok, De Aar, Durban, Cape Town, Port Elizabeth, and Gough Island. The parameters measured by the radiosonde instruments include: pressure, air temperature, relative humidity, wind speed, and wind direction.
This data set contains a subset for southern Africa of Wilson and Henderson-Sellers' Global Vegetation and Soils 1-degree data. The data are available in both ASCII GRID and binary image file formats.
This data set contains a subset for southern Africa of Wilson and Henderson-Sellers' Global Vegetation and Soils 1-degree data. The data are available in both ASCII GRID and binary image file formats.
ABSTRACT: This data set contains a subset for southern Africa of Wilson and Henderson-Sellers' Global Vegetation and Soils 1-degree data. The data are available in both ASCII GRID and binary image file formats.
Vegetation cover and composition, including species types and richness assessments, were measured at four locations along the Kalahari Transect in Botswana (Pandamatenga, Maun, Okwa River, and Tshane) during the SAFARI 2000 wet season field campaign. The sites visited showed interesting degrees of variability despite the apparent homogeneity of the Kalahari sands and predominantly semi-arid savanna shrub-woodlands vegetation cover (Ringrose et al., 2003).At each site, twelve individual locations were chosen by random stratified techniques within a 30-km radius at each location, based on differences in topography, soils, and known disturbance, to help determine local variability (Huennecke et al., 2001). Data collection methods were identical at each location (Ringrose et al., 1996; 1998): (1) identification and enumeration of all species along 3 x 90-m transects, spaced 45-m apart; (2) visual estimation (tape measure and pacing) of canopy diameter along each transect; and (3) visual estimation of percent live and dead herbaceous cover, litter, and bare soil using 3 x 50 m2 quadrats spaced at 30-m intervals along each transect. In addition, vegetation components were calculated for each site comprising woody vegetation cover, green herbaceous cover in terms of grass and forbs, dead herbaceous cover, plant litter, and bare soil. Species richness was calculated as the actual number of species per three transects (270 m2) at each site (Kent and Coker, 1996).The data set consists of two data files (ASCII tables) in comma-delimited format (.csv) with descriptive header records.
Vegetation cover and composition, including species types and richness assessments, were measured at four locations along the Kalahari Transect in Botswana (Pandamatenga, Maun, Okwa River, and Tshane) during the SAFARI 2000 wet season field campaign. The sites visited showed interesting degrees of variability despite the apparent homogeneity of the Kalahari sands and predominantly semi-arid savanna shrub-woodlands vegetation cover (Ringrose et al., 2003).At each site, twelve individual locations were chosen by random stratified techniques within a 30-km radius at each location, based on differences in topography, soils, and known disturbance, to help determine local variability (Huennecke et al., 2001). Data collection methods were identical at each location (Ringrose et al., 1996; 1998): (1) identification and enumeration of all species along 3 x 90-m transects, spaced 45-m apart; (2) visual estimation (tape measure and pacing) of canopy diameter along each transect; and (3) visual estimation of percent live and dead herbaceous cover, litter, and bare soil using 3 x 50 m2 quadrats spaced at 30-m intervals along each transect. In addition, vegetation components were calculated for each site comprising woody vegetation cover, green herbaceous cover in terms of grass and forbs, dead herbaceous cover, plant litter, and bare soil. Species richness was calculated as the actual number of species per three transects (270 m2) at each site (Kent and Coker, 1996).The data set consists of two data files (ASCII tables) in comma-delimited format (.csv) with descriptive header records.
ABSTRACT: Vegetation cover and composition, including species types and richness assessments, were measured at four locations along the Kalahari Transect in Botswana (Pandamatenga, Maun, Okwa River, and Tshane) during the SAFARI 2000 wet season field campaign. The sites visited showed interesting degrees of variability despite the apparent homogeneity of the Kalahari sands and predominantly semi-arid savanna shrub-woodlands vegetation cover (Ringrose et al., 2003).At each site, twelve individual locations were chosen by random stratified techniques within a 30-km radius at each location, based on differences in topography, soils, and known disturbance, to help determine local variability (Huennecke et al., 2001). Data collection methods were identical at each location (Ringrose et al., 1996; 1998): (1) identification and enumeration of all species along 3 x 90-m transects, spaced 45-m apart; (2) visual estimation (tape measure and pacing) of canopy diameter along each transect; and (3) visual estimation of percent live and dead herbaceous cover, litter, and bare soil using 3 x 50 m2 quadrats spaced at 30-m intervals along each transect. In addition, vegetation components were calculated for each site comprising woody vegetation cover, green herbaceous cover in terms of grass and forbs, dead herbaceous cover, plant litter, and bare soil. Species richness was calculated as the actual number of species per three transects (270 m2) at each site (Kent and Coker, 1996).The data set consists of two data files (ASCII tables) in comma-delimited format (.csv) with descriptive header records.
Tree basal area, percent tree canopy cover, and proportional contribution of main species to canopy cover were measured at 60 sampling points at 50 m intervals along six transects in the vicinity of the MODIS validation site tower in Kataba Forest, near Mongu, Zambia, in late February to early March 2000 as part of the SAFARI 2000 Wet Season Campaign. The aim of the study was to provide a broad description of the tree canopy layer around the tower.Tree and shrub species composition was recorded for each grid and measurements of canopy cover (% and rank) and frequency of occurrence (%) were made. Basal area was estimated at each grid site in a single 360 degree sweep using a basal area prism. Four estimates of canopy cover, oriented north, south, east, and west around the sample point, were taken at each grid site using a spherical densiometer and the data were averaged to give a single value for each grid. Only the canopies of trees and shrubs above 1.5 m height were measured.The data are stored in an ASCII file, in csv format. The file lists all tree and shrub species recorded and provides the proportional contribution of these species to canopy cover in each grid. Total tree basal area (m2 ha-1) and overall tree canopy cover (%) in each grid is also provided. The companion file provides additional vegetation data, graphics, long-term meteorological data, a discussion of the study results, and photographs of the study site.
Tree basal area, percent tree canopy cover, and proportional contribution of main species to canopy cover were measured at 60 sampling points at 50 m intervals along six transects in the vicinity of the MODIS validation site tower in Kataba Forest, near Mongu, Zambia, in late February to early March 2000 as part of the SAFARI 2000 Wet Season Campaign. The aim of the study was to provide a broad description of the tree canopy layer around the tower.Tree and shrub species composition was recorded for each grid and measurements of canopy cover (% and rank) and frequency of occurrence (%) were made. Basal area was estimated at each grid site in a single 360 degree sweep using a basal area prism. Four estimates of canopy cover, oriented north, south, east, and west around the sample point, were taken at each grid site using a spherical densiometer and the data were averaged to give a single value for each grid. Only the canopies of trees and shrubs above 1.5 m height were measured.The data are stored in an ASCII file, in csv format. The file lists all tree and shrub species recorded and provides the proportional contribution of these species to canopy cover in each grid. Total tree basal area (m2 ha-1) and overall tree canopy cover (%) in each grid is also provided. The companion file provides additional vegetation data, graphics, long-term meteorological data, a discussion of the study results, and photographs of the study site.
ABSTRACT: Tree basal area, percent tree canopy cover, and proportional contribution of main species to canopy cover were measured at 60 sampling points at 50 m intervals along six transects in the vicinity of the MODIS validation site tower in Kataba Forest, near Mongu, Zambia, in late February to early March 2000 as part of the SAFARI 2000 Wet Season Campaign. The aim of the study was to provide a broad description of the tree canopy layer around the tower.Tree and shrub species composition was recorded for each grid and measurements of canopy cover (% and rank) and frequency of occurrence (%) were made. Basal area was estimated at each grid site in a single 360 degree sweep using a basal area prism. Four estimates of canopy cover, oriented north, south, east, and west around the sample point, were taken at each grid site using a spherical densiometer and the data were averaged to give a single value for each grid. Only the canopies of trees and shrubs above 1.5 m height were measured.The data are stored in an ASCII file, in csv format. The file lists all tree and shrub species recorded and provides the proportional contribution of these species to canopy cover in each grid. Total tree basal area (m2 ha-1) and overall tree canopy cover (%) in each grid is also provided. The companion file provides additional vegetation data, graphics, long-term meteorological data, a discussion of the study results, and photographs of the study site.
This database provides information on the distribution and environmental characteristics of natural wetlands. The database was developed to evaluate the role of wetlands in the annual emission of methane from terrestrial sources. The original data consists of five global 1-degree latitude by 1-degree longitude arrays. The subset retains all five arrays at the 1-degree resolution but only for the area of interest. The arrays are (1) wetland data source, (2) wetland type, (3) fractional inundation, (4) vegetation type, and (5) soil type.
This database provides information on the distribution and environmental characteristics of natural wetlands. The database was developed to evaluate the role of wetlands in the annual emission of methane from terrestrial sources. The original data consists of five global 1-degree latitude by 1-degree longitude arrays. The subset retains all five arrays at the 1-degree resolution but only for the area of interest. The arrays are (1) wetland data source, (2) wetland type, (3) fractional inundation, (4) vegetation type, and (5) soil type.
ABSTRACT: This database provides information on the distribution and environmental characteristics of natural wetlands. The database was developed to evaluate the role of wetlands in the annual emission of methane from terrestrial sources. The original data consists of five global 1-degree latitude by 1-degree longitude arrays. The subset retains all five arrays at the 1-degree resolution but only for the area of interest. The arrays are (1) wetland data source, (2) wetland type, (3) fractional inundation, (4) vegetation type, and (5) soil type.
This data set contains species composition, basal area, height, and crown cover of all woody plants at six sites along the Kalahari Transect visited in February-March of 2000 as part of SAFARI 2000. Similar measurements on woody and herbaceous vegetation at the Skukuza Flux Tower site in Kruger National Park, South Africa, were made in June of 2000. Leaf area index was derived from measurements made using PAR sensors at each site.Sampling protocol was the same at each site, with a slight variation at Skukuza.  A grid of 42 points, 6 rows of 7 columns, each 50 m apart, was laid down in an area 300 m x 350 m for the Kalahari Transect sites. At Skukuza, the grid was 7x7, or 350 m x 350 m, centered on the tower site, yielding 49 points. At each grid point, all woody plants within a circular plot of a fixed radius were identified and measured. Stem circumference was measured on all stems and basal area per stem was derived. Basal area for the circular plots, per species, was calculated and extrapolated to hectares. Tree and stem densities were determined from the number of trees and stems in subplots and extrapolated to hectares. Woody plant height and canopy cover were determined, and aboveground woody biomass and peak leaf area index were estimated. The files are in comma-delimited ASCII format, with the first line listing the data set, author, and date, followed by the data records.
This data set contains species composition, basal area, height, and crown cover of all woody plants at six sites along the Kalahari Transect visited in February-March of 2000 as part of SAFARI 2000. Similar measurements on woody and herbaceous vegetation at the Skukuza Flux Tower site in Kruger National Park, South Africa, were made in June of 2000. Leaf area index was derived from measurements made using PAR sensors at each site.Sampling protocol was the same at each site, with a slight variation at Skukuza.  A grid of 42 points, 6 rows of 7 columns, each 50 m apart, was laid down in an area 300 m x 350 m for the Kalahari Transect sites. At Skukuza, the grid was 7x7, or 350 m x 350 m, centered on the tower site, yielding 49 points. At each grid point, all woody plants within a circular plot of a fixed radius were identified and measured. Stem circumference was measured on all stems and basal area per stem was derived. Basal area for the circular plots, per species, was calculated and extrapolated to hectares. Tree and stem densities were determined from the number of trees and stems in subplots and extrapolated to hectares. Woody plant height and canopy cover were determined, and aboveground woody biomass and peak leaf area index were estimated. The files are in comma-delimited ASCII format, with the first line listing the data set, author, and date, followed by the data records.
ABSTRACT: This data set contains species composition, basal area, height, and crown cover of all woody plants at six sites along the Kalahari Transect visited in February-March of 2000 as part of SAFARI 2000. Similar measurements on woody and herbaceous vegetation at the Skukuza Flux Tower site in Kruger National Park, South Africa, were made in June of 2000. Leaf area index was derived from measurements made using PAR sensors at each site.Sampling protocol was the same at each site, with a slight variation at Skukuza.  A grid of 42 points, 6 rows of 7 columns, each 50 m apart, was laid down in an area 300 m x 350 m for the Kalahari Transect sites. At Skukuza, the grid was 7x7, or 350 m x 350 m, centered on the tower site, yielding 49 points. At each grid point, all woody plants within a circular plot of a fixed radius were identified and measured. Stem circumference was measured on all stems and basal area per stem was derived. Basal area for the circular plots, per species, was calculated and extrapolated to hectares. Tree and stem densities were determined from the number of trees and stems in subplots and extrapolated to hectares. Woody plant height and canopy cover were determined, and aboveground woody biomass and peak leaf area index were estimated. The files are in comma-delimited ASCII format, with the first line listing the data set, author, and date, followed by the data records.
Level 1B pixel group transmission profiles for a single solar event (Suggested Usage: Vertical transmission profiles for input into an inversion algorithm)
Level 1B pixel group transmission profiles for a single solar event (Suggested Usage: Vertical transmission profiles for input into an inversion algorithm)
Level 1B pixel group transmission profiles for a single solar event (Suggested Usage: Vertical transmission profiles for input into an inversion algorithm)
Level 1B pixel group transmission profiles for a single solar event (Suggested Usage: Vertical transmission profiles for input into an inversion algorithm)
A Level 2 data file containing all the species products for a single lunar event (Suggested Usage: Atmospheric studies of O3, NO2, NO3, OClO and water vapor using vertical profiles from lunar occultation)
A Level 2 data file containing all the species products for a single lunar event (Suggested Usage: Atmospheric studies of O3, NO2, NO3, OClO and water vapor using vertical profiles from lunar occultation)
A monthly data file coincident with solar event granules, that provides information about cloud presence during data capture of the granules (Suggested Usage: For the studies of atmospheric science, global warming and radiative balance)
A monthly data file coincident with solar event granules, that provides information about cloud presence during data capture of the granules (Suggested Usage: For the studies of atmospheric science, global warming and radiative balance)
A Level 2 data file containing all the species products for a single solar event (Suggested Usage: Atmospheric studies of aerosols, ozone, nitrogen dioxide and water vapor using vertical profiles from solar occultation measurements.)
A Level 2 data file containing all the species products for a single solar event (Suggested Usage: Atmospheric studies of aerosols, ozone, nitrogen dioxide and water vapor using vertical profiles from solar occultation measurements.)
A Level 2 data file containing all the species products for a single solar event (Suggested Usage: Atmospheric studies of aerosols, ozone, nitrogen dioxide and water vapor using vertical profiles from solar occultation measurements.)
A Level 2 data file containing all the species products for a single solar event (Suggested Usage: Atmospheric studies of aerosols, ozone, nitrogen dioxide and water vapor using vertical profiles from solar occultation measurements.)
This data set provides Synthetic Aperture Radar (SAR) images for 42 selected sites from various terrestrial ecology and meteorological monitoring networks including FLUXNET, Ameriflux, Long Term Ecological Research (LTER), and the Greenland Climate Network (GC-Net).The data set contains at least one image for all 42 sites, and six sites have multiple images. See Table 1 for the sites and the temporal range of the available images. The scenes are in GeoTIFF format in Universal Transverse Mercator (UTM), WGS-84 projection, and 15-meter resolution.The SAR images are subset scenes of approximately 60 km x 70 km that include an established site in one of the monitoring networks. The spatial resolution of all scenes is 15 meters. These scenes are distributed as geotif files with appropriate projection information defined within the file.The acquisition mode for all data is the Fine Beam Double Polarization or FBD with the HH/HV polarization. The HH and HV channels are distributed as 3 channels to allow for an intuitive image display. The HH band is displayed in the red and blue channels and the HV band is displayed in the green channel. For some images only single polarization is available; these images are distributed as grayscale images.The source of the data is the PALSAR (Phased Array type L-band Synthetic Aperture Radar) sensor flying on the Advanced Land Observing Satellite (ALOS). The PALSAR data are in dual Polarization, HH+HV, mode. Bands HH (red and blue) and Band-HV (green) can be used to visualize land use patterns. The resulting images show vegetation in shades of green and barren land in shades of pink or purple.
This data set provides Synthetic Aperture Radar (SAR) images for 42 selected sites from various terrestrial ecology and meteorological monitoring networks including FLUXNET, Ameriflux, Long Term Ecological Research (LTER), and the Greenland Climate Network (GC-Net).The data set contains at least one image for all 42 sites, and six sites have multiple images. See Table 1 for the sites and the temporal range of the available images. The scenes are in GeoTIFF format in Universal Transverse Mercator (UTM), WGS-84 projection, and 15-meter resolution.The SAR images are subset scenes of approximately 60 km x 70 km that include an established site in one of the monitoring networks. The spatial resolution of all scenes is 15 meters. These scenes are distributed as geotif files with appropriate projection information defined within the file.The acquisition mode for all data is the Fine Beam Double Polarization or FBD with the HH/HV polarization. The HH and HV channels are distributed as 3 channels to allow for an intuitive image display. The HH band is displayed in the red and blue channels and the HV band is displayed in the green channel. For some images only single polarization is available; these images are distributed as grayscale images.The source of the data is the PALSAR (Phased Array type L-band Synthetic Aperture Radar) sensor flying on the Advanced Land Observing Satellite (ALOS). The PALSAR data are in dual Polarization, HH+HV, mode. Bands HH (red and blue) and Band-HV (green) can be used to visualize land use patterns. The resulting images show vegetation in shades of green and barren land in shades of pink or purple.
ABSTRACT: This data set provides Synthetic Aperture Radar (SAR) images for 42 selected sites from various terrestrial ecology and meteorological monitoring networks including FLUXNET, Ameriflux, Long Term Ecological Research (LTER), and the Greenland Climate Network (GC-Net).The data set contains at least one image for all 42 sites, and six sites have multiple images. See Table 1 for the sites and the temporal range of the available images. The scenes are in GeoTIFF format in Universal Transverse Mercator (UTM), WGS-84 projection, and 15-meter resolution.The SAR images are subset scenes of approximately 60 km x 70 km that include an established site in one of the monitoring networks. The spatial resolution of all scenes is 15 meters. These scenes are distributed as geotif files with appropriate projection information defined within the file.The acquisition mode for all data is the Fine Beam Double Polarization or FBD with the HH/HV polarization. The HH and HV channels are distributed as 3 channels to allow for an intuitive image display. The HH band is displayed in the red and blue channels and the HV band is displayed in the green channel. For some images only single polarization is available; these images are distributed as grayscale images.The source of the data is the PALSAR (Phased Array type L-band Synthetic Aperture Radar) sensor flying on the Advanced Land Observing Satellite (ALOS). The PALSAR data are in dual Polarization, HH+HV, mode. Bands HH (red and blue) and Band-HV (green) can be used to visualize land use patterns. The resulting images show vegetation in shades of green and barren land in shades of pink or purple.
Coefficients required to convert satellite radiances to reflectance/temperature
Coefficients required to convert satellite radiances to reflectance/temperature
ABSTRACT: Coefficients required to convert satellite radiances to reflectance/temperature
Site specifice radiance, exoatmospheric reflectance & surface reflectance
Site specifice radiance, exoatmospheric reflectance & surface reflectance
ABSTRACT: Site specifice radiance, exoatmospheric reflectance & surface reflectance
Site reflectances extracted from Landsat TM imagery over FIFE study area
Site reflectances extracted from Landsat TM imagery over FIFE study area
ABSTRACT: Site reflectances extracted from Landsat TM imagery over FIFE study area
Site reflectances extracted from SPOT HRV imagery over FIFE study area
Site reflectances extracted from SPOT HRV imagery over FIFE study area
ABSTRACT: Site reflectances extracted from SPOT HRV imagery over FIFE study area
The Solar Backscattered Ultra Violet (SBUV) from Nimbus-7 Level-2 daily product (SBUVN07L2) contains ozone nadir profile and total column data from retrievals generated from the v8.6 SBUV algorithm. The v8.6 SBUV algorithm estimates the ozone nadir profile and total column from SBUV measurements using 1) the Brion-Daumont-Malicet ozone cross sections, 2) an OMI-derived cloud-height climatology, 3) a revised a priori ozone climatology, and 4) inter-instrument calibration based on comparisons with no local time difference.

The SBUVN07L2 product is written as daily files using the HDF5 format, with file sizes ranging from about 1 to 5 Mbytes. Data are available from November 1978 through May 1990. The SBUVN07L2 data product was used as input in creating the SBUVN07L3zm monthly zonal mean data product.
The version 8 SBUV Nimbus-7 ozone data were first released at the 2004 Quadrennial Ozone Symposium on DVD. The DVD contained all of the SBUV/2 data from NOAA-9, NOAA-11 and NOAA-16 satellites as well as SBUV data from the Nimbus-7 satellite. The DVD is no longer available, however all the data are available on-line from the NASA GES DISC. The Nimbus-7 SBUV v8 data are available from 1978-10-31 to 1990-06-21. The instrument spatial resolution is 180 km x 180 km footprint at nadir. The ozone profiles are made at 21 pressure levels between 1000 and 0.1 hPa. Each data file contains a days worth of ozone measurements, and is written in an ASCII text format.

The SBUV measures incoming solar irradiance and radiance backscattered by the atmosphere at 12 wavelengths in the UV range [0.25-0.34 micrometer] with a spectral band pass of 0.001 micrometer. The wavelength channels used for ozone retrievals for SBUV were: 256, 273, 283, 288, 292, 298, 302, 306, 312, 318, 331, and 340 nm. Radiation at these wavelengths are absorbed by ozone, such that the difference between the incoming and outgoing radiation can be related to the amount of ozone in the atmosphere.The SBUV consists of a double Ebert-Fastie spectrometer and a filter photometer similar to the BUV on Nimbus 4. The bandwidth of the photometer is about 3 nm and the spectral resolution for SBUV monochromator is 1.1 nm.From these data, the following atmospheric properties can be deduced:
* The global and vertical distribution of stratospheric ozone.
* The structure and dynamics of stratospheric ozone.
* Photochemical processes and the influence of "trace" constituents on the ozone layer.
* Long-term solar activity in the Ultraviolet spectrum.
The Solar Backscattered Ultra Violet (SBUV) from NOAA-9 Level-2 daily product (SBUV2N09L2) contains ozone nadir profile and total column data from retrievals generated from the v8.6 SBUV algorithm. The v8.6 SBUV algorithm estimates the ozone nadir profile and total column from SBUV measurements using 1) the Brion-Daumont-Malicet ozone cross sections, 2) an OMI-derived cloud-height climatology, 3) a revised a priori ozone climatology, and 4) inter-instrument calibration based on comparisons with no local time difference.

The SBUV2N09L2 product is written as daily files using the HDF5 format, with file sizes ranging from about 1 to 5 Mbytes. Data are available from February 1985 through January 1998. The SBUV2N09L2 data product was used as input in creating the SBUV2N09L3zm monthly zonal mean data product.
The Solar Backscattered Ultra Violet (SBUV) from NOAA-11 Level-2 daily product (SBUV2N11L2) contains ozone nadir profile and total column data from retrievals generated from the v8.6 SBUV algorithm. The v8.6 SBUV algorithm estimates the ozone nadir profile and total column from SBUV measurements using 1) the Brion-Daumont-Malicet ozone cross sections, 2) an OMI-derived cloud-height climatology, 3) a revised a priori ozone climatology, and 4) inter-instrument calibration based on comparisons with no local time difference.

The SBUV2N11L2 product is written as daily files using the HDF5 format, with file sizes ranging from about 1 to 5 Mbytes. Data are available from January 1989 through March 2001. The SBUV2N11L2 data product was used as input in creating the SBUV2N11L3zm monthly zonal mean data product.
The Solar Backscattered Ultra Violet (SBUV) from NOAA-14 Level-2 daily product (SBUV2N14L2) contains ozone nadir profile and total column data from retrievals generated from the v8.6 SBUV algorithm. The v8.6 SBUV algorithm estimates the ozone nadir profile and total column from SBUV measurements using 1) the Brion-Daumont-Malicet ozone cross sections, 2) an OMI-derived cloud-height climatology, 3) a revised a priori ozone climatology, and 4) inter-instrument calibration based on comparisons with no local time difference.

The SBUV2N14L2 product is written as daily files using the HDF5 format, with file sizes ranging from about 1 to 5 Mbytes. Data are available from March 1995 through September 2006. The SBUV2N14L2 data product was used as input in creating the SBUV2N14L3zm monthly zonal mean data product.
The Solar Backscattered Ultra Violet (SBUV) from NOAA-16 Level-2 daily product (SBUV2N16L2) contains ozone nadir profile and total column data from retrievals generated from the v8.6 SBUV algorithm. The v8.6 SBUV algorithm estimates the ozone nadir profile and total column from SBUV measurements using 1) the Brion-Daumont-Malicet ozone cross sections, 2) an OMI-derived cloud-height climatology, 3) a revised a priori ozone climatology, and 4) inter-instrument calibration based on comparisons with no local time difference.

The SBUV2N16L2 product is written as daily files using the HDF5 format, with file sizes ranging from about 1 to 5 Mbytes. Data are available from October 2000 through July 2013. The SBUV2N16L2 data product was used as input in creating the SBUV2N16L3zm monthly zonal mean data product.
The Solar Backscattered Ultra Violet (SBUV) from NOAA-17 Level-2 daily product (SBUV2N17L2) contains ozone nadir profile and total column data from retrievals generated from the v8.6 SBUV algorithm. The v8.6 SBUV algorithm estimates the ozone nadir profile and total column from SBUV measurements using 1) the Brion-Daumont-Malicet ozone cross sections, 2) an OMI-derived cloud-height climatology, 3) a revised a priori ozone climatology, and 4) inter-instrument calibration based on comparisons with no local time difference.

The SBUV2N17L2 product is written as daily files using the HDF5 format, with file sizes ranging from about 1 to 5 Mbytes. Data are available from July 2002 through April 2013. The SBUV2N17L2 data product was used as input in creating the SBUV2N17L3zm monthly zonal mean data product.
The Solar Backscattered Ultra Violet (SBUV) from NOAA-18 Level-2 daily product (SBUV2N18L2) contains ozone nadir profile and total column data from retrievals generated from the v8.6 SBUV algorithm. The v8.6 SBUV algorithm estimates the ozone nadir profile and total column from SBUV measurements using 1) the Brion-Daumont-Malicet ozone cross sections, 2) an OMI-derived cloud-height climatology, 3) a revised a priori ozone climatology, and 4) inter-instrument calibration based on comparisons with no local time difference.

The SBUV2N18L2 product is written as daily files using the HDF5 format, with file sizes ranging from about 1 to 5 Mbytes. Data are available from June 2005 through December 2012. The SBUV2N18L2 data product was used as input in creating the SBUV2N18L3zm monthly zonal mean data product.
The Solar Backscattered Ultra Violet (SBUV) from NOAA-19 Level-2 daily product (SBUV2N19L2) contains ozone nadir profile and total column data from retrievals generated from the v8.6 SBUV algorithm. The v8.6 SBUV algorithm estimates the ozone nadir profile and total column from SBUV measurements using 1) the Brion-Daumont-Malicet ozone cross sections, 2) an OMI-derived cloud-height climatology, 3) a revised a priori ozone climatology, and 4) inter-instrument calibration based on comparisons with no local time difference.

The SBUV2N19L2 product is written as daily files using the HDF5 format, with file sizes ranging from about 1 to 5 Mbytes. Data are available from February 2009 through July 2013. The SBUV2N19L2 data product was used as input in creating the SBUV2N19L3zm monthly zonal mean data product.
Spectral reflectance measurements made by Spectron SE590 instruments in the context of validation of geometric-optical BRDF models
Spectral reflectance measurements made by Spectron SE590 instruments in the context of validation of geometric-optical BRDF models
ABSTRACT: Spectral reflectance measurements made by Spectron SE590 instruments in the context of validation of geometric-optical BRDF models
Bidirectional reflectances measured with SE590 (Middleton)
Bidirectional reflectances measured with SE590 (Middleton)
ABSTRACT: Bidirectional reflectances measured with SE590 (Middleton)
Bidirectional reflectances measured with SE590
Bidirectional reflectances measured with SE590
ABSTRACT: Bidirectional reflectances measured with SE590
Laboratory hemispherical reflectance spectra measurements taken to eliminate the effects of atmosphere, understory, exposed soils, mixed species and canopy architecture
Laboratory hemispherical reflectance spectra measurements taken to eliminate the effects of atmosphere, understory, exposed soils, mixed species and canopy architecture
ABSTRACT: Laboratory hemispherical reflectance spectra measurements taken to eliminate the effects of atmosphere, understory, exposed soils, mixed species and canopy architecture
Bidirectional spectal reflectance factors of landscape elements (litter, soil, bark, scrubs & grasses, leaves) measured by Spectron SE590 spectroradiometer
Bidirectional spectal reflectance factors of landscape elements (litter, soil, bark, scrubs & grasses, leaves) measured by Spectron SE590 spectroradiometer
ABSTRACT: Bidirectional spectal reflectance factors of landscape elements (litter, soil, bark, scrubs & grasses, leaves) measured by Spectron SE590 spectroradiometer
Leaf optical properties (reflectance & transmittance) from SE590 & LICOR
Leaf optical properties (reflectance & transmittance) from SE590 & LICOR
ABSTRACT: Leaf optical properties (reflectance & transmittance) from SE590 & LICOR
Low altitude (Ultralight) spectral reflectances of OTTER research sites measured by Spectron SE590 spectrophotometer
Low altitude (Ultralight) spectral reflectances of OTTER research sites measured by Spectron SE590 spectrophotometer
ABSTRACT: Low altitude (Ultralight) spectral reflectances of OTTER research sites measured by Spectron SE590 spectrophotometer
SE-590 reflectance factors and radiances measured from a helicopter
SE-590 reflectance factors and radiances measured from a helicopter
ABSTRACT: SE-590 reflectance factors and radiances measured from a helicopter
The Sea Level Rise Impacts on Ramsar Wetlands of International Importance data set represents the results of an analysis using the boundaries for Ramsar sites designated under the Ramsar Convention on Wetlands and intersecting them with different elevation zones in the coastal zone to assess area and percent area that would become inundated under 1 and 2 meter sea level rise scenarios. This data set provides results for 613 sites with defined boundaries that were found to intersect with the 0-5m above mean sea level coastal zone, defined by NASA Shuttle Radar Topography Mission (SRTM) elevation data. In addition to assessing the degree of risk of inundation, the data set provides data on population density and percent of land that is urban within the site and within 1km and 5km buffers surrounding the site. The data set also reports on infant mortality rates within 1km and 5km buffers around the site, as a measure of poverty levels that may affect adaptive capacity.
The Sea Level Rise Impacts on Ramsar Wetlands of International Importance data set represents the results of an analysis using the boundaries for Ramsar sites designated under the Ramsar Convention on Wetlands and intersecting them with different elevation zones in the coastal zone to assess area and percent area that would become inundated under 1 and 2 meter sea level rise scenarios. This data set provides results for 613 sites with defined boundaries that were found to intersect with the 0-5m above mean sea level coastal zone, defined by NASA Shuttle Radar Topography Mission (SRTM) elevation data. In addition to assessing the degree of risk of inundation, the data set provides data on population density and percent of land that is urban within the site and within 1km and 5km buffers surrounding the site. The data set also reports on infant mortality rates within 1km and 5km buffers around the site, as a measure of poverty levels that may affect adaptive capacity.
The Sea Level Rise Impacts on Ramsar Wetlands of International Importance data set represents the results of an analysis using the boundaries for Ramsar sites designated under the Ramsar Convention on Wetlands and intersecting them with different elevation zones in the coastal zone to assess area and percent area that would become inundated under 1 and 2 meter sea level rise scenarios. This data set provides results for 613 sites with defined boundaries that were found to intersect with the 0-5m above mean sea level coastal zone, defined by NASA Shuttle Radar Topography Mission (SRTM) elevation data. In addition to assessing the degree of risk of inundation, the data set provides data on population density and percent of land that is urban within the site and within 1km and 5km buffers surrounding the site. The data set also reports on infant mortality rates within 1km and 5km buffers around the site, as a measure of poverty levels that may affect adaptive capacity.
<p><font color="#FF0000">Note: This data set is now on FTP so references to CD-ROM are historic and no longer applicable.</font></p>

The Ice Altimetry System (IAS) data seet contains surface elevations of
the Antarctic and Greenland ice sheets derived from Seasat and GEOSAT
radar altimetry data. The Seasat data were collected for a continuous
90 days in 1978, at latitudes between 72 degrees South and 72 degrees
North. GEOSAT was launched in 1985 and placed in a nearly identical
orbit to Seasat, also at latitudes of between 72 degrees South and 72
degrees North. The orbit was designed to provide high-density
measurements over the Earth's surface, at a maximum grid spacing of 2.7 kilometers at the equator and much denser spacing over polar ice
sheets. Data were acquired between April 1985 and September 1986.

Initially acquired by the Johns Hopkins APL (Applied Physics Lab)
satellite tracking facility, the raw altimetry satellite data from
Seasat and GEOSAT were passed on to NASA, via the US Navy. NASA
developed slope correction routines for the higher slopes over the ice
sheets, relative to ocean surfaces. The data are height profile Level
3 data and gridded height Level 4 data provided by the Oceans and Ice
branch of the Laboratory for Hydrospheric Physics of Goddard Space
Flight Center. Elevations from the full data rate (i.e., one
measurement every 662.5 m) are provided in georeferenced databases.
These elevations are relative to the WGS-84 ellipsoid. Gridded
elevations at 10-kilometer and 20-kilometer spacing are provided in
the gridded data sets created from the GEOSAT and Seasat data,
respectively. Software to extract and browse subsets of these data is
included. The IAS software also allows the user to view
contours created from the gridded data and groundtracks of the
full-rate data.
<p><font color="#FF0000">Note: This data set is now on FTP so references to CD-ROM are historic and no longer applicable.</font></p>

The Ice Altimetry System (IAS) data seet contains surface elevations of
the Antarctic and Greenland ice sheets derived from Seasat and GEOSAT
radar altimetry data. The Seasat data were collected for a continuous
90 days in 1978, at latitudes between 72 degrees South and 72 degrees
North. GEOSAT was launched in 1985 and placed in a nearly identical
orbit to Seasat, also at latitudes of between 72 degrees South and 72
degrees North. The orbit was designed to provide high-density
measurements over the Earth's surface, at a maximum grid spacing of 2.7 kilometers at the equator and much denser spacing over polar ice
sheets. Data were acquired between April 1985 and September 1986.

Initially acquired by the Johns Hopkins APL (Applied Physics Lab)
satellite tracking facility, the raw altimetry satellite data from
Seasat and GEOSAT were passed on to NASA, via the US Navy. NASA
developed slope correction routines for the higher slopes over the ice
sheets, relative to ocean surfaces. The data are height profile Level
3 data and gridded height Level 4 data provided by the Oceans and Ice
branch of the Laboratory for Hydrospheric Physics of Goddard Space
Flight Center. Elevations from the full data rate (i.e., one
measurement every 662.5 m) are provided in georeferenced databases.
These elevations are relative to the WGS-84 ellipsoid. Gridded
elevations at 10-kilometer and 20-kilometer spacing are provided in
the gridded data sets created from the GEOSAT and Seasat data,
respectively. Software to extract and browse subsets of these data is
included. The IAS software also allows the user to view
contours created from the gridded data and groundtracks of the
full-rate data.
<p><font color="#FF0000">Note: This data set is now on FTP so references to CD-ROM are historic and no longer applicable.</font></p>

The Ice Altimetry System (IAS) data seet contains surface elevations of
the Antarctic and Greenland ice sheets derived from Seasat and GEOSAT
radar altimetry data. The Seasat data were collected for a continuous
90 days in 1978, at latitudes between 72 degrees South and 72 degrees
North. GEOSAT was launched in 1985 and placed in a nearly identical
orbit to Seasat, also at latitudes of between 72 degrees South and 72
degrees North. The orbit was designed to provide high-density
measurements over the Earth's surface, at a maximum grid spacing of 2.7 kilometers at the equator and much denser spacing over polar ice
sheets. Data were acquired between April 1985 and September 1986.

Initially acquired by the Johns Hopkins APL (Applied Physics Lab)
satellite tracking facility, the raw altimetry satellite data from
Seasat and GEOSAT were passed on to NASA, via the US Navy. NASA
developed slope correction routines for the higher slopes over the ice
sheets, relative to ocean surfaces. The data are height profile Level
3 data and gridded height Level 4 data provided by the Oceans and Ice
branch of the Laboratory for Hydrospheric Physics of Goddard Space
Flight Center. Elevations from the full data rate (i.e., one
measurement every 662.5 m) are provided in georeferenced databases.
These elevations are relative to the WGS-84 ellipsoid. Gridded
elevations at 10-kilometer and 20-kilometer spacing are provided in
the gridded data sets created from the GEOSAT and Seasat data,
respectively. Software to extract and browse subsets of these data is
included. The IAS software also allows the user to view
contours created from the gridded data and groundtracks of the
full-rate data.
SEASAT std frame product
SEASAT std frame product
SEASAT std frame product
SEASAT std frame product Processed to Level 1
SEASAT std frame product Processed to Level 1
SEASAT std frame product Processed to Level 1
The SeaWiFS Deep Blue Level 3 Product contains daily global gridded (0.5 x 0.5 deg) data derived from SeaWiFS Deep Blue Level 2 data. 

In most cases, each data field represents the arithmetic mean of all cells whose latitude and longitude places it within the bounds of each grid element. Furthermore, only cells measured on the day of interest are included in this calculation. The local date based on the longitude of the cell is calculated from the time of measurement. If the local date equals the day of interest, the cell is included in the L3 data processing

The primary data parameters are aerosol optical thickness, Angstrom exponent, and single scattering albedo.

(The Shortname for this product is SWDB_L305).


Parameters contained in the SeaWiFS Deep Blue (SWDB) data files include the following:

aerosol_optical_thickness_550_land | aerosol optical thickness estimated at 550 nm over land | (unitless)
aerosol_optical_thickness_550_land_ocean | aerosol optical thickness estimated at 550 nm over land and ocean | (unitless)
aerosol_optical_thickness_550_ocean | aerosol optical thickness estimated at 550 nm over ocean | (unitless)
aerosol_optical_thickness_land | aerosol optical thickness at 412 nm, 490 nm, and 670 nm over land  | (unitless)
aerosol_optical_thickness_ocean | aerosol optical thickness at 412 nm, 490 nm, and 670 nm over ocean | (unitless)
angstrom_exponent_land | angstrom exponent over land as derived from aerosol optical thickness at 412 nm and 490 nm  | (unitless)
angstrom_exponent_land_ocean | angstrom exponent over land and ocean as derived from aerosol optical thickness at 412 nm and 490 nm  | (unitless)
angstrom_exponent_ocean | angstrom exponent over ocean as derived from aerosol optical thickness at 412 nm and 490 nm  | (unitless)

End of parameter information
The SeaWiFS Deep Blue Level 3 Product contains daily global gridded (1 x 1 deg) data derived from SeaWiFS Deep Blue Level 2 data. 

In most cases, each data field represents the arithmetic mean of all cells whose latitude and longitude places it within the bounds of each grid element. Furthermore, only cells measured on the day of interest are included in this calculation. The local date based on the longitude of the cell is calculated from the time of measurement. If the local date equals the day of interest, the cell is included in the L3 data processing

The primary data parameters are aerosol optical thickness, Angstrom exponent, and single scattering albedo.

(The Shortname for this product is SWDB_L310).

Parameters contained in the SeaWiFS Deep Blue (SWDB) data files include the following:

aerosol_optical_thickness_550_land | aerosol optical thickness estimated at 550 nm over land | (unitless)
aerosol_optical_thickness_550_land_ocean | aerosol optical thickness estimated at 550 nm over land and ocean | (unitless)
aerosol_optical_thickness_550_ocean | aerosol optical thickness estimated at 550 nm over ocean | (unitless)
aerosol_optical_thickness_land | aerosol optical thickness at 412 nm, 490 nm, and 670 nm over land  | (unitless)
aerosol_optical_thickness_ocean | aerosol optical thickness at 412 nm, 490 nm, and 670 nm over ocean | (unitless)
angstrom_exponent_land | angstrom exponent over land as derived from aerosol optical thickness at 412 nm and 490 nm  | (unitless)
angstrom_exponent_land_ocean | angstrom exponent over land and ocean as derived from aerosol optical thickness at 412 nm and 490 nm  | (unitless)
angstrom_exponent_ocean | angstrom exponent over ocean as derived from aerosol optical thickness at 412 nm and 490 nm  | (unitless)


End of parameter information
The SeaWiFS Deep Blue Level 3 Monthly Product contains monthly global gridded (0.5 x 0.5 deg) data derived from SeaWiFS Deep Blue Level 3 daily gridded data. 

The primary data parameters are aerosol optical thickness, Angstrom exponent, and single scattering albedo.

(The Shortname for this product is SWDB_L3M05).

Parameters contained in the SeaWiFS Deep Blue (SWDB) data files include the following:

aerosol_optical_thickness_550_land | aerosol optical thickness estimated at 550 nm over land | (unitless)
aerosol_optical_thickness_550_land_ocean | aerosol optical thickness estimated at 550 nm over land and ocean | (unitless)
aerosol_optical_thickness_550_ocean | aerosol optical thickness estimated at 550 nm over ocean | (unitless)
aerosol_optical_thickness_land | aerosol optical thickness at 412 nm, 490 nm, and 670 nm over land  | (unitless)
aerosol_optical_thickness_ocean | aerosol optical thickness at 412 nm, 490 nm, and 670 nm over ocean | (unitless)
angstrom_exponent_land | angstrom exponent over land as derived from aerosol optical thickness at 412 nm and 490 nm  | (unitless)
angstrom_exponent_land_ocean | angstrom exponent over land and ocean as derived from aerosol optical thickness at 412 nm and 490 nm  | (unitless)
angstrom_exponent_ocean | angstrom exponent over ocean as derived from aerosol optical thickness at 412 nm and 490 nm  | (unitless)

End of parameter information
The SeaWiFS Deep Blue Level 3 Monthly Product contains monthly global gridded (1 x 1 deg) data derived from SeaWiFS Deep Blue Level 3 daily gridded data. 

The primary data parameters are aerosol optical thickness, Angstrom exponent, and single scattering albedo.

(The Shortname for this product is SWDB_L3M10).

Parameters contained in the SeaWiFS Deep Blue (SWDB) data files include the following:

aerosol_optical_thickness_550_land | aerosol optical thickness estimated at 550 nm over land | (unitless)
aerosol_optical_thickness_550_land_ocean | aerosol optical thickness estimated at 550 nm over land and ocean | (unitless)
aerosol_optical_thickness_550_ocean | aerosol optical thickness estimated at 550 nm over ocean | (unitless)
aerosol_optical_thickness_land | aerosol optical thickness at 412 nm, 490 nm, and 670 nm over land  | (unitless)
aerosol_optical_thickness_ocean | aerosol optical thickness at 412 nm, 490 nm, and 670 nm over ocean | (unitless)
angstrom_exponent_land | angstrom exponent over land as derived from aerosol optical thickness at 412 nm and 490 nm  | (unitless)
angstrom_exponent_land_ocean | angstrom exponent over land and ocean as derived from aerosol optical thickness at 412 nm and 490 nm  | (unitless)
angstrom_exponent_ocean | angstrom exponent over ocean as derived from aerosol optical thickness at 412 nm and 490 nm  | (unitless)

End of parameter information
The SeaWiFS Deep Blue Level 3 Monthly Climatology Product contains monthly global climatology gridded (0.5 x 0.5 deg) data derived from SeaWiFS Deep Blue Level 3 monthly gridded data. 

The primary data parameters are aerosol optical thickness, and single scattering albedo.

(The Shortname for this product is SWDB_L3MC05).

Parameters contained in the SeaWiFS Deep Blue (SWDB) data files include the following:

aerosol_optical_thickness_550_land | aerosol optical thickness estimated at 550 nm over land | (unitless)
aerosol_optical_thickness_550_land_ocean | aerosol optical thickness estimated at 550 nm over land and ocean | (unitless)
aerosol_optical_thickness_550_ocean | aerosol optical thickness estimated at 550 nm over ocean | (unitless)
aerosol_optical_thickness_land | aerosol optical thickness at 412 nm, 490 nm, and 670 nm over land  | (unitless)
aerosol_optical_thickness_ocean | aerosol optical thickness at 412 nm, 490 nm, and 670 nm over ocean | (unitless)

End of parameter information
The SeaWiFS Deep Blue Level 3 Monthly Climatology Product contains monthly global climatology gridded (1 x 1 deg) data derived from SeaWiFS Deep Blue Level 3 monthly gridded data. 

The primary data parameters are aerosol optical thickness, and single scattering albedo.

(The Shortname for this product is SWDB_L3MC10).

Parameters contained in the SeaWiFS Deep Blue (SWDB) data files include the following:

aerosol_optical_thickness_550_land | aerosol optical thickness estimated at 550 nm over land | (unitless)
aerosol_optical_thickness_550_land_ocean | aerosol optical thickness estimated at 550 nm over land and ocean | (unitless)
aerosol_optical_thickness_550_ocean | aerosol optical thickness estimated at 550 nm over ocean | (unitless)
aerosol_optical_thickness_land | aerosol optical thickness at 412 nm, 490 nm, and 670 nm over land  | (unitless)
aerosol_optical_thickness_ocean | aerosol optical thickness at 412 nm, 490 nm, and 670 nm over ocean | (unitless)

End of parameter information
The Geological Survey of Alabama (GSA) analyzed changes in the coastal shoreline and sedimentation using Landsat geotiff images as part of the Sediment Analysis Network for Decision Support (SANDS) project.  The daytime geotiffs images from Landsat 5 and Landsat 7 were analyzed for sediment re-distribution after a hurricane over the Gulf of Mexico coastline in Alabama and part of the Florida area having coordinates 31 to 27 North latitude and 90 to 84.25 West longitude.  These are seasonal data for storms from 2001-2008.  In addition to the analyzed files, the data files include the ESRI files for zipped bands and grids, metadata, and storm temporal information for the sediment analysis images.
The Geological Survey of Alabama (GSA) analyzed changes in the coastal shoreline and sedimentation using Landsat geotiff images as part of the Sediment Analysis Network for Decision Support (SANDS) project.  The daytime geotiffs images from Landsat 5 and Landsat 7 were analyzed for sediment re-distribution after a hurricane over the Gulf of Mexico coastline in Alabama and part of the Florida area having coordinates 31 to 27 North latitude and 90 to 84.25 West longitude.  These are seasonal data for storms from 2001-2008.  In addition to the analyzed files, the data files include the ESRI files for zipped bands and grids, metadata, and storm temporal information for the sediment analysis images.
The Geological Survey of Alabama (GSA) analyzed changes in the coastal shoreline and sedimentation using Landsat geotiff images as part of the Sediment Analysis Network for Decision Support (SANDS) project.  The daytime geotiffs images from Landsat 5 and Landsat 7 were analyzed for sediment re-distribution after a hurricane over the Gulf of Mexico coastline in Alabama and part of the Florida area having coordinates 31 to 27 North latitude and 90 to 84.25 West longitude.  These are seasonal data for storms from 2001-2008.  In addition to the analyzed files, the data files include the ESRI files for zipped bands and grids, metadata, and storm temporal information for the sediment analysis images.
The Sediment Analysis Network for Decision Support (SANDS) analyzes Geotiff images for sediment redistribution after a hurricane on the Gulf coast and then creates a product based on the analysis.  This dataset consists of the set of daytime geotiff images from Landsat 5 and Landsat 7 provided to Geological Survey of Alabama for their analysis.  Subsetted coordinates are 31-27N latitude and 90-84.25W longitude (Gulf of Mexico coastline in Alabama and portions of Florida).  These are seasonal data for storms.
The Sediment Analysis Network for Decision Support (SANDS) analyzes Geotiff images for sediment redistribution after a hurricane on the Gulf coast and then creates a product based on the analysis.  This dataset consists of the set of daytime geotiff images from Landsat 5 and Landsat 7 provided to Geological Survey of Alabama for their analysis.  Subsetted coordinates are 31-27N latitude and 90-84.25W longitude (Gulf of Mexico coastline in Alabama and portions of Florida).  These are seasonal data for storms.
The Sediment Analysis Network for Decision Support (SANDS) analyzes Geotiff images for sediment redistribution after a hurricane on the Gulf coast and then creates a product based on the analysis.  This dataset consists of the set of daytime geotiff images from Landsat 5 and Landsat 7 provided to Geological Survey of Alabama for their analysis.  Subsetted coordinates are 31-27N latitude and 90-84.25W longitude (Gulf of Mexico coastline in Alabama and portions of Florida).  These are seasonal data for storms.
Sediment Analysis Network for Decision Support (SANDS) MODIS Geological Survey of AL (GSA) Analysis -- The Geological Survey of Alabama (GSA) generated this dataset from geoTIFF MODIS images as part of the Sediment Analysis Network for Decision Support (SANDS) project. The geoTIFF images were analyzed for sediment redistribution after hurricanes on the Gulf coast. Daytime images for Terra and Aqua MODIS Reflectance bands 8-16 for H10V6 and H10V5 were analyzed for each storm. These are seasonal data for storms from 2001-2008. In addition to the analyzed files, the data files include the ESRI files for zipped bands and/or grids, metadata, and storm temporal information for the sediment analysis images.
Sediment Analysis Network for Decision Support (SANDS) MODIS Geological Survey of AL (GSA) Analysis -- The Geological Survey of Alabama (GSA) generated this dataset from geoTIFF MODIS images as part of the Sediment Analysis Network for Decision Support (SANDS) project. The geoTIFF images were analyzed for sediment redistribution after hurricanes on the Gulf coast. Daytime images for Terra and Aqua MODIS Reflectance bands 8-16 for H10V6 and H10V5 were analyzed for each storm. These are seasonal data for storms from 2001-2008. In addition to the analyzed files, the data files include the ESRI files for zipped bands and/or grids, metadata, and storm temporal information for the sediment analysis images.
Sediment Analysis Network for Decision Support (SANDS) MODIS Geological Survey of AL (GSA) Analysis -- The Geological Survey of Alabama (GSA) generated this dataset from geoTIFF MODIS images as part of the Sediment Analysis Network for Decision Support (SANDS) project. The geoTIFF images were analyzed for sediment redistribution after hurricanes on the Gulf coast. Daytime images for Terra and Aqua MODIS Reflectance bands 8-16 for H10V6 and H10V5 were analyzed for each storm. These are seasonal data for storms from 2001-2008. In addition to the analyzed files, the data files include the ESRI files for zipped bands and/or grids, metadata, and storm temporal information for the sediment analysis images.
Sediment Analysis Network for Decision Support (SANDS) MODIS GeoTIFF -- The Sediment Analysis Network for Decision Support (SANDS) analyzes GeoTIFF images to determine sediment redistribution after a hurricane on the Gulf coast and then creates a product based on the analysis. This dataset consists of the set of GeoTIFF images provided to the Geological Survey of Alabama for their analysis. Only daytime images for Terra and Aqua MODIS Reflectance bands 8-16 for H10V6 and H10V5 were used to create the GeoTIFF images for each storm. These are seasonal data for storms.
Sediment Analysis Network for Decision Support (SANDS) MODIS GeoTIFF -- The Sediment Analysis Network for Decision Support (SANDS) analyzes GeoTIFF images to determine sediment redistribution after a hurricane on the Gulf coast and then creates a product based on the analysis. This dataset consists of the set of GeoTIFF images provided to the Geological Survey of Alabama for their analysis. Only daytime images for Terra and Aqua MODIS Reflectance bands 8-16 for H10V6 and H10V5 were used to create the GeoTIFF images for each storm. These are seasonal data for storms.
Sediment Analysis Network for Decision Support (SANDS) MODIS GeoTIFF -- The Sediment Analysis Network for Decision Support (SANDS) analyzes GeoTIFF images to determine sediment redistribution after a hurricane on the Gulf coast and then creates a product based on the analysis. This dataset consists of the set of GeoTIFF images provided to the Geological Survey of Alabama for their analysis. Only daytime images for Terra and Aqua MODIS Reflectance bands 8-16 for H10V6 and H10V5 were used to create the GeoTIFF images for each storm. These are seasonal data for storms.
Sediment Analysis Network for Decision Support (SANDS) MODIS Gulf Subsetted -- The Sediment Analysis Network for Decision Support (SANDS) analyzes GeoTIFF images to determine sediment redistribution after a hurricane on the Gulf coast and then creates a product based on the analysis. This dataset consists of daytime images for Terra and Aqua MODIS Reflectance bands 8-16 for H10V6 and H10V5 for each storm, subsetted to 31-27N latitude and 90-84.25W longitude (Gulf of Mexico coastline in Alabama and portions of Florida). These are seasonal data for storms.
Sediment Analysis Network for Decision Support (SANDS) MODIS Gulf Subsetted -- The Sediment Analysis Network for Decision Support (SANDS) analyzes GeoTIFF images to determine sediment redistribution after a hurricane on the Gulf coast and then creates a product based on the analysis. This dataset consists of daytime images for Terra and Aqua MODIS Reflectance bands 8-16 for H10V6 and H10V5 for each storm, subsetted to 31-27N latitude and 90-84.25W longitude (Gulf of Mexico coastline in Alabama and portions of Florida). These are seasonal data for storms.
Sediment Analysis Network for Decision Support (SANDS) MODIS Gulf Subsetted -- The Sediment Analysis Network for Decision Support (SANDS) analyzes GeoTIFF images to determine sediment redistribution after a hurricane on the Gulf coast and then creates a product based on the analysis. This dataset consists of daytime images for Terra and Aqua MODIS Reflectance bands 8-16 for H10V6 and H10V5 for each storm, subsetted to 31-27N latitude and 90-84.25W longitude (Gulf of Mexico coastline in Alabama and portions of Florida). These are seasonal data for storms.
The nitrogen and chlorophyll concentrations of constructed Douglas-fir and bigleaf maple seedling canopies were determined. Canopy reflectance spectra were measured before foliage samples were collected.
The nitrogen and chlorophyll concentrations of constructed Douglas-fir and bigleaf maple seedling canopies were determined. Canopy reflectance spectra were measured before foliage samples were collected.
ABSTRACT: The nitrogen and chlorophyll concentrations of constructed Douglas-fir and bigleaf maple seedling canopies were determined. Canopy reflectance spectra were measured before foliage samples were collected.
The reflectance spectra of Douglas-fir and bigleaf maple seedling canopies were measured. Canopies varied in fertilizer treatment and leaf area density respectively.
The reflectance spectra of Douglas-fir and bigleaf maple seedling canopies were measured. Canopies varied in fertilizer treatment and leaf area density respectively.
ABSTRACT: The reflectance spectra of Douglas-fir and bigleaf maple seedling canopies were measured. Canopies varied in fertilizer treatment and leaf area density respectively.
Daily coordinate time series of geodetic station positions, velocity fields, strain and strain rate, and time series offsets for Western North America produced by JPL and Scripps Orbit and Permanent Array Center (SOPAC) as part of the MeASUReS investigation Solid Earth Science ESDR System (SESES).
Daily coordinate time series of geodetic station positions, velocity fields, strain and strain rate, and time series offsets for Western North America produced by JPL and Scripps Orbit and Permanent Array Center (SOPAC) as part of the MeASUReS investigation Solid Earth Science ESDR System (SESES).
Daily coordinate time series of geodetic station positions, velocity fields, strain and strain rate, and time series offsets for Western North America produced by JPL and Scripps Orbit and Permanent Array Center (SOPAC) as part of the MeASUReS investigation Solid Earth Science ESDR System (SESES).
The Shuttle Solar Backscatter Ultraviolet (SSBUV) Level-2 Ozone data are available for eight space shuttle missions flown between 1989 and 1996. SSBUV, a successor to the SBUV flown on the Nimbus-7 satellite, is nearly identical to the SBUV/2 instruments flying on the NOAA satellites. Data are available in the ASCII AMES text format. Ozone profiles of the uppoer atmosphere and total column ozone values are available for the following time periods:

 Flight #1:  1989 October 19, 20, 21.
 Flight #2:  1990 October 7, 8, 9.
 Flight #3:  1991 August 3, 4, 5, 6.
 Flight #4:  1992 March 29, 31.
 Flight #5:  1993 April 9, 11, 13, 15, 16.
 Flight #6:  1994 March 14, 15, 17.
 Flight #7:  1994 November 5, 7, 10, 13.
 Flight #8:  1996 January 12, 16, 18.

SSBUV measures spectral ultraviolet radiances backscattered by the earth's atmosphere. For the ozone measurements the instrument steps over wavelengths between 252.2 and 339.99 nm while viewing the earth in the nadir position (50 km x 50 km footprint at nadir) at 19 pressure levels between 0.3 mb and 100 mb.
The Shuttle Solar Backscatter Ultraviolet (SSBUV) level-2 irradiance data are available for eight space shuttle missions flown between 1989 and 1996. SSBUV, a successor to the SBUV flown on the Nimbus-7 satellite, is nearly identical to the SBUV/2 instruments flown on the NOAA polar orbiting satellites. Data are available in an ASCII text format. UV irradiance data are available for the following days from the eight missions:

Flight #1: 1989 October 19, 20, 21
Flight #2: 1990 October 7, 8, 9
Flight #3: 1991 August 3, 4, 5, 6
Flight #4: 1992 March 29, 30
Flight #5: 1993 April 9, 11, 13, 15, 16
Flight #6: 1994 March 14, 15, 17
Flight #7: 1994 November 5, 7, 10, 13
Flight #8: 1996 January 12, 16, 18
      
The Shuttle SBUV (SSBUV) instrument measured solar spectral UV irradiance during the maximum and declining phase of solar cycle 22. The SSBUV data accurately represent the absolute solar UV irradiance between 200–405 nm, and also show the long-term variations during eight flights between October 1989 and January 1996. These data have been used to correct long-term sensitivity changes in the NOAA-11 SBUV/2 data, which provide a near-daily record of solar UV variations over the 170–400 nm region between December 1988 and October 1994. These data demonstrate the evolution of short-term solar UV activity during solar cycle 22.
Site averaged product of the Portable Automatic Meteorological Station (AMS) data acquired during the 1987-1989 FIFE experiment. Data are in 30-minute time intervals in 1987.
Site averaged product of the Portable Automatic Meteorological Station (AMS) data acquired during the 1987-1989 FIFE experiment. Data are in 30-minute time intervals in 1987.
ABSTRACT: Site averaged product of the Portable Automatic Meteorological Station (AMS) data acquired during the 1987-1989 FIFE experiment. Data are in 30-minute time intervals in 1987.
Site averaged product of the Portable Automatic Meteorological Station (AMS) data acquired during the 1987-1989 FIFE experiment. Data are in 30-minute time intervals.
Site averaged product of the Portable Automatic Meteorological Station (AMS) data acquired during the 1987-1989 FIFE experiment. Data are in 30-minute time intervals.
ABSTRACT: Site averaged product of the Portable Automatic Meteorological Station (AMS) data acquired during the 1987-1989 FIFE experiment. Data are in 30-minute time intervals.
Site averaged product of the Portable Automatic Meteorological Station (AMS) data acquired during the 1987-1989 FIFE experiment. Data are in 30-minute time intervals in 1988.
Site averaged product of the Portable Automatic Meteorological Station (AMS) data acquired during the 1987-1989 FIFE experiment. Data are in 30-minute time intervals in 1988.
ABSTRACT: Site averaged product of the Portable Automatic Meteorological Station (AMS) data acquired during the 1987-1989 FIFE experiment. Data are in 30-minute time intervals in 1988.
Site averaged product of the Portable Automatic Meteorological Station (AMS) data acquired during the 1987-1989 FIFE experiment. Data are in 30-minute time intervals in 1989.
Site averaged product of the Portable Automatic Meteorological Station (AMS) data acquired during the 1987-1989 FIFE experiment. Data are in 30-minute time intervals in 1989.
ABSTRACT: Site averaged product of the Portable Automatic Meteorological Station (AMS) data acquired during the 1987-1989 FIFE experiment. Data are in 30-minute time intervals in 1989.
Site averaged product of the flux data collected by many PIs during the 1987-1989 FIFE experiment. Data are in 30-minute intervals and include data only for 1987.
Site averaged product of the flux data collected by many PIs during the 1987-1989 FIFE experiment. Data are in 30-minute intervals and include data only for 1987.
ABSTRACT: Site averaged product of the flux data collected by many PIs during the 1987-1989 FIFE experiment. Data are in 30-minute intervals and include data only for 1987.
Site averaged product of the flux data collected by many PIs during the 1987-1989 FIFE experiment. Data are in 30-minute intervals and include the entire period 1987-1989.
Site averaged product of the flux data collected by many PIs during the 1987-1989 FIFE experiment. Data are in 30-minute intervals and include the entire period 1987-1989.
ABSTRACT: Site averaged product of the flux data collected by many PIs during the 1987-1989 FIFE experiment. Data are in 30-minute intervals and include the entire period 1987-1989.
Site averaged product of the flux data collected by many PIs during the 1987-1989 FIFE experiment. Data are in 30-minute intervals and include data only for 1988.
Site averaged product of the flux data collected by many PIs during the 1987-1989 FIFE experiment. Data are in 30-minute intervals and include data only for 1988.
ABSTRACT: Site averaged product of the flux data collected by many PIs during the 1987-1989 FIFE experiment. Data are in 30-minute intervals and include data only for 1988.
Site averaged product of the flux data collected by many PIs during the 1987-1989 FIFE experiment. Data are in 30-minute intervals and include data only for 1989.
Site averaged product of the flux data collected by many PIs during the 1987-1989 FIFE experiment. Data are in 30-minute intervals and include data only for 1989.
ABSTRACT: Site averaged product of the flux data collected by many PIs during the 1987-1989 FIFE experiment. Data are in 30-minute intervals and include data only for 1989.
Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes only 1987 data.
Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes only 1987 data.
ABSTRACT: Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes only 1987 data.
Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes 1987-1989 data.
Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes 1987-1989 data.
ABSTRACT: Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes 1987-1989 data.
Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes only 1988 data.
Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes only 1988 data.
ABSTRACT: Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes only 1988 data.
Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes only 1989 data.
Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes only 1989 data.
ABSTRACT: Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes only 1989 data.
Site averaged product of the neutron probe soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes only 1987 data.
Site averaged product of the neutron probe soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes only 1987 data.
ABSTRACT: Site averaged product of the neutron probe soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes only 1987 data.
Site averaged product of the neutron probe soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes 1987-1989 data.
Site averaged product of the neutron probe soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes 1987-1989 data.
ABSTRACT: Site averaged product of the neutron probe soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes 1987-1989 data.
Site averaged product of the neutron probe soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes only 1988 data.
Site averaged product of the neutron probe soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes only 1988 data.
ABSTRACT: Site averaged product of the neutron probe soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Includes only 1988 data.
Site averaged product of the neutron probe soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Only 15 days available in 89.
Site averaged product of the neutron probe soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Only 15 days available in 89.
ABSTRACT: Site averaged product of the neutron probe soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each day. Only 15 days available in 89.
AVIRIS image scenes were acquired in 1992 over ACCP sites. Pixels that coincided with field study plots were extracted and reflectance values were correlated  with estimated canopy carbon and nitrogen content.
AVIRIS image scenes were acquired in 1992 over ACCP sites. Pixels that coincided with field study plots were extracted and reflectance values were correlated  with estimated canopy carbon and nitrogen content.
ABSTRACT: AVIRIS image scenes were acquired in 1992 over ACCP sites. Pixels that coincided with field study plots were extracted and reflectance values were correlated  with estimated canopy carbon and nitrogen content.
This data set contains in situ vegetation data collected at several agricultural sites as a part of the Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12).
This data set consists of land cover classification data derived from satellite imagery as part of the Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12).
This data set contains backscatter data obtained by the Passive Active L-band System (PALS) microwave aircraft instrument as a part of the Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12).
This data set contains brightness temperature data obtained by the Passive Active L-band System (PALS) microwave aircraft instrument as a part of the Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12).
This data set contains in situ soil moisture data collected at several agricultural sites as a part of the Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12).
This data set contains in situ soil moisture data collected at several forested sites as a part of the Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12).
This data set contains surface roughness data collected at several agricultural sites as a part of the Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12).
This data set contains surface roughness data collected at several forested sites as a part of the Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12).
This data set contains backscatter data obtained by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) instrument as partof the Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12).
This data set contains the vegetation water content map derived by calculating Normalized Difference Water Index (NDWI) from SPOT and RapidEye satellite imagery as part of the Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12).
This data set consists of observations of atmospheric parameters including spectral aerosol optical depths, precipitable water, sky radiance distributions and aerosol volume, and particle size distribution. Data were collected by the Aerosol Robotic Network (AERONET) program, a federation of ground-based remote sensing aerosol networks composed of automatic sun and sky scanning radiometers. AERONET's goal is to assess aerosol optical properties and validate satellite data. The study site was in the Soil Moisture Experiment 2002 (SMEX02) area of Iowa, USA for the period from 20 June to 17 July 2002. 

A sun photometer was set up at a centrally located site within the Walnut Creek watershed for the collection of aerosol optical properties throughout the course of the SMEX02 field campaign.  Three levels of data are available: Level 1.0 (unscreened), Level 1.5 (cloud-screened), and Level 2.0 (cloud-screened and quality-assured).

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002. AMSR-E validation studies linked to SMEX are designed to evaluate the accuracy of AMSR-E soil moisture data. Specific validation objectives include assessing and refining soil moisture algorithm performance; verifying soil moisture estimation accuracy; investigating the effects of vegetation, surface temperature, topography, and soil texture on soil moisture accuracy; and determining the regions that are useful for AMSR-E soil moisture measurements.
This is a combined data set of canopy, subcanopy and understory composition by vegetation species and study site ID
This is a combined data set of canopy, subcanopy and understory composition by vegetation species and study site ID
ABSTRACT: This is a combined data set of canopy, subcanopy and understory composition by vegetation species and study site ID
Measurements of green leaf coverage during the spring of 1984 for canopy, canopy, and understory species for two aspen sites in the Superior National Forest, Minnesota
Measurements of green leaf coverage during the spring of 1984 for canopy, canopy, and understory species for two aspen sites in the Superior National Forest, Minnesota
ABSTRACT: Measurements of green leaf coverage during the spring of 1984 for canopy, canopy, and understory species for two aspen sites in the Superior National Forest, Minnesota
SNF study location measurements of percent ground coverage provided by each understory species; percentages are averages of five 2-meter-diameter subsamples in each site (presented as list format)
SNF study location measurements of percent ground coverage provided by each understory species; percentages are averages of five 2-meter-diameter subsamples in each site (presented as list format)
ABSTRACT: SNF study location measurements of percent ground coverage provided by each understory species; percentages are averages of five 2-meter-diameter subsamples in each site (presented as list format)
SNF study location measurements of percent ground coverage provided by each understory species; percentages are averages of five 2-meter-diameter subsamples in each site (presented in table format)
SNF study location measurements of percent ground coverage provided by each understory species; percentages are averages of five 2-meter-diameter subsamples in each site (presented in table format)
ABSTRACT: SNF study location measurements of percent ground coverage provided by each understory species; percentages are averages of five 2-meter-diameter subsamples in each site (presented in table format)
Reflectance and transmittance properties of the leaves, needles, branches, moss, and litter of 8 major overstory tree species and 3 understory shrubs measured by Cary-14 spectrometer in the SNF, MN
Reflectance and transmittance properties of the leaves, needles, branches, moss, and litter of 8 major overstory tree species and 3 understory shrubs measured by Cary-14 spectrometer in the SNF, MN
ABSTRACT: Reflectance and transmittance properties of the leaves, needles, branches, moss, and litter of 8 major overstory tree species and 3 understory shrubs measured by Cary-14 spectrometer in the SNF, MN
Reflectance and transmittance properties of canopy components, measured by Cary-14 spectrometer and averaged (weighted average) to Thematic Mapper Simulator (TMS) wavelength bands; see SNF_CAN_SPEC
Reflectance and transmittance properties of canopy components, measured by Cary-14 spectrometer and averaged (weighted average) to Thematic Mapper Simulator (TMS) wavelength bands; see SNF_CAN_SPEC
ABSTRACT: Reflectance and transmittance properties of canopy components, measured by Cary-14 spectrometer and averaged (weighted average) to Thematic Mapper Simulator (TMS) wavelength bands; see SNF_CAN_SPEC
Canopy spectral reflectance data collected from the NASA C-130-mounted NS001 Thematic Mapper Simulator (TMS) over the Superior National Forest, MN on 13JUL1983, 06AUG1983, and 28JUN1984.
Canopy spectral reflectance data collected from the NASA C-130-mounted NS001 Thematic Mapper Simulator (TMS) over the Superior National Forest, MN on 13JUL1983, 06AUG1983, and 28JUN1984.
ABSTRACT: Canopy spectral reflectance data collected from the NASA C-130-mounted NS001 Thematic Mapper Simulator (TMS) over the Superior National Forest, MN on 13JUL1983, 06AUG1983, and 28JUN1984.
Inventory of various satellite image data acquired for the Superior National Forest, MN study including MSS, TM, SPOT, and HRV1-HRV2 over a period from 03JUL1983 to 16AUG1990
Inventory of various satellite image data acquired for the Superior National Forest, MN study including MSS, TM, SPOT, and HRV1-HRV2 over a period from 03JUL1983 to 16AUG1990
ABSTRACT: Inventory of various satellite image data acquired for the Superior National Forest, MN study including MSS, TM, SPOT, and HRV1-HRV2 over a period from 03JUL1983 to 16AUG1990
Site characterization parameters (canopy density, litter components, soil characterization: color, moisture, components) for selected sites within the Superior National Forest, MN during 1988-89
Site characterization parameters (canopy density, litter components, soil characterization: color, moisture, components) for selected sites within the Superior National Forest, MN during 1988-89
ABSTRACT: Site characterization parameters (canopy density, litter components, soil characterization: color, moisture, components) for selected sites within the Superior National Forest, MN during 1988-89
Site characterization parameters (canopy density, litter components, species composition) collected from selected sites in the SNF, MN, during 1986 for validating image classification methodology
Site characterization parameters (canopy density, litter components, species composition) collected from selected sites in the SNF, MN, during 1986 for validating image classification methodology
ABSTRACT: Site characterization parameters (canopy density, litter components, species composition) collected from selected sites in the SNF, MN, during 1986 for validating image classification methodology
Biophysical parameters (DBH, shrub diameter, growth format, frequency) for selected sites within the Superior National Forest, MN, during 1988-89
Biophysical parameters (DBH, shrub diameter, growth format, frequency) for selected sites within the Superior National Forest, MN, during 1988-89
ABSTRACT: Biophysical parameters (DBH, shrub diameter, growth format, frequency) for selected sites within the Superior National Forest, MN, during 1988-89
The Socioeconomic Data and Applications Center (SEDAC) Collection of Treaty Texts consists of environmental treaty texts compiled in collaboration with the Columbia University Center for International Earth Science Information Network (CIESIN), United Nations Environmental Programme (UNEP), Tufts University Fletcher School of Law and Diplomacy (FSLD), British Columbia Ministry of Environment, Lands, and Parks (BCMELP), Antarctic Cooperative Research Centre (ACRC), and American Society of International Law (ASIL).
The Socioeconomic Data and Applications Center (SEDAC) Collection of Treaty Texts consists of environmental treaty texts compiled in collaboration with the Columbia University Center for International Earth Science Information Network (CIESIN), United Nations Environmental Programme (UNEP), Tufts University Fletcher School of Law and Diplomacy (FSLD), British Columbia Ministry of Environment, Lands, and Parks (BCMELP), Antarctic Cooperative Research Centre (ACRC), and American Society of International Law (ASIL).
The Socioeconomic Data and Applications Center (SEDAC) Collection of Treaty Texts consists of environmental treaty texts compiled in collaboration with the Columbia University Center for International Earth Science Information Network (CIESIN), United Nations Environmental Programme (UNEP), Tufts University Fletcher School of Law and Diplomacy (FSLD), British Columbia Ministry of Environment, Lands, and Parks (BCMELP), Antarctic Cooperative Research Centre (ACRC), and American Society of International Law (ASIL). (Suggested Usage: To provide search and retrieval of texts of multilateral environmental agreements (MEAs).)
The Socioeconomic Data and Application Center (SEDAC) Treaty Status Dataset contains comprehensive treaty information for multilateral environmental agreements, countries and organizations. The original data were obtained from the International Union for the Conservation of Nature and Natural Resources (IUCN) Environmental Law Center. SEDAC reorganized the data and added new variables computed from the original variables to include the year of agreement, year of entry into force, length of time to enter into force, number of signatories, parties, and former parties (if applicable), in addition to year of signature, ratification, accession or adherence, acceptance or approval, succession and denunciation. This dataset is produced in collaboration with IUCN and the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide information on the status of country participation in international environmental agreements.)
The Socioeconomic Data and Application Center (SEDAC) Treaty Status Dataset contains comprehensive treaty information for multilateral environmental agreements, countries and organizations. The original data were obtained from the International Union for the Conservation of Nature and Natural Resources (IUCN) Environmental Law Center. SEDAC reorganized the data and added new variables computed from the original variables to include the year of agreement, year of entry into force, length of time to enter into force, number of signatories, parties, and former parties (if applicable), in addition to year of signature, ratification, accession or adherence, acceptance or approval, succession and denunciation. This dataset is produced in collaboration with IUCN and the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide information on the status of country participation in international environmental agreements.)
The Socioeconomic Data and Application Center (SEDAC) Treaty Status Dataset contains comprehensive treaty information for multilateral environmental agreements, countries and organizations. The original data were obtained from the International Union for the Conservation of Nature and Natural Resources (IUCN) Environmental Law Center. SEDAC reorganized the data and added new variables computed from the original variables to include the year of agreement, year of entry into force, length of time to enter into force, number of signatories, parties, and former parties (if applicable), in addition to year of signature, ratification, accession or adherence, acceptance or approval, succession and denunciation. This dataset is produced in collaboration with IUCN and the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide information on the status of country participation in international environmental agreements.)
Soil bulk density data collected on the Konza Prairie
Soil bulk density data collected on the Konza Prairie
ABSTRACT: Soil bulk density data collected on the Konza Prairie
Contains TGB-01 carbon soil profile data for Northern Study Area.
Contains TGB-01 carbon soil profile data for Northern Study Area.
ABSTRACT: Contains TGB-01 carbon soil profile data for Northern Study Area.
Soil surface CO2 flux data collected by John Norman
Soil surface CO2 flux data collected by John Norman
ABSTRACT: Soil surface CO2 flux data collected by John Norman
Nitrous oxide flux and CO2 from soil respiration measured using soil cores
Nitrous oxide flux and CO2 from soil respiration measured using soil cores
ABSTRACT: Nitrous oxide flux and CO2 from soil respiration measured using soil cores
Field saturated hydraulic conductivity, using constant well head permeameter
Field saturated hydraulic conductivity, using constant well head permeameter
ABSTRACT: Field saturated hydraulic conductivity, using constant well head permeameter
Soil impedance & temperature measured with Radio Frequency Soil Moisture Probe
Soil impedance & temperature measured with Radio Frequency Soil Moisture Probe
ABSTRACT: Soil impedance & temperature measured with Radio Frequency Soil Moisture Probe
Gravimetric soil moisture data collected in conjunction w/ gamma ray soil study
Gravimetric soil moisture data collected in conjunction w/ gamma ray soil study
ABSTRACT: Gravimetric soil moisture data collected in conjunction w/ gamma ray soil study
Soil moisture collected at 25mm, 75mm, and 150mm
Soil moisture collected at 25mm, 75mm, and 150mm
ABSTRACT: Soil moisture collected at 25mm, 75mm, and 150mm
Soil moisture data collected using a neutron probe 200cm in length
Soil moisture data collected using a neutron probe 200cm in length
ABSTRACT: Soil moisture data collected using a neutron probe 200cm in length
Soil moisture release characteristics
Soil moisture release characteristics
ABSTRACT: Soil moisture release characteristics
Soil moisture & bulk density measurements
Soil moisture & bulk density measurements
ABSTRACT: Soil moisture & bulk density measurements
Spectral reflectance of soils, Atlas of Soil Reflectance Properties (Stoner '80)
Spectral reflectance of soils, Atlas of Soil Reflectance Properties (Stoner '80)
ABSTRACT: Spectral reflectance of soils, Atlas of Soil Reflectance Properties (Stoner '80)
Soil properties reference information
Soil properties reference information
ABSTRACT: Soil properties reference information
1989 FIFE staff science soil properties measurements
1989 FIFE staff science soil properties measurements
ABSTRACT: 1989 FIFE staff science soil properties measurements
Soil hydraulic properties
Soil hydraulic properties
ABSTRACT: Soil hydraulic properties
The Total Solar Irradiance (TSI) data set SOR3TSI6 contains the total solar irradiance (a.k.a solar constant) data collected by the Total Irradiance Monitor (TIM) instrument covering the full wavelength spectrum averaged at 6-hour intervals. The data are normalized to one astronomical unit (1 AU).

The TIM instrument measures the Total Solar Irradiance (TSI), monitoring changes in incident sunlight to the Earth's atmosphere using an ambient temperature active cavity radiometer to a designed absolute accuracy of 100 parts per million (ppm, 1 ppm=0.0001% at 1-sigma) and a precision and long-term relative accuracy of 10 ppm per year. Due to the small size these data and to maximize ease of use to end-users, each delivered TSI product contains science results for the entire mission. Updates to Level 3 TSI data occur monthly in order to reduce repeated delivery of data.
The Total Solar Irradiance (TSI) data set SOR3TSID contains the total solar irradiance (a.k.a solar constant) data collected by the Total Irradiance Monitor (TIM) instrument covering the full wavelength spectrum averaged at daily intervals. The data are normalized to one astronomical unit (1 AU).

The TIM instrument measures the Total Solar Irradiance (TSI), monitoring changes in incident sunlight to the Earth's atmosphere using an ambient temperature active cavity radiometer to a designed absolute accuracy of 100 parts per million (ppm, 1 ppm=0.0001% at 1-sigma) and a precision and long-term relative accuracy of 10 ppm per year. Due to the small size these data and to maximize ease of use to end-users, each delivered TSI product contains science results for the entire mission. Updates to Level 3 TSI data occur monthly in order to reduce repeated delivery of data.
The SORCE SIM Solar Spectral Irradiance (SSI) data product SOR3SIMD is constructed using measurements from the SIM instruments, which are combined into merged daily solar spectra over the spectral range from 310 to 2413 nm at a spectral resolution ranging from 1 to 27 nm. Irradiances are reported at a mean solar distance of 1 AU and zero relative line-of-sight velocity with respect to the Sun. The SIM absolute uncertainty is about 2%.

All of the SOR3SIMD data are arranged in a single file in a tabular ASCII text file which can be easily read into a spreadsheet application. The columns contain the date, Julian day, minimum wavelength, maximum wavelength, instrument mode, data version number, irradiance value, irradiance uncertainty, and data quality. The rows are arranged with data at each wavelength over the full SIM wavelength range, repeating for each day for the length of the measurement period.
The SORCE SOLSTICE Far-UV Solar Spectral Irradiance (SSI) data product SOR3SOLFUVD is constructed using measurements from the SOLSTICE FUV instrument, which are combined into merged daily solar spectra over the spectral range from 115 to 180 nm at a spectral resolution of 1 nm. Irradiances are reported at a mean solar distance of 1 AU and zero relative line-of-sight velocity with respect to the Sun. The SOLSTICE absolute uncertainty better than 5%.

All of the SOR3SOLFUVD data are arranged in a single file in a tabular ASCII text file which can be easily read into a spreadsheet application. The columns contain the date, Julian day, minimum wavelength, maximum wavelength, instrument mode, data version number, irradiance value, irradiance uncertainty, and data quality. The rows are arranged with data at each wavelength over the full SOLSTICE FUV wavelength range, repeating for each day for the length of the measurement period.
The SORCE SOLSTICE Mid-UV Solar Spectral Irradiance (SSI) data product SOR3SOLMUVD is constructed using measurements from the SOLSTICE MUV instrument, which are combined into merged daily solar spectra over the spectral range from 180 to 310 nm at a spectral resolution of 1 nm. Irradiances are reported at a mean solar distance of 1 AU and zero relative line-of-sight velocity with respect to the Sun. The SOLSTICE absolute uncertainty better than 5%.

All of the SOR3SOLMUVD data are arranged in a single file in a tabular ASCII text file which can be easily read into a spreadsheet application. The columns contain the date, Julian day, minimum wavelength, maximum wavelength, instrument mode, data version number, irradiance value, irradiance uncertainty, and data quality. The rows are arranged with data at each wavelength over the full SOLSTICE FUV wavelength range, repeating for each day for the length of the measurement period.
The SORCE XUV Photometer System (XPS) Solar Spectral Irradiance (SSI) 6-Hour Data Product SOR3XPS6 contains solar XUV irradiances in the 0.1 to 27 nm range, as well as Lyman-alpha, in broad bands (7-10 nm resolution) as listed below:

 Diode  1:   0.1 -   7.0 nm
 Diode  2:   0.1 -   7.0 nm
 Diode  3:  17.0 -  23.0 nm
 Diode  6:   0.1 -  11.0 nm
 Diode  7:   0.1 -   7.0 nm
 Diode  9:   0.1 -   7.0 nm
 Diode 11: 121.0 - 122.0 nm

The data are reported at a mean solar distance of 1 AU and zero relative line-of-sight velocity with respect to the Sun. The accuracy for the XPS Level 3 irradiance is 12-30%, photometer dependent, and the long-term repeatability is 1%/year.

The SOR3XPS6 data are arranged in a single tabular ASCII text file which can be easily read into a spreadsheet application. The columns contain the date, Julian day, average measurement date, standard deviation of measurement date, diode number, minimum wavelength, maximum wavelength, instrument mode, data version number, median irradiance, mean irradiance, absolute uncertainty, measurement precision, calculation precision, degradation model, degradation version, and number of data points. The rows are arranged with data for each 6 hour time increment, repeating for each diode wavelength.
The SORCE XUV Photometer System (XPS) Solar Spectral Irradiance (SSI) Daily Data Product SOR3XPSD contains solar XUV irradiances in the 0.1 to 27 nm range, as well as Lyman-alpha, in broad bands (7-10 nm resolution) as listed below:

 Diode  1:   0.1 -   7.0 nm
 Diode  2:   0.1 -   7.0 nm
 Diode  3:  17.0 -  23.0 nm
 Diode  6:   0.1 -  11.0 nm
 Diode  7:   0.1 -   7.0 nm
 Diode  9:   0.1 -   7.0 nm
 Diode 11: 121.0 - 122.0 nm

The data are reported at a mean solar distance of 1 AU and zero relative line-of-sight velocity with respect to the Sun. The accuracy for the XPS Level 3 irradiance is 12-30%, photometer dependent, and the long-term repeatability is 1%/year.

The SOR3XPSD data are arranged in a single tabular ASCII text file which can be easily read into a spreadsheet application. The columns contain the date, Julian day, average measurement date, standard deviation of measurement date, diode number, minimum wavelength, maximum wavelength, instrument mode, data version number, median irradiance, mean irradiance, absolute uncertainty, measurement precision, calculation precision, degradation model, degradation version, and number of data points. The rows are arranged with data for each day, repeating for each diode wavelength.
Surface Radiation Budget (SRB) Release 3.0 CLDPROPS 3 hourly Data in Native Format
Surface Radiation Budget (SRB) Release 3.0 QC Longwave 3 hourly Data in Native Format
Surface Radiation Budget (SRB) Release 3.0 QC Longwave 3 hourly monthly Data in Native Format
Surface Radiation Budget (SRB) Release 3.0 QC Longwave 3 hourly monthly Data in netcdf Format
Surface Radiation Budget (SRB) Release 3.0 QC Longwave 3 hourly Data in netcdf Format
Surface Radiation Budget (SRB) Release 3.0 QC Longwave 3 hourly Data in Native Format
Surface Radiation Budget (SRB) Release 3.0 QC Longwave daily Data in netcdf Format
Surface Radiation Budget (SRB) Release 3.0 QC Longwave 3 hourly monthly Data in Native Format
Surface Radiation Budget (SRB) Release 3.0 QC Longwave monthly Data in netcdf Format
Surface Radiation Budget (SRB) Release 3.0 QC Shortwave Daily Data in Native Format
Surface Radiation Budget (SRB) Release 3.0 QC Shortwave Daily Data in netcdf Format
Surface Radiation Budget (SRB) Release 3.0 QCShortwave MONTHLY Data in Native Format
Surface Radiation Budget (SRB) Release 3.0 QCShortwave MONTHLY Data in netcdf Format
Surface Radiation Budget (SRB) Release 3.0 Shortwave 3 hourly Data in Native Format
Surface Radiation Budget (SRB) Release 3.0 Shortwave 3 hourly MONTHLY Data in Native Format
Surface Radiation Budget (SRB) Release 3.0 Shortwave 3 hourly MONTHLY LOCAL Data in netcdf Format
Surface Radiation Budget (SRB) Release 3.0 Shortwave 3 hourly MONTHLY UTC Data in netcdf Format
Surface Radiation Budget (SRB) Release 3.0 Shortwave 3 hourly Data in netcdf Format
Surface Radiation Budget (SRB) Release 3.0 Shortwave Daily Local Data in Native Format
Surface Radiation Budget (SRB) Release 3.0 Shortwave Daily Local Data in netcdf Format
Surface Radiation Budget (SRB) Release 3.0 Shortwave Daily UTC Data in Native Format
Surface Radiation Budget (SRB) Release 3.0 Shortwave Daily UTC Data in netcdf Format
Surface Radiation Budget (SRB) Release 3.0 Shortwave MONTHLY LOCAL Data in Native Format
Surface Radiation Budget (SRB) Release 3.0 Shortwave MONTHLY LOCAL Data in netcdf Format
Surface Radiation Budget (SRB) Release 3.0 Shortwave MONTHLY UTC Data in Native Format
Surface Radiation Budget (SRB) Release 3.0 Shortwave MONTHLY UTC Data in netcdf Format
Surface Radiation Budget (SRB) Release 3.1 G4TskinOnly Longwave 3 hourly Data in Native Format
Surface Radiation Budget (SRB) Release 3.1 G4TskinOnly LW 3 hourly MONTHLY Data in Native Format
Surface Radiation Budget (SRB) Release 3.1 G4TskinOnly LW Daily Data in Native Format
Surface Radiation Budget (SRB) Release 3.1 G4TskinOnly Longwave monthly Data in Native Format
Surface Radiation Budget (SRB) Release 3.1 Longwave 3 hourly Data in Native Format
Surface Radiation Budget (SRB) Release 3.1 longwave 3 hourly MONTHLY Data in Native Format
Surface Radiation Budget (SRB) Release 3.1 longwave 3 hourly MONTHLY Data in netcdf Format
Surface Radiation Budget (SRB) Release 3.1 Longwave 3 hourly Data in netcdf Format
Surface Radiation Budget (SRB) Release 3.1 longwave Daily Local Data in Native Format
Surface Radiation Budget (SRB) Release 3.1 longwave Daily Data in netcdf Format
Surface Radiation Budget (SRB) Release 3.1 Longwave monthly Data in Native Format
Surface Radiation Budget (SRB) Release 3.1 Longwave monthly Data in netcdf Format
Biomass weight & nitrogen content for plants collected along transects & dried
Biomass weight & nitrogen content for plants collected along transects & dried
ABSTRACT: Biomass weight & nitrogen content for plants collected along transects & dried
USGS daily stream flow data for Kings Creek on the Konza Prairie
USGS daily stream flow data for Kings Creek on the Konza Prairie
ABSTRACT: USGS daily stream flow data for Kings Creek on the Konza Prairie
USGS stream flow during storm events around Kings Creek on the Konza Prairie
USGS stream flow during storm events around Kings Creek on the Konza Prairie
ABSTRACT: USGS stream flow during storm events around Kings Creek on the Konza Prairie
Baseline 92 cross-calibrated surface fluxes for 1987 data (spike checked)
Baseline 92 cross-calibrated surface fluxes for 1987 data (spike checked)
ABSTRACT: Baseline 92 cross-calibrated surface fluxes for 1987 data (spike checked)
NCDC surface meteorology data for 1989
NCDC surface meteorology data for 1989
ABSTRACT: NCDC surface meteorology data for 1989
Canopy IR & air temperature, albedo, incoming and reflected shortwave, humidity
Canopy IR & air temperature, albedo, incoming and reflected shortwave, humidity
ABSTRACT: Canopy IR & air temperature, albedo, incoming and reflected shortwave, humidity
The Peace-Athabasca Delta (PAD) is a large boreal wetland located in northeastern Alberta, Canada at the confluence of the Peace and Athabasca Rivers with Lake Athabasca (Figures 1 and 2). A Ramsar Convention wetland and UNESCO World Heritage Site, it is among the world's most ecologically significant wetlands.  This data set contains four comma-delimited ASCII files, two of which contain water surface elevation site and measurement information and two contain water quality and ancillary parameter location and measurement data for 120 sites within the PAD.Data archived include water surface elevation and water quality parameters measured at points throughout the Delta during summers 2006 and 2007. These data sets were originally collected to improve understanding of hydrologic recharge processes in low-relief environments and to provide ground-based measurements to validate satellite observations of inundation and sediment transport. All work was supported by the NASA Terrestrial Hydrology Program under grant NNG06GE05G to the Department of Geography, University of California-Los Angeles, Los Angeles, California.
The Peace-Athabasca Delta (PAD) is a large boreal wetland located in northeastern Alberta, Canada at the confluence of the Peace and Athabasca Rivers with Lake Athabasca (Figures 1 and 2). A Ramsar Convention wetland and UNESCO World Heritage Site, it is among the world's most ecologically significant wetlands.  This data set contains four comma-delimited ASCII files, two of which contain water surface elevation site and measurement information and two contain water quality and ancillary parameter location and measurement data for 120 sites within the PAD.Data archived include water surface elevation and water quality parameters measured at points throughout the Delta during summers 2006 and 2007. These data sets were originally collected to improve understanding of hydrologic recharge processes in low-relief environments and to provide ground-based measurements to validate satellite observations of inundation and sediment transport. All work was supported by the NASA Terrestrial Hydrology Program under grant NNG06GE05G to the Department of Geography, University of California-Los Angeles, Los Angeles, California.
ABSTRACT: The Peace-Athabasca Delta (PAD) is a large boreal wetland located in northeastern Alberta, Canada at the confluence of the Peace and Athabasca Rivers with Lake Athabasca (Figures 1 and 2). A Ramsar Convention wetland and UNESCO World Heritage Site, it is among the world's most ecologically significant wetlands.  This data set contains four comma-delimited ASCII files, two of which contain water surface elevation site and measurement information and two contain water quality and ancillary parameter location and measurement data for 120 sites within the PAD.Data archived include water surface elevation and water quality parameters measured at points throughout the Delta during summers 2006 and 2007. These data sets were originally collected to improve understanding of hydrologic recharge processes in low-relief environments and to provide ground-based measurements to validate satellite observations of inundation and sediment transport. All work was supported by the NASA Terrestrial Hydrology Program under grant NNG06GE05G to the Department of Geography, University of California-Los Angeles, Los Angeles, California.
Synthetic Assessment of Global Distribution of Vulnerability to Climate Change: Maps and Data, 2005, 2050, and 2100 consist of maps and vulnerability 

index to climate change of 100 countries based on the Vulnerability-Resilience Indicator Model (VRIM), which not only presents sensitivity to climate change stresses but allows the division 

of indicators into components that reflects sensitivity and adaptive capacity. It was produced in collaboration with the Wesleyan University, Joint Global Change Research Insitute, 

University of Illinois and the Columbia University Center for International Earth Science Information Network (CIESIN).
Synthetic Assessment of Global Distribution of Vulnerability to Climate Change: Maps and Data, 2005, 2050, and 2100 consist of maps and vulnerability 

index to climate change of 100 countries based on the Vulnerability-Resilience Indicator Model (VRIM), which not only presents sensitivity to climate change stresses but allows the division 

of indicators into components that reflects sensitivity and adaptive capacity. It was produced in collaboration with the Wesleyan University, Joint Global Change Research Insitute, 

University of Illinois and the Columbia University Center for International Earth Science Information Network (CIESIN).
Synthetic Assessment of Global Distribution of Vulnerability to Climate Change: Maps and Data, 2005, 2050, and 2100 consist of maps and vulnerability 

index to climate change of 100 countries based on the Vulnerability-Resilience Indicator Model (VRIM), which not only presents sensitivity to climate change stresses but allows the division 

of indicators into components that reflects sensitivity and adaptive capacity. It was produced in collaboration with the Wesleyan University, Joint Global Change Research Insitute, 

University of Illinois and the Columbia University Center for International Earth Science Information Network (CIESIN).
The Tropical Composition, Cloud and Climate Coupling (TC4) mission TC4 field experiment was completed during July and August 2007 based out of San Jose, Costa Rica.  The Advanced Microwave Precipitation Radiometer (AMPR) instrument played a key role in the experiment.  The AMPR remotely senses passive microwave signatures of geophysical parameters from an airborne platform.  The instrument is a low noise system which can provide multi-frequency microwave imagery with high spatial and temporal resolution.  AMPR data were collected at a combination of frequencies (10.7, 19.35, 37.1, and 85.5 GHz) unique to current NASA aircraft instrumentation.  These frequencies are well suited to the study of rain cloud systems, but are also useful to studies of various ocean and land surface processes.
The Tropical Composition, Cloud and Climate Coupling (TC4) mission TC4 field experiment was completed during July and August 2007 based out of San Jose, Costa Rica.  The Advanced Microwave Precipitation Radiometer (AMPR) instrument played a key role in the experiment.  The AMPR remotely senses passive microwave signatures of geophysical parameters from an airborne platform.  The instrument is a low noise system which can provide multi-frequency microwave imagery with high spatial and temporal resolution.  AMPR data were collected at a combination of frequencies (10.7, 19.35, 37.1, and 85.5 GHz) unique to current NASA aircraft instrumentation.  These frequencies are well suited to the study of rain cloud systems, but are also useful to studies of various ocean and land surface processes.
The Tropical Composition, Cloud and Climate Coupling (TC4) mission TC4 field experiment was completed during July and August 2007 based out of San Jose, Costa Rica.  The Advanced Microwave Precipitation Radiometer (AMPR) instrument played a key role in the experiment.  The AMPR remotely senses passive microwave signatures of geophysical parameters from an airborne platform.  The instrument is a low noise system which can provide multi-frequency microwave imagery with high spatial and temporal resolution.  AMPR data were collected at a combination of frequencies (10.7, 19.35, 37.1, and 85.5 GHz) unique to current NASA aircraft instrumentation.  These frequencies are well suited to the study of rain cloud systems, but are also useful to studies of various ocean and land surface processes.
The Tropical Composition, Cloud and Climate Coupling (TC4) mission TC4 field experiment was completed during July and August 2007 based out of San Jose, Costa Rica.  These lightning data were collected during the NASA TC4 field campaign and are restricted to the TC4 community.
Measurements of air temperature, pressure, and relative humidity were made on each flight using two Vaisalla RS902 sondes located under the wings of the aircraft. A Heiltronics KT11.k6 infrared pyrometer was used to measure sea surface temperatures (SST).
Measurements of air temperature, pressure, and relative humidity were made on each flight using two Vaisalla RS902 sondes located under the wings of the aircraft. A Heiltronics KT11.k6 infrared pyrometer was used to measure sea surface temperatures (SST).
Measurements of air temperature, pressure, and relative humidity were made on each flight using two Vaisalla RS902 sondes located under the wings of the aircraft. A Heiltronics KT11.k6 infrared pyrometer was used to measure sea surface temperatures (SST).
The Advanced Microwave Precipitation Radiometer (AMPR) remotely senses passive microwave signatures of geophysical parameters from an airborne platform. The instrument is a low noise system which can provide multi-frequency microwave imagery with high spatial and temporal resolution. AMPR data are collected at a combination of frequencies (10.7, 19.35, 37.1, and 85.5 GHz) unique to current NASA aircraft instrumentation. These frequencies are well suited to the study of rain cloud systems, but are also useful to studies of various ocean and land surface processes.  AMPR data were collected at four microwave frequencies (10.7, 19.35, 37.1 and 85.5 GHz) for the period of 06-18-2005 through 07-28-2005.
The Advanced Microwave Precipitation Radiometer (AMPR) remotely senses passive microwave signatures of geophysical parameters from an airborne platform. The instrument is a low noise system which can provide multi-frequency microwave imagery with high spatial and temporal resolution. AMPR data are collected at a combination of frequencies (10.7, 19.35, 37.1, and 85.5 GHz) unique to current NASA aircraft instrumentation. These frequencies are well suited to the study of rain cloud systems, but are also useful to studies of various ocean and land surface processes.  AMPR data were collected at four microwave frequencies (10.7, 19.35, 37.1 and 85.5 GHz) for the period of 06-18-2005 through 07-28-2005.
The Advanced Microwave Precipitation Radiometer (AMPR) remotely senses passive microwave signatures of geophysical parameters from an airborne platform. The instrument is a low noise system which can provide multi-frequency microwave imagery with high spatial and temporal resolution. AMPR data are collected at a combination of frequencies (10.7, 19.35, 37.1, and 85.5 GHz) unique to current NASA aircraft instrumentation. These frequencies are well suited to the study of rain cloud systems, but are also useful to studies of various ocean and land surface processes.  AMPR data were collected at four microwave frequencies (10.7, 19.35, 37.1 and 85.5 GHz) for the period of 06-18-2005 through 07-28-2005.
The Cloud Radar System (CRS) provides vertically profiled reflectivity and Doppler velocity at aircraft nadir along the flight track.  The CRS is a 94 GHz (W-band; 3 mm wavelength) Doppler radar developed for autonomous operation in the NASA ER-2 high-altitude aircraft and for ground-based operation. It will provide high-resolution profiles of reflectivity and Doppler velocity in clouds and it has important applications to atmospheric remote sensing studies. The CRS was designed to fly with the Cloud Lidar System (CLS), in the tail cone of an ER-2 superpod. There are two basic modes of operation of the CRS: 1) ER-2 with reflectivity, Doppler, and linear-depolarization measurements, and 2) ground-based with full polarimetric capability. The TCSP mission used the ER-2 mode.
The Cloud Radar System (CRS) provides vertically profiled reflectivity and Doppler velocity at aircraft nadir along the flight track.  The CRS is a 94 GHz (W-band; 3 mm wavelength) Doppler radar developed for autonomous operation in the NASA ER-2 high-altitude aircraft and for ground-based operation. It will provide high-resolution profiles of reflectivity and Doppler velocity in clouds and it has important applications to atmospheric remote sensing studies. The CRS was designed to fly with the Cloud Lidar System (CLS), in the tail cone of an ER-2 superpod. There are two basic modes of operation of the CRS: 1) ER-2 with reflectivity, Doppler, and linear-depolarization measurements, and 2) ground-based with full polarimetric capability. The TCSP mission used the ER-2 mode.
The Cloud Radar System (CRS) provides vertically profiled reflectivity and Doppler velocity at aircraft nadir along the flight track.  The CRS is a 94 GHz (W-band; 3 mm wavelength) Doppler radar developed for autonomous operation in the NASA ER-2 high-altitude aircraft and for ground-based operation. It will provide high-resolution profiles of reflectivity and Doppler velocity in clouds and it has important applications to atmospheric remote sensing studies. The CRS was designed to fly with the Cloud Lidar System (CLS), in the tail cone of an ER-2 superpod. There are two basic modes of operation of the CRS: 1) ER-2 with reflectivity, Doppler, and linear-depolarization measurements, and 2) ground-based with full polarimetric capability. The TCSP mission used the ER-2 mode.
The EDOP  provides vertically profiled reflectivity and Doppler velocity at aircraft nadir along the flight track.  The ER-2 Doppler radar (EDOP) is an X-band (9.6 GHz) Doppler radar mounted in the nose of the ER-2 aircraft. The instrument has two fixed antennas, one pointing at nadir and the second pointing approximately 33 degree ahead of nadir. The beam width of the antenna is 3 degree in the vertical and horizontal directions which, for a 20 km altitude, yields a nadir footprint at the surface of 1 km. Each Antenna measures the doppler velocity, doppler spectral width, and reflectivity factor. Doppler velocities provide a measure of the pulse volume-weighted hydrometer motion (hydrometer fallspeed + air motion.) Vertical air motion can be calculated from the nadir beam by removing the fallspeed contribution with an approximation.  Along-track horizontal air motion can be calculated by combining doppler wind speeds from forward and nadir beams. The linear depolarization ratio (the ratio of the cross-polar to the co-polar reflectivites) can be measured along forward beam. EDOP is a coherent Doppler radar system at 9.6 GHz. EDOP provides measurements from a forward pointing beam that is used in combination with the nadir beam for estimating the along-track winds.
The EDOP  provides vertically profiled reflectivity and Doppler velocity at aircraft nadir along the flight track.  The ER-2 Doppler radar (EDOP) is an X-band (9.6 GHz) Doppler radar mounted in the nose of the ER-2 aircraft. The instrument has two fixed antennas, one pointing at nadir and the second pointing approximately 33 degree ahead of nadir. The beam width of the antenna is 3 degree in the vertical and horizontal directions which, for a 20 km altitude, yields a nadir footprint at the surface of 1 km. Each Antenna measures the doppler velocity, doppler spectral width, and reflectivity factor. Doppler velocities provide a measure of the pulse volume-weighted hydrometer motion (hydrometer fallspeed + air motion.) Vertical air motion can be calculated from the nadir beam by removing the fallspeed contribution with an approximation.  Along-track horizontal air motion can be calculated by combining doppler wind speeds from forward and nadir beams. The linear depolarization ratio (the ratio of the cross-polar to the co-polar reflectivites) can be measured along forward beam. EDOP is a coherent Doppler radar system at 9.6 GHz. EDOP provides measurements from a forward pointing beam that is used in combination with the nadir beam for estimating the along-track winds.
The EDOP  provides vertically profiled reflectivity and Doppler velocity at aircraft nadir along the flight track.  The ER-2 Doppler radar (EDOP) is an X-band (9.6 GHz) Doppler radar mounted in the nose of the ER-2 aircraft. The instrument has two fixed antennas, one pointing at nadir and the second pointing approximately 33 degree ahead of nadir. The beam width of the antenna is 3 degree in the vertical and horizontal directions which, for a 20 km altitude, yields a nadir footprint at the surface of 1 km. Each Antenna measures the doppler velocity, doppler spectral width, and reflectivity factor. Doppler velocities provide a measure of the pulse volume-weighted hydrometer motion (hydrometer fallspeed + air motion.) Vertical air motion can be calculated from the nadir beam by removing the fallspeed contribution with an approximation.  Along-track horizontal air motion can be calculated by combining doppler wind speeds from forward and nadir beams. The linear depolarization ratio (the ratio of the cross-polar to the co-polar reflectivites) can be measured along forward beam. EDOP is a coherent Doppler radar system at 9.6 GHz. EDOP provides measurements from a forward pointing beam that is used in combination with the nadir beam for estimating the along-track winds.
The ER-2 Lightning Instrument Package (LIP) consists of 7 rotating vane type electric field sensors and a two channel conductivity probe along with a central computer to record and monitor the instruments.  The field mills measure the components of the electric field over a wide dynamic range extending from fair weather electric fields, (i.e., a few to tens of V/m) to larger thunderstorm fields (i.e., tens of kV/m).  Total lightning (i.e., cloud-to-ground, intracloud) is identified from the abrupt electric field changes in the data. The conductivity probe measures the air conductivity at the aircraft flight altitude. Storm electric currents can be derived using the electric field and air conductivity measurements. A more detailed discription of the LIP can be found at: tcsp.nsstc.nasa.gov/camex4/instrument_documentation/lip.pdf
The ER-2 Lightning Instrument Package (LIP) consists of 7 rotating vane type electric field sensors and a two channel conductivity probe along with a central computer to record and monitor the instruments.  The field mills measure the components of the electric field over a wide dynamic range extending from fair weather electric fields, (i.e., a few to tens of V/m) to larger thunderstorm fields (i.e., tens of kV/m).  Total lightning (i.e., cloud-to-ground, intracloud) is identified from the abrupt electric field changes in the data. The conductivity probe measures the air conductivity at the aircraft flight altitude. Storm electric currents can be derived using the electric field and air conductivity measurements. A more detailed discription of the LIP can be found at: tcsp.nsstc.nasa.gov/camex4/instrument_documentation/lip.pdf
The ER-2 Lightning Instrument Package (LIP) consists of 7 rotating vane type electric field sensors and a two channel conductivity probe along with a central computer to record and monitor the instruments.  The field mills measure the components of the electric field over a wide dynamic range extending from fair weather electric fields, (i.e., a few to tens of V/m) to larger thunderstorm fields (i.e., tens of kV/m).  Total lightning (i.e., cloud-to-ground, intracloud) is identified from the abrupt electric field changes in the data. The conductivity probe measures the air conductivity at the aircraft flight altitude. Storm electric currents can be derived using the electric field and air conductivity measurements. A more detailed discription of the LIP can be found at: tcsp.nsstc.nasa.gov/camex4/instrument_documentation/lip.pdf
The ER2 MTP is a passive microwave radiometer which measures the thermal emission from oxygen molecules in the atmosphere for a selection of elevation angles (normally 10 between +60 and -58 degrees). The current observing frequencies are 55.5, 56.6 and 58.8 GHz. Measured 'brightness temperature' versus elevation angle is converted to air temperature versus altitude using a modified statistical retrieval procedure with a Bayesian component. An altitude temperature profile (ATP) is produced in this manner every 13 seconds or approximately 3 km along the flight path. The ATP can be used to produce a color-coded temperature curtain (CTC) of the temperature field which the ER2 has flown through, and to identify the tropopause location. ATPs can also be used to locate altitudes where the air is cold enough to condense nitric acid or water vapor to form polar stratospheric
clouds (PSCs).
The ER2 MTP is a passive microwave radiometer which measures the thermal emission from oxygen molecules in the atmosphere for a selection of elevation angles (normally 10 between +60 and -58 degrees). The current observing frequencies are 55.5, 56.6 and 58.8 GHz. Measured 'brightness temperature' versus elevation angle is converted to air temperature versus altitude using a modified statistical retrieval procedure with a Bayesian component. An altitude temperature profile (ATP) is produced in this manner every 13 seconds or approximately 3 km along the flight path. The ATP can be used to produce a color-coded temperature curtain (CTC) of the temperature field which the ER2 has flown through, and to identify the tropopause location. ATPs can also be used to locate altitudes where the air is cold enough to condense nitric acid or water vapor to form polar stratospheric
clouds (PSCs).
The ER2 MTP is a passive microwave radiometer which measures the thermal emission from oxygen molecules in the atmosphere for a selection of elevation angles (normally 10 between +60 and -58 degrees). The current observing frequencies are 55.5, 56.6 and 58.8 GHz. Measured 'brightness temperature' versus elevation angle is converted to air temperature versus altitude using a modified statistical retrieval procedure with a Bayesian component. An altitude temperature profile (ATP) is produced in this manner every 13 seconds or approximately 3 km along the flight path. The ATP can be used to produce a color-coded temperature curtain (CTC) of the temperature field which the ER2 has flown through, and to identify the tropopause location. ATPs can also be used to locate altitudes where the air is cold enough to condense nitric acid or water vapor to form polar stratospheric
clouds (PSCs).
The MODIS Airborne Simulator (MAS) is a multi-spectral line-scanner system that acquires image data in 50 spectral bands over wavelengths ranging from 0.46 to 14.3 microns.  Flown on the ER-2 aircraft at an operating altitude of 19.8 km (65,000 ft.) it produces nominal pixel sizes of 50 meters.  MAS includes nine spectral bands in the visible/near infrared, 16 bands in the shortwave infrared, 16 bands in the mid-wave infrared, and nine bands in the thermal infrared regions of the spectrum.  The instrument field-of-view is 86 degrees, with an IFOV of 2.5 mrad.The MODIS Airborne Simulator (MAS) collected calibrated multi-spectral imagery from the ER-2 aircraft during the TCSP experiment.  The MAS was developed by NASA primarily to validate L1B and L2 science products from the EOS satellite program.  MAS data enables (1) the mapping of sub-pixel variation within the co-incident footprints of many orbital instruments (e.g. MODIS, AIRS, HIRS, AVHRR, GOES) in the visible and thermal infrared spectral regions and (2) the estimation of surface, aerosol, and cloud properties at 50 meter spatial resolution.
The MODIS Airborne Simulator (MAS) is a multi-spectral line-scanner system that acquires image data in 50 spectral bands over wavelengths ranging from 0.46 to 14.3 microns.  Flown on the ER-2 aircraft at an operating altitude of 19.8 km (65,000 ft.) it produces nominal pixel sizes of 50 meters.  MAS includes nine spectral bands in the visible/near infrared, 16 bands in the shortwave infrared, 16 bands in the mid-wave infrared, and nine bands in the thermal infrared regions of the spectrum.  The instrument field-of-view is 86 degrees, with an IFOV of 2.5 mrad.The MODIS Airborne Simulator (MAS) collected calibrated multi-spectral imagery from the ER-2 aircraft during the TCSP experiment.  The MAS was developed by NASA primarily to validate L1B and L2 science products from the EOS satellite program.  MAS data enables (1) the mapping of sub-pixel variation within the co-incident footprints of many orbital instruments (e.g. MODIS, AIRS, HIRS, AVHRR, GOES) in the visible and thermal infrared spectral regions and (2) the estimation of surface, aerosol, and cloud properties at 50 meter spatial resolution.
The MODIS Airborne Simulator (MAS) is a multi-spectral line-scanner system that acquires image data in 50 spectral bands over wavelengths ranging from 0.46 to 14.3 microns.  Flown on the ER-2 aircraft at an operating altitude of 19.8 km (65,000 ft.) it produces nominal pixel sizes of 50 meters.  MAS includes nine spectral bands in the visible/near infrared, 16 bands in the shortwave infrared, 16 bands in the mid-wave infrared, and nine bands in the thermal infrared regions of the spectrum.  The instrument field-of-view is 86 degrees, with an IFOV of 2.5 mrad.The MODIS Airborne Simulator (MAS) collected calibrated multi-spectral imagery from the ER-2 aircraft during the TCSP experiment.  The MAS was developed by NASA primarily to validate L1B and L2 science products from the EOS satellite program.  MAS data enables (1) the mapping of sub-pixel variation within the co-incident footprints of many orbital instruments (e.g. MODIS, AIRS, HIRS, AVHRR, GOES) in the visible and thermal infrared spectral regions and (2) the estimation of surface, aerosol, and cloud properties at 50 meter spatial resolution.
Geostationary satellite-derived wind sets have traditionally been generated from image triplets with 30 or 60 minute intervals, and occasionally 15 minute intervals. During GOES special rapid-scan operations, co-located images are available at intervals of 7.5, 5, 3, and even 1 minute. The area covered is reduced as the interval decreases. In this experiment images at five minute intervals were used for the 0.65 micrometer VIS, 3.9 micrometer IR (darkness only), and 10.7 micrometer IR channels.  GOES-11 was brought out of storage and image products were centered on the TCSP study region.  Regular image processing was available beginning on 12 July.  The scan schedule was maintained through the end of July.
Geostationary satellite-derived wind sets have traditionally been generated from image triplets with 30 or 60 minute intervals, and occasionally 15 minute intervals. During GOES special rapid-scan operations, co-located images are available at intervals of 7.5, 5, 3, and even 1 minute. The area covered is reduced as the interval decreases. In this experiment images at five minute intervals were used for the 0.65 micrometer VIS, 3.9 micrometer IR (darkness only), and 10.7 micrometer IR channels.  GOES-11 was brought out of storage and image products were centered on the TCSP study region.  Regular image processing was available beginning on 12 July.  The scan schedule was maintained through the end of July.
Geostationary satellite-derived wind sets have traditionally been generated from image triplets with 30 or 60 minute intervals, and occasionally 15 minute intervals. During GOES special rapid-scan operations, co-located images are available at intervals of 7.5, 5, 3, and even 1 minute. The area covered is reduced as the interval decreases. In this experiment images at five minute intervals were used for the 0.65 micrometer VIS, 3.9 micrometer IR (darkness only), and 10.7 micrometer IR channels.  GOES-11 was brought out of storage and image products were centered on the TCSP study region.  Regular image processing was available beginning on 12 July.  The scan schedule was maintained through the end of July.
In support of the Tropical Cloud Systems and Processes (TCSP) mission, visible and infrared imagery from the Geostationary Operational Environmental Satellite 11 and 12 (GOES11, GOES 12) was collected and archived. Two channels were archived: channel 1-- visible (0.65 microns), and channel 2-- infrared (11 microns). Data files in McIDAS format as well as browse images were created.
In support of the Tropical Cloud Systems and Processes (TCSP) mission, visible and infrared imagery from the Geostationary Operational Environmental Satellite 11 and 12 (GOES11, GOES 12) was collected and archived. Two channels were archived: channel 1-- visible (0.65 microns), and channel 2-- infrared (11 microns). Data files in McIDAS format as well as browse images were created.
In support of the Tropical Cloud Systems and Processes (TCSP) mission, visible and infrared imagery from the Geostationary Operational Environmental Satellite 11 and 12 (GOES11, GOES 12) was collected and archived. Two channels were archived: channel 1-- visible (0.65 microns), and channel 2-- infrared (11 microns). Data files in McIDAS format as well as browse images were created.
HAMSR is a 25-channel microwave atmospheric sounder operating as a cross-track scanner. It is functionally similar to AMSU-A/B, but with additional channels. There are three bands: an 8-channel band near 50-GHz, used for primary temperature sounding; a 10-channel band near 118 GHz, used for secondary temperature sounding and assessment of scattering; a 7-channel band near 183 GHz, used for water vapor sounding. The instrument is continuously self-calibrating using internal calibration targets. Radiometric sensitivity at the composite sampling cells provided in the archive is typically 0.1 and ranges up to 0.25 K for the stratospheric channels. Calibration accuracy is estimated at better than 1 K for temperature sounding and better than 2 K for water vapor sounding. Temperature weighting function peaks are distributed between the surface and the flight altitude. HAMSR was mounted in a wing pod of a NASA ER-2 research aircraft.
HAMSR is a 25-channel microwave atmospheric sounder operating as a cross-track scanner. It is functionally similar to AMSU-A/B, but with additional channels. There are three bands: an 8-channel band near 50-GHz, used for primary temperature sounding; a 10-channel band near 118 GHz, used for secondary temperature sounding and assessment of scattering; a 7-channel band near 183 GHz, used for water vapor sounding. The instrument is continuously self-calibrating using internal calibration targets. Radiometric sensitivity at the composite sampling cells provided in the archive is typically 0.1 and ranges up to 0.25 K for the stratospheric channels. Calibration accuracy is estimated at better than 1 K for temperature sounding and better than 2 K for water vapor sounding. Temperature weighting function peaks are distributed between the surface and the flight altitude. HAMSR was mounted in a wing pod of a NASA ER-2 research aircraft.
HAMSR is a 25-channel microwave atmospheric sounder operating as a cross-track scanner. It is functionally similar to AMSU-A/B, but with additional channels. There are three bands: an 8-channel band near 50-GHz, used for primary temperature sounding; a 10-channel band near 118 GHz, used for secondary temperature sounding and assessment of scattering; a 7-channel band near 183 GHz, used for water vapor sounding. The instrument is continuously self-calibrating using internal calibration targets. Radiometric sensitivity at the composite sampling cells provided in the archive is typically 0.1 and ranges up to 0.25 K for the stratospheric channels. Calibration accuracy is estimated at better than 1 K for temperature sounding and better than 2 K for water vapor sounding. Temperature weighting function peaks are distributed between the surface and the flight altitude. HAMSR was mounted in a wing pod of a NASA ER-2 research aircraft.
The Tropical Cloud Systems and Processes (TCSP) Mission Reports were filed every day that an aircraft flew in support of the experiment.  The reports include a short description of the day's mission, its objective and notes.
The Tropical Cloud Systems and Processes (TCSP) Mission Reports were filed every day that an aircraft flew in support of the experiment.  The reports include a short description of the day's mission, its objective and notes.
The Tropical Cloud Systems and Processes (TCSP) Mission Reports were filed every day that an aircraft flew in support of the experiment.  The reports include a short description of the day's mission, its objective and notes.
The Ticosonde/Aura-TCSP 2005 radiosonde data set consists of 4 soundings per day (00, 06, 12 and 18 UT) launched from Juan Santamaria International Airport, WMO station 78762, latitude 10 degrees N and 84.2 degrees W.  The launch program began at 00 UT on 16 June 2005 and ended 00 UT 24 August 2005. With a very few exceptions, the sondes were Vaiasala model RS92-SGP and the ground station was a DigiCORA MW11 equipped for GPS wind-finding and upgraded for RS92 telemetry. A small number of ascents were made with RS90-AG and RS80-15G sondes.  Most ascents were done with 500-g latex balloons filled with hydrogen. Exceptions included 24 ascents at 06 and 18UT in July that were piggybacked on a larger payload consisting of the University of Colorado cryogenic frostpoint hygrometer (CFH) and an ECC ozonesonde. Median termination altitude for all ascents was approximately 26 km.  Data were recorded at the maximum MW11 sample rate of one every two seconds.
The Ticosonde/Aura-TCSP 2005 radiosonde data set consists of 4 soundings per day (00, 06, 12 and 18 UT) launched from Juan Santamaria International Airport, WMO station 78762, latitude 10 degrees N and 84.2 degrees W.  The launch program began at 00 UT on 16 June 2005 and ended 00 UT 24 August 2005. With a very few exceptions, the sondes were Vaiasala model RS92-SGP and the ground station was a DigiCORA MW11 equipped for GPS wind-finding and upgraded for RS92 telemetry. A small number of ascents were made with RS90-AG and RS80-15G sondes.  Most ascents were done with 500-g latex balloons filled with hydrogen. Exceptions included 24 ascents at 06 and 18UT in July that were piggybacked on a larger payload consisting of the University of Colorado cryogenic frostpoint hygrometer (CFH) and an ECC ozonesonde. Median termination altitude for all ascents was approximately 26 km.  Data were recorded at the maximum MW11 sample rate of one every two seconds.
The Ticosonde/Aura-TCSP 2005 radiosonde data set consists of 4 soundings per day (00, 06, 12 and 18 UT) launched from Juan Santamaria International Airport, WMO station 78762, latitude 10 degrees N and 84.2 degrees W.  The launch program began at 00 UT on 16 June 2005 and ended 00 UT 24 August 2005. With a very few exceptions, the sondes were Vaiasala model RS92-SGP and the ground station was a DigiCORA MW11 equipped for GPS wind-finding and upgraded for RS92 telemetry. A small number of ascents were made with RS90-AG and RS80-15G sondes.  Most ascents were done with 500-g latex balloons filled with hydrogen. Exceptions included 24 ascents at 06 and 18UT in July that were piggybacked on a larger payload consisting of the University of Colorado cryogenic frostpoint hygrometer (CFH) and an ECC ozonesonde. Median termination altitude for all ascents was approximately 26 km.  Data were recorded at the maximum MW11 sample rate of one every two seconds.
Temperature & humidity profile data derived from Brutsaert's radiosonde data
Temperature & humidity profile data derived from Brutsaert's radiosonde data
ABSTRACT: Temperature & humidity profile data derived from Brutsaert's radiosonde data
The L1B Limb granule consists of radiometrically calibrated spectra & associated NESR, observed at 0.025 cm-1 resolution for an entire Global Survey & organized by observed target scene & instrument parameters such as focal plane/filter & pixel ID. (Suggested Usage: The L1B Limb Calibrated Spectra file consists of radiometrically calibrated spectra and associated NESR observed at 0.025 cm-1 resolution. These spectra are the input measurements to the Level 2 retrieval algorithm that will produce the TES Standard Data Products. The spectra can be used directly as radiance measurements of the earth and atmosphere.)
The L1B Limb granule consists of radiometrically calibrated spectra & associated NESR, observed at 0.025 cm-1 resolution for an entire Global Survey & organized by observed target scene & instrument parameters such as focal plane/filter & pixel ID. (Suggested Usage: The L1B Limb Calibrated Spectra file consists of radiometrically calibrated spectra and associated NESR observed at 0.025 cm-1 resolution. These spectra are the input measurements to the Level 2 retrieval algorithm that will produce the TES Standard Data Products. The spectra can be used directly as radiance measurements of the earth and atmosphere.)
The L1B Limb granule consists of radiometrically calibrated spectra & associated NESR, observed at 0.025 cm-1 resolution for an entire Global Survey & organized by observed target scene & instrument parameters such as focal plane/filter & pixel ID. (Suggested Usage: The L1B Limb Calibrated Spectra file consists of radiometrically calibrated spectra and associated NESR observed at 0.025 cm-1 resolution. These spectra are the input measurements to the Level 2 retrieval algorithm that will produce the TES Standard Data Products. The spectra can be used directly as radiance measurements of the earth and atmosphere.)
The L1B Nadir granule consists of radiometrically calibrated spectra & associated NESR, observed at 0.1 cm-1 resolution for an entire Global Survey & organized by observed target scene & instrument parameters such as focal plane/filter & pixel ID. (Suggested Usage: The L1B Nadir Calibrated Spectra file consists of radiometrically calibrated spectra and associated NESR observed at 0.1 cm-1 resolution. These spectra are the input measurements to the Level 2 retrieval algorithm that will produce the TES Standard Data Products. The spectra can be used directly as radiance measurements of the earth and atmosphere.)
The L1B Nadir granule consists of radiometrically calibrated spectra & associated NESR, observed at 0.1 cm-1 resolution for an entire Global Survey & organized by observed target scene & instrument parameters such as focal plane/filter & pixel ID. (Suggested Usage: The L1B Nadir Calibrated Spectra file consists of radiometrically calibrated spectra and associated NESR observed at 0.1 cm-1 resolution. These spectra are the input measurements to the Level 2 retrieval algorithm that will produce the TES Standard Data Products. The spectra can be used directly as radiance measurements of the earth and atmosphere.)
A L1B High Resolution granule consists of radiometrically calibrated spectra & associated NESR, observed at 0.025 cm-1 resolution for a Special Observation & organized by observed target scene & instrument parameters such as focal plane/filter & pixel ID. (Suggested Usage: The L1B Spectra Special Observation High Resolution file consists of radiometrically calibrated spectra and associated NESR observed at 0.025 cm-1 resolution. These spectra are the input measurements to the Level 2 retrieval algorithm that will produce the L2 Special Observation Data Products. The spectra can be used directly as radiance measurements of the earth and atmosphere.)
A L1B High Resolution granule consists of radiometrically calibrated spectra & associated NESR, observed at 0.025 cm-1 resolution for a Special Observation & organized by observed target scene & instrument parameters such as focal plane/filter & pixel ID. (Suggested Usage: The L1B Spectra Special Observation High Resolution file consists of radiometrically calibrated spectra and associated NESR observed at 0.025 cm-1 resolution. These spectra are the input measurements to the Level 2 retrieval algorithm that will produce the L2 Special Observation Data Products. The spectra can be used directly as radiance measurements of the earth and atmosphere.)
The L1B Low Resolution granule consists of radiometrically calibrated spectra & associated NESR, observed at 0.1 cm-1 resolution for a Special Observation & organized by observed target scene & instrument parameters such as focal plane/filter & pixel ID. (Suggested Usage: The L1B Spectra Special Observation Low Resolution file consists of radiometrically calibrated spectra and associated NESR observed at 0.1 cm-1 resolution. These spectra are the input measurements to the Level 2 retrieval algorithm that will produce the L2 Special Observation Data Products. The spectra can be used directly as radiance measurements of the earth and atmosphere.)
The L1B Low Resolution granule consists of radiometrically calibrated spectra & associated NESR, observed at 0.1 cm-1 resolution for a Special Observation & organized by observed target scene & instrument parameters such as focal plane/filter & pixel ID. (Suggested Usage: The L1B Spectra Special Observation Low Resolution file consists of radiometrically calibrated spectra and associated NESR observed at 0.1 cm-1 resolution. These spectra are the input measurements to the Level 2 retrieval algorithm that will produce the L2 Special Observation Data Products. The spectra can be used directly as radiance measurements of the earth and atmosphere.)
The L1B Low Resolution granule consists of radiometrically calibrated spectra & associated NESR, observed at 0.1 cm-1 resolution for a Special Observation & organized by observed target scene & instrument parameters such as focal plane/filter & pixel ID. (Suggested Usage: The L1B Spectra Special Observation Low Resolution file consists of radiometrically calibrated spectra and associated NESR observed at 0.1 cm-1 resolution. These spectra are the input measurements to the Level 2 retrieval algorithm that will produce the L2 Special Observation Data Products. The spectra can be used directly as radiance measurements of the earth and atmosphere.)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: The L2 Ancillary Product file consists of measured and static parameters common to all species, such as Surface Pressure and Emissivity. The file is used in conjunction with other L2 species files for detailed studies. There are separate data (Swath) objects corresponding to the Nadir and three Limb views. Each row (nTimes dimension) lines up with the data objects in the species files.)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: The L2 Ancillary Product file consists of measured and static parameters common to all species, such as Surface Pressure and Emissivity. The file is used in conjunction with other L2 species files for detailed studies. There are separate data (Swath) objects corresponding to the Nadir and three Limb views. Each row (nTimes dimension) lines up with the data objects in the species files.)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: The L2 Ancillary Product file consists of measured and static parameters common to all species, such as Surface Pressure and Emissivity. The file is used in conjunction with other L2 species files for detailed studies. There are separate data (Swath) objects corresponding to the Nadir and three Limb views. Each row (nTimes dimension) lines up with the data objects in the species files.)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: The L2 Ancillary Product file consists of measured and static parameters common to all species, such as Surface Pressure and Emissivity. The file is used in conjunction with other L2 species files for detailed studies. There are separate data (Swath) objects corresponding to the Nadir and three Limb views. Each row (nTimes dimension) lines up with the data objects in the species files.)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: The L2 Ancillary Special Observation Product file consists of measured and static parameters common to all species, such as Surface Pressure and Emissivity. The file is used in conjunction with other L2 Special Observation species files for detailed studies. There are separate data (Swath) objects corresponding to the Nadir and three Limb views. Each row (nTimes dimension) lines up with the data objects in the species files.)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: The L2 Ancillary Special Observation Product file consists of measured and static parameters common to all species, such as Surface Pressure and Emissivity. The file is used in conjunction with other L2 Special Observation species files for detailed studies. There are separate data (Swath) objects corresponding to the Nadir and three Limb views. Each row (nTimes dimension) lines up with the data objects in the species files.)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: The L2 Ancillary Special Observation Product file consists of measured and static parameters common to all species, such as Surface Pressure and Emissivity. The file is used in conjunction with other L2 Special Observation species files for detailed studies. There are separate data (Swath) objects corresponding to the Nadir and three Limb views. Each row (nTimes dimension) lines up with the data objects in the species files.)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: The L2 Ancillary Special Observation Product file consists of measured and static parameters common to all species, such as Surface Pressure and Emissivity. The file is used in conjunction with other L2 Special Observation species files for detailed studies. There are separate data (Swath) objects corresponding to the Nadir and three Limb views. Each row (nTimes dimension) lines up with the data objects in the species files.)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors (diagonals and covariance matrices), along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates, along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates, along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates, along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates, along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates, along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates, along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates, along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates, along with retrieved surface temperature, cloud effective optical depth, column estimates, quality flags, and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Input data to the TES radiance forward model. These are profiles generated from climatology databases to be used in the forward model calculation but are not retrieved parameters. (Suggested Usage: These profiles should only be used in the context of understanding the inputs to the TES forward model and retrieval. They could be used as inputs to an independent forward model spectral radiance calculation for comparison to TES L1B radiance spectra.)
Input data to the TES radiance forward model. These are profiles generated from climatology databases to be used in the forward model calculation but are not retrieved parameters. (Suggested Usage: These profiles should only be used in the context of understanding the inputs to the TES forward model and retrieval. They could be used as inputs to an independent forward model spectral radiance calculation for comparison to TES L1B radiance spectra.)
Input data to the TES radiance forward model. These are profiles generated from climatology databases to be used in the forward model calculation but are not retrieved parameters. (Suggested Usage: These profiles should only be used in the context of understanding the inputs to the TES forward model and retrieval. They could be used as inputs to an independent forward model spectral radiance calculation for comparison to TES L1B radiance spectra.)
Input data to the TES radiance forward model. These are profiles generated from climatology databases to be used in the forward model calculation but are not retrieved parameters. (Suggested Usage: These profiles should only be used in the context of understanding the inputs to the TES forward model and retrieval. They could be used as inputs to an independent forward model spectral radiance calculation for comparison to TES L1B radiance spectra.)
Input data to the TES radiance forward model. These are profiles generated from climatology databases to be used in the forward model calculation but are not retrieved parameters. (Suggested Usage: These profiles should only be used in the context of understanding the inputs to the TES forward model and retrieval. They could be used as inputs to an independent forward model spectral radiance calculation for comparison to TES L1B radiance spectra.)
Input data to the TES radiance forward model. These are profiles generated from climatology databases to be used in the forward model calculation but are not retrieved parameters. (Suggested Usage: These profiles should only be used in the context of understanding the inputs to the TES forward model and retrieval. They could be used as inputs to an independent forward model spectral radiance calculation for comparison to TES L1B radiance spectra.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels.  Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels.  Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels.  Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric temperature and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric temperature and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric temperature and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels.  Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels.  Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels.  Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric temperature and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric temperature and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric temperature and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels.  Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels.  Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels.  Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric temperature and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric temperature and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric temperature and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric vertical profile estimates and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly avgs. of atmospheric vert. profile estimates and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and subsetted TES standard pressure levels.  Algms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data of a reduced set of pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric vertical profiles estimates and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES std. pressure levels. Algorithms for deriving TES L3 data provided in data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric temperature and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric temperature and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric temperature and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric temperature and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric temperature and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric temperature and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric vertical profile estimates and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric vertical profiles estimates and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES std. pressure levels. Algorithms for deriving TES L3 data provided in data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Daily atmospheric temperature and VMR for the atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric temperature and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric temperature and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Monthly averages of atmospheric temperature and VMR for atmospheric species are provided at 2 deg. lat. X 4 deg. long. spatial grids and at a subset of TES standard pressure levels. Algorithms for deriving TES L3 data will be provided in the data files. (Suggested Usage: Image maps of L3 data at different pressure levels provide quick views of the global distributions of TES species retrievals. Data usages for science investigations need to reference the algorithms for deriving TES L3 data.)
Atmospheric vertical profile estimates and associated errors derived using TES & MLS spectral radiance measurements taken at nearest time and locations. Also provided are calculated total vertical column, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Atmospheric vertical profile estimates and associated errors derived using TES & MLS spectral radiance measurements taken at nearest time and locations. Also provided are calculated total vertical column, averaging kernels and a priori constraint vectors. (Suggested Usage: Profiles can be compared to other measurements or models of this species or used as input to global chemical/dynamical models)
Height, crown width, DBH, and height-to-crown distance collected using variable-radius plot sampling with steel tape and hand-held compass to locate points along transect
Height, crown width, DBH, and height-to-crown distance collected using variable-radius plot sampling with steel tape and hand-held compass to locate points along transect
ABSTRACT: Height, crown width, DBH, and height-to-crown distance collected using variable-radius plot sampling with steel tape and hand-held compass to locate points along transect
This data product contains TOMS/Earth Probe Total Column Ozone Daily L3 Global 1x1.25 deg Lat/Lon Grid Version 8 data in ASCII format.

(The shortname for this Level-3 Earth Probe TOMS Product is TOMSEPL3dtoz) 

The Total Ozone Mapping Spectrometer (TOMS) Version 8 daily global gridded data consist of total column ozone, aerosol index, Lambertian effective surface reflectivity (Rayleigh corrected) and surface UV-B erythemal irradiances. 
                  
Four TOMS instruments have been successfully flown on the following satellites:  Nimbus-7 (Nov. 1978 - May 1993), Meteor-3 (Aug. 1991 - Dec. 1994), Earth Probe (July 1996 - current), and ADEOS (Sep. 1996 - June 1997).
               
Earth Probe, Meteor-3 and Nimbus-7 data are currently reprocessed using the Version-8 algorithm ( http://ozoneaq.gsfc.nasa.gov/documents.md ) . These Version-8 data are archived at the Goddard Distributed Active Archive Center (DAAC). 
                  
The total ozone, aerosol index, reflectivity data and UV-B Erythemal irradiances are mapped to a global grid of size 180 x 288 with a Lat/Lon resolution of 1.00 x 1.25 degrees. These data are also stored in the EOS version of Hierarchical Data Format (HDF-EOS). HDF was developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois at Urbana-Champaign.

TOMS data are produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 613). The Version-8 Algorithm Theoretical Basis Document (ATBD) is available from the TOMS site http://ozoneaq.gsfc.nasa.gov/documents.md

For detailed information about the TOMS instrument, data, and ozone see the TOMS official Home Page at: http://ozoneaq.gsfc.nasa.gov/
This data product contains TOMS/Earth Probe Total Column Ozone Monthly L3 Global 1x1.25 deg Lat/Lon Grid Version 8 data in ASCII format.

(The shortname for this Level-3 Earth Probe TOMS Product is TOMSEPL3mtoz) 

The Total Ozone Mapping Spectrometer (TOMS) Version 8 monthly global gridded data consist of total column ozone, aerosol index, Lambertian effective surface reflectivity (Rayleigh corrected) and surface UV-B erythemal irradiances. 
                  
Four TOMS instruments have been successfully flown on the following satellites:  Nimbus-7 (Nov. 1978 - May 1993), Meteor-3 (Aug. 1991 - Dec. 1994), Earth Probe (July 1996 - current), and ADEOS (Sep. 1996 - June 1997).
               
Earth Probe, Meteor-3 and Nimbus-7 data are currently reprocessed using the Version-8 algorithm (http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf) . These Version-8 data are archived at the Goddard Distributed Active Archive Center (DAAC). 
                  
The total ozone, aerosol index, reflectivity data and UV-B Erythemal irradiances are mapped to a global grid of size 180 x 288 with a Lat/Lon resolution of 1.00 x 1.25 degrees. These data are also stored in the EOS version of Hierarchical Data Format (HDF-EOS). HDF was developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois at Urbana-Champaign.

TOMS data are produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 613). The Version-8 Algorithm Theoretical Basis Document (ATBD) is available from the TOMS site http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf

For detailed information about the TOMS instrument, data, and ozone see the TOMS official Home Page at: http://toms.gsfc.nasa.gov/
This data product contains TOMS/Earth Probe UV Aerosol Index Daily L3 Global 1x1.25 deg Lat/Lon Grid Version 8 data in ASCII format.

(The shortname for this Level-3 Earth Probe TOMS Product is TOMSEPL3daer) 

The Total Ozone Mapping Spectrometer (TOMS) Version 8 daily global gridded data consist of total column ozone, aerosol index, Lambertian effective surface reflectivity (Rayleigh corrected) and surface UV-B erythemal irradiances. 
                  
Four TOMS instruments have been successfully flown on the following satellites:  Nimbus-7 (Nov. 1978 - May 1993), Meteor-3 (Aug. 1991 - Dec. 1994), Earth Probe (July 1996 - current), and ADEOS (Sep. 1996 - June 1997).
               
Earth Probe, Meteor-3 and Nimbus-7 data are currently reprocessed using the Version-8 algorithm (http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf) . These Version-8 data are archived at the Goddard Distributed Active Archive Center (DAAC). 
                  
The total ozone, aerosol index, reflectivity data and UV-B Erythemal irradiances are mapped to a global grid of size 180 x 288 with a Lat/Lon resolution of 1.00 x 1.25 degrees. These data are also stored in the EOS version of Hierarchical Data Format (HDF-EOS). HDF was developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois at Urbana-Champaign.

TOMS data are produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 613). The Version-8 Algorithm Theoretical Basis Document (ATBD) is available from the TOMS site http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf

For detailed information about the TOMS instrument, data, and ozone see the TOMS official Home Page at: http://toms.gsfc.nasa.gov/
This data product contains TOMS/Earth Probe UV Aerosol Index Monthly L3 Global 1x1.25 deg Lat/Lon Grid Version 8 data in ASCII format.

(The shortname for this Level-3 Earth Probe TOMS Product is TOMSEPL3maer) 

The Total Ozone Mapping Spectrometer (TOMS) Version 8 monthly global gridded data consist of total column ozone, aerosol index, Lambertian effective surface reflectivity (Rayleigh corrected) and surface UV-B erythemal irradiances. 
                  
Four TOMS instruments have been successfully flown on the following satellites:  Nimbus-7 (Nov. 1978 - May 1993), Meteor-3 (Aug. 1991 - Dec. 1994), Earth Probe (July 1996 - current), and ADEOS (Sep. 1996 - June 1997).
               
Earth Probe, Meteor-3 and Nimbus-7 data are currently reprocessed using the Version-8 algorithm ( http://ozoneaq.gsfc.nasa.gov/documents.md ) . These Version-8 data are archived at the Goddard Distributed Active Archive Center (DAAC). 
                  
The total ozone, aerosol index, reflectivity data and UV-B Erythemal irradiances are mapped to a global grid of size 180 x 288 with a Lat/Lon resolution of 1.00 x 1.25 degrees. These data are also stored in the EOS version of Hierarchical Data Format (HDF-EOS). HDF was developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois at Urbana-Champaign.

TOMS data are produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 613). The Version-8 Algorithm Theoretical Basis Document (ATBD) is available from the TOMS site http://ozoneaq.gsfc.nasa.gov/documents.md

For detailed information about the TOMS instrument, data, and ozone see the TOMS official Home Page at: http://ozoneaq.gsfc.nasa.gov/
This data product contains TOMS/Earth Probe UV Reflectivity Daily L3 Global 1x1.25 deg Lat/Lon Grid Version 8 data in ASCII format.

(The shortname for this Level-3 Earth Probe TOMS Product is TOMSEPL3dref) 

The Total Ozone Mapping Spectrometer (TOMS) Version 8 daily global gridded data consist of total column ozone, aerosol index, Lambertian effective surface reflectivity (Rayleigh corrected) and surface UV-B erythemal irradiances. 
                  
Four TOMS instruments have been successfully flown on the following satellites:  Nimbus-7 (Nov. 1978 - May 1993), Meteor-3 (Aug. 1991 - Dec. 1994), Earth Probe (July 1996 - current), and ADEOS (Sep. 1996 - June 1997).
               
Earth Probe, Meteor-3 and Nimbus-7 data are currently reprocessed using the Version-8 algorithm (http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf) . These Version-8 data are archived at the Goddard Distributed Active Archive Center (DAAC). 
                  
The total ozone, aerosol index, reflectivity data and UV-B Erythemal irradiances are mapped to a global grid of size 180 x 288 with a Lat/Lon resolution of 1.00 x 1.25 degrees. These data are also stored in the EOS version of Hierarchical Data Format (HDF-EOS). HDF was developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois at Urbana-Champaign.

TOMS data are produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 613). The Version-8 Algorithm Theoretical Basis Document (ATBD) is available from the TOMS site http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf

For detailed information about the TOMS instrument, data, and ozone see the TOMS official Home Page at: http://toms.gsfc.nasa.gov/
This data product contains TOMS/Earth Probe UV Reflectivity Monthly L3 Global 1x1.25 deg Lat/Lon Grid Version 8 data in ASCII format.

(The shortname for this Level-3 Earth Probe TOMS Product is TOMSEPL3mref) 

The Total Ozone Mapping Spectrometer (TOMS) Version 8 monthly global gridded data consist of total column ozone, aerosol index, Lambertian effective surface reflectivity (Rayleigh corrected) and surface UV-B erythemal irradiances. 
                  
Four TOMS instruments have been successfully flown on the following satellites:  Nimbus-7 (Nov. 1978 - May 1993), Meteor-3 (Aug. 1991 - Dec. 1994), Earth Probe (July 1996 - current), and ADEOS (Sep. 1996 - June 1997).
               
Earth Probe, Meteor-3 and Nimbus-7 data are currently reprocessed using the Version-8 algorithm (http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf) . These Version-8 data are archived at the Goddard Distributed Active Archive Center (DAAC). 
                  
The total ozone, aerosol index, reflectivity data and UV-B Erythemal irradiances are mapped to a global grid of size 180 x 288 with a Lat/Lon resolution of 1.00 x 1.25 degrees. These data are also stored in the EOS version of Hierarchical Data Format (HDF-EOS). HDF was developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois at Urbana-Champaign.

TOMS data are produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 613). The Version-8 Algorithm Theoretical Basis Document (ATBD) is available from the TOMS site http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf

For detailed information about the TOMS instrument, data, and ozone see the TOMS official Home Page at: http://toms.gsfc.nasa.gov/
This data product contains TOMS/Earth Probe UV-B Erythemal Local Noon Irradiance Daily L3 Global 1x1.25 deg Lat/Lon Grid Version 8 data in ASCII format.

(The shortname for this Level-3 Earth Probe TOMS Product is TOMSEPL3dery) 

The Total Ozone Mapping Spectrometer (TOMS) Version 8 daily global gridded data consist of total column ozone, aerosol index, Lambertian effective surface reflectivity (Rayleigh corrected) and surface UV-B erythemal irradiances. 
                  
Four TOMS instruments have been successfully flown on the following satellites:  Nimbus-7 (Nov. 1978 - May 1993), Meteor-3 (Aug. 1991 - Dec. 1994), Earth Probe (July 1996 - current), and ADEOS (Sep. 1996 - June 1997).
               
Earth Probe, Meteor-3 and Nimbus-7 data are currently reprocessed using the Version-8 algorithm (http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf) . These Version-8 data are archived at the Goddard Distributed Active Archive Center (DAAC). 
                  
The total ozone, aerosol index, reflectivity data and UV-B Erythemal irradiances are mapped to a global grid of size 180 x 288 with a Lat/Lon resolution of 1.00 x 1.25 degrees. These data are also stored in the EOS version of Hierarchical Data Format (HDF-EOS). HDF was developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois at Urbana-Champaign.

TOMS data are produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 613). The Version-8 Algorithm Theoretical Basis Document (ATBD) is available from the TOMS site http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf

For detailed information about the TOMS instrument, data, and ozone see the TOMS official Home Page at: http://toms.gsfc.nasa.gov/
This data product contains TOMS/Earth Probe UV-B Erythemal Local Noon Irradiance Monthly L3 Global 1x1.25 deg Lat/Lon Grid Version 8 data in ASCII format.

(The shortname for this Level-3 Earth Probe TOMS Product is TOMSEPL3mery) 

The Total Ozone Mapping Spectrometer (TOMS) Version 8 monthly global gridded data consist of total column ozone, aerosol index, Lambertian effective surface reflectivity (Rayleigh corrected) and surface UV-B erythemal irradiances. 
                  
Four TOMS instruments have been successfully flown on the following satellites:  Nimbus-7 (Nov. 1978 - May 1993), Meteor-3 (Aug. 1991 - Dec. 1994), Earth Probe (July 1996 - current), and ADEOS (Sep. 1996 - June 1997).
               
Earth Probe, Meteor-3 and Nimbus-7 data are currently reprocessed using the Version-8 algorithm (http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf) . These Version-8 data are archived at the Goddard Distributed Active Archive Center (DAAC). 
                  
The total ozone, aerosol index, reflectivity data and UV-B Erythemal irradiances are mapped to a global grid of size 180 x 288 with a Lat/Lon resolution of 1.00 x 1.25 degrees. These data are also stored in the EOS version of Hierarchical Data Format (HDF-EOS). HDF was developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois at Urbana-Champaign.

TOMS data are produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 613). The Version-8 Algorithm Theoretical Basis Document (ATBD) is available from the TOMS site http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf

For detailed information about the TOMS instrument, data, and ozone see the TOMS official Home Page at: http://toms.gsfc.nasa.gov/
Total Ozone Mapping Spectrometer (TOMS)instruments have been successfully flown in orbit aboard the Nimbus-7(Nov. 1978 - May 1993), Meteor-3 (Aug. 1991 - Dec. 1994), Earth Probe (July 1996 - current), and ADEOS (Sep. 1996 - June 1997) satellites. Since last thirty years, TOMS data have been providing useful information related to the ozone depletion, recovery and global trend. The Earth Probe, Meteor-3 and Nimbus-7 Total Ozone Mapping Spectrometer (TOMS) data are currently reprocessed using version-8 algorithm ( http://ozoneaq.gsfc.nasa.gov/documents.md ). 
                  
The TOMS version 8 daily Level-2 swath data product consists of total column ozone, aerosol index, and Lambertian effective surface reflectivity (Rayleigh corrected) at approximately 50x50 km resolution (at nadir). This product also contains some auxiliary derived and ancillary parameters including N-values, SO2 index, cloud fraction, cloud pressure, ozone below clouds, terrain height, geolocation, solar and satellite viewing angles, and data quality flags.
                  
(The shortname for this Level-2 Earth Probe TOMS Product is TOMSEPL2) 

These Level-2 data are stored in the EOS version of Hierarchical Data Format 5 (HDF-EOS5) and are available from the Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC). 
                                          
TOMS data are produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 613.1). The Version-8 Algorithm Theoretial Basis Document (ATBD)is available from the TOMS site http://ozoneaq.gsfc.nasa.gov/documents.md
The Total Ozone Mapping Spectrometer (TOMS) version 8 daily global gridded data consist of total column ozone, aerosol index, Lambertian effective surface reflectivity (Rayleigh corrected) and surface UV-B erythemal irradiances. 

(The shortname for this Level-3 Earth Probe TOMS Product is TOMSEPL3) 
                  
Four TOMS instruments have been successfully flown in orbit aboard the Nimbus-7 (Nov. 1978 - May 1993), Meteor-3 (Aug. 1991 - Dec. 1994), Earth Probe (July  1996 - current), and ADEOS (Sep. 1996 - June 1997) satellites. 
                  
Earth Probe, Meteor-3 and Nimbus-7 data are currently reprocessed using version-8 algorithm ( http://ozoneaq.gsfc.nasa.gov/epsat.md ) . These version-8 data are archived at the Goddard Distributed Active Archive Center (DAAC).                          
                 
The total ozone, aerosol index, reflectivity data and UV-B Erythemal irradiances are mapped to a global grid of size 180 x 288 with a lat-long resolution of 1.00 x 1.25 degrees. These data are stored in the EOS version of Hierarchical Data Format (HDF-EOS). HDF was developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois at Urbana-Champaign.

TOMS data are produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 916). The Version-8 Algorithm Theoretial Basis Document (ATBD)is available from the TOMS site http://ozoneaq.gsfc.nasa.gov/epsat.md
                  
The Level-3 data from Nimbus-7 TOMS, Meteor-3 TOMS, and Earth Probe TOMS are also made available from the Code 916 TOMS site in the ASCII format. For detailed information about the TOMS instrument, data, and ozone see the TOMS official Home Page at: http://ozoneaq.gsfc.nasa.gov/
This data product contains  TOMS/EP Total Column Ozone Daily and Monthly Zonal Means Version 8 data in ASCII format.

(The shortname for this Level-3 Earth Probe TOMS Product is TOMSEPL3ztoz) 

The Total Ozone Mapping Spectrometer (TOMS) Version 8 daily and monthly global gridded data consist of total column ozone, aerosol index, Lambertian effective surface reflectivity (Rayleigh corrected) and surface UV-B erythemal irradiances. 
                  
Four TOMS instruments have been successfully flown on the following satellites:  Nimbus-7 (Nov. 1978 - May 1993), Meteor-3 (Aug. 1991 - Dec. 1994), Earth Probe (July 1996 - current), and ADEOS (Sep. 1996 - June 1997).
               
Earth Probe, Meteor-3 and Nimbus-7 data are currently reprocessed using the Version-8 algorithm (http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf) . These Version-8 data are archived at the Goddard Distributed Active Archive Center (DAAC). 
                  
The total ozone, aerosol index, reflectivity data and UV-B Erythemal irradiances are mapped to a global grid of size 180 x 288 with a Lat/Lon resolution of 1.00 x 1.25 degrees. These data are also stored in the EOS version of Hierarchical Data Format (HDF-EOS). HDF was developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois at Urbana-Champaign.
                  
TOMS data are produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 613). The Version-8 Algorithm Theoretical Basis Document (ATBD) is available from the TOMS site http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf

For detailed information about the TOMS instrument, data, and ozone see the TOMS official Home Page at: http://toms.gsfc.nasa.gov/
This data product contains TOMS/EP UV Aerosol Index Daily and Monthly Zonal Means Version 8 data in ASCII format.

(The shortname for this Level-3 Earth Probe TOMS Product is TOMSEPL3zaer) 

The Total Ozone Mapping Spectrometer (TOMS) Version 8 daily and monthly global gridded data consist of total column ozone, aerosol index, Lambertian effective surface reflectivity (Rayleigh corrected) and surface UV-B erythemal irradiances. 
                  
Four TOMS instruments have been successfully flown on the following satellites:  Nimbus-7 (Nov. 1978 - May 1993), Meteor-3 (Aug. 1991 - Dec. 1994), Earth Probe (July 1996 - current), and ADEOS (Sep. 1996 - June 1997).
               
Earth Probe, Meteor-3 and Nimbus-7 data are currently reprocessed using the Version-8 algorithm (http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf) . These Version-8 data are archived at the Goddard Distributed Active Archive Center (DAAC). 
                  
The total ozone, aerosol index, reflectivity data and UV-B Erythemal irradiances are mapped to a global grid of size 180 x 288 with a Lat/Lon resolution of 1.00 x 1.25 degrees. These data are also stored in the EOS version of Hierarchical Data Format (HDF-EOS). HDF was developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois at Urbana-Champaign.

TOMS data are produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 613). The Version-8 Algorithm Theoretical Basis Document (ATBD) is available from the TOMS site http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf

For detailed information about the TOMS instrument, data, and ozone see the TOMS official Home Page at: http://toms.gsfc.nasa.gov/
This data product contains TOMS/EP UV Reflectivity Daily and Monthly Zonal Means Version 8 data in ASCII format.

(The shortname for this Level-3 Earth Probe TOMS Product is TOMSEPL3zref) 

The Total Ozone Mapping Spectrometer (TOMS) Version 8 daily and monthly global gridded data consist of total column ozone, aerosol index, Lambertian effective surface reflectivity (Rayleigh corrected) and surface UV-B erythemal irradiances. 
                  
Four TOMS instruments have been successfully flown on the following satellites:  Nimbus-7 (Nov. 1978 - May 1993), Meteor-3 (Aug. 1991 - Dec. 1994), Earth Probe (July 1996 - current), and ADEOS (Sep. 1996 - June 1997).
               
Earth Probe, Meteor-3 and Nimbus-7 data are currently reprocessed using the Version-8 algorithm (http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf) . These Version-8 data are archived at the Goddard Distributed Active Archive Center (DAAC). 
                  
The total ozone, aerosol index, reflectivity data and UV-B Erythemal irradiances are mapped to a global grid of size 180 x 288 with a Lat/Lon resolution of 1.00 x 1.25 degrees. These data are also stored in the EOS version of Hierarchical Data Format (HDF-EOS). HDF was developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois at Urbana-Champaign.

TOMS data are produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 613). The Version-8 Algorithm Theoretical Basis Document (ATBD) is available from the TOMS site http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf

For detailed information about the TOMS instrument, data, and ozone see the TOMS official Home Page at: http://toms.gsfc.nasa.gov/
This data product contains TOMS/Meteor-3 Total Column Ozone Daily L3 Global 1x1.25 deg Lat/Lon Grid Version 8 data in ASCII format. 

(The shortname for this Meteor-3 TOMS Product is TOMSM3L3dtoz)

The Metero-3 Total Ozone Mapping Spectrometer (TOMS) Version 8 Daily Gridded Data consist of daily, global coverage of total column ozone and UV-B Lambertian effective surface reflectivity (Rayleigh corrected).   
   
Four TOMS instruments have been successfully flown on the following satellites: Nimbus-7 (Nov. 1978 - May 1993), Meteor-3 (Aug. 1991 - Dec. 1994), Earth Probe (July 1996 - current), and ADEOS (Sep. 1996 - June 1997).

Earth Probe, Meteor-3 and Nimbus-7 data are currently reprocessed using the Version-8 algorithm (http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf) . These Version-8 data are archived at the Goddard Distributed Active Archive Center (DAAC).

The total ozone, aerosol index, reflectivity data and UV-B Erythemal irradiances are mapped to a global grid of size 180 x 288 with a Lat/Lon resolution of 1.00 x 1.25 degrees. These data are also stored in the EOS Version of Hierarchical Data Format (HDF-EOS). HDF was developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois at Urbana-Champaign.

TOMS data are produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 613). The Version-8 Algorithm Theoretical Basis Document (ATBD) is available from the TOMS site http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf

For detailed information about the TOMS instrument, data, and ozone see the TOMS official Home Page at: http://toms.gsfc.nasa.gov/
The Metero-3 Total Ozone Mapping Spectrometer (TOMS) version 8 Daily Gridded Data consist of daily, global coverage of total column ozone and UV-B  Lambertian effective surface reflectivity (Rayleigh corrected).       Four TOMS instruments have been successfully flown in orbit aboard the Nimbus-7 (Nov. 1978 - May 1993), Meteor-3 (Aug. 1991 - Dec. 1994), ADEOS (Sep. 1996 - June 1997) and Earth Probe (July 1996 - 2005) satellites. 

(The shortname for this Meteor-3 TOMS Product is TOMSM3L3)
                  
The temporal coverage of the Meteor-3 TOMS data is from Aug 1991 to Dec 1994. Nimbus-7, Meteor-3, and Earth Probe TOMS data have been reprocessed using version-8 algorithm. These data are archived at the Goddard Distributed Active Archive Center (DAAC). 
                  
The Total column ozone and Effective surface reflectivity data for the Meteor-3 TOMS are mapped to a global grid of size 180 x 288 with a lat-long resolution of 1.00 x 1.25 degrees. These data are stored in the EOS version of Hierarchical Data Format (HDF-EOS). HDF was developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois at Urbana-Champaign.
                  
TOMS data are produced by the Laboratory for Atmospheres at NASA Goddard
Space Flight Center (Code 613.1). The Version-8 Algorithm Theoretical Basis
Document (ATBD)is available from the TOMS site
http://ozoneaq.gsfc.nasa.gov/m3sat.md
                  
The Level-3 data from Nimbus-7 TOMS, Meteor-3 TOMS and Earth Probe
TOMS are also made available from the Code 916 TOMS site in the ASCII format.
TOMS official Home Page at: http://ozoneaq.gsfc.nasa.gov/
This data product contains TOMS/Meteor-3 UV Reflectivity Daily L3 Global 1x1.25 deg Lat/Lon Grid Version 8 data in ASCII format. 

(The shortname for this Meteor-3 TOMS Product is TOMSM3L3dref)

The Metero-3 Total Ozone Mapping Spectrometer (TOMS) Version 8 Daily Gridded Data consist of daily, global coverage of total column ozone and UV-B Lambertian effective surface reflectivity (Rayleigh corrected).      

Four TOMS instruments have been successfully flown on the following satellites: Nimbus-7 (Nov. 1978 - May 1993), Meteor-3 (Aug. 1991 - Dec. 1994), Earth Probe (July 1996 - current), and ADEOS (Sep. 1996 - June 1997).

Earth Probe, Meteor-3 and Nimbus-7 data are currently reprocessed using the Version-8 algorithm (http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf) . These Version-8 data are archived at the Goddard Distributed Active Archive Center (DAAC).

The total ozone, aerosol index, reflectivity data and UV-B Erythemal irradiances are mapped to a global grid of size 180 x 288 with a Lat/Lon resolution of 1.00 x 1.25 degrees. These data are also stored in the EOS Version of Hierarchical Data Format (HDF-EOS). HDF was developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois at Urbana-Champaign.

TOMS data are produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 613). The Version-8 Algorithm Theoretical Basis Document (ATBD) is available from the TOMS site http://toms.gsfc.nasa.gov/version8/v8toms_atbd.pdf

For detailed information about the TOMS instrument, data, and ozone see the TOMS official Home Page at: http://toms.gsfc.nasa.gov/
Leaf water potential data collected w/ Scholander pressure chamber by University of Nebraska
Leaf water potential data collected w/ Scholander pressure chamber by University of Nebraska
ABSTRACT: Leaf water potential data collected w/ Scholander pressure chamber by University of Nebraska
The Atmospheric Tracer Transport Model Intercomparison Project (TransCom) was created to quantify and diagnose the uncertainty in inversion calculations of the global carbon budget that results from errors in simulated atmospheric transport, the choice of measured atmospheric carbon dioxide data used, and the inversion methodology employed. Under the third phase of TransCom (TransCom 3), surface-atmosphere CO2 fluxes were estimated from an intercomparison of 16 different atmospheric tracer transport models and model variants in order to assess the contribution of uncertainties in transport to the uncertainties in flux estimates for annual mean, seasonal cycle, and interannual inversions (referred to as Level 1, 2, and 3 experiments, respectively).This data set provides the model output and inversion results for the TransCom 3, Level I annual mean inversion experiments. Annual mean CO2 concentration data (GLOBALVIEW-CO2, 2000) were used to estimate CO2 sources. The annual average fluxes were estimated for the 1992-1996 period using each of the 16 transport models and a common inversion set-up (Gurney et al., 2002). Methodological choices for this control inversion were selected on the basis of knowledge gained from a wide range of sensitivity tests (Law et al., 2003). Gurney et al. (2003) present results from the control inversion for individual models as well as results from a number of sensitivity tests related to the specification of prior flux information. Additional information about the experimental protocol and results is provided in the companion files and the TransCom project web site (http://www.purdue.edu/transcom/index.php).The results of the Level 1 experiments presented here are grouped into two broad categories: forward simulation fields and response functions (model output) and estimated fluxes (inversion results).
The Atmospheric Tracer Transport Model Intercomparison Project (TransCom) was created to quantify and diagnose the uncertainty in inversion calculations of the global carbon budget that results from errors in simulated atmospheric transport, the choice of measured atmospheric carbon dioxide data used, and the inversion methodology employed. Under the third phase of TransCom (TransCom 3), surface-atmosphere CO2 fluxes were estimated from an intercomparison of 16 different atmospheric tracer transport models and model variants in order to assess the contribution of uncertainties in transport to the uncertainties in flux estimates for annual mean, seasonal cycle, and interannual inversions (referred to as Level 1, 2, and 3 experiments, respectively).This data set provides the model output and inversion results for the TransCom 3, Level I annual mean inversion experiments. Annual mean CO2 concentration data (GLOBALVIEW-CO2, 2000) were used to estimate CO2 sources. The annual average fluxes were estimated for the 1992-1996 period using each of the 16 transport models and a common inversion set-up (Gurney et al., 2002). Methodological choices for this control inversion were selected on the basis of knowledge gained from a wide range of sensitivity tests (Law et al., 2003). Gurney et al. (2003) present results from the control inversion for individual models as well as results from a number of sensitivity tests related to the specification of prior flux information. Additional information about the experimental protocol and results is provided in the companion files and the TransCom project web site (http://www.purdue.edu/transcom/index.php).The results of the Level 1 experiments presented here are grouped into two broad categories: forward simulation fields and response functions (model output) and estimated fluxes (inversion results).
ABSTRACT: The Atmospheric Tracer Transport Model Intercomparison Project (TransCom) was created to quantify and diagnose the uncertainty in inversion calculations of the global carbon budget that results from errors in simulated atmospheric transport, the choice of measured atmospheric carbon dioxide data used, and the inversion methodology employed. Under the third phase of TransCom (TransCom 3), surface-atmosphere CO2 fluxes were estimated from an intercomparison of 16 different atmospheric tracer transport models and model variants in order to assess the contribution of uncertainties in transport to the uncertainties in flux estimates for annual mean, seasonal cycle, and interannual inversions (referred to as Level 1, 2, and 3 experiments, respectively).This data set provides the model output and inversion results for the TransCom 3, Level I annual mean inversion experiments. Annual mean CO2 concentration data (GLOBALVIEW-CO2, 2000) were used to estimate CO2 sources. The annual average fluxes were estimated for the 1992-1996 period using each of the 16 transport models and a common inversion set-up (Gurney et al., 2002). Methodological choices for this control inversion were selected on the basis of knowledge gained from a wide range of sensitivity tests (Law et al., 2003). Gurney et al. (2003) present results from the control inversion for individual models as well as results from a number of sensitivity tests related to the specification of prior flux information. Additional information about the experimental protocol and results is provided in the companion files and the TransCom project web site (http://www.purdue.edu/transcom/index.php).The results of the Level 1 experiments presented here are grouped into two broad categories: forward simulation fields and response functions (model output) and estimated fluxes (inversion results).
This data set provides model outputs and seasonal mean CO2 fluxes from the Atmospheric Carbon Cycle Inversion Intercomparison (TransCom 3), Level 2 inversion experiment. Inversion methods can be used to estimate surface CO2 fluxes from atmospheric CO2 concentration measurements, given an atmospheric transport model to relate the two. This Level 2 experiment inverted for the spatial and temporal pattern of the residual CO2 sources and sinks. There were 12 atmospheric tracer transport models utilized in this experiment. The data inverted were mean CO2 concentration data from 75 sites from the GLOBALVIEW-CO2 2000 data set for the period 1992-1996. The seasonal inversion consists of a 3 year forward simulation (365 days per year) containing 4 presubtracted tracers, 11 SF6 tracers, and 22 CO2 tracers (11 terrestrial, 11 oceanic) (Gurney et al., 2000). Carbon fluxes were estimated for each month of an average year determined as the mean of the 1990-1996 time period from an intercomparison of 12 different atmospheric tracer transport models. This data set provides input data, model output data,the cyclo inversion code, a basis function map, and estimated fluxes.
This data set provides model outputs and seasonal mean CO2 fluxes from the Atmospheric Carbon Cycle Inversion Intercomparison (TransCom 3), Level 2 inversion experiment. Inversion methods can be used to estimate surface CO2 fluxes from atmospheric CO2 concentration measurements, given an atmospheric transport model to relate the two. This Level 2 experiment inverted for the spatial and temporal pattern of the residual CO2 sources and sinks. There were 12 atmospheric tracer transport models utilized in this experiment. The data inverted were mean CO2 concentration data from 75 sites from the GLOBALVIEW-CO2 2000 data set for the period 1992-1996. The seasonal inversion consists of a 3 year forward simulation (365 days per year) containing 4 presubtracted tracers, 11 SF6 tracers, and 22 CO2 tracers (11 terrestrial, 11 oceanic) (Gurney et al., 2000). Carbon fluxes were estimated for each month of an average year determined as the mean of the 1990-1996 time period from an intercomparison of 12 different atmospheric tracer transport models. This data set provides input data, model output data,the cyclo inversion code, a basis function map, and estimated fluxes.
ABSTRACT: This data set provides model outputs and seasonal mean CO2 fluxes from the Atmospheric Carbon Cycle Inversion Intercomparison (TransCom 3), Level 2 inversion experiment. Inversion methods can be used to estimate surface CO2 fluxes from atmospheric CO2 concentration measurements, given an atmospheric transport model to relate the two. This Level 2 experiment inverted for the spatial and temporal pattern of the residual CO2 sources and sinks. There were 12 atmospheric tracer transport models utilized in this experiment. The data inverted were mean CO2 concentration data from 75 sites from the GLOBALVIEW-CO2 2000 data set for the period 1992-1996. The seasonal inversion consists of a 3 year forward simulation (365 days per year) containing 4 presubtracted tracers, 11 SF6 tracers, and 22 CO2 tracers (11 terrestrial, 11 oceanic) (Gurney et al., 2000). Carbon fluxes were estimated for each month of an average year determined as the mean of the 1990-1996 time period from an intercomparison of 12 different atmospheric tracer transport models. This data set provides input data, model output data,the cyclo inversion code, a basis function map, and estimated fluxes.
This data set provides a map of selected areas with defined tree canopy cover over the circumpolar taiga-tundra ecotone (TTE). Canopy cover was derived from the 500-meter MODIS Vegetation Continuous Fields (VCF) product as averaged over six years from 2000-2005 and processed as described in Ranson et al. (2011). This process identified patches of low tree canopy cover which are indicative of the transition from forest to tundra and differentiate the circumpolar taiga-tundra ecotone for the 2000-2005 period. The TTE is the Earth's longest vegetation transition zone and stretches for more than 13,400 km around Arctic North America, Scandinavia, and Eurasia. In Eurasia, the map extends from 60 degrees N to 70 degrees N, and in North America from 50 degrees N to 70 degrees N, excluding Baffin Island in northeastern Canada and the Aleutian Peninsula in southwestern Alaska. Note that for this product, taiga is being used one and the same as boreal forest.This circumpolar TTE area was classified according to VCF tree canopy cover.
This data set provides a map of selected areas with defined tree canopy cover over the circumpolar taiga-tundra ecotone (TTE). Canopy cover was derived from the 500-meter MODIS Vegetation Continuous Fields (VCF) product as averaged over six years from 2000-2005 and processed as described in Ranson et al. (2011). This process identified patches of low tree canopy cover which are indicative of the transition from forest to tundra and differentiate the circumpolar taiga-tundra ecotone for the 2000-2005 period. The TTE is the Earth's longest vegetation transition zone and stretches for more than 13,400 km around Arctic North America, Scandinavia, and Eurasia. In Eurasia, the map extends from 60 degrees N to 70 degrees N, and in North America from 50 degrees N to 70 degrees N, excluding Baffin Island in northeastern Canada and the Aleutian Peninsula in southwestern Alaska. Note that for this product, taiga is being used one and the same as boreal forest.This circumpolar TTE area was classified according to VCF tree canopy cover.
ABSTRACT: This data set provides a map of selected areas with defined tree canopy cover over the circumpolar taiga-tundra ecotone (TTE). Canopy cover was derived from the 500-meter MODIS Vegetation Continuous Fields (VCF) product as averaged over six years from 2000-2005 and processed as described in Ranson et al. (2011). This process identified patches of low tree canopy cover which are indicative of the transition from forest to tundra and differentiate the circumpolar taiga-tundra ecotone for the 2000-2005 period. The TTE is the Earth's longest vegetation transition zone and stretches for more than 13,400 km around Arctic North America, Scandinavia, and Eurasia. In Eurasia, the map extends from 60 degrees N to 70 degrees N, and in North America from 50 degrees N to 70 degrees N, excluding Baffin Island in northeastern Canada and the Aleutian Peninsula in southwestern Alaska. Note that for this product, taiga is being used one and the same as boreal forest.This circumpolar TTE area was classified according to VCF tree canopy cover.
Abstract: The Landsat Orthorectified data collection consists of a global
                set of high-quality, relatively cloud-free orthorectified MSS, TM and ETM+ imagery
                from Landsats 1-5 and 7. This dataset was selected and generated through NASA's
                Commercial Remote Sensing Program, as part of a cooperative effort between NASA and
                the commercial remote sensing community to provide users with access to
                quality-screened, high-resolution satellite images with global coverage over the
                Earth's land masses. The data collection was compiled via NASA contract with Earth
                Satellite Corporation (Rockville, MD) in association with NASA's Scientific Data
                Purchase program. The Landsat Orthorectified data collection consists of
                approximately 7,500 MSS (Landsat 1-5) images, 7,461 TM (Landsat 4-5) images and
                approximately 8,500 ETM+ (Landsat 7) images, which were selected to provide two full
                sets of global coverage over an approximate 10-year interval (circa 1990 and circa
                2000). All selected images were either cloud-free or contained minimal cloud cover.
                In addition, only images with a high quality ranking in regards to the possible
                presence of errors such as missing scans or saturated bands were selected. Purpose:
                To provide users with access to quality-screened, high-resolution satellite images
                with global coverage over the Earth's land masses. Supplemental_Information: The
                average acquisition date for the Landsat Orthorectified ETM+ data is 2000 (+/- 1
                year). All scenes were acquired between 1999 and 2001. These data have been
                orthorectified for coregistration with the earlier (circa 1990) Landsat TM coverage.
Abstract: The Landsat Orthorectified data collection consists of a global
                set of high-quality, relatively cloud-free orthorectified MSS, TM and ETM+ imagery
                from Landsats 1-5 and 7. This dataset was selected and generated through NASA's
                Commercial Remote Sensing Program, as part of a cooperative effort between NASA and
                the commercial remote sensing community to provide users with access to
                quality-screened, high-resolution satellite images with global coverage over the
                Earth's land masses. The data collection was compiled via NASA contract with Earth
                Satellite Corporation (Rockville, MD) in association with NASA's Scientific Data
                Purchase program. The Landsat Orthorectified data collection consists of
                approximately 7,500 MSS (Landsat 1-5) images, 7,461 TM (Landsat 4-5) images and
                approximately 8,500 ETM+ (Landsat 7) images, which were selected to provide two full
                sets of global coverage over an approximate 10-year interval (circa 1990 and circa
                2000). All selected images were either cloud-free or contained minimal cloud cover.
                In addition, only images with a high quality ranking in regards to the possible
                presence of errors such as missing scans or saturated bands were selected. Purpose:
                To provide users with access to quality-screened, high-resolution satellite images
                with global coverage over the Earth's land masses. Supplemental_Information: The
                average acquisition date for the Landsat Orthorectified ETM+ data is 2000 (+/- 1
                year). All scenes were acquired between 1999 and 2001. These data have been
                orthorectified for coregistration with the earlier (circa 1990) Landsat TM coverage.
Abstract: The Landsat Orthorectified data collection consists of a global
                set of high-quality, relatively cloud-free orthorectified MSS, TM and ETM+ imagery
                from Landsats 1-5 and 7. This dataset was selected and generated through NASA's
                Commercial Remote Sensing Program, as part of a cooperative effort between NASA and
                the commercial remote sensing community to provide users with access to
                quality-screened, high-resolution satellite images with global coverage over the
                Earth's land masses. The data collection was compiled via NASA contract with Earth
                Satellite Corporation (Rockville, MD) in association with NASA's Scientific Data
                Purchase program. The Landsat Orthorectified data collection consists of
                approximately 7,500 MSS (Landsat 1-5) images, 7,461 TM (Landsat 4-5) images and
                approximately 8,500 ETM+ (Landsat 7) images, which were selected to provide two full
                sets of global coverage over an approximate 10-year interval (circa 1990 and circa
                2000). All selected images were either cloud-free or contained minimal cloud cover.
                In addition, only images with a high quality ranking in regards to the possible
                presence of errors such as missing scans or saturated bands were selected. Purpose:
                To provide users with access to quality-screened, high-resolution satellite images
                with global coverage over the Earth's land masses. Supplemental_Information: The
                average acquisition date for the Landsat Orthorectified ETM+ data is 2000 (+/- 1
                year). All scenes were acquired between 1999 and 2001. These data have been
                orthorectified for coregistration with the earlier (circa 1990) Landsat TM coverage.
Abstract: The Landsat Orthorectified data collection consists of a global
                set of high-quality, relatively cloud-free orthorectified MSS, TM and ETM+ imagery
                from Landsats 1-5 and 7. This dataset was selected and generated through NASA's
                Commercial Remote Sensing Program, as part of a cooperative effort between NASA and
                the commercial remote sensing community to provide users with access to
                quality-screened, high-resolution satellite images with global coverage over the
                Earth's land masses. The data collection was compiled via NASA contract with Earth
                Satellite Corporation (Rockville, MD) in association with NASA's Scientific Data
                Purchase program. The Landsat Orthorectified data collection consists of
                approximately 7,500 MSS (Landsat 1-5) images, 7,461 TM (Landsat 4-5) images and
                approximately 8,500 ETM+ (Landsat 7) images, which were selected to provide two full
                sets of global coverage over an approximate 10-year interval (circa 1990 and circa
                2000). All selected images were either cloud-free or contained minimal cloud cover.
                In addition, only images with a high quality ranking in regards to the possible
                presence of errors such as missing scans or saturated bands were selected. Purpose:
                To provide users with access to quality-screened, high-resolution satellite images
                with global coverage over the Earth's land masses. Supplemental_Information: The
                average acquisition date for the Landsat Orthorectified ETM+ data is 2000 (+/- 1
                year). All scenes were acquired between 1999 and 2001. These data have been
                orthorectified for coregistration with the earlier (circa 1990) Landsat TM coverage.
Abstract: The Landsat Orthorectified data collection consists of a global
                set of high-quality, relatively cloud-free orthorectified MSS, TM and ETM+ imagery
                from Landsats 1-5 and 7. This dataset was selected and generated through NASA's
                Commercial Remote Sensing Program, as part of a cooperative effort between NASA and
                the commercial remote sensing community to provide users with access to
                quality-screened, high-resolution satellite images with global coverage over the
                Earth's land masses. The data collection was compiled via NASA contract with Earth
                Satellite Corporation (Rockville, MD) in association with NASA's Scientific Data
                Purchase program. The Landsat Orthorectified data collection consists of
                approximately 7,500 MSS (Landsat 1-5) images, 7,461 TM (Landsat 4-5) images and
                approximately 8,500 ETM+ (Landsat 7) images, which were selected to provide two full
                sets of global coverage over an approximate 10-year interval (circa 1990 and circa
                2000). All selected images were either cloud-free or contained minimal cloud cover.
                In addition, only images with a high quality ranking in regards to the possible
                presence of errors such as missing scans or saturated bands were selected. Purpose:
                To provide users with access to quality-screened, high-resolution satellite images
                with global coverage over the Earth's land masses. Supplemental_Information: The
                average acquisition date for the Landsat Orthorectified ETM+ data is 2000 (+/- 1
                year). All scenes were acquired between 1999 and 2001. These data have been
                orthorectified for coregistration with the earlier (circa 1990) Landsat TM coverage.
Abstract: The Landsat Orthorectified data collection consists of a global
                set of high-quality, relatively cloud-free orthorectified MSS, TM and ETM+ imagery
                from Landsats 1-5 and 7. This dataset was selected and generated through NASA's
                Commercial Remote Sensing Program, as part of a cooperative effort between NASA and
                the commercial remote sensing community to provide users with access to
                quality-screened, high-resolution satellite images with global coverage over the
                Earth's land masses. The data collection was compiled via NASA contract with Earth
                Satellite Corporation (Rockville, MD) in association with NASA's Scientific Data
                Purchase program. The Landsat Orthorectified data collection consists of
                approximately 7,500 MSS (Landsat 1-5) images, 7,461 TM (Landsat 4-5) images and
                approximately 8,500 ETM+ (Landsat 7) images, which were selected to provide two full
                sets of global coverage over an approximate 10-year interval (circa 1990 and circa
                2000). All selected images were either cloud-free or contained minimal cloud cover.
                In addition, only images with a high quality ranking in regards to the possible
                presence of errors such as missing scans or saturated bands were selected. Purpose:
                To provide users with access to quality-screened, high-resolution satellite images
                with global coverage over the Earth's land masses. Supplemental_Information: The
                average acquisition date for the Landsat Orthorectified ETM+ data is 2000 (+/- 1
                year). All scenes were acquired between 1999 and 2001. These data have been
                orthorectified for coregistration with the earlier (circa 1990) Landsat TM coverage.
The Tropical Rainfall Measuring Mission (TRMM) is a joint U.S.-Japan satellite mission to monitor tropical and subtropical precipitation and to estimate its associated latent heating. TRMM was successfully launched on November 27, at 4:27 PM (EST) from the Tanegashima Space Center in Japan.

The rainfall measuring instruments on the TRMM satellite include the Precipitation Radar (PR), an electronically scanning radar operating at 13.8 GHz; TRMM Microwave Image (TMI), a nine-channel passive microwave radiometer; and Visible and Infrared Scanner (VIRS), a five-channel visible/infrared radiometer.

The purpose of the 3B42 algorithm is to produce TRMM-adjusted merged-infrared (IR) precipitation and root-mean-square (RMS) precipitation-error estimates.  The algorithm consists of two separate steps. The first step uses the TRMM VIRS and TMI orbit data (TRMM products 1B01 and 2A12) and the monthly TMI/TRMM Combined Instrument (TCI) calibration parameters (from TRMM product 3B31) to produce monthly IR calibration parameters. The second step uses these derived monthly IR calibration parameters to adjust the merged-IR precipitation data, which consists of GMS, GOES-E, GOES-W, Meteosat-7, Meteosat-5, and NOAA-12 data. The final gridded, adjusted merged-IR precipitation (mm/hr) and RMS precipitation-error estimates have a daily temporal resolution and a 0.25-degree by 0.25-degree spatial resolution. Spatial coverage extends from 50 degrees south to 50 degrees north latitude.

The data are stored in the Hierarchical Data Format (HDF), which includes both core and product specific metadata. The file size is about 0.25 MB (compressed).
This document provides basic information on 3B43, TRMM and Other Data Precipitation Product. The TRMM Multi-Satellite Precipitation Analysis (TMPA; computed at monthly intervals as 3B-43) combines the estimates generated by the TRMM and other satellites product (3B-42) and the CAMS global gridded rain gauge data, produced by NOAA&apos;s Climate Prediction Center and/or the global rain gauge product produced by the Global Precipitation Climatology Center (GPCC). The output is rainfall for 0.25x0.25 degree grid boxes for each month. For more details of the algorithm, go to http://trmm.gsfc.nasa.gov/3b43.html
The TRMM Microwave Imager (TMI) is a nine-channel passive microwave radiometer
                        which builds on the heritage of the Special Sensor Microwave/Imager (SSM/I)
                        instrument.  It is flown aboard the Defense Meteorological Satellite Program
                        (DMSP)
                        platforms. 
                        
                        
                        The TRMM Precipitation Radar (PR), the first of its kind in space, is an
                        electronically scanning radar, operating at 13.8 GHz that measures the 3-D
                        rainfall distribution over both land and ocean, and defines the layer depth of
                        the precipitation.
                        
                        
                        The TRMM 3B31 Monthly 5? x 5? Combined Rainfall product, contains Rain rate,
                        cloud liquid water, rain water, cloud ice and graupel at 14 levels for a
                        latitude band from 40 degree N to 40 degree S.  It is derived from the TRMM
                        combined algorithm (2B31), which combines data from the TMI and PR to produce
                        the best rain estimate for TRMM.
The TRMM Microwave Imager (TMI) is a nine-channel passive microwave radiometer which builds on the heritage of the Special Sensor Microwave/Imager (SSM/I) instrument. It is flown aboard the Defense Meteorological Satellite Program (DMSP) platforms. 

The TRMM Precipitation Radar (PR), the first of its kind in space, is an electronically scanning radar, operating at 13.8 GHz that measures the 3-D rainfall distribution over both land and ocean, and defines the layer depth of the precipitation.

The TRMM 3B31 Monthly 0.5 deg. x 0.5 deg. Combined Rainfall product, contains Rain rate, rain water, snow and graupel at 28 levels for a latitude band from 40 degree N to 40 degree S. It is derived from the TRMM combined algorithm (2B31), which combines data from the TMI and PR to produce the best rain estimate for TRMM.
The TRMM Microwave Imager (TMI) is a nine-channel passive microwave radiometer,
                                                which builds on the heritage of the Special Sensor Microwave/Imager (SSM/I)
                                                instrument flown aboard the Defense Meteorological Satellite Program (DMSP)
                                                platforms. 
                                                
                                                The TRMM Precipitation Radar (PR), the first of its kind in space, is an
                                                electronically scanning radar, operating at 13.8 GHz that measures the 3-D
                                                rainfall distribution over both land and ocean, and defines the layer depth of
                                                the precipitation.
                                                
                                                The TRMM combined algorithm (2B31) combines data from the TMI and PR to produce
                                                the best rain estimate for TRMM. Currently, it uses the low frequency channels
                                                of TMI to find the total path attenuation. This information is used to
                                                constrain the radar equation.
The TRMM Microwave Imager (TMI) is a nine-channel passive microwave radiometer, which builds on the heritage of the Special Sensor Microwave/Imager (SSM/I) instrument flown aboard the Defense Meteorological Satellite Program (DMSP) platforms. 
                                                
The TRMM Precipitation Radar (PR), the first of its kind in space, is an electronically scanning radar, operating at 13.8 GHz that measures the 3-D rainfall distribution over both land and ocean, and defines the layer depth of the precipitation.
                                                
The TRMM combined algorithm (2B31) combines data from the TMI and PR to produce the best rain estimate for TRMM. Currently, it uses the low frequency channels of TMI to find the total path attenuation. This information is used to constrain the radar equation.
The Advanced Microwave Precipitation Radiometer (AMPR) was deployed during the Tropical Rainfall Measuring Mission - Large Scale Biosphere-Atmosphere Experiment (TRMM-LBA); the second of three TRMM ground validation missions.  AMPR data were collected at four distinct microwave frequencies (10.7, 19.35, 37.1 and 85.5 GHz) for the time period of January 23 through February 26, 1999.  The geographic domain of the TRMM-LBA region was wholly within Brazilian Amazon Basin between 16 S to 6N latitude and 76W to 49 W longitude.  The TRMM-LBA mission was to study convection over humid tropical land regions within the range of research-quality radar, lightning, radiosonde and raingage sites located in the Amazon Basin (Rondonia, Brazil).
The Advanced Microwave Precipitation Radiometer (AMPR) was deployed during the Tropical Rainfall Measuring Mission - Large Scale Biosphere-Atmosphere Experiment (TRMM-LBA); the second of three TRMM ground validation missions.  AMPR data were collected at four distinct microwave frequencies (10.7, 19.35, 37.1 and 85.5 GHz) for the time period of January 23 through February 26, 1999.  The geographic domain of the TRMM-LBA region was wholly within Brazilian Amazon Basin between 16 S to 6N latitude and 76W to 49 W longitude.  The TRMM-LBA mission was to study convection over humid tropical land regions within the range of research-quality radar, lightning, radiosonde and raingage sites located in the Amazon Basin (Rondonia, Brazil).
The Advanced Microwave Precipitation Radiometer (AMPR) was deployed during the Tropical Rainfall Measuring Mission - Large Scale Biosphere-Atmosphere Experiment (TRMM-LBA); the second of three TRMM ground validation missions.  AMPR data were collected at four distinct microwave frequencies (10.7, 19.35, 37.1 and 85.5 GHz) for the time period of January 23 through February 26, 1999.  The geographic domain of the TRMM-LBA region was wholly within Brazilian Amazon Basin between 16 S to 6N latitude and 76W to 49 W longitude.  The TRMM-LBA mission was to study convection over humid tropical land regions within the range of research-quality radar, lightning, radiosonde and raingage sites located in the Amazon Basin (Rondonia, Brazil).
The average operating altitude for TRMM was changed from 350 to 403 km during the period of August 7-24, 2001. This orbit boost maneuver extended the mission life significantly. All post-boost data products had been released by the TRMM Science Project, as of early December 2001. All TRMM data products (post-boost and pre-boost) are available via the TRMM data search-and-order system at http://mirador.gsfc.nasa.gov/cgi-bin/mirador/presentNavigation.pl?tree=project&project=TRMM . The time period before August 7, 2001 is referred to as pre-boost, and the time period after August 24, 2001 is referred to as post-boost. [Summary provided by the GES-DISC DAAC]
The Tropical Rainfall Measuring Mission (TRMM) is a joint U.S.-Japan satellite mission to monitor tropical and subtropical precipitation and to estimate its associated latent heating.

Hydrometeor profiles of cloud liquid water, precipitation water, cloud ice water, precipitation ice, rainfall type, and latent heating are reported in 14 layers, with a vertical resolution of 0.5 km from the surface to 18.0 km. Geolocation, time stamp, data quality, surface type, and surface rain confidence are included for each pixel. Spatial coverage is between 38 degrees North and 38 degrees South, owing to the 35 degree inclination of the TRMM satellite. This orbit provides extensive coverage in the tropics and allows each location to be covered at a different local time each day, enabling the analysis of the diurnal cycle of precipitation. There are, in general, 2991 scans along the orbit, with each scan consisting of 208 high resolution (85 GHz) pixels. The scan width is about 760 km.

The data are stored in the Hierarchical Data Format (HDF), which includes both core and product specific metadata applicable to the TMI measurements. A file contains a single orbit of data with a file size of about 95 MB (uncompressed). The HDF-EOS &quot;swath&quot; structure is used to accommodate the actual geophysical data arrays. There are 16 files of TMI 2A12 data produced per day.
The Tropical Rainfall Measuring Mission (TRMM) is a joint U.S.-Japan satellite mission to monitor tropical and subtropical precipitation and to estimate its associated latent heating.

Hydrometeor profiles of cloud liquid water, precipitation water, cloud ice water, precipitation ice, rainfall type, and latent heating are reported in 28 layers, with a vertical resolution of 0.5 km from the surface to 18.0 km. Geolocation, time stamp, data quality, surface type, and surface rain confidence are included for each pixel. Spatial coverage is between 38 degrees North and 38 degrees South, owing to the 35 degree inclination of the TRMM satellite. This orbit provides extensive coverage in the tropics and allows each location to be covered at a different local time each day, enabling the analysis of the diurnal cycle of precipitation. There are, in general, 2991 scans along the orbit, with each scan consisting of 208 high resolution (85 GHz) pixels. The scan width is about 760 km.

The data are stored in the Hierarchical Data Format (HDF), which includes both core and product specific metadata applicable to the TMI measurements. A file contains a single orbit of data with a file size of about 95 MB (uncompressed). The HDF-EOS "swath" structure is used to accommodate the actual geophysical data arrays. There are 16 files of TMI 2A12 data produced per day.
This document provides basic information on 3A12, TMI Monthly 0.5 deg. x 0.5 deg. Profiling. Algorithm 3A12 produces global 0.5 deg. x 0.5 deg. monthly gridded means using 2A12 data. Vertical hydrometeor profiles and surface rainfall means are computed. Various pixel counts are also reported. The granule size is one month.This document provides basic information on 3A12, TMI Monthly 0.5 deg. x 0.5 deg. Profiling. Algorithm 3A12 produces global 0.5 deg. x 0.5 deg. monthly gridded means using 2A12 data. Vertical hydrometeor profiles and surface rainfall means are computed. Various pixel counts are also reported. The granule size is one month.
   
The average operating altitude for TRMM was changed from 350 to 403 km during the period of August 7-24, 2001. This orbit boost maneuver extended the mission life significantly. All post-boost data products had been released by the TRMM Science Project, as of early December 2001. All TRMM data products (post- and pre-boost) are available via the TRMM data search-and-order system at http://mirador.gsfc.nasa.gov/cgi-bin/mirador/presentNavigation.pl?tree=project&project=TRMM . The time period before August 7, 2001 is referred to as pre-boost, and the time period after August 24, 2001 is referred to as post-boost.

[Summary provided by the GES-DISC DAAC]
This document provides basic information on 3A12, TMI Monthly 0.5 deg. x 0.5 deg. Profiling. Algorithm 3A12 produces global 0.5 deg. x 0.5 deg. monthly gridded means using 2A12 data. Vertical hydrometeor profiles and surface rainfall means are computed. Various pixel counts are also reported. The granule size is one month.This document provides basic information on 3A12, TMI Monthly 0.5 deg. x 0.5 deg. Profiling. Algorithm 3A12 produces global 0.5 deg. x 0.5 deg. monthly gridded means using 2A12 data. Vertical hydrometeor profiles and surface rainfall means are computed. Various pixel counts are also reported. The granule size is one month.
   
The average operating altitude for TRMM was changed from 350 to 403 km during the period of August 7-24, 2001. This orbit boost maneuver extended the mission life significantly. All post-boost data products had been released by the TRMM Science Project, as of early December 2001. All TRMM data products (post- and pre-boost) are available via the TRMM data search-and-order system at http://mirador.gsfc.nasa.gov/cgi-bin/mirador/presentNavigation.pl?tree=project&project=TRMM . The time period before August 7, 2001 is referred to as pre-boost, and the time period after August 24, 2001 is referred to as post-boost.

[Summary provided by the GES-DISC DAAC]
The TRMM Microwave Imager (TMI) is a 5-channel, dual-polarized, passive microwave radiometer.  Microwave radiation is emitted by the Earth's surface and by water droplets within clouds.  The TMI is used to measure several important meteorological parameters over sea surfaces.  The TMI, a successor to the SSM/I, measures radiation at frequencies of 10.7, 19.4, 21.3, 37, 85.5 GHz.  It orbits at an altitude of 218 miles, much lower than the SSM/I, thus providing better resolution.
The TRMM Microwave Imager (TMI) is a 5-channel, dual-polarized, passive microwave radiometer.  Microwave radiation is emitted by the Earth's surface and by water droplets within clouds.  The TMI is used to measure several important meteorological parameters over sea surfaces.  The TMI, a successor to the SSM/I, measures radiation at frequencies of 10.7, 19.4, 21.3, 37, 85.5 GHz.  It orbits at an altitude of 218 miles, much lower than the SSM/I, thus providing better resolution.
The TRMM Microwave Imager (TMI) is a 5-channel, dual-polarized, passive microwave radiometer.  Microwave radiation is emitted by the Earth's surface and by water droplets within clouds.  The TMI is used to measure several important meteorological parameters over sea surfaces.  The TMI, a successor to the SSM/I, measures radiation at frequencies of 10.7, 19.4, 21.3, 37, 85.5 GHz.  It orbits at an altitude of 218 miles, much lower than the SSM/I, thus providing better resolution.
TRMM product 3A46 consists of monthly Special Sensor Microwave/Imager (SSM/I) data averaged over 1 deg. x 1 deg. grid boxes and one month.  

This orbit boost maneuver extended the mission life significantly. All post-boost data products had been released by the TRMM Science Project, as of early December 2001. All TRMM data products (post-boost and pre-boost) are available via the TRMM data search-and-order system at:

http://mirador.gsfc.nasa.gov/cgi-bin/mirador/presentNavigation.pl?tree=project&project=TRMM
The ER-2 Lightning Instrument Package measures the electric field above, below, and around the aircraft. The ER-2 LIP consists of eight electric field mills, a conductivity probe, and the associated data system. One of the field mills is installed on the upper Q-bay hatch cover and the second one is mounted on the aft section of the Advanced Microwave Precipitation Radiometer (AMPR) fairing. Three mills are each located on the superpods: one on the top, two on the bottom. The conductivity probe is integrated in the right hand superpod nose cone. The ER-2 LIP data system is mounted in a 19 inch vertical rack located in the aft section of the ER-2 Q-bay. The ER-2 electric field mills and the conductivity probe are compact sensors, each weighing less than 5 lbs.
The ER-2 Lightning Instrument Package measures the electric field above, below, and around the aircraft. The ER-2 LIP consists of eight electric field mills, a conductivity probe, and the associated data system. One of the field mills is installed on the upper Q-bay hatch cover and the second one is mounted on the aft section of the Advanced Microwave Precipitation Radiometer (AMPR) fairing. Three mills are each located on the superpods: one on the top, two on the bottom. The conductivity probe is integrated in the right hand superpod nose cone. The ER-2 LIP data system is mounted in a 19 inch vertical rack located in the aft section of the ER-2 Q-bay. The ER-2 electric field mills and the conductivity probe are compact sensors, each weighing less than 5 lbs.
The ER-2 Lightning Instrument Package measures the electric field above, below, and around the aircraft. The ER-2 LIP consists of eight electric field mills, a conductivity probe, and the associated data system. One of the field mills is installed on the upper Q-bay hatch cover and the second one is mounted on the aft section of the Advanced Microwave Precipitation Radiometer (AMPR) fairing. Three mills are each located on the superpods: one on the top, two on the bottom. The conductivity probe is integrated in the right hand superpod nose cone. The ER-2 LIP data system is mounted in a 19 inch vertical rack located in the aft section of the ER-2 Q-bay. The ER-2 electric field mills and the conductivity probe are compact sensors, each weighing less than 5 lbs.
U.S. Census Grids (Summary File 1), 1990 contain grids of demographic and socioeconomic data from the year 1990 U.S. census in ASCII and geotiff formats. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 1990 TIGER/Line Files and census variables (population, households, and housing variables). This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Census Grids (Summary File 1), 1990 contain grids of demographic and socioeconomic data from the year 1990 U.S. census in ASCII and geotiff formats. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 1990 TIGER/Line Files and census variables (population, households, and housing variables). This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Census Grids (Summary File 1), 1990 contain grids of demographic and socioeconomic data from the year 1990 U.S. census in ASCII and geotiff formats. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 1990 TIGER/Line Files and census variables (population, households, and housing variables). This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide gridded demographic data, including characteristics of age, race, ethnicity, and housing, for the United States.)
U.S. Census Grids (Summary File 1), 1990: Metropolitan Statistical Areas contain grids of demographic and socioeconomic data from the year 1990 U.S. census in ASCII and geotiff formats for 39 metropolitan statistical areas with at least one million in population. The grids have a resolution of 7.5 arc-seconds (0.002075 decimal degrees), or approximately 250 square meters. The gridded variables are based on census block geography from Census 1990 TIGER/Line Files and census variables (population, households, and housing variables). This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Census Grids (Summary File 1), 1990: Metropolitan Statistical Areas contain grids of demographic and socioeconomic data from the year 1990 U.S. census in ASCII and geotiff formats for 39 metropolitan statistical areas with at least one million in population. The grids have a resolution of 7.5 arc-seconds (0.002075 decimal degrees), or approximately 250 square meters. The gridded variables are based on census block geography from Census 1990 TIGER/Line Files and census variables (population, households, and housing variables). This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Census Grids (Summary File 1), 1990: Metropolitan Statistical Areas contain grids of demographic and socioeconomic data from the year 1990 U.S. census in ASCII and geotiff formats for 39 metropolitan statistical areas with at least one million in population. The grids have a resolution of 7.5 arc-seconds (0.002075 decimal degrees), or approximately 250 square meters. The gridded variables are based on census block geography from Census 1990 TIGER/Line Files and census variables (population, households, and housing variables). This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide gridded demographic data, including characteristics of age, race, ethnicity, and housing, for the United States.)
U.S. Census Grids (Summary File 1), 2000 contain grids of demographic and socioeconomic data 

from the year 2000 U.S. census in ASCII and geotiff formats. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), 

or approximately 1 square km. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census 

variables (population, households, and housing variables). This dataset is produced by the Columbia University Center for 

International Earth Science Information Network (CIESIN).
U.S. Census Grids (Summary File 1), 2000 contain grids of demographic and socioeconomic data 

from the year 2000 U.S. census in ASCII and geotiff formats. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), 

or approximately 1 square km. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census 

variables (population, households, and housing variables). This dataset is produced by the Columbia University Center for 

International Earth Science Information Network (CIESIN).
U.S. Census Grids (Summary File 1), 2000 contain grids of demographic and socioeconomic data 

from the year 2000 U.S. census in ASCII and geotiff formats. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), 

or approximately 1 square km. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census 

variables (population, households, and housing variables). This dataset is produced by the Columbia University Center for 

International Earth Science Information Network (CIESIN).
U.S. Population Grids (Summary File 1), 2000: Metropolitan Statistical Areas contain grids of 

demographic and socioeconomic data from the year 2000 U.S. census in ASCII and geotiff formats for 50 metropolitan statistical areas 

with at least one million in population. The grids have a resolution of 7.5 arc-seconds (0.002075 decimal degrees), or approximately 

250 square meters. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables 

(population, households, and housing variables). This dataset is produced by the Columbia University Center for International Earth 

Science Information Network (CIESIN).
U.S. Population Grids (Summary File 1), 2000: Metropolitan Statistical Areas contain grids of 

demographic and socioeconomic data from the year 2000 U.S. census in ASCII and geotiff formats for 50 metropolitan statistical areas 

with at least one million in population. The grids have a resolution of 7.5 arc-seconds (0.002075 decimal degrees), or approximately 

250 square meters. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables 

(population, households, and housing variables). This dataset is produced by the Columbia University Center for International Earth 

Science Information Network (CIESIN).
U.S. Population Grids (Summary File 1), 2000: Metropolitan Statistical Areas contain grids of 

demographic and socioeconomic data from the year 2000 U.S. census in ASCII and geotiff formats for 50 metropolitan statistical areas 

with at least one million in population. The grids have a resolution of 7.5 arc-seconds (0.002075 decimal degrees), or approximately 

250 square meters. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables 

(population, households, and housing variables). This dataset is produced by the Columbia University Center for International Earth 

Science Information Network (CIESIN).
U.S. Census Grids (Summary File 3), 1990 contain grids of demographic and socioeconomic data from the year 1990 U.S. census in ASCII and geotiff formats. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 1990 TIGER/Line Files and census variables (population, households, and housing variables). This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Census Grids (Summary File 3), 1990 contain grids of demographic and socioeconomic data from the year 1990 U.S. census in ASCII and geotiff formats. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 1990 TIGER/Line Files and census variables (population, households, and housing variables). This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Census Grids (Summary File 3), 1990 contain grids of demographic and socioeconomic data from the year 1990 U.S. census in ASCII and geotiff formats. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 1990 TIGER/Line Files and census variables (population, households, and housing variables). This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
 (Suggested Usage: To provide gridded demographic data, including characteristics of income, education, and housing, for the United States for data integration.)
U.S. Census Grids (Summary File 3), 1990: Metropolitan Statistical Areas contain grids of demographic and socioeconomic data from the year 1990 U.S. Census in ASCII and geotiff formats for 50 metropolitan statistical areas with at least one million in population. The grids have a resolution of 7.5 arc-seconds (0.002075 decimal degrees), or approximately 250 square meters. The gridded variables are based on census block geography from Census 1990 TIGER/Line Files and census variables (population, households, and housing variables). This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Census Grids (Summary File 3), 1990: Metropolitan Statistical Areas contain grids of demographic and socioeconomic data from the year 1990 U.S. Census in ASCII and geotiff formats for 50 metropolitan statistical areas with at least one million in population. The grids have a resolution of 7.5 arc-seconds (0.002075 decimal degrees), or approximately 250 square meters. The gridded variables are based on census block geography from Census 1990 TIGER/Line Files and census variables (population, households, and housing variables). This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Census Grids (Summary File 3), 1990: Metropolitan Statistical Areas contain grids of demographic and socioeconomic data from the year 1990 U.S. Census in ASCII and geotiff formats for 50 metropolitan statistical areas with at least one million in population. The grids have a resolution of 7.5 arc-seconds (0.002075 decimal degrees), or approximately 250 square meters. The gridded variables are based on census block geography from Census 1990 TIGER/Line Files and census variables (population, households, and housing variables). This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide gridded demographic data, including characteristics of income, education, and housing, for metropolitan statistical areas at a finer resolution than is available in the 30 arc-second grids used for the United States as a whole.)
U.S. Census Grids (Summary File 3), 2000 contain grids of demographic and socioeconomic data from the year 2000 U.S. census in ASCII and geotiff formats. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (population, households, and housing variables). This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Census Grids (Summary File 3), 2000 contain grids of demographic and socioeconomic data from the year 2000 U.S. census in ASCII and geotiff formats. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (population, households, and housing variables). This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Census Grids (Summary File 3), 2000 contain grids of demographic and socioeconomic data from the year 2000 U.S. census in ASCII and geotiff formats. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (population, households, and housing variables). This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Census Grids (Summary File 3), 2000 contain grids of demographic and socioeconomic data from the year 2000 U.S. census in ASCII and geotiff formats. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (population, households, and housing variables). This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Population Grids (Summary File 3), 2000: Metropolitan Statistical Areas contain grids of demographic and socioeconomic data from the year 2000 U.S. census in ASCII and geotiff formats for 50 metropolitan statistical areas with at least one million in population. The grids have a resolution of 7.5 arc-seconds (0.002075 decimal degrees), or approximately 250 square meters. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (population, households, and housing variables). This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Population Grids (Summary File 3), 2000: Metropolitan Statistical Areas contain grids of demographic and socioeconomic data from the year 2000 U.S. census in ASCII and geotiff formats for 50 metropolitan statistical areas with at least one million in population. The grids have a resolution of 7.5 arc-seconds (0.002075 decimal degrees), or approximately 250 square meters. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (population, households, and housing variables). This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Population Grids (Summary File 3), 2000: Metropolitan Statistical Areas contain grids of demographic and socioeconomic data from the year 2000 U.S. census in ASCII and geotiff formats for 50 metropolitan statistical areas with at least one million in population. The grids have a resolution of 7.5 arc-seconds (0.002075 decimal degrees), or approximately 250 square meters. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (population, households, and housing variables). This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
The U.S. Environmental Protection Agency (EPA) National Priorities List (NPL) Sites Point Data with CIESIN Modifications, 2008 is a modified version of the 2008 EPA NPL list. It includes all the sites that have been proposed to, currently on, and deleted from the Final NPL as of June 7, 2008. CIESIN has fixed six of the original coordinates by correcting latitude or longitude coordinates and providing the missing coordinates for one site. It contains the point locations, including the seven corrections, for 1,641 U.S. hazardous waste sites on the National Priorities List (NPL) of EPA's Comprehensive Environmental Response, Compensation, and Liability Information System (CERCLIS) for the US States and Puerto Rico. The sites in CERCLIS are also known as Superfund Sites. The NPL is intended primarily to guide the EPA in determining which sites warrant further investigation. The dataset presented here provides the latitude and longitudinal coordinates of the centroid for each of the 1641 NPL sites. Some of the National Priorities List (NPL) sites have latitude and longitude data accurate to within 30 meters and, in some cases, in the sub-meter range. The latitude and longitude for other sites is the centroid of the ZIP code area for the ZIP code of the site's address. This dataset is modified and distributed by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide an easily accessible, corrected dataset of the geo-referenced locations for all the National Priorities List sites in the United States and Puerto Rico.)
The U.S. Environmental Protection Agency (EPA) National Priorities List (NPL) Sites Point Data with CIESIN Modifications, 2008 is a modified version of the 2008 EPA NPL list. It includes all the sites that have been proposed to, currently on, and deleted from the Final NPL as of June 7, 2008. CIESIN has fixed six of the original coordinates by correcting latitude or longitude coordinates and providing the missing coordinates for one site. It contains the point locations, including the seven corrections, for 1,641 U.S. hazardous waste sites on the National Priorities List (NPL) of EPA's Comprehensive Environmental Response, Compensation, and Liability Information System (CERCLIS) for the US States and Puerto Rico. The sites in CERCLIS are also known as Superfund Sites. The NPL is intended primarily to guide the EPA in determining which sites warrant further investigation. The dataset presented here provides the latitude and longitudinal coordinates of the centroid for each of the 1641 NPL sites. Some of the National Priorities List (NPL) sites have latitude and longitude data accurate to within 30 meters and, in some cases, in the sub-meter range. The latitude and longitude for other sites is the centroid of the ZIP code area for the ZIP code of the site's address. This dataset is modified and distributed by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide an easily accessible, corrected dataset of the geo-referenced locations for all the National Priorities List sites in the United States and Puerto Rico.)
The U.S. Environmental Protection Agency (EPA) National Priorities List (NPL) Sites Point Data with CIESIN Modifications, 2008 is a modified version of the 2008 EPA NPL list. It includes all the sites that have been proposed to, currently on, and deleted from the Final NPL as of June 7, 2008. CIESIN has fixed six of the original coordinates by correcting latitude or longitude coordinates and providing the missing coordinates for one site. It contains the point locations, including the seven corrections, for 1,641 U.S. hazardous waste sites on the National Priorities List (NPL) of EPA's Comprehensive Environmental Response, Compensation, and Liability Information System (CERCLIS) for the US States and Puerto Rico. The sites in CERCLIS are also known as Superfund Sites. The NPL is intended primarily to guide the EPA in determining which sites warrant further investigation. The dataset presented here provides the latitude and longitudinal coordinates of the centroid for each of the 1641 NPL sites. Some of the National Priorities List (NPL) sites have latitude and longitude data accurate to within 30 meters and, in some cases, in the sub-meter range. The latitude and longitude for other sites is the centroid of the ZIP code area for the ZIP code of the site's address. This dataset is modified and distributed by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide an easily accessible, corrected dataset of the geo-referenced locations for all the National Priorities List sites in the United States and Puerto Rico.)
U.S. Population Grids (Summary File 1), 2000: Alabama, Louisiana, Mississippi and Texas, Alpha Version contains an ARC/INFO Workspace with grids of demographic data from the year 2000 census. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (population, households, and housing variables). This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Population Grids (Summary File 1), 2000: Alabama, Louisiana, Mississippi and Texas, Alpha Version contains an ARC/INFO Workspace with grids of demographic data from the year 2000 census. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (population, households, and housing variables). This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Population Grids (Summary File 1), 2000: Alabama, Louisiana, Mississippi and Texas, Alpha Version contains an ARC/INFO Workspace with grids of demographic data from the year 2000 census. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (population, households, and housing variables). This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide gridded demographic data, including characteristics of age, race, ethnicity, and housing, for Alabama, Louisiana, Mississippi and Texas.)
U.S. Population Grids (Summary File 1), 2000: Houston Metropolitan Statistical Area, Alpha Version contains an ARC/INFO Workspace with grids of demographic data from the 2000 census. The grids have a resolution of 7.5 arc-seconds (0.002075 decimal degrees), or approximately 250 square meters. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (population, households, and housing variables) from Summary File 1. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Population Grids (Summary File 1), 2000: Houston Metropolitan Statistical Area, Alpha Version contains an ARC/INFO Workspace with grids of demographic data from the 2000 census. The grids have a resolution of 7.5 arc-seconds (0.002075 decimal degrees), or approximately 250 square meters. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (population, households, and housing variables) from Summary File 1. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Population Grids (Summary File 1), 2000: Houston Metropolitan Statistical Area, Alpha Version contains an ARC/INFO Workspace with grids of demographic data from the 2000 census. The grids have a resolution of 7.5 arc-seconds (0.002075 decimal degrees), or approximately 250 square meters. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (population, households, and housing variables) from Summary File 1. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Population Grids (Summary File 1), 2000: New Orleans Metropolitan Statistical Area, Alpha Version contains an ARC/INFO Workspace with grids of demographic data from the 2000 census. The grids have a resolution of 7.5 arc-seconds (0.002075 decimal degrees), or approximately 250 square meters. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (population, households, and housing variables) from Summary File 1. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Population Grids (Summary File 1), 2000: New Orleans Metropolitan Statistical Area, Alpha Version contains an ARC/INFO Workspace with grids of demographic data from the 2000 census. The grids have a resolution of 7.5 arc-seconds (0.002075 decimal degrees), or approximately 250 square meters. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (population, households, and housing variables) from Summary File 1. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Population Grids (Summary File 1), 2000: New Orleans Metropolitan Statistical Area, Alpha Version contains an ARC/INFO Workspace with grids of demographic data from the 2000 census. The grids have a resolution of 7.5 arc-seconds (0.002075 decimal degrees), or approximately 250 square meters. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (population, households, and housing variables) from Summary File 1. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Population Grids (Summary File 3), 2000: Alabama, Louisiana, and Mississippi, Alpha Version contain an ARC/INFO Workspace with grids of demographic data from the year 2000 census. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (income, poverty, education, housing age). This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Population Grids (Summary File 3), 2000: Alabama, Louisiana, and Mississippi, Alpha Version contain an ARC/INFO Workspace with grids of demographic data from the year 2000 census. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (income, poverty, education, housing age). This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Population Grids (Summary File 3), 2000: Alabama, Louisiana, and Mississippi, Alpha Version contain an ARC/INFO Workspace with grids of demographic data from the year 2000 census. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (income, poverty, education, housing age). This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide gridded demographic data, including characteristics of income, poverty, education, and housing age, for Alabama, Louisiana and Mississippi.)
U.S. Population Grids (Summary File 3), 2000: New Orleans Metropolitan Statistical Area, Alpha Version contain an ARC/INFO Workspace with grids of demographic data from the year 2000 census. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (income, poverty, education, housing age). This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Population Grids (Summary File 3), 2000: New Orleans Metropolitan Statistical Area, Alpha Version contain an ARC/INFO Workspace with grids of demographic data from the year 2000 census. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (income, poverty, education, housing age). This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
U.S. Population Grids (Summary File 3), 2000: New Orleans Metropolitan Statistical Area, Alpha Version contain an ARC/INFO Workspace with grids of demographic data from the year 2000 census. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (income, poverty, education, housing age). This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide gridded demographic data, including characteristics of income, poverty, education, and housing age, for New Orleans.)
The UARS Correlative assimilation data from the U.K. Meteorological Office (UKMO) consists of daily model runs at 12:00 GMT as a means of providing an independent analysis for comparison with data from the UARS instruments. The UKMO product includes temperature (Kelvin), geopotential height (m), zonal and meridional wind components (m/s), and vertical velocity (Pa/s).

Note: vertical velocity (omega) data are available from 26 August 1992 forward.

The numerical model used in the assimilation system is a global primitive equation model, with a split-explicit time integration scheme.  It incorporates a comprehensive range of physical parameterization schemes.  It uses a hybrid vertical coordinate system, with terrain-following model levels at low levels, gradually changing to pressure levels in the stratosphere.  The input to the assimilation system are from the World Weather Watch network of surface and upper air observations and satellite data.

The UKMO product consists of a single granule per day containing all the geophysical parameters.  Data coverage is global for where the horizontal resolution is 2.5 degrees latitude by 3.75 degrees longitude, using a staggered grid system.  For parameters other than wind components, each horizontal field consists of 73 rows of 96 points, starting at 90N, 0E.  The wind data are staggered by half a grid, starting at 88.75N, 1.875E (with 72 rows).

The UKMO correlative assimilation data are on the UARS standard pressure levels (in mbars) given by:

P(i) =  1000 * 10**(-i/6)  for i = 0, 1, 2, ...

The data files are available in a binary record oriented format.
The Improved Stratospheric and Mesospheric Sounder (ISAMS) Level 3AL data product consists of daily, 4 degree increment latitude-ordered vertical profiles of temperature and concentrations of O3, H2O, CH4, CO, N2O, N2O5, NO2, and aerosol absorption coefficients.  The insrument measured infrared molecular emmissions in the spectral region from 4.6 to 16.6 microns.  ISAMS was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure the global temperature and composition profiles in the stratosphere and mesosphere. Limb measurements were made in the altitude range between 15 and 60 km at about 2.5 km resolution. Data were collected between latitude 34S and 80N and 80S and 34N, alternating each satellite yaw cycle of about 36 days. The ISAMS Level 3AL data were processed with the version 10 algorithm, except H2O which is version 9.

The ISAMS level 3AL product consists of 10 granules per day. A data granule is one ISAMS species or subtype per day. The following species are measured:


 1) AERO12P1 - aerosol at 12.1 microns  [1/km]
 2) AERO6P23 - aerosol at 6.23 microns  [1/km]
 3) CH4      - methane                  [vmr]
 4) CO       - carbon monoxide          [vmr]
 5) H2O      - water vapor              [vmr]
 6) N2O      - nitrous oxide            [vmr]
 7) N2O5     - nitrogen pentoxide       [vmr]
 8) NO2      - nitrogen dioxide         [vmr]
 9) O3       - ozone                    [vmr]
10) TEMP     - atmospheric temperature  [Kelvin]

*vmr = volume mixing ratio

ISAMS data are on the UARS standard pressure levels (in mbars) given by:

P(i) =  1000 * 10**(-i/6)  for i = 0, 1, 2, ...

Each of the 10 ISAMS granules is accompanied by its own additional parameter file, designated as level 3LP.  The parameter file, contains the additional ancillary and quality information not found in the 3AL file. The data files are available in a binary record oriented format.
The Improved Stratospheric and Mesospheric Sounder (ISAMS) Level 3AT data product consists of daily, 65.536 second interval time-ordered vertical profiles of temperature and concentrations of O3, H2O, CH4, CO, N2O, N2O5, NO2, and aerosol absorption coefficients.  The insrument measured infrared molecular emmissions in the spectral region from 4.6 to 16.6 microns.  ISAMS was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure the global temperature and composition profiles in the stratosphere and mesosphere. Limb measurements were made in the altitude range between 15 and 60 km at about 2.5 km resolution.  Data were collected between latitude 34S and 80N and 80S and 34N, alternating each satellite yaw cycle of about 36 days. The ISAMS Level 3AT data were processed with the version 10 algorithm, except H2O which is version 9.

The ISAMS level 3AT product consists of 10 granules per day. A data granule is one ISAMS species or subtype per day. The following species are measured:

 1) AERO12P1 - aerosol at 12.1 microns  [1/km]
 2) AERO6P23 - aerosol at 6.23 microns  [1/km]
 3) CH4      - methane                  [vmr]
 4) CO       - carbon monoxide          [vmr]
 5) H2O      - water vapor              [vmr]
 6) N2O      - nitrous oxide            [vmr]
 7) N2O5     - nitrogen pentoxide       [vmr]
 8) NO2      - nitrogen dioxide         [vmr]
 9) O3       - ozone                    [vmr]
10) TEMP     - atmospheric temperature  [Kelvin]

*vmr = volume mixing ratio

ISAMS data are on the UARS standard pressure levels (in mbars) given by:

P(i) =  1000 * 10**(-i/6)  for i = 0, 1, 2, ...

Each of the 10 ISAMS granules is accompanied by its own additional parameter file, designated as level 3TP.  The parameter file, contains the additional ancillary and quality information not found in the 3AT file. The data files are available in a binary record oriented format.
The Microwave Limb Sounder (MLS) Level 3AL data product consists of daily, 4 degree increment latitude-ordered vertical profiles of temperature, geopotential height, concentrations of O3, H2O, CH3CN, ClO, HNO3, and SO2. The insrument measures in the microwave spectral region at frequencies of 63, 183 and 205 GHz. MLS was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure the chemical composition of the stratosphere and mesosphere, relationship between chlorine monoxide and ozone destruction. Limb measurements were made in the altitude range between 10 and 85 km at about 2.5 km resolution. Data were collected between latitude 34S and 80N and 80S and 34N, alternating each satellite yaw cycle of about 36 days. The MLS Level 3AL data were processed with the version 5 algorithm, except H2O which is version 6, and SO2 which is version 4.

Note: H2O and O3 at 183 GHz data are available only through April 15, 1993 when the 183 GHz radiometer failed.

The MLS level 3AL product consists of 9 granules per day. A data granule is one MLS species or subtype per day.  The following subtypes are available:

 1) CH3CN - methyl cyanide            [vmr]
 2) CLO - chlorine monoxide           [vmr]
 3) H2O - water vapor                 [vmr]
 4) HNO3 - nitric acid                [vmr]
 5) O3_183 - ozone at 183 GHz         [vmr]
 6) O3_205 - ozone at 205 GHz         [vmr]
 7) SO2 - sulfur dioxide              [vmr]
 8) GPH - geopotential height         [m]
 9) TEMP - atmospheric temperature    [Kelvin]

*vmr = volume mixing ratio

MLS data are on the UARS standard pressure levels (in mbars) given by:

P(i) =  1000 * 10**(-i/6)  for i = 0, 1, 2, ...

Each of the 9 MLS granules is accompanied by an additional parameter file, designated as level 3LP.  The parameter file, contains the additional ancillary and quality information, as well as total column amounts not found in the 3AL files.  The data files are available in a binary record oriented format.
The Particle Environment Monitor (PEM) Level 3TP data product consists of daily, 65.536 second and 2.048 interval time-ordered, vertical profiles of electron and proton rates. PEM was made up of four instruments: the Atmospheric X-Ray Imaging Spectrometer (AXIS), the High Energy Particle Spectrometer (HEPS), the Medium Energy Spectrometer (MEPS), and the Vector Magnetometer (VMAG).  PEM was flown on NASA's Upper Atmosphere Research Satellite (UARS) to measure the type, amount, energy, and distribution of charged particles injected into the Earth's thermosphere, mesosphere, and stratosphere.  The PEM Level 3TP data are processed with the version 4 algorithm.

The PEM level 3TP data are a special data product, providing higher temporal resolution than the level 3AT data, with the HEPS and MEPS instrument data in separate files.  The HEPS profiles are made every 65.536 seconds, and the MEPS profiles are made every 2.048 seconds.  The PEM level 3TP data consist of 4 granules per day:
      
 1. HEPS_ELEC_ED - HEPS electron energy deposition
 2. HEPS_PROT_ED - HEPS proton energy deposition
 3. MEPS_ELEC_ED - MEPS electron energy deposition
 4. MEPS_PROT_ED - MEPS proton energy deposition
      
 The units for energy deposition rate are in [erg/cm**3/sec].  The PEM data are on the UARS standard altitude levels (in km) given by:

z(i) = 5 * i,                i <= 12
z(i) = 60 + (i - 12) * 3,    13 <= i <= 32
z(i) = 120 + (i - 32) * 10,  33 <= i <= 50

The data files are available in a binary record oriented format.
The UARS Particle Environment Monitor (PEM) level 2 Atmosphere X-Ray Imaging Spectrometer (AXIS) unit 1 daily product contains the X-ray high-resolution spectral data converted to number intensity units from the AXIS1 pixels mounted on the UARS body.  PEM was flown on the UARS spacecraft to measure the type, amount, energy, and distribution of charged particles injected into the Earth's thermosphere, mesosphere, and stratosphere. 
  
The PEM AXIS1 X-ray data cover roughly the energy range from 2 keV to 300 keV.  There are eight AXIS1 pixels mounted in the AXIS1 housing, each viewing different directions.  The AXIS1 pixels are aligned on the spacecraft to project about 45 deg toward the +x-axis direction from the Earthward pointing direction (+z-axis).  Each pixel of AXIS1 is staggered about the 45 degree direction in an every-other fashion.  Pixel 1 is closest to the center line of the spacecraft and Pixel 8 is furtherest away; however, their ground projection is dependent on the spacecraft orientation.
                        
There is one data file per day for the PEM AXIS1 product, and the temporal coverage is from Oct. 1, 1991 to Aug. 23, 2005. Spatial coverage for the AXIS1 product ranges between -80 and +80 deg latitude.  The AXIS1 data files are written in network binary format. For more information please review the PEM AXIS1 data format guide.
The UARS Particle Environment Monitor (PEM) level 2 Atmosphere X-Ray Imaging Spectrometer (AXIS) unit 2 daily product contains the X-ray high-resolution spectral data converted to number intensity units from the AXIS2 pixels mounted on the UARS body. PEM was flown on the UARS spacecraft to measure the type, amount, energy, and distribution of charged particles injected into the Earth's thermosphere, mesosphere, and stratosphere.
                        
The PEM AXIS2 X-ray data cover roughly the energy range from 2 keV to 300 keV.  There are eight AXIS2 pixels mounted in the AXIS2 housing, each viewing different directions.  The AXIS2 pixels are aligned on the spacecraft to project about 45 deg toward the +x axis direction from the Earthward pointing direction (+z axis).  Each pixel of AXIS2 is staggered about the 45 degree direction in an every-other fashion.  Pixel 1 is closest to the center line of the spacecraft and Pixel 8 is furtherest away; however, their ground projection is dependent on the spacecraft orientation.

There is one data file per day for the PEM AXIS2 product, and the temporal coverage is from Oct. 1, 1991 to Aug. 23, 2005. Spatial coverage for the AXIS2 product ranges between -80 and +80 deg latitude.  The AXIS2 data files are written in network binary format. For more information please review the PEM AXIS2 data format guide.
The Particle Environment Monitor (PEM) level 2 High-Energy Particle Spectrometer (HEPS) A daily product contains electron high-resolution spectral data converted to number intensity units from the HEPS telescopes mounted on the zenith UARS boom.  PEM was flown on the UARS spacecraft to measure the type, amount, energy, and distribution of charged particles injected into the Earth's thermosphere, mesosphere, and stratosphere.

The PEM HEPS electron data covers roughly the energy range from 35 keV to 5 MeV.  There are four telescopes mounted in different directions.  These measure -15 deg, +15 deg, +45 deg, and +90 deg with respect to the spacecraft -z-axis and along the spacecraft +x-axis.  The HEPS electron units accumulate a spectrum in 4.086 seconds.  There are two HEPS units in these data product files (labeled HEPS1 and HEPS2), each containing two telescopes (labeled telescope 1 and telescope 2).  Each telescope contains a stack of solid state crystals.  The signals from each of the crystals are combined by energy processing electronics of the instrument to yield two logical crystals or detectors, called the DE and EE detectors.  The DE detector has the rough energy range from 35 keV to 300 keV and the EE detector rough energy range is from 300 keV to 5 MeV.
                        
There is one data file per day for the PEM HEPSA product, and the temporal coverage is from Oct. 1, 1991 to Aug. 23, 2005. Spatial coverage for the HEPSA product ranges between -57 and +57 deg latitude.  The HEPSA data files are written in network binary format. For more information please review the PEM HEPSA data format guide.
The Particle Environment Monitor (PEM) level 2 Medium-Energy Particle Spectrometer (MEPS) daily product contains the electron and proton high-resolution spectral data converted to number intensity units from the MEPS sensors mounted on both the zenith and nadir UARS booms.  PEM was flown on the UARS spacecraft to measure the type, amount, energy, and distribution of charged particles injected into the Earth's thermosphere, mesosphere, and stratosphere.

The PEM MEPS data covers roughly the energy range from 1 eV - 5 eV to 32 keV, where the lower energy cutoff is determined by internal instrument protection potentials.  There are five analyzers mounted in different directions on the zenith boom, each of which contains an electron and ion sensor.  These analyzers are mounted at -23.7 deg, +6.3 deg, +21.3 deg, +36.3 deg, and +66.3 deg with respect to the spacecraft -z axis and along the spacecraft +y axis.  There are three analyzers mounted in different directions on the nadir boom, each of which contain only an electron sensor.  These analyzers are mounted at -158.7 deg, +156.3 deg, and +126.3 deg, with respect to the spacecraft -z axis and along the spacecraft +y axis.  All MEPS analyzers accumulate a spectrum in 2.046 sec.

There is one data file per day for the PEM MEPS product, and the temporal coverage is from Oct. 1, 1991 to Aug. 23, 2005. Spatial coverage for the MEPS product ranges between -57 and +57 deg latitude.  The MEPS data files are written in network binary format. For more information please review the PEM MEPS data format guide.
The Particle Environment Monitor (PEM) level 2 Vector Magnetometer (VMAG) AC daily product contains the Vector Magnetic Field AC component.  PEM was flown on the UARS spacecraft to measure the type, amount, energy, and distribution of charged particles injected into the Earth's thermosphere, mesosphere, and stratosphere.

The VMAG DC magnetic field measurements are limited to frequencies less than 2.5 Hz by an 18 db/octave antialiasing filter.  Higher frequencies are measured with a peak detector and are the Vector Magnetic Field AC component.  The AC value is derived from each vector field component where the sensor output is pass band filtered from 2.5 to 50 Hz.  The resultant signal is then half wave rectified and passed to an RC circuit with a time constant of 4.7 s.  The voltage across the RC circuit is the peak detector output which therefore represents the peak positive amplitude of the 2.5-50 Hz filtered sensor output occurring during the previous 5 seconds; however, the peak detector is determined at a rate of about every second (the VMAG AC data has been adjusted for this time offset).  The X and Z peak detectors have full scale of 1oo nT peak to peak (= 5 Volts) and the Y peak detector has a full scale of 10 nT peak to peak (= 5 Volts).  The analog 0 to 5 Volts peak detector outputs are sent directly to the PEM central electronics package where they are digitized into a 265 binary word.  This is the raw value in the data.  No in-flight calibration of the AC peak detection electronics is provided. The VMAG unit is located on the zenith boom of UARS.
                        
There is one data file per day for the PEM VMAG AC product, and the temporal coverage is from Oct. 1, 1991 to Aug. 23, 2005. Spatial coverage for the VMAG AC product ranges between -57 and +57 deg latitude.  The VMAG AC data files are written in network binary format. For more information please review the PEM VMAG AC data format guide.
The Particle Environment Monitor (PEM) level 2 Vector Magnetometer (VMAG) DC daily product contains the Vector Magnetic Field component, UARS Aspect Magnetometers component, and UARS Torquer Bars component data converted to nanoTesla and milliAmp units.  PEM was flown on the UARS spacecraft to measure the type, amount, energy, and distribution of charged particles injected into the Earth's thermosphere, mesosphere, and stratosphere.

The VMAG DC data range is from -65000 nT to +65000 nT, with 2 nT resolution.  Measurements were from the three vector components, X, Y, and Z with respect to the UARS spacecraft orientation.  The VMAG sensor consists of three orthogonal ring-core fluxgate sensors, surrounded by a thermal sphere.  Stray magnetic fields from the spacecraft can be accounted for by use of the UARS torquer bar currents.  The VMAG unit is located on the zenith boom of UARS. The UARS aspect magnetometers and torquer bars are located on the body of the UARS spacecraft.
                        
There is one data file per day for the PEM VMAG DC product, and the temporal coverage is from Oct. 1, 1991 to Aug. 23, 2005. Spatial coverage for the VMAG DC product ranges between -57 and +57 deg latitude.  The VMAG DC data files are written in network binary format. For more information please review the PEM VMAG DC data format guide.
The Solar Ultraviolet Spectral Irradiance Monitor (SUSIM) Level 3BS data product consists of daily, 1 nm resolution, solar spectral irradiances and selected solar parameters.  The instrument consisted of two identical double-dispersion scanning spectrometers, seven detectors (5 photodiodes, 2 photon counters), and solar ultraviolet calibration sources measuring in the wavelength range from 110 to 410 nm.  One spectrometer measured the solar disk while the other was for calibration using high-precision deuterium lamps calibrated by NIST.  SUSIM was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure the full disk solar irradiance with high precision and accuracy to follow short-term (minutes to hours), intermediate-term (days to weeks), and long-term (11 year sunspot, and 22 year solar magnetic field cycles) variations in the solar output.

The SUSIM Level 3BS data consists of 1 granule per day. The data are normalized to an earth-sun distance of 1 AU, and instrument degradation have been applied to the data. Included with the primary solar spectral irradiance values are the following solar indices: Lyman alpha, O-I (130 nm), C-II (134 nm) and C-IV (155 nm), Al Edge, and core-wing ratios of Mg-I and Mg-II.  The data files are available in a binary record oriented format.
The Solar-Stellar Irradiance Comparison Experiment (SOLSTICE) Level 3BS data product consists of daily, 1 nm resolution, solar spectral irradiances and selected solar parameters.  The instrument was a three-channel ultraviolet spectrometer that measured the magnitude of solar and spectral irradiances in the wavelength range from 119 to 420 nm.  The design of the instrument allowed for observations of both the sun and bright blue stars, whose spectra is assumed to be constant. SOLSTICE was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure the full disk solar irradiance with high precision and accuracy to follow short-term (minutes to hours), intermediate-term (days to weeks), and long-term (11 year sunspot, and 22 year solar magnetic field cycles) variations in the solar output.

The SOLSTICE Level 3BS data consists of 1 granule per day. The data are normalized to an earth-sun distance of 1 AU, and instrument degradation have been applied to the data. Included with the primary solar spectral irradiance values are daily average integrated intensities of Lyman alpha (121.6 nm), O-I (130.4 nm), C-IV (154.8 nm) and C-I (156.1 and 165.6 nm), and core-wing ratios of Mg-II (280.0 nm) and Ca-II (393.3 nm), as well as Carrington latitude and longitudes.  The data files are available in a binary record oriented format.
The Wind Imaging Interferometer (WINDII) Level 3AL data product consists of daily, 4 degree increment latitude-ordered vertical profiles of meridional and zonal wind components, and temperature. The instrument was a Michelson interferometer designed to measure Doppler shifts of spectral lines in the visible between 550 and 780 nm.  WINDII was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure wind, temperature and emission rates in the mesosphere and thermosphere between 80 and 300 km at about 5 km resolution. Data were collected between latitude 40S and 72N and 72S and 40N, alternating each satellite yaw cycle of about 36 days. The WINDII Level 3AL data were processed with the version 11 algorithm.
      
The WINDII level 3AL product consists of 3 granules per day. A data granule is one WINDII species or subtype per day.  The following subtypes are available:

 1) MERWIN_A - meridional wind component on altitude grid  [m/s]
 2) ZONWIN_A - zonal wind component on altitude grid       [m/s]
 3) TEMP - temperature on altitude grid                    [Kelvin]

WINDII data are on the UARS standard altitude levels (in km) given by:

z(i) = 5*i                 for  1 <= i <= 12
z(i) = 60 + (i-12)*3       for 13 <= i <= 32
z(i) = 120 + (i-32)*5      for 33 <= i <= 88
      
Each of the 3 WINDII granules is accompanied by an additional parameter file, designated as level 3LP.  The parameter file, contains additional ancillary and quality information not found in the 3AL files.  The data files are available in a binary record oriented format.
The Wind Imaging Interferometer (WINDII) Level 3AT data product consists of daily, 65.536 second interval time-ordered vertical profiles of meridional and zonal wind components, and temperature. The instrument was a Michelson interferometer designed to measure Doppler shifts of spectral lines in the visible between 550 and 780 nm.  WINDII was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure wind, temperature and emission rates in the mesosphere and thermosphere between 80 and 300 km at about 5 km resolution. Data were collected between latitude 40S and 72N and 72S and 40N, alternating each satellite yaw cycle of about 36 days. The WINDII Level 3AT data were processed with the version 11 algorithm.

The WINDII level 3AT product consists of 3 granules per day. A data granule is one WINDII species or subtype per day.  The following subtypes are available:

 1) MERWIN_A - meridional wind component on altitude grid  [m/s]
 2) ZONWIN_A - zonal wind component on altitude grid       [m/s]
 3) TEMP - temperature on altitude grid                    [Kelvin]

WINDII data are on the UARS standard altitude levels (in km) given by:

z(i) = 5*i                 for  1 <= i <= 12
z(i) = 60 + (i-12)*3       for 13 <= i <= 32
z(i) = 120 + (i-32)*5      for 33 <= i <= 88

Each of the 3 WINDII granules is accompanied by an additional parameter file, designated as level 3TP.  The parameter file, contains additional ancillary and quality information not found in the 3AT files.  The data files are available in a binary record oriented format.
UAVSAR Repeat Pass Interferometry Scene
UAVSAR Repeat Pass Interferometry Scene
UAVSAR Repeat Pass Interferometry Scene
UAVSAR PolSAR Scene
UAVSAR PolSAR Scene
UAVSAR PolSAR Scene
The Urban Landsat: Cities from Space dataset contains images for 66 urban areas and the raw, 

unerlying data for 28 of these places. Each image shows a Landsat false color composite in UTM projection. The R/G/B layers 

correspond to TM/ETM+ bands 7/4/2. Each pixel is 30x30 meters in area and most images are 30x30 km in area. A 2% linear stretch has 

been applied to the images. The Landsat data files contain six reflected bands of calibrated exoatmospheric reflectance stored in 

ENVI band sequential (BSQ) format. Geographic coordinates are included in the header file. The data file contains 1000x1000x6 4 byte 

floating point numbers as indicated in the header. This dataset is distributed by the Socioeconomic Data and Applications Center 

(SEDAC) at Center for International Earth Science Information Network (CIESIN), Columbia University.
The Urban Landsat: Cities from Space dataset contains images for 66 urban areas and the raw, 

unerlying data for 28 of these places. Each image shows a Landsat false color composite in UTM projection. The R/G/B layers 

correspond to TM/ETM+ bands 7/4/2. Each pixel is 30x30 meters in area and most images are 30x30 km in area. A 2% linear stretch has 

been applied to the images. The Landsat data files contain six reflected bands of calibrated exoatmospheric reflectance stored in 

ENVI band sequential (BSQ) format. Geographic coordinates are included in the header file. The data file contains 1000x1000x6 4 byte 

floating point numbers as indicated in the header. This dataset is distributed by the Socioeconomic Data and Applications Center 

(SEDAC) at Center for International Earth Science Information Network (CIESIN), Columbia University.
The Urban Landsat: Cities from Space dataset contains images for 66 urban areas and the raw, 

unerlying data for 28 of these places. Each image shows a Landsat false color composite in UTM projection. The R/G/B layers 

correspond to TM/ETM+ bands 7/4/2. Each pixel is 30x30 meters in area and most images are 30x30 km in area. A 2% linear stretch has 

been applied to the images. The Landsat data files contain six reflected bands of calibrated exoatmospheric reflectance stored in 

ENVI band sequential (BSQ) format. Geographic coordinates are included in the header file. The data file contains 1000x1000x6 4 byte 

floating point numbers as indicated in the header. This dataset is distributed by the Socioeconomic Data and Applications Center 

(SEDAC) at Center for International Earth Science Information Network (CIESIN), Columbia University.
The Lightning Imaging Sensor (LIS) Science Computing Facility (SCF) generates a cloud-to-ground lightning product from the data collected from the U.S. National Lightning Detection Network, a commercial lightning detection network operated by Global Atmospherics, Inc. (GAI), formerly Geomet Data Services. The lightning products are made by binning the number of  flashes that occur over a 15 min period to a pixel (pixel is approximately 8 km by 8 km). The data set begins on July 19, 1994 and continues through the present.  This data is distributed by the Global Hydrology Resource Center (GHRC).
The Global Hydrology Resource Center generates a cloud-to-ground lightning product from the data collected from the U.S. National Lightning Detection Network, a commercial lightning detection network operated by Global Atmospherics, Inc. (GAI), formerly Geomet Data Services. The daily products are produced by binning the number of flashes occurring in each pixel (pixel is approximately 8 km by 8 km) during a 24 hr period (00 UTC to 00 UTC). The data set begins on July 8, 1994 and continues through the present.
The U.S. National Lightning Detection Network is a commercial lightning detection network operated by Vaisala. A network of over 100 antennae are connected to a central processor that records the time, polarity, signal strength, and number of strokes of each cloud-to-ground lightning flash detected over the United States starting from Jan. 1, 1995 to present.
Measurements of leaf area index and biomass of different canopy components
Measurements of leaf area index and biomass of different canopy components
ABSTRACT: Measurements of leaf area index and biomass of different canopy components
Species composition data, by site and date
Species composition data, by site and date
ABSTRACT: Species composition data, by site and date
LTER species names, codes, types, and other reference information
LTER species names, codes, types, and other reference information
ABSTRACT: LTER species names, codes, types, and other reference information
An integrated input data set for ecosystem and vegetation modeling for the conterminous United States: Georeferencing
An integrated input data set for ecosystem and vegetation modeling for the conterminous United States: Georeferencing
ABSTRACT: An integrated input data set for ecosystem and vegetation modeling for the conterminous United States: Georeferencing
The VEMAP 1: Model Input Database CD-ROM ISO image contains long-term data that were used as input in comparing models during Phase 1 of the Vegetation Ecosystem Modeling and Analysis Project. Compiled and model-generated data sets of long-term mean climate, soils, vegetation, and climate change scenarios for the conterminous United States.  Dates of the data sets range between 1895 and 1996.  The data are gridded at 0.5 degree latitude by 0.5 degree longitude.
The VEMAP 1: Model Input Database CD-ROM ISO image contains long-term data that were used as input in comparing models during Phase 1 of the Vegetation Ecosystem Modeling and Analysis Project. Compiled and model-generated data sets of long-term mean climate, soils, vegetation, and climate change scenarios for the conterminous United States.  Dates of the data sets range between 1895 and 1996.  The data are gridded at 0.5 degree latitude by 0.5 degree longitude.
ABSTRACT: The VEMAP 1: Model Input Database CD-ROM ISO image contains long-term data that were used as input in comparing models during Phase 1 of the Vegetation Ecosystem Modeling and Analysis Project. Compiled and model-generated data sets of long-term mean climate, soils, vegetation, and climate change scenarios for the conterminous United States.  Dates of the data sets range between 1895 and 1996.  The data are gridded at 0.5 degree latitude by 0.5 degree longitude.
The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) was a multi-institutional, international effort addressing the response of biogeography and biogeochemistry to environmental variability in climate and other drivers in both space and time domains. The objectives of VEMAP are the intercomparison of biogeochemistry models and vegetation type distribution models (biogeography models) and determination of their sensitivity to changing climate, elevated atmospheric carbon dioxide concentrations, and other sources of altered forcing.Selected variable output results from the VEMAP Phase I modeling exercise are now available for several combinations of biogeochemistry and biogeography models and climate change scenarios through the ORNL DAAC. For a description of the models and climate scenarios employed in the VEMAP 1 project and a discussion of the results please refer to the following publication: VEMAP Members. 1995. Vegetation/Ecosystem Modeling and Analysis Project: Comparing biogeography and biogeochemistry models in a continental-scale study of terrestrial ecosystem responses to climate change and CO2 doubling. Global Biogeochem. Cycles 9:407-437.
The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) was a multi-institutional, international effort addressing the response of biogeography and biogeochemistry to environmental variability in climate and other drivers in both space and time domains. The objectives of VEMAP are the intercomparison of biogeochemistry models and vegetation type distribution models (biogeography models) and determination of their sensitivity to changing climate, elevated atmospheric carbon dioxide concentrations, and other sources of altered forcing.Selected variable output results from the VEMAP Phase I modeling exercise are now available for several combinations of biogeochemistry and biogeography models and climate change scenarios through the ORNL DAAC. For a description of the models and climate scenarios employed in the VEMAP 1 project and a discussion of the results please refer to the following publication: VEMAP Members. 1995. Vegetation/Ecosystem Modeling and Analysis Project: Comparing biogeography and biogeochemistry models in a continental-scale study of terrestrial ecosystem responses to climate change and CO2 doubling. Global Biogeochem. Cycles 9:407-437.
ABSTRACT: The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) was a multi-institutional, international effort addressing the response of biogeography and biogeochemistry to environmental variability in climate and other drivers in both space and time domains. The objectives of VEMAP are the intercomparison of biogeochemistry models and vegetation type distribution models (biogeography models) and determination of their sensitivity to changing climate, elevated atmospheric carbon dioxide concentrations, and other sources of altered forcing.Selected variable output results from the VEMAP Phase I modeling exercise are now available for several combinations of biogeochemistry and biogeography models and climate change scenarios through the ORNL DAAC. For a description of the models and climate scenarios employed in the VEMAP 1 project and a discussion of the results please refer to the following publication: VEMAP Members. 1995. Vegetation/Ecosystem Modeling and Analysis Project: Comparing biogeography and biogeochemistry models in a continental-scale study of terrestrial ecosystem responses to climate change and CO2 doubling. Global Biogeochem. Cycles 9:407-437.
An integrated input data set for ecosystem and vegetation modeling for the conterminous United States: Climate Scenarios
An integrated input data set for ecosystem and vegetation modeling for the conterminous United States: Climate Scenarios
ABSTRACT: An integrated input data set for ecosystem and vegetation modeling for the conterminous United States: Climate Scenarios
An integrated input data set for ecosystem and vegetation modeling for the conterminous United States: Climate
An integrated input data set for ecosystem and vegetation modeling for the conterminous United States: Climate
ABSTRACT: An integrated input data set for ecosystem and vegetation modeling for the conterminous United States: Climate
An integrated input data set for ecosystem and vegetation modeling for the conterminous United States: Vegetation
An integrated input data set for ecosystem and vegetation modeling for the conterminous United States: Vegetation
ABSTRACT: An integrated input data set for ecosystem and vegetation modeling for the conterminous United States: Vegetation
An integrated input data set for ecosystem and vegetation modeling for the conterminous United States: Site Files
An integrated input data set for ecosystem and vegetation modeling for the conterminous United States: Site Files
ABSTRACT: An integrated input data set for ecosystem and vegetation modeling for the conterminous United States: Site Files
An integrated input data set for ecosystem and vegetation modeling for the conterminous United States: Soil
An integrated input data set for ecosystem and vegetation modeling for the conterminous United States: Soil
ABSTRACT: An integrated input data set for ecosystem and vegetation modeling for the conterminous United States: Soil
Phase 2 of the VEMAP Project developed historical (1895-1993) gridded data sets of climate (temperature, precipitation, solar radiation, humidity, and wind speed) and projected (1994-2100) gridded annual and monthly climate data sets using output from two climate system models [CCCma (Canadian Centre for Climate Modeling and Analysis) and Hadley Centre models]. Two Phase 2 model experiments were run.  First, a set of selected  biogeochemical models and coupled biogeochemical-biogeographical models were run from 1895 to 1993 to compare model responses to the historical time series and current ecosystem biogeochemistry.  Second, these same models were run on the projected 1994 to 2100 data to compare their ecological responses to transient scenarios of climate and atmospheric CO2 change. Model runs were performed for daily, monthly, and annual gridded data sets. The output of the annual model runs in VEMAP grid format are contained in this data set. The models investigated included five biogeochemical cycling models, which simulate plant production and nutrient cycles.
Phase 2 of the VEMAP Project developed historical (1895-1993) gridded data sets of climate (temperature, precipitation, solar radiation, humidity, and wind speed) and projected (1994-2100) gridded annual and monthly climate data sets using output from two climate system models [CCCma (Canadian Centre for Climate Modeling and Analysis) and Hadley Centre models]. Two Phase 2 model experiments were run.  First, a set of selected  biogeochemical models and coupled biogeochemical-biogeographical models were run from 1895 to 1993 to compare model responses to the historical time series and current ecosystem biogeochemistry.  Second, these same models were run on the projected 1994 to 2100 data to compare their ecological responses to transient scenarios of climate and atmospheric CO2 change. Model runs were performed for daily, monthly, and annual gridded data sets. The output of the annual model runs in VEMAP grid format are contained in this data set. The models investigated included five biogeochemical cycling models, which simulate plant production and nutrient cycles.
ABSTRACT: Phase 2 of the VEMAP Project developed historical (1895-1993) gridded data sets of climate (temperature, precipitation, solar radiation, humidity, and wind speed) and projected (1994-2100) gridded annual and monthly climate data sets using output from two climate system models [CCCma (Canadian Centre for Climate Modeling and Analysis) and Hadley Centre models]. Two Phase 2 model experiments were run.  First, a set of selected  biogeochemical models and coupled biogeochemical-biogeographical models were run from 1895 to 1993 to compare model responses to the historical time series and current ecosystem biogeochemistry.  Second, these same models were run on the projected 1994 to 2100 data to compare their ecological responses to transient scenarios of climate and atmospheric CO2 change. Model runs were performed for daily, monthly, and annual gridded data sets. The output of the annual model runs in VEMAP grid format are contained in this data set. The models investigated included five biogeochemical cycling models, which simulate plant production and nutrient cycles.
Phase 2 developed historical (1895-1993) gridded data sets of climate (temperature, precipitation, solar radiation, humidity, and wind speed) and projected (1994-2100) gridded annual and monthly climate data sets using output from two climate system models [CCCma (Canadian Centre for Climate Modeling and Analysis) and Hadley Centre models]. Two Phase 2 model experiments were run. First, a set of selected  biogeochemical models and coupled biogeochemical-biogeographical models were run from 1895 to 1993 to compare model responses to the historical time series and current ecosystem biogeochemistry.  Second, these same models were run on the projected 1994 to 2100 data to compare their ecological responses to transient scenarios of climate and atmospheric CO2 change. Model runs were performed for daily, monthly, and annual gridded data sets. The output of the monthly model runs in VEMAP grid format are contained in this data set.
Phase 2 developed historical (1895-1993) gridded data sets of climate (temperature, precipitation, solar radiation, humidity, and wind speed) and projected (1994-2100) gridded annual and monthly climate data sets using output from two climate system models [CCCma (Canadian Centre for Climate Modeling and Analysis) and Hadley Centre models]. Two Phase 2 model experiments were run. First, a set of selected  biogeochemical models and coupled biogeochemical-biogeographical models were run from 1895 to 1993 to compare model responses to the historical time series and current ecosystem biogeochemistry.  Second, these same models were run on the projected 1994 to 2100 data to compare their ecological responses to transient scenarios of climate and atmospheric CO2 change. Model runs were performed for daily, monthly, and annual gridded data sets. The output of the monthly model runs in VEMAP grid format are contained in this data set.
ABSTRACT: Phase 2 developed historical (1895-1993) gridded data sets of climate (temperature, precipitation, solar radiation, humidity, and wind speed) and projected (1994-2100) gridded annual and monthly climate data sets using output from two climate system models [CCCma (Canadian Centre for Climate Modeling and Analysis) and Hadley Centre models]. Two Phase 2 model experiments were run. First, a set of selected  biogeochemical models and coupled biogeochemical-biogeographical models were run from 1895 to 1993 to compare model responses to the historical time series and current ecosystem biogeochemistry.  Second, these same models were run on the projected 1994 to 2100 data to compare their ecological responses to transient scenarios of climate and atmospheric CO2 change. Model runs were performed for daily, monthly, and annual gridded data sets. The output of the monthly model runs in VEMAP grid format are contained in this data set.
Data sets of transient climate change scenarios based on coupled atmosphere-ocean general circulation model (AOGCM) transient climate experiments with transient greenhouse gas and sulfate aerosol forcing.
Data sets of transient climate change scenarios based on coupled atmosphere-ocean general circulation model (AOGCM) transient climate experiments with transient greenhouse gas and sulfate aerosol forcing.
ABSTRACT: Data sets of transient climate change scenarios based on coupled atmosphere-ocean general circulation model (AOGCM) transient climate experiments with transient greenhouse gas and sulfate aerosol forcing.
An integrated input data set for ecosystem and vegetation modeling for the conterminous United States.   The data set is a ~100 year fully gridded annual time series of climate that includes realistic interannual variability.
An integrated input data set for ecosystem and vegetation modeling for the conterminous United States.   The data set is a ~100 year fully gridded annual time series of climate that includes realistic interannual variability.
ABSTRACT: An integrated input data set for ecosystem and vegetation modeling for the conterminous United States.   The data set is a ~100 year fully gridded annual time series of climate that includes realistic interannual variability.
VEMAP Phase 2 has developed a number of transient climate change scenarios based on coupled atmosphere-ocean general circulation model (AOGCM) transient climate experiments.  The purpose of these scenarios is to reflect time-dependent changes in surface climate from AOGCMs in terms of both (1) long-term trends and (2) changes in multiyear (3-5 yr) to decadal variability, such as El Nino/Southern Oscillation (ENSO).
VEMAP Phase 2 has developed a number of transient climate change scenarios based on coupled atmosphere-ocean general circulation model (AOGCM) transient climate experiments.  The purpose of these scenarios is to reflect time-dependent changes in surface climate from AOGCMs in terms of both (1) long-term trends and (2) changes in multiyear (3-5 yr) to decadal variability, such as El Nino/Southern Oscillation (ENSO).
ABSTRACT: VEMAP Phase 2 has developed a number of transient climate change scenarios based on coupled atmosphere-ocean general circulation model (AOGCM) transient climate experiments.  The purpose of these scenarios is to reflect time-dependent changes in surface climate from AOGCMs in terms of both (1) long-term trends and (2) changes in multiyear (3-5 yr) to decadal variability, such as El Nino/Southern Oscillation (ENSO).
VEMAP Phase 2 has developed a data set of ~100-year gridded monthly and daily time series of climate for the conterminous United States that includes realistic interannual variability.  This data set has been used to compare time-dependent ecological responses of biogeochemical and coupled biogeochemical-biogeographical models to historical time series and projected scenarios of climate, atmospheric CO2, and N-Deposition, and N-Deposition
VEMAP Phase 2 has developed a data set of ~100-year gridded monthly and daily time series of climate for the conterminous United States that includes realistic interannual variability.  This data set has been used to compare time-dependent ecological responses of biogeochemical and coupled biogeochemical-biogeographical models to historical time series and projected scenarios of climate, atmospheric CO2, and N-Deposition, and N-Deposition
ABSTRACT: VEMAP Phase 2 has developed a data set of ~100-year gridded monthly and daily time series of climate for the conterminous United States that includes realistic interannual variability.  This data set has been used to compare time-dependent ecological responses of biogeochemical and coupled biogeochemical-biogeographical models to historical time series and projected scenarios of climate, atmospheric CO2, and N-Deposition, and N-Deposition
Data sets of transient climate change scenarios based on coupled atmosphere-ocean general circulation model (AOGCM) transient climate experiments with transient greenhouse gas and sulfate aerosol forcing.
Data sets of transient climate change scenarios based on coupled atmosphere-ocean general circulation model (AOGCM) transient climate experiments with transient greenhouse gas and sulfate aerosol forcing.
ABSTRACT: Data sets of transient climate change scenarios based on coupled atmosphere-ocean general circulation model (AOGCM) transient climate experiments with transient greenhouse gas and sulfate aerosol forcing.
An integrated input data set for ecosystem and vegetation modeling for the conterminous United States. The data set is a ~100 year gridded monthly time series of climate that includes realistic interannual variability.
An integrated input data set for ecosystem and vegetation modeling for the conterminous United States. The data set is a ~100 year gridded monthly time series of climate that includes realistic interannual variability.
ABSTRACT: An integrated input data set for ecosystem and vegetation modeling for the conterminous United States. The data set is a ~100 year gridded monthly time series of climate that includes realistic interannual variability.
Visible/NIR reflectance spectra data for both fresh and dry leaf samples were collected to determine the relationship of foliar chemical concentrations with reflectance.
Visible/NIR reflectance spectra data for both fresh and dry leaf samples were collected to determine the relationship of foliar chemical concentrations with reflectance.
ABSTRACT: Visible/NIR reflectance spectra data for both fresh and dry leaf samples were collected to determine the relationship of foliar chemical concentrations with reflectance.
ABSTRACT: The original objectives of the long-term vegetation survey of Walker Branch Watershed in eastern Tennessee (WBW; Curlin and Nelson 1968) was to quantify the standing crop of vegetation through time including measures of tree/plant size distribution, species composition, above-ground biomass, and chemical balance. Field studies of permanent vegetation plots using one sample design were conducted over a 30-year period (1967 to 1997), and observations continue with funding from the U.S. Department of Energy's Program for Ecosystem Research. This data set consists of long-term measurements of diameter at breast height (DBH) determined on randomly located permanent inventory plots within the 4 different vegetation types located on WBW in 1967.  In addition, the lignin to nitrogen content in leaves (g lignin / g N of leaf tissue) for species present in WBW was obtained from the literature. More information can be found at: http://walkerbranch.ornl.gov/.  Funding for long-term data collection efforts on Walker Branch was provided by the U.S. Department of Energy (DOE), Office of Science, Biological and Environmental Research (BER), as a part of the Program for Ecosystem Research (PER).
ABSTRACT: The original objectives of the long-term vegetation survey of Walker Branch Watershed in eastern Tennessee (WBW; Curlin and Nelson 1968) was to quantify the standing crop of vegetation through time including measures of tree/plant size distribution, species composition, above-ground biomass, and chemical balance. Field studies of permanent vegetation plots using one sample design were conducted over a 30-year period (1967 to 1997), and observations continue with funding from the U.S. Department of Energy's Program for Ecosystem Research. This data set consists of long-term measurements of diameter at breast height (DBH) determined on randomly located permanent inventory plots within the 4 different vegetation types located on WBW in 1967.  In addition, the lignin to nitrogen content in leaves (g lignin / g N of leaf tissue) for species present in WBW was obtained from the literature. More information can be found at: http://walkerbranch.ornl.gov/.  Funding for long-term data collection efforts on Walker Branch was provided by the U.S. Department of Energy (DOE), Office of Science, Biological and Environmental Research (BER), as a part of the Program for Ecosystem Research (PER).
ABSTRACT: The original objectives of the long-term vegetation survey of Walker Branch Watershed in eastern Tennessee (WBW; Curlin and Nelson 1968) was to quantify the standing crop of vegetation through time including measures of tree/plant size distribution, species composition, above-ground biomass, and chemical balance. Field studies of permanent vegetation plots using one sample design were conducted over a 30-year period (1967 to 1997), and observations continue with funding from the U.S. Department of Energy's Program for Ecosystem Research. This data set consists of long-term measurements of diameter at breast height (DBH) determined on randomly located permanent inventory plots within the 4 different vegetation types located on WBW in 1967.  In addition, the lignin to nitrogen content in leaves (g lignin / g N of leaf tissue) for species present in WBW was obtained from the literature. More information can be found at: http://walkerbranch.ornl.gov/.  Funding for long-term data collection efforts on Walker Branch was provided by the U.S. Department of Energy (DOE), Office of Science, Biological and Environmental Research (BER), as a part of the Program for Ecosystem Research (PER).
The Peace-Athabasca Delta (PAD) is a hydrologically complex and ecologically diverse freshwater delta formed by the confluence of the Peace, Athabasca, and Birch Rivers near the western end of Lake Athabasca, Alberta, Canada. This data set includes 3 comma-delimited ASCII files: one containing water quality data and site characteristics from June and July 2010, a second containing water quality data and site characteristics for June and July 2011, and a third containing spectral reflectance of the water surface for 2011. The 2010 data file has measurements from 62 unique sites, the majority of which were revisited in 2011. Both of the 2011 data files have measurements from 99 unique sites visited 1-4 times.
The Peace-Athabasca Delta (PAD) is a hydrologically complex and ecologically diverse freshwater delta formed by the confluence of the Peace, Athabasca, and Birch Rivers near the western end of Lake Athabasca, Alberta, Canada. This data set includes 3 comma-delimited ASCII files: one containing water quality data and site characteristics from June and July 2010, a second containing water quality data and site characteristics for June and July 2011, and a third containing spectral reflectance of the water surface for 2011. The 2010 data file has measurements from 62 unique sites, the majority of which were revisited in 2011. Both of the 2011 data files have measurements from 99 unique sites visited 1-4 times.
ABSTRACT: The Peace-Athabasca Delta (PAD) is a hydrologically complex and ecologically diverse freshwater delta formed by the confluence of the Peace, Athabasca, and Birch Rivers near the western end of Lake Athabasca, Alberta, Canada. This data set includes 3 comma-delimited ASCII files: one containing water quality data and site characteristics from June and July 2010, a second containing water quality data and site characteristics for June and July 2011, and a third containing spectral reflectance of the water surface for 2011. The 2010 data file has measurements from 62 unique sites, the majority of which were revisited in 2011. Both of the 2011 data files have measurements from 99 unique sites visited 1-4 times.
Wind profile data from NOAA LIDAR measurements
Wind profile data from NOAA LIDAR measurements
ABSTRACT: Wind profile data from NOAA LIDAR measurements
Wind profile data derived from Brutsaert's radiosonde measurements
Wind profile data derived from Brutsaert's radiosonde measurements
ABSTRACT: Wind profile data derived from Brutsaert's radiosonde measurements
Estimates of the woody biomass density and pools were derived at the county scale of resolution of all forests of the eastern United States using new approaches for converting inventoried wood volume to estimates of above and belowground biomass.
Estimates of the woody biomass density and pools were derived at the county scale of resolution of all forests of the eastern United States using new approaches for converting inventoried wood volume to estimates of above and belowground biomass.
ABSTRACT: Estimates of the woody biomass density and pools were derived at the county scale of resolution of all forests of the eastern United States using new approaches for converting inventoried wood volume to estimates of above and belowground biomass.
Sun photometer measurements of the direct (collimated) solar radiation provide information to calculate the columnar aerosol optical depth (AOD). AOD can be used to compute columnar water vapor (Precipitable Water) and estimate the aerosol size using the Angstrom parameter relationship. Two data versions (Versions 1 and 2) and three quality levels (Levels 1.0, 1.5, 2.0) exist for each product. While Levels 1.0 and 1.5 are provided in near real-time, the 12-month or longer delay (due to final calibration and manual inspection) ensures that the highest quality data can be found in Version 2, Level 2.0 data products. Level 2: pre- and post-field calibration applied, automatically cloud cleared and manually inspected.
Sun photometer measurements of the direct (collimated) solar radiation provide information to calculate the columnar aerosol optical depth (AOD). AOD can be used to compute columnar water vapor (Precipitable Water) and estimate the aerosol size using the Angstrom parameter relationship. Two data versions (Versions 1 and 2) and three quality levels (Levels 1.0, 1.5, 2.0) exist for each product. While Levels 1.0 and 1.5 are provided in near real-time, the 12-month or longer delay (due to final calibration and manual inspection) ensures that the highest quality data can be found in Version 2, Level 2.0 data products. Level 2: pre- and post-field calibration applied, automatically cloud cleared and manually inspected.
AERONET inversion code provides aerosoloptical properties in the total atmospheric column derived from the direct and diffuse radiation measured byAERONETCimel sun/sky-radiometers. AERONET inversion developmentand researchactivitiesare described in the papers by Dubovik and King, [2000], Dubovik et al. [2000], Dubovik et al. [2002a], Dubovik et al. [2002b], Dubovik et al., [2006a], Sinyuk et al. [2006]. The Version 2(V2)inversion (or retrieval)products are summarized below. These products are available through the internal analysis system&#x0022;demonstrat&#x0022; and the AERONET website. Adetailed description of V2 AERONET retrieval will be provided in the paper by Dubovik et al., [2006b].
AERONET inversion code provides aerosoloptical properties in the total atmospheric column derived from the direct and diffuse radiation measured byAERONETCimel sun/sky-radiometers. AERONET inversion developmentand researchactivitiesare described in the papers by Dubovik and King, [2000], Dubovik et al. [2000], Dubovik et al. [2002a], Dubovik et al. [2002b], Dubovik et al., [2006a], Sinyuk et al. [2006]. The Version 2(V2)inversion (or retrieval)products are summarized below. These products are available through the internal analysis system&#x0022;demonstrat&#x0022; and the AERONET website. Adetailed description of V2 AERONET retrieval will be provided in the paper by Dubovik et al., [2006b].
AERONET inversion code provides aerosoloptical properties in the total atmospheric column derived from the direct and diffuse radiation measured byAERONETCimel sun/sky-radiometers. AERONET inversion developmentand researchactivitiesare described in the papers by Dubovik and King, [2000], Dubovik et al. [2000], Dubovik et al. [2002a], Dubovik et al. [2002b], Dubovik et al., [2006a], Sinyuk et al. [2006]. The Version 2(V2)inversion (or retrieval)products are summarized below. These products are available through the internal analysis system&#x0022;demonstrat&#x0022; and the AERONET website. Adetailed description of V2 AERONET retrieval will be provided in the paper by Dubovik et al., [2006b].
AERONET inversion code provides aerosoloptical properties in the total atmospheric column derived from the direct and diffuse radiation measured byAERONETCimel sun/sky-radiometers. AERONET inversion developmentand researchactivitiesare described in the papers by Dubovik and King, [2000], Dubovik et al. [2000], Dubovik et al. [2002a], Dubovik et al. [2002b], Dubovik et al., [2006a], Sinyuk et al. [2006]. The Version 2(V2)inversion (or retrieval)products are summarized below. These products are available through the internal analysis system&#x0022;demonstrat&#x0022; and the AERONET website. Adetailed description of V2 AERONET retrieval will be provided in the paper by Dubovik et al., [2006b].
AERONET inversion code provides aerosoloptical properties in the total atmospheric column derived from the direct and diffuse radiation measured byAERONETCimel sun/sky-radiometers. AERONET inversion developmentand researchactivitiesare described in the papers by Dubovik and King, [2000], Dubovik et al. [2000], Dubovik et al. [2002a], Dubovik et al. [2002b], Dubovik et al., [2006a], Sinyuk et al. [2006]. The Version 2(V2)inversion (or retrieval)products are summarized below. These products are available through the internal analysis system&#x0022;demonstrat&#x0022; and the AERONET website. Adetailed description of V2 AERONET retrieval will be provided in the paper by Dubovik et al., [2006b].
AERONET inversion code provides aerosoloptical properties in the total atmospheric column derived from the direct and diffuse radiation measured byAERONETCimel sun/sky-radiometers. AERONET inversion developmentand researchactivitiesare described in the papers by Dubovik and King, [2000], Dubovik et al. [2000], Dubovik et al. [2002a], Dubovik et al. [2002b], Dubovik et al., [2006a], Sinyuk et al. [2006]. The Version 2(V2)inversion (or retrieval)products are summarized below. These products are available through the internal analysis system&#x0022;demonstrat&#x0022; and the AERONET website. Adetailed description of V2 AERONET retrieval will be provided in the paper by Dubovik et al., [2006b].
AERONET inversion code provides aerosoloptical properties in the total atmospheric column derived from the direct and diffuse radiation measured byAERONETCimel sun/sky-radiometers. AERONET inversion developmentand researchactivitiesare described in the papers by Dubovik and King, [2000], Dubovik et al. [2000], Dubovik et al. [2002a], Dubovik et al. [2002b], Dubovik et al., [2006a], Sinyuk et al. [2006]. The Version 2(V2)inversion (or retrieval)products are summarized below. These products are available through the internal analysis system&#x0022;demonstrat&#x0022; and the AERONET website. Adetailed description of V2 AERONET retrieval will be provided in the paper by Dubovik et al., [2006b].
AERONET inversion code provides aerosoloptical properties in the total atmospheric column derived from the direct and diffuse radiation measured byAERONETCimel sun/sky-radiometers. AERONET inversion developmentand researchactivitiesare described in the papers by Dubovik and King, [2000], Dubovik et al. [2000], Dubovik et al. [2002a], Dubovik et al. [2002b], Dubovik et al., [2006a], Sinyuk et al. [2006]. The Version 2(V2)inversion (or retrieval)products are summarized below. These products are available through the internal analysis system&#x0022;demonstrat&#x0022; and the AERONET website. Adetailed description of V2 AERONET retrieval will be provided in the paper by Dubovik et al., [2006b].
AERONET inversion code provides aerosoloptical properties in the total atmospheric column derived from the direct and diffuse radiation measured byAERONETCimel sun/sky-radiometers. AERONET inversion developmentand researchactivitiesare described in the papers by Dubovik and King, [2000], Dubovik et al. [2000], Dubovik et al. [2002a], Dubovik et al. [2002b], Dubovik et al., [2006a], Sinyuk et al. [2006]. The Version 2(V2)inversion (or retrieval)products are summarized below. These products are available through the internal analysis system&#x0022;demonstrat&#x0022; and the AERONET website. Adetailed description of V2 AERONET retrieval will be provided in the paper by Dubovik et al., [2006b].
AERONET inversion code provides aerosoloptical properties in the total atmospheric column derived from the direct and diffuse radiation measured byAERONETCimel sun/sky-radiometers. AERONET inversion developmentand researchactivitiesare described in the papers by Dubovik and King, [2000], Dubovik et al. [2000], Dubovik et al. [2002a], Dubovik et al. [2002b], Dubovik et al., [2006a], Sinyuk et al. [2006]. The Version 2(V2)inversion (or retrieval)products are summarized below. These products are available through the internal analysis system&#x0022;demonstrat&#x0022; and the AERONET website. Adetailed description of V2 AERONET retrieval will be provided in the paper by Dubovik et al., [2006b].
AERONET inversion code provides aerosoloptical properties in the total atmospheric column derived from the direct and diffuse radiation measured byAERONETCimel sun/sky-radiometers. AERONET inversion developmentand researchactivitiesare described in the papers by Dubovik and King, [2000], Dubovik et al. [2000], Dubovik et al. [2002a], Dubovik et al. [2002b], Dubovik et al., [2006a], Sinyuk et al. [2006]. The Version 2(V2)inversion (or retrieval)products are summarized below. These products are available through the internal analysis system&#x0022;demonstrat&#x0022; and the AERONET website. Adetailed description of V2 AERONET retrieval will be provided in the paper by Dubovik et al., [2006b].
AERONET inversion code provides aerosoloptical properties in the total atmospheric column derived from the direct and diffuse radiation measured byAERONETCimel sun/sky-radiometers. AERONET inversion developmentand researchactivitiesare described in the papers by Dubovik and King, [2000], Dubovik et al. [2000], Dubovik et al. [2002a], Dubovik et al. [2002b], Dubovik et al., [2006a], Sinyuk et al. [2006]. The Version 2(V2)inversion (or retrieval)products are summarized below. These products are available through the internal analysis system&#x0022;demonstrat&#x0022; and the AERONET website. Adetailed description of V2 AERONET retrieval will be provided in the paper by Dubovik et al., [2006b].
SolRad-Net (Solar Radiation Network) is an established network of ground-based sensors providing high-frequency solar flux measurements in quasi-realtime to the scientific community and various other end users.This network was implemented as a companion to AERONET and its instrumentation are invariably collocated with AERONET sites. The Brazilian core of the present network was developed within the scientific framework of the LBA-ECO component of the Large-Scale Biosphere-Atmosphere Experiment in Amazônia.  Historically, SolRad-Net has preferentially selected sites that routinely experience intervals of biomass-burning, such as Amazônia and Sub-Saharan Africa for its long-term monitoring. Data that have been cleared as free of any operational problems are designated as Level 1.5.  The raw, unscreened data are Level 1.0 by default and may contain observations that have been compromised for any of the (occasionally subtle) reasons described above.  The Level 1.0 data are made available in the interest of presenting a comprehensive dataset and to provide full transparency of our methods, however any use of these data is strongly discouraged.
The Aerosol Robotic Network (AERONET), developed to sustain atmospheric studies at various scales with measurements from worldwide distributed autonomous sun-photometers has  been extended to support marine applications. This new network component called AERONET – Ocean Color (AERONET-OC), provides the additional capability of measuring the radiance emerging from the sea  (i.e., water-leaving radiance) with modified sun-photometers installed on offshore platforms like lighthouses, oceanographic and oil towers. AERONET-OC is instrumental in satellite ocean color validation activities through standardized measurements a) performed at different sites with a single measuring system and protocol, b) calibrated with an identical reference source and method, and c) processed with the same code.
The Aerosol Robotic Network (AERONET), developed to sustain atmospheric studies at various scales with measurements from worldwide distributed autonomous sun-photometers has  been extended to support marine applications. This new network component called AERONET – Ocean Color (AERONET-OC), provides the additional capability of measuring the radiance emerging from the sea  (i.e., water-leaving radiance) with modified sun-photometers installed on offshore platforms like lighthouses, oceanographic and oil towers. AERONET-OC is instrumental in satellite ocean color validation activities through standardized measurements a) performed at different sites with a single measuring system and protocol, b) calibrated with an identical reference source and method, and c) processed with the same code.
The Aerosol Robotic Network (AERONET), developed to sustain atmospheric studies at various scales with measurements from worldwide distributed autonomous sun-photometers has  been extended to support marine applications. This new network component called AERONET – Ocean Color (AERONET-OC), provides the additional capability of measuring the radiance emerging from the sea  (i.e., water-leaving radiance) with modified sun-photometers installed on offshore platforms like lighthouses, oceanographic and oil towers. AERONET-OC is instrumental in satellite ocean color validation activities through standardized measurements a) performed at different sites with a single measuring system and protocol, b) calibrated with an identical reference source and method, and c) processed with the same code.
The aerosol optical depth processing includes the spectral de-convolution algorithm (SDA) described in O'Neill et al. (2003). This algorithm yields fine (sub-micron) and coarse (super-micron) aerosol optical depths at a standard wavelength of 500 nm (from which FMF*, the fraction of fine mode to total aerosol optical depth can be computed).
The aerosol optical depth processing includes the spectral de-convolution algorithm (SDA) described in O'Neill et al. (2003). This algorithm yields fine (sub-micron) and coarse (super-micron) aerosol optical depths at a standard wavelength of 500 nm (from which FMF*, the fraction of fine mode to total aerosol optical depth can be computed).
The aerosol optical depth processing includes the spectral de-convolution algorithm (SDA) described in O'Neill et al. (2003). This algorithm yields fine (sub-micron) and coarse (super-micron) aerosol optical depths at a standard wavelength of 500 nm (from which FMF*, the fraction of fine mode to total aerosol optical depth can be computed).
The aerosol optical depth processing includes the spectral de-convolution algorithm (SDA) described in O'Neill et al. (2003). This algorithm yields fine (sub-micron) and coarse (super-micron) aerosol optical depths at a standard wavelength of 500 nm (from which FMF*, the fraction of fine mode to total aerosol optical depth can be computed).
The aerosol optical depth processing includes the spectral de-convolution algorithm (SDA) described in O'Neill et al. (2003). This algorithm yields fine (sub-micron) and coarse (super-micron) aerosol optical depths at a standard wavelength of 500 nm (from which FMF*, the fraction of fine mode to total aerosol optical depth can be computed).
The aerosol optical depth processing includes the spectral de-convolution algorithm (SDA) described in O'Neill et al. (2003). This algorithm yields fine (sub-micron) and coarse (super-micron) aerosol optical depths at a standard wavelength of 500 nm (from which FMF*, the fraction of fine mode to total aerosol optical depth can be computed).
NASA makes annual reports of progress made on Freedom of Information Act (FOIA) requests. This database contains PDF and XML versions of reports from 1999 to the present.
Contains a brief summary and high resolution imagery from various lunar rock and core drive tubes collected from the Apollo and Luna missions to the moon.
Image database of meteorites of lunar origin collected by the Antarctic Search for Meteorites Program.
Image database of meteorites of martian origin collected by the Antarctic Search for Meteorites Program.
Image database of meteorites believed to have originated from Vesta.
This Catalog summarizes the samples examined in the course of the Preliminary Examination (PE) Team (PET) of the Stardust Mission to comet Wild 2, and the results of the analyses of those samples. The Catalog is intended as a preliminary guide to the samples that are available for allocation to the larger planetary science community. Thus there is very detailed information about the samples that have been removed from the sample tray. In addition, there is enough detail about the samples that remain in the aerogel in the tray to permit investigators to request 'fresher' samples as well.
The Genesis mission, launched in August 2001, collected solar wind at Earth-Sun L1 location for 28 months, and returned to Earth September 2004 with collectors (very pure materials with highly polished surfaces) into which solar wind atoms were implanted, typically 40 to 100 nm below the surface. The Genesis mission included three separate collections: high speed solar wind, coronal mass ejection solar wind and interstream low speed solar wind. Information from these different solar regimes is adding to the understanding of solar physics (figure 1). The catalog contains images, the material, the dimensions and area, the solar wind regime, and a qualitative assessment of surface condition. Cataloging is an ongoing process with more than 1850 samples characterized.
Since May 1981, the National Aeronautics and Space Administration (NASA) has used aircraft to collect cosmic dust (CD) particles from Earth's stratosphere. Specially designed dust collectors are prepared for flight and processed after flight in an ultraclean (Class-100) laboratory constructed for this purpose at the Lyndon B. Johnson Space Center (JSC) in Houston, Texas. Particles are individually retrieved from the collectors, examined and cataloged, and then made available to the scientific community for research. Cosmic dust thereby joins lunar samples and meteorites as an additional source of extraterrestrial materials for scientific study.
Since May 1981, the National Aeronautics and Space Administration (NASA) has used aircraft to collect cosmic dust (CD) particles from Earth's stratosphere. Specially designed dust collectors are prepared for flight and processed after flight in an ultraclean (Class-100) laboratory constructed for this purpose at the Lyndon B. Johnson Space Center (JSC) in Houston, Texas. Particles are individually retrieved from the collectors, examined and cataloged, and then made available to the scientific community for research. Cosmic dust thereby joins lunar samples and meteorites as an additional source of extraterrestrial materials for scientific study.
Since May 1981, the National Aeronautics and Space Administration (NASA) has used aircraft to collect cosmic dust (CD) particles from Earth's stratosphere. Specially designed dust collectors are prepared for flight and processed after flight in an ultraclean (Class-100) laboratory constructed for this purpose at the Lyndon B. Johnson Space Center (JSC) in Houston, Texas. Particles are individually retrieved from the collectors, examined and cataloged, and then made available to the scientific community for research. Cosmic dust thereby joins lunar samples and meteorites as an additional source of extraterrestrial materials for scientific study.
The Apollo Image Atlas is a comprehensive collection of Apollo-Saturn mission photography. Included are almost 25,000 lunar images, both from orbit and from the moon's surface, as well as photographs of the earth, astronauts and mission hardware.
The Apollo Image Atlas is a comprehensive collection of Apollo-Saturn mission photography. Included are almost 25,000 lunar images, both from orbit and from the moon's surface, as well as photographs of the earth, astronauts and mission hardware.
The Apollo Image Atlas is a comprehensive collection of Apollo-Saturn mission photography. Included are almost 25,000 lunar images, both from orbit and from the moon's surface, as well as photographs of the earth, astronauts and mission hardware.
The Apollo Image Atlas is a comprehensive collection of Apollo-Saturn mission photography. Included are almost 25,000 lunar images, both from orbit and from the moon's surface, as well as photographs of the earth, astronauts and mission hardware.
The Apollo Image Atlas is a comprehensive collection of Apollo-Saturn mission photography. Included are almost 25,000 lunar images, both from orbit and from the moon's surface, as well as photographs of the earth, astronauts and mission hardware.
The Apollo Image Atlas is a comprehensive collection of Apollo-Saturn mission photography. Included are almost 25,000 lunar images, both from orbit and from the moon's surface, as well as photographs of the earth, astronauts and mission hardware.
The Apollo Image Atlas is a comprehensive collection of Apollo-Saturn mission photography. Included are almost 25,000 lunar images, both from orbit and from the moon's surface, as well as photographs of the earth, astronauts and mission hardware.
Apollo Surface Panoramas is a digital library of photographic panoramas that the Apollo astronauts took while exploring the Moon's surface. These images provide a spectacular boots-on-the-ground view of the lunar landscape. Lunar surface features captured in the panoramas can be studied using zoom and pan tools. An annotated version of each panorama is also available to assist users with the identification of major geographic features around each Apollo landing site.
Numerically-generated  gravitational waveforms for circular inspiral into Kerr black holes. These waveforms were developed using Scott Hughes' black hole perturbation theory code (the 'Teukolsky code').
Numerically-generated gravitational waveforms for binary black holes.
Gravitational radiation waveforms for black hole-neutron star coalescence calculations. The physical input is Newtonian physics, an ideal gas equation of state with varying compressibility (through the index gamma), and point-mass gravitational radiation back reaction, which is switched off in the simulation once the star is tidally disrupted. All the simulations are 3D, done using SPH.
Numerically-generated  gravitational waveforms for binary neutron stars.
Plotted images and a dataset for getting underlying coordinate data of extratropical storms.
Plotted images and a dataset for getting underlying coordinate data of extratropical storms.
This web page leads to a database of images and information about the 150 major impact craters on Callisto and is updated semi-regularly based on continuing analysis of Voyager images.
This web page leads to a database of images and information about the 150 major impact craters on Callisto and is updated semi-regularly based on continuing analysis of Voyager images.
This web page leads to a database of images and information about the 150 major impact craters on Callisto and is updated semi-regularly based on continuing analysis of Voyager images.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international 'A-Train' (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international 'A-Train' (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international 'A-Train' (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES.
The Clouds and the Earth's Radiant Energy System (CERES) is a key component of the Earth Observing System (EOS) program. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions are a follow-on to the successful Earth Radiation Budget Experiment (ERBE) mission. The first CERES instrument (PFM) was launched on November 27, 1997 as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit on board the EOS flagship Terra on December 18, 1999, and two additional CERES instruments (FM3 and FM4) were launched on board EOS Aqua on May 4, 2002.
The CEOS IDN is an international effort developed to assist researchers in locating information on available datasets and services.  The directory is sponsored as a service to the Earth science community.
The Consolidated Lunar Atlas is a collection of the best photographic images of the moon, including low-oblique photography, full-moon photography, and tabular and positional plates.
The Consolidated Lunar Atlas is a collection of the best photographic images of the moon, including low-oblique photography, full-moon photography, and tabular and positional plates.
The Consolidated Lunar Atlas is a collection of the best photographic images of the moon, including low-oblique photography, full-moon photography, and tabular and positional plates.
The Consolidated Lunar Atlas is a collection of the best photographic images of the moon, including low-oblique photography, full-moon photography, and tabular and positional plates.
The Consolidated Lunar Atlas is a collection of the best photographic images of the moon, including low-oblique photography, full-moon photography, and tabular and positional plates.
The Consolidated Lunar Atlas is a collection of the best photographic images of the moon, including low-oblique photography, full-moon photography, and tabular and positional plates.
The Lunar Orbiter Photographic Atlas of the Moon is considered the definitive reference manual to the global photographic coverage of the Moon. The images contained within the atlas are excellent for studying lunar morphology because they were obtained at low to moderate Sun angles. The digital Lunar Orbiter Atlas of the Moon is a reproduction of the 675 plates contained in Bowker and Hughes. The digital archive, however, offers many improvements upon its original hardbound predecessor. Multiple search capabilities were added to the database to expedite locating images and features of interest. For accuracy and usability, surface feature information has been updated and improved. Lastly, to aid in feature identification, a companion image containing feature annotation has been included.
The Lunar Orbiter Photographic Atlas of the Moon is considered the definitive reference manual to the global photographic coverage of the Moon. The images contained within the atlas are excellent for studying lunar morphology because they were obtained at low to moderate Sun angles. The digital Lunar Orbiter Atlas of the Moon is a reproduction of the 675 plates contained in Bowker and Hughes. The digital archive, however, offers many improvements upon its original hardbound predecessor. Multiple search capabilities were added to the database to expedite locating images and features of interest. For accuracy and usability, surface feature information has been updated and improved. Lastly, to aid in feature identification, a companion image containing feature annotation has been included.
The Lunar Orbiter Photographic Atlas of the Moon is considered the definitive reference manual to the global photographic coverage of the Moon. The images contained within the atlas are excellent for studying lunar morphology because they were obtained at low to moderate Sun angles. The digital Lunar Orbiter Atlas of the Moon is a reproduction of the 675 plates contained in Bowker and Hughes. The digital archive, however, offers many improvements upon its original hardbound predecessor. Multiple search capabilities were added to the database to expedite locating images and features of interest. For accuracy and usability, surface feature information has been updated and improved. Lastly, to aid in feature identification, a companion image containing feature annotation has been included.
The Lunar Orbiter Photographic Atlas of the Moon is considered the definitive reference manual to the global photographic coverage of the Moon. The images contained within the atlas are excellent for studying lunar morphology because they were obtained at low to moderate Sun angles. The digital Lunar Orbiter Atlas of the Moon is a reproduction of the 675 plates contained in Bowker and Hughes. The digital archive, however, offers many improvements upon its original hardbound predecessor. Multiple search capabilities were added to the database to expedite locating images and features of interest. For accuracy and usability, surface feature information has been updated and improved. Lastly, to aid in feature identification, a companion image containing feature annotation has been included.
Tiny solid and liquid particles suspended in the atmosphere are called aerosols. Windblown dust, sea salts, volcanic ash, smoke from wildfires, and pollution from factories are all examples of aerosols. Depending upon their size, type, and location, aerosols can either cool the surface, or warm it. They can help clouds to form, or they can inhibit cloud formation. And if inhaled, some aerosols can be harmful to people’s health.
Tiny solid and liquid particles suspended in the atmosphere are called aerosols. Windblown dust, sea salts, volcanic ash, smoke from wildfires, and pollution from factories are all examples of aerosols. Depending upon their size, type, and location, aerosols can either cool the surface, or warm it. They can help clouds to form, or they can inhibit cloud formation. And if inhaled, some aerosols can be harmful to people’s health.
Earth+ makes NASA satellite photos and data accessible to blind students.
Earth+ makes NASA satellite photos and data accessible to blind students.
Earth+ makes NASA satellite photos and data accessible to blind students.
Earth+ makes NASA satellite photos and data accessible to blind students.
Earth+ makes NASA satellite photos and data accessible to blind students.
Earth+ makes NASA satellite photos and data accessible to blind students.
Earth+ makes NASA satellite photos and data accessible to blind students.
Earth+ makes NASA satellite photos and data accessible to blind students.
Earth+ makes NASA satellite photos and data accessible to blind students.
Sponsored by NASA, EarthKAM (Earth Knowledge Acquired by Middle School Students) is an educational outreach program allowing middle school students to take pictures of our Earth from a digital camera on board the International Space Station.
Fermi is a powerful space observatory that will open a wide window on the universe. Gamma rays are the highest-energy form of light, and the gamma-ray sky is spectacularly different from the one we perceive with own eyes. With a huge leap in all key capabilities, Fermi data will enable scientists to answer persistent questions across a broad range of topics, including supermassive black-hole systems, pulsars, the origin of cosmic rays, and searches for signals of new physics.
This web page leads to a database of images and information about the 150 major impact craters on Ganymede and is updated semi-regularly based on continuing analysis of Voyager 2 images.
This web page leads to a database of images and information about the 150 major impact craters on Ganymede and is updated semi-regularly based on continuing analysis of Voyager 2 images.
This web page leads to a database of images and information about the 150 major impact craters on Ganymede and is updated semi-regularly based on continuing analysis of Voyager 2 images.
This web page leads to a database of images and information about the 150 major impact craters on Ganymede and is updated semi-regularly based on continuing analysis of Voyager 2 images.
This web page leads to a database of images and information about the 150 major impact craters on Ganymede and is updated semi-regularly based on continuing analysis of Voyager 2 images.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Planetary nomenclature, like terrestrial nomenclature, is used to uniquely identify a feature on the surface of a planet or satellite so that the feature can be easily located, described, and discussed. This gazetteer contains detailed information about all names of topographic and albedo features on planets and satellites (and some planetary ring and ring-gap systems) that the International Astronomical Union (IAU) has named and approved from its founding in 1919 through the present time.
Giovanni is a Web-based application developed by the GES DISC that provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data without having to download the data. Giovanni is an acronym for the GES-DISC (Goddard Earth Sciences Data and Information Services Center) Interactive Online Visualization ANd aNalysis Infrastructure.
JPL OurOcean Portal: A daily, global Sea Surface Temperature (SST) data set is produced at 1-km (also known as ultra-high resolution) by the JPL ROMS (Regional Ocean Modeling System) group.
The GCMD database holds more than 30,000 descriptions of Earth science data sets and services covering all aspects of Earth and environmental sciences.  The mission of the GCMD is to (1) Assist the scientific community in the discovery of Earth science data, related services, and ancillary information (platforms, instruments, projects, data centers/service providers); and (2) Provide discovery/collection-level metadata of Earth science resources and provide scientists a comprehensive and high quality database to reduce overall expenditures for scientific data collection and dissemination.
Data from NASA's Grace satellites show that the land ice sheets in both Antarctica and Greenland are losing mass. The continent of Antarctica (left chart) has been losing more than 100 cubic kilometers (24 cubic miles) of ice per year since 2002.
Carbon dioxide (CO2) is an important greenhouse gas released through natural processes such as respiration and volcano eruptions and through huma activities such as deforestation and burning fossil fuels. AIRS is the Atmospheric InfraRed Sounder, AIRS, was launched aboard the Aqua Spacecraft in 2002 as part of NASA’s Earth Observing System Afternoon Constellation of satellites known as the ‘A-Train’.
September Arctic sea ice is now declining at a rate of 11.5 percent per decade, relative to the 1979 to 2000 average. Data from NASA show that the land ice sheets in both Anarctica and Greenland are losing mass. The continent of Antarctica (left chart) has been losing more than 100 cubic kilometers (24 cubic miles) of ice per year since 2002. The International Satellite Cloud Climatology Project (ISCCP) was established in 1982 as part of the World Climate Research Programme (WCRP) to collect and analyze the global distribution of clouds, their properties, and their diurnal, seasonal, and interannual variations. This research includes snow and ice datat that can provide insight into the Land and Artic Ice issues that are being investigated.
Global surface temperatures in 2010 tied 2005 as the warmest on record. The International Satellite Cloud Climatology Project (ISCCP) was established in 1982 as part of the World Climate Research Programme (WCRP) to collect and analyze the global distribution of clouds, their properties, and their diurnal, seasonal, and interannual variations. The LAS provides data for Monthly Near-Surface Air Temperature Averages from 1994 to 2008.
Sea level rise is caused by the thermal expansion of sea water due to climate warming and widespread melting of land ice. The TOPEX/POSEIDON mission a joint satellite mission between NASA and the French space agency CNES, which operated between 1992 and 2005 to collect ocean surface and sea level data to support the mission of understanding ocean circulation.
The GHRC is the data management and user services arm of the Global Hydrology and Climate Center. It encompasses the data and information management, supporting product generation, archival, and distribution of research quality and operational datasets for a variety of data types, including lightning, passive microwave, radar and others.
The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) is the home (archive) of Precipitation, Atmospheric Chemistry and Dynamics, and information, as well as data and information from other related disciplines.
Research at the NASA Goddard Institute for Space Studies (GISS) emphasizes a broad study of global change, which is an interdisciplinary initiative addressing natural and man-made changes in our environment that occur on various time scales from one-time forcings such as volcanic explosions, to seasonal and annual effects such as El Nino, and on up to the millennia of ice ages and that affect the habitability of our planet.
A collection of lunar maps and charts. This tool is an exciting new way to explore the story of the Apollo missions, still the only time mankind has set foot on another world.
GRIN is a collection of over a thousand images of significant historical interest scanned at high-resolution in several sizes. This collection is intended for the media, publishers, and the general public looking for high-quality photographs.
The High Energy Astrophysics Science Archive Research Center (HEASARC) is the primary archive for NASA missions dealing with extremely energetic phenomena, from black holes to the Big Bang.
The JPL HORIZONS on-line solar system data and ephemeris computation service provides access to key solar system data and flexible production of highly accurate ephemerides for solar system objects ( 561485 asteroids, 3099 comets, 171 planetary satellites, 8 planets, the Sun, L1, L2, select spacecraft, and system barycenters ). HORIZONS is provided by the Solar System Dynamics Group of the Jet Propulsion Laboratory.
International Satellite Cloud Climatology Project (ISCCP) focuses on the distribution and variation of cloud radiative properties to improve the understanding of the effects of clouds on climate, the radiation budget, and the long-term global hydrologic cycle.
ECCO was established in 1998 as part of the World Ocean Circulation Experiment (WOCE) with the goal of combining a general circulation model (GCM) with diverse observations in order to produce a quantitative depiction of the time-evolving global ocean state.
View detailed images of the planets, the sun, small bodies, and the Universe from various NASA exploration programs.
The JPL Tropical Cyclone Information System (TCIS) brings together satellite and in situ data sets from various sources to help you find information for a particular tropical cyclone over the world's oceans.
World Wind allows any user to zoom from satellite altitude into any place on Earth, leveraging high resolution LandSat imagery and SRTM elevation data to experience Earth in visually rich 3D, just as if you were really there.
MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth is timed so that it passes from north to south across the equator in the morning, while Aqua passes south to north over the equator in the afternoon. Terra MODIS and Aqua MODIS are viewing the entire Earth's surface every 1 to 2 days, acquiring data in 36 spectral bands, or groups of wavelengths (see MODIS Technical Specifications). This map shows the temperature of Earth's lands during the nighttime.
The purpose of the Aerospace Technical Facility Inventory is to facilitate the sharing of specialized capabilities within the aerospace research/engineering community primarily within NASA, but also throughout the nation and the entire world. A second use is to assist in answering questions regarding NASA capabilities for future missions or various alternative scenarios regarding mission support to help the Agency maintain the right set of assets.
Public data set for NASA Agency Intellectual Property (IP).  The distribution contains both Patent information as well as General Release of Open Source Software.
Public data set for NASA Agency Intellectual Property (IP).  The distribution contains both Patent information as well as General Release of Open Source Software.
The Yohkoh Legacy data Archive (YLA) is intended to provide all usable scientific data obtained with the Yohkoh satellite, in convenient forms for research and education. The YLA consists of the whole set of Yohkoh data (from raw data to highly processed catalogs), with the web services of quick look, data search, and a sufficient amount of explanatory materials.
The SPDF is a project of the Heliospheric Science Division (HSD) at NASA's Goddard Space Flight Center. SPDF consists of web-based services for survey and high resolution data and trajectories. The Facility supports data from most NASA Heliophysics missions to promote correlative and collaborative research across discipline and mission boundaries.
The SPDF is a project of the Heliospheric Science Division (HSD) at NASA's Goddard Space Flight Center. SPDF consists of web-based services for survey and high resolution data and trajectories. The Facility supports data from most NASA Heliophysics missions to promote correlative and collaborative research across discipline and mission boundaries.
The centuries-old quest for other worlds like our Earth has been rejuvenated by the intense excitement and popular interest surrounding the discovery of hundreds of planets orbiting other stars. There is now clear evidence for substantial numbers of three types of exoplanets; gas giants, hot-super-Earths in short period orbits, and ice giants. The following websites are tracking the day-by-day increase in new discoveries and are providing information on the characteristics of the planets as well as those of the stars they orbit: The Extrasolar Planets Encyclopedia, NASA Exoplanet Archive, New Worlds Atlas, and Current Planet Count Widget.&#160;&#160;The challenge now is to find terrestrial planets (i.e., those one half to twice the size of the Earth), especially those in the habitable zone of their stars where liquid water and possibly life might exist. The Kepler Mission, NASA Discovery mission #10, is specifically designed to survey a portion of our region of the Milky Way galaxy&#160;to discover dozens of Earth-size planets in or near the habitable zone and determine how many of the billions of stars in our galaxy have such planets. Results from this mission will allow us to place our solar system within the continuum of planetary systems in the Galaxy.
The High Energy Astrophysics Science Archive Research Center (HEASARC) and the Legacy Archive for Microwave Background Data Analysis (LAMBDA) have merged into a single organization that will use the name HEASARC. The merged archive will continue to provide all of the services currently being offered by the two archives, while better serving users interested in studies requiring both high energy and microwave data. Users will notice few immediate changes, but we will gradually fully integrate all the services of the archives.
Landsat.org, an affiliate of the Tropical Rain Forest Information Center (TRFIC), now hosts the Global Orthorectified Landsat Datasets for four epochs: 1970's MSS, 1990's TM, 2000's ETM+, and 2005's ETM+. We provide access to these data for the global community of users for FREE.
Landsat represents the world's longest continuously acquired collection of space-based moderate-resolution land remote sensing data. Four decades of imagery provides a unique resource for those who work in agriculture, geology, forestry, regional planning, education, mapping, and global change research. Landsat images are also invaluable for emergency response and disaster relief.
NASA's Life Sciences Data Archive (LSDA) is an active archive that provides information and data from 1961 (Mercury Project) through current flight and flight analog studies (International Space Station, Shuttle, bed rest studies, etc.) involving human, plant and animal subjects.
The Lunar Map Catalog includes various maps of the moon's surface, including Apollo landing sites; earthside, farside, and polar charts; photography index maps; zone mosaics; shaded relief; topographic; and a geologic atlas.
The Lunar Orbiter Photo Gallery is an extensive collection of over 2,600 high- and moderate-resolution photographs produced by all five of the Lunar Orbiter missions. These photographs were taken in 1966 and 1967 to survey possible lunar landing sites and provide baseline imagery for geologic analysis of the lunar surface. The images were used to select the Apollo landing sites and to produce many of our existing lunar geologic maps. This photo gallery is the web's most comprehensive collection of Lunar Orbiter photography and supporting documents.
The Lunar Sample Atlas provides pictures of the Apollo samples taken in the Lunar Sample Laboratory, full-color views of the samples in microscopic thin-sections, cutting views and diagrams that illustrate how the samples were subdivided for scientific analyses, and in situ views of the samples on the lunar surface. The atlas contains information about the type of sample (e.g., rock, soil), the lithology (e.g., basalt, norite), and a description of the sample.
The purpose of the Lunar Sample Compendium is to inform scientists, astronauts and the public about the various lunar samples that have been returned from the Moon. This compendium is organized rock by rock and by category.
NASA provides a number of lunar samples for display at museums, planetariums, and scientific expositions around the world. Lunar displays are open to the public.   This is a database of every location around the planet displaying returned lunar samples from the Apollo missions.
Beginning with the systematic mapping of the lunar surface more than three decades ago, this database contains over 1600 maps of the planets and satellites of the Solar System. This collection of maps is a unique resource that has been derived from images and data returned by a series of space missions. Many of the maps have not been replicated or updated with data from new missions, and thus they represent a very special legacy from the beginnings of space exploration. The total map database includes controlled photomosaics, geologic maps, shaded relief portrayals, topographic maps, and panoramas of the martian surface.
The Mariner 10 Image Archive includes tools to view shaded relief maps of the surface of Mercury, a 3D globe, and all images acquired by NASA's Mariner 10 mission.
The Mars Maps Catalog includes various mappings of the surface of Mars.
View full-resolution images downlinked from the Mars Science Laboratory, sorted by Sol and by camera type.
The Mercury Map Catalog includes various mappings of the surface of Mercury published by the U.S. Geological Survey from 1976 - 1990.
Earth Science data access made simple. Atmospheric Composition is focused on the composition of Earth's atmosphere in relation to climate prediction, solar effects, ground emissions and time.
Earth Science data access made simple. This Focus Area deals with the cycling of carbon in reservoirs and ecosystems as it changes naturally, is changed by humans, and is affected by climate change.
Earth Science data access made simple. NASA's role in climate variability study is centered around providing the global scale observational data sets on oceans and ice, their forcings, and the interactions with the entire Earth system.
Earth Science data access made simple. The goal of the Earth Surface and Interior focus area is to assess, mitigate and forecast the natural hazards that affect society, including earthquakes, landslides, coastal and interior erosion, floods and volcanic eruptions.
Earth Science data access made simple. Through water and energy cycle research we can improve hurricane prediction, quantify tropical rainfall and eventually begin to balance the water budget at global and regional scales.
Earth Science data access made simple. Our weather system includes the dynamics of the atmosphere and its interaction with the oceans and land. The improvement of our understanding of weather processes and phenomena is crucial in gaining an understanding of the Earth system.
The Multi-angle Imaging SpectroRadiometer (MISR) was successfully launched into sun-synchronous polar orbit aboard Terra, NASA's first Earth Observing System (EOS) spacecraft, on December 18, 1999. MISR measurements are designed to improve our understanding of the Earth's environment and climate. Viewing the sunlit Earth simultaneously at nine widely-spaced angles, MISR provides radiometrically and geometrically calibrated images in four spectral bands at each of the angles. Spatial sampling of 275 and 1100 meters is provided on a global basis.
MY NASA DATA (MND) is a tool that allows anyone to make use of satellite data that was previously unavailable.Through the use of MND’s Live Access Server (LAS) a multitude of charts, plots and graphs can be generated using a wide variety of constraints. This site provides a large number of lesson plans with a wide variety of topics, all with the students in mind. Not only can you use our lesson plans, you can use the LAS to improve the ones that you are currently implementing in your classroom.
The NASA Earth Exchange (NEX) represents a new platform for the Earth science community that provides a mechanism for scientific collaboration and knowledge sharing. NEX combines state-of-the-art supercomputing, Earth system modeling, workflow management, NASA remote sensing data feeds, and a knowledge sharing platform to deliver a complete work environment in which users can explore and analyze large datasets, run modeling codes, collaborate on new or existing projects, and quickly share results among the Earth Science communities.
Our mission is to help you picture climate change and environmental changes happening on our home planet. Here you can search for and retrieve satellite images of Earth. Download them; export them to GoogleEarth; perform basic analysis. Tracking regional and global changes around the world just got easier.
Our mission is to help you picture climate change and environmental changes happening on our home planet. Here you can search for and retrieve satellite images of Earth. Download them; export them to GoogleEarth; perform basic analysis. Tracking regional and global changes around the world just got easier.
Our mission is to help you picture climate change and environmental changes happening on our home planet. Here you can search for and retrieve satellite images of Earth. Download them; export them to GoogleEarth; perform basic analysis. Tracking regional and global changes around the world just got easier.
Our mission is to help you picture climate change and environmental changes happening on our home planet. Here you can search for and retrieve satellite images of Earth. Download them; export them to GoogleEarth; perform basic analysis. Tracking regional and global changes around the world just got easier.
The NASA Lessons Learned system provides access to official, reviewed lessons learned from NASA programs and projects. These lessons have been made available to the public by the NASA Office of the Chief Engineer and the NASA Engineering Network. Each lesson describes the original driving event and provides recommendations that feed into NASA’s continual improvement via training, best practices, policies, and procedures.
NASA Technical Reports Server (NTRS) provides access to aerospace-related citations, full-text online documents, and images and videos. The types of information include: conference papers, journal articles, meeting papers, patents, research reports, images, movies, and technical videos – scientific and technical information (STI) created or funded by NASA.The NTRS integrates the following three NASA collections and enables search and retrieval through a common interface:NACA Collection: Citations and reports from the National Advisory Committee for Aeronautics period lasting from 1915 to 1958.NASA Collection: Citations and documents created or sponsored by NASA starting in 1958 and continuing to the present.NIX Collection: Citations and links to the images, photos, movies, and videos from the discontinued NASA Image eXchange (NIX).
The NASA Technical Standards Program provides access to NASA developed standards and handbooks. The NASA Standards and Technical Assistance Resource Tool, or START, is a Web tool sponsored by the NASA Technical Standards Program. The idea is to make it simpler for technical people to access great NASA technical information quickly and conveniently.
The NTRS is a valuable resource for researchers, students, educators, and the public to access NASA's current and historical technical literature and engineering results. Over 500,000 aerospace-related citations, over 200,000 full-text online documents, and over 500,000 images and videos are available. NTRS content continues to grow as new scientific and technical information (STI) is created or funded by NASA. The types of information found in the NTRS include: conference papers, journal articles, meeting papers, patents, research reports, images, movies, and technical videos.  NTRS is&#160;Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) enabled
The NASA Thesaurus contains the authorized NASA subject terms used to index and retrieve materials in the NASA Technical Reports Server (NTRS) and the NTRS Registered (Formerly NA&SD). The scope of this controlled vocabulary includes not only aerospace engineering, but all supporting areas of engineering and physics, the natural space sciences (astronomy, astrophysics, planetary science), Earth sciences, and the biological sciences. The NASA Thesaurus contains over 18,400 subject terms, 4,300 definitions, and more than 4,500 USE cross references.
The NASA/GEWEX Surface Radiation Budget (SRB) Release-3.0 data sets contains global 3-hourly, daily, monthly/3-hourly, and monthly averages of surface and top-of atmosphere (TOA) longwave and shortwave radiative parameters on a 1Ã‚Â°x1Ã‚Â° grid. Model inputs of cloud amounts and other atmospheric state parameters are also available in some of the data sets. Primary inputs to the models include: visible and infrared radiances from International Satellite Cloud Climatology Project (ISCCP) pixel-level (DX) data, cloud and surface properties derived from those data, temperature and moisture profiles from GEOS-4 reanalysis product obtained from the NASA Global Modeling and Assimilation Office (GMAO), and column ozone amounts constituted from Total Ozone Mapping Spectrometer (TOMS), TIROS Operational Vertical Sounder (TOVS) archives, and Stratospheric Monitoring-group's Ozone Blended Analysis (SMOBA), an assimilation product from NOAA's Climate Prediction Center. SRB products are reformatted for the use of renewable energy and agricultural communities and made available through the Surface meteorology and Solar Energy (SSE) website. SRB products now overlap a portion of surface and TOA flux data sets that are available from Clouds and the Earth's Radiant Energy System (CERES) project. These CERES data products and those from the CERES Fast Longwave and SHortwave Radiative Fluxes (FLASHFlux) project extend past the SRB time frame. The latter project provides radiative fluxes on a near real-time basis. The CERES and CERES/FLASHFlux data sets also make use of global observations from Moderate-resolution Imaging SpectroRadiometer (MODIS) instruments.
IRSA is chartered to curate the calibrated science products from NASAs infrared and sub-millimeter missions, including five major large-area/all-sky surveys. IRSA data sets are cited in about 10% of astronomical refereed papers.<br /> IRSA offers access to digital archives through powerful query engines, including VO-compliant interfaces, and offers unique tools such as the IRAS scan processing tool Scanpi. IRSA exploits a re-useable architecture to deploy cost-effective archives for customers, including: the Spitzer Space Telescope; the 2MASS and IRAS all-sky surveys; and multi-mission datasets such as COSMOS. In the near future, IRSA will serve public data from the WISE all-sky survey and the Planck mission.
The National Space Science Data Center serves as the permanent archive for NASA space science mission data. 'Space science' means astronomy and astrophysics, solar and space plasma physics, and planetary and lunar science. As permanent archive, NSSDC teams with NASA's discipline-specific space science 'active archives' which provide access to data to researchers and, in some cases, to the general public. Search by event, spacecraft, experiment, map, or publication query. NSSDC is part of the Solar System Exploration Data Services Office (SSEDSO) in the Solar System Exploration Division at NASA's Goddard Space Flight Center in Greenbelt, MD.
The Navigation and Ancillary Information Facility (NAIF), acting under the directions of NASA's Planetary Science Division, has built an information system named 'SPICE' to assist NASA scientists in planning and interpreting scientific observations from space-borne instruments, and to assist NASA engineers involved in modeling, planning andexecuting activities needed to conduct planetary exploration missions The use of SPICE extends from mission concept development through the post-mission data analysis phase,including help with correlation of individual instrument data sets with those from other instruments on the same or on other spacecraft.
PO.DAAC is an element of the Earth Observing System Data Information System (EOSDIS). PO.DAAC's primary responsibility is to provide distribution and archive support for NASA's physical oceanography missions such as TOPEX/Poseidon and SeaWinds on QuikSCAT. However, PO.DAAC additionally collaborates with other institutes to acquire complementary data products and value-added services.
Planet Counter: Keep track of the latest planet discoveries on your desktop. New and updates about quest to discover exoplanets.
The Planetary Data System (PDS) is an archive of data products from NASA planetary missions, which is sponsored by NASA's Science Mission Directorate. We actively manage the archive to maximize its usefulness, and it has become a basic resource for scientists around the world.
Tropical Rainfall Measuring Mission (TRMM) data products are currently available from 1998 to the present. Global Precipitation Measurement (GPM) mission data products are currently available from March 2014 to the present. TRMM and GPM are joint missions between NASA and the Japan Aerospace Exploration Agency (JAXA) designed to monitor and study global precipitation. Here we outline the types of products currently available for TRMM and GPM and the various ways to query, view and download these precipitation products.
Tropical Rainfall Measuring Mission (TRMM) data products are currently available from 1998 to the present. Global Precipitation Measurement (GPM) mission data products are currently available from March 2014 to the present. TRMM and GPM are joint missions between NASA and the Japan Aerospace Exploration Agency (JAXA) designed to monitor and study global precipitation. Here we outline the types of products currently available for TRMM and GPM and the various ways to query, view and download these precipitation products.
Reverb has been developed utilizing modern web development technologies and presents you with a fresh new look and interface for discovering Earth Science data. We invite you to give it a try and let us know what you think. Reverb will be continually updated on a monthly basis taking into account your user feedback and other enhancements which are currently planned.
SERVIR is a Spanish acronym for 'Regional Visualization and Monitoring System.' The&#160;SERVIR project enables the use of Earth observations and predictive models for timely decision making through regional platforms in Mesoamerica, East Africa, and the Hindu-Kush Himalayas. &#160;The SERVIR project was initially developed by NASA, the US Agency for International Development, the World Bank, the Central American Commission for Environment and Development (CCAD), and the Water Center for the Humid Tropics of Latin America and the Caribbean (CATHALAC) in 2005. &#160; In 2008, the Regional Center for Mapping of Resources for Development (RCMRD) in Nairobi, Kenya, joined the SERVIR project, and in 2010, SERVIR inaugurated its third hub at the International Centre for Integrated Mountain Development (ICIMOD) in Kathmandu, Nepal. &#160; SERVIR also stands for the Spanish verb 'to serve,' which is what the project aims to do in terms of providing improved access to data and knowledge for decision-making.
A near-global Digital Elevation Model that allows software authors to determine the terrain height of nearly any point on Earth.
An integrated resource of solar imagery and data.
A searchable database of all Solar Dynamics Observatory data including EUV, magnetograms, visible light and X-ray.  SDO: The Solar Dynamics Observatory is the first mission to be launched for NASA's Living With a Star (LWS) Program, a program designed to understand the causes of solar variability and its impacts on Earth. SDO is designed to help us understand the Sun's influence on Earth and Near-Earth space by studying the solar atmosphere on small scales of space and time and in many wavelengths simultaneously.  SDO's goal is to understand, driving towards a predictive capability, the solar variations that influence life on Earth and humanity's technological systems by determining how the Sun's magnetic field is generated and structured and how this stored magnetic energy is converted and released into the heliosphere and geospace in the form of solar wind, energetic particles, and variations in the solar irradiance.
This compilation of outgassing data of materials intended for spacecraft use were obtained at the Goddard Space Flight Center (GSFC), utilizing equipment developed at Stanford Research Institue (SRI) under contract to the Jet Propulsion Laboratory (JPL).  SRI personnel developed an apparatus for determining the mass loss in vacuum and for collecting the outgassed products. Their report (Reference 1), which contained data from June 1964 to August 1967, served well as a foundation for selecting spacecraft materials with low outgassing properties. The apparatus was also constructed at GSFC and, based on the SRI data and GSFC data, a GSFC report (Reference 2) was published. That report included data for those materials meeting two criteria: a maximum total mass loss (TML) of 1.0 percent and maximum collected volatile condensable material (CVCM) of 0.10 percent.  After a series of tests and verification of procedures, an American Society for Testing and Materials (ASTM) Standard Test Method was developed, based upon this apparatus. The method, 'Total Mass Loss (TML) and Collected Volatile Condensable Materials (CVCM) from Outgassing in a Vacuum Environment,' is identified as E 595-77/84/90. The data developed through the years have been reported in References 3, 4, 5, 6, 7, 8, and 9 as a means of assisting in selecting materials for space flight use.
Surface Meteorology and Solar Energy data - over 200 satellite-derived meteorology and solar energy parameters, monthly averaged from 22 years of data, global solar data for 1195 ground sites
TES focuses on the troposphere, the layer of atmosphere that stretches from the ground to the altitude at which airplanes fly. With very high spectral resolution, TES can distinguish concentrations of gases at different altitudes, a key factor in understanding their behavior and impact. It's the first orbiting instrument able to do this with ozone, a very important chemical with regard to both global warming and air pollution.<br /> The primary location for obtaining TES data is NASA's Warehouse Inventory Search Tool (WIST). The TES Data Sets page at NASA Langley Research Center (LaRC ASDC) provides access to software read tools, a Data Pool, and supporting documentation.
This web page leads to a database of images and information about the 900 or so impact craters on the surface of Venus by diameter, latitude, and name.
A catalog of NASA images and animations of our home planet.
Workforce Information Cubes for NASA, sourced from NASA's personnel/payroll system, gives data about who is working where and on what. Includes records for every civil service employee in NASA, snapshots of workforce composition as of certain dates, and data on personnel transactions, such as hires, losses and promotions. Updates occur every 2 weeks.
High-resolution, current space physics data with graphics and listings from many missions. This web service consists of public data from current (1992 -> present) space physics missions (including ACE, Cluster, C/NOFS, FAST, Geotail, GOES 5-12, IMAGE, LANL 1989-2002, NOAA 10-14, OMNI, Polar, STEREO, THEMIS, TIMED, Ulysses, Van Allen Probes, Voyager, Wind and others) and public data from older missions (including Alouette, CRRES, DE, Hawkeye, IMP-8, ISIS, NOAA 5-10, OMNI and others).
Hourly-averaged near-Earth solar wind magnetic field and plasma, etc. The web services consists of OMNI data (spacecraft-interspersed, near-Earth solar wind data); spacecraft-specific data sets (near 1 AU, including near-Earth) including ACE, Geotail, IMP-8, IMP6&7, Wind, Explorer 33&35, Genesis, ISEE 3, Prognoz, SOHO, GOES, and Moon Related Spacecraft; deep space data including COHOWeb-formatted hourly solar wind field and plasma, Pioneer, Ulysses, Voyager, Cassini, Helios, Mariner, and STEREO; and Interfaces for comparing multi-source data.
Hourly-averaged deep space magnetic field, plasma, and ephemerides. This web service includes data from  missions including Helios1, Helios2, OMNI_M, Pioneer10, Pioneer11, Pioneer Venus, Stereo-A, Stereo-B, Ulysses, Voyager1, Voyager2, Mariner2, Pioneer6, Pioneer7.
ATMOWeb ( as the part of FTPBrowser interface) provides a graphical browsing,subsetting and retrieval capability for selected ionospheric and atmospheric data. Data can be displayed as time series plots, filtering and scatter plot options are also included for a few spacecraft. ATMOWeb allows a user to list data by specifying a time interval and any combination of parameters and then to download (using the browser's capabilities) the data subset to the user's system.
FTPBrowser at GSFC/SPDF is an interface for graphical or digital display and/or retrieval of subsets of data that are in selected ones of SPDF's ftp-accessible ASCII or g-zipped ASCII data sets.
GIFWalk is an interface allowing the user to browse pre-generated data and orbit plots from missions including ACE, Cluster, Geotail, THEMIS, Polar, IMAGE, IMP 8, Wind, and Van Allen Probes (RBSP).
The CDAWeb data service (at http://cdaweb.gsfc.nasa.gov) offers graphic, listing, subsetting and data computation services for a continuously increasing database of current and past Sun-Earth-Connections mission and ground-based data. As a complement to the CDAWeb data service, we also provide the publicly-released subset of the underlying database directly accessible as an anonymous FTP service (accessible at ftp://cdaweb.gsfc.nasa.gov). All data available from the FTP service are also available from CDAWeb itself; the major advantage of the FTP service is support for functions like mget.
Display and download Earth orbiting trajectory data.
This interface enables one to plot and list heliocentric orbit information for spacecraft remote from Earth and for planets having heliophysics spacecraft in orbit about them. The object(s) of interest, time span, time resolution (daily or lower) and coordinate system (solar ecliptic, inertial and rotating heliographic)are specified by users. Underlying data files contain heliocentric distances and elevation and longitude angles at daily resolution.  Plot options include object-specific time series plots of the radial distance and direction angles,  as well as X-Y, X-Z, and Y-Z projections of the heliocentric position vectors.
SolRad-Net (Solar Radiation Network) is an established network of ground-based sensors providing high-frequency solar flux measurements in quasi-realtime to the scientific community and various other end users. This network was implemented as a companion to AERONET and its instrumentation are invariably collocated with AERONET sites.  The Brazilian core of the present network was developed within the scientific framework of the LBA-ECO component of the Large-Scale Biosphere-Atmosphere Experiment in Amazônia. Historically, SolRad-Nethas preferentially selected sites that routinely experience intervals of biomass-burning, such as Amazônia and Sub-Saharan Africa for its long-term monitoring. Data that have been cleared as free of any operational problems are designated as Level 1.5. The raw, unscreened data are Level 1.0 by default and may contain observations that have been compromised for any of the (occasionally subtle) reasons described above. The Level 1.0 data are made available in the interest of presenting a comprehensive  dataset and to provide full transparency of our methods, however any use of these data is strongly discouraged. Data are available from several flux instruments including filtered and unfiltered pyranometers, photosynthetically active radiation (PAR) energy and quantum sensors, and UV-A and UV-B flux sensors. To maintain the integrity of the database and fairness to the individuals who have contributed, use of these data for publication requires an offer of authorship to the SolRad-Net PI(s).
The SDA dataset uses the spectral behavior of AOD to partition between fine and coarse modes, without a size-cutoff radius of the type used by the Dubovik and King [2000] inversion algorithm. The SDA data are derived from the direct-Sun observations rather than almucantar scans. Datasets are available at annual, monthly and daily accrurals.
Numerically-generated gravitational waveforms for circular inspiral into Kerr black holes. These waveforms were developed using Scott Hughes' black hole perturbation theory code (the "Teukolsky code").
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist of half orbit (Night and Day) emissivity and cloud particle data related to pixels that have been co-located to the Lidar track.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist of half orbit (Night and Day) emissivity and cloud particle data related to pixels that have been co-located to the Lidar track.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist of half orbit (Night and Day) emissivity and cloud particle data related to pixels that have been co-located to the Lidar track.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist of half orbit (Night and Day) emissivity and cloud particle data related to pixels that have been co-located to the Lidar track.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist of half orbit (Night and Day) emissivity and cloud particle data related to pixels that have been co-located to the Lidar track.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consists of half orbit (Night and Day) emissivity and cloud particle data assigned to IIR pixels on a 1 km grid centered on the Lidar track.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consists of half orbit (Night and Day) emissivity and cloud particle data assigned to IIR pixels on a 1 km grid centered on the Lidar track.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist of half orbit (Night and Day) emissivity and cloud particle data related to pixels that have been co-located to the Lidar track.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist of half orbit (Night and Day) emissivity and cloud particle data related to pixels that have been co-located to the Lidar track.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international “A-Train” (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES. These data consist 5 km aerosol layer data.
Fermi is a powerful space observatory that will open a wide window on the universe. Gamma rays are the highest-energy form of light, and the gamma-ray sky is spectacularly different from the one we perceive with our own eyes. With a huge leap in all key capabilities, Fermi data will enable scientists to answer persistent questions across a broad range of topics, including supermassive black-hole systems, pulsars, the origin of cosmic rays, and searches for signals of new physics.
Fermi is a powerful space observatory that will open a wide window on the universe. Gamma rays are the highest-energy form of light, and the gamma-ray sky is spectacularly different from the one we perceive with our own eyes. With a huge leap in all key capabilities, Fermi data will enable scientists to answer persistent questions across a broad range of topics, including supermassive black-hole systems, pulsars, the origin of cosmic rays, and searches for signals of new physics.
Fermi is a powerful space observatory that will open a wide window on the universe. Gamma rays are the highest-energy form of light, and the gamma-ray sky is spectacularly different from the one we perceive with our own eyes. With a huge leap in all key capabilities, Fermi data will enable scientists to answer persistent questions across a broad range of topics, including supermassive black-hole systems, pulsars, the origin of cosmic rays, and searches for signals of new physics.
Fermi is a powerful space observatory that will open a wide window on the universe. Gamma rays are the highest-energy form of light, and the gamma-ray sky is spectacularly different from the one we perceive with our own eyes. With a huge leap in all key capabilities, Fermi data will enable scientists to answer persistent questions across a broad range of topics, including supermassive black-hole systems, pulsars, the origin of cosmic rays, and searches for signals of new physics.
Fermi is a powerful space observatory that will open a wide window on the universe. Gamma rays are the highest-energy form of light, and the gamma-ray sky is spectacularly different from the one we perceive with our own eyes. With a huge leap in all key capabilities, Fermi data will enable scientists to answer persistent questions across a broad range of topics, including supermassive black-hole systems, pulsars, the origin of cosmic rays, and searches for signals of new physics.
Fermi is a powerful space observatory that will open a wide window on the universe. Gamma rays are the highest-energy form of light, and the gamma-ray sky is spectacularly different from the one we perceive with our own eyes. With a huge leap in all key capabilities, Fermi data will enable scientists to answer persistent questions across a broad range of topics, including supermassive black-hole systems, pulsars, the origin of cosmic rays, and searches for signals of new physics.
Fermi is a powerful space observatory that will open a wide window on the universe. Gamma rays are the highest-energy form of light, and the gamma-ray sky is spectacularly different from the one we perceive with our own eyes. With a huge leap in all key capabilities, Fermi data will enable scientists to answer persistent questions across a broad range of topics, including supermassive black-hole systems, pulsars, the origin of cosmic rays, and searches for signals of new physics.
The LAT team monitors flux values for a number of bright sources and transient sources that have shown flares during the mission. (See up-to-date weekly reports on flaring sources at the Fermi-LAT Flare Advocate Blog.) As sources cross the monitoring flux threshold of 1x10-6 cm-2s-1, they are added to the monitored source list. (The initial flux threshold was 2x10-6 cm-2s-1, but this value was lowered in June 2009.) In addition to the light curves below, the flux values in several bands are available via Browse. This list will continue to grow as the mission progresses.
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the second full catalog of LAT sources, based on the first 24 months of survey data. For a full explanation about the catalog and its construction see the LAT 2-year Catalog Paper (also available on arxiv).
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the second full catalog of LAT sources, based on the first 24 months of survey data. For a full explanation about the catalog and its construction see the LAT 2-year Catalog Paper (also available on arxiv).
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the second full catalog of LAT sources, based on the first 24 months of survey data. For a full explanation about the catalog and its construction see the LAT 2-year Catalog Paper (also available on arxiv).
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the second full catalog of LAT sources, based on the first 24 months of survey data. For a full explanation about the catalog and its construction see the LAT 2-year Catalog Paper (also available on arxiv).
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the second full catalog of LAT sources, based on the first 24 months of survey data. For a full explanation about the catalog and its construction see the LAT 2-year Catalog Paper (also available on arxiv).
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the second full catalog of LAT sources, based on the first 24 months of survey data. For a full explanation about the catalog and its construction see the LAT 2-year Catalog Paper (also available on arxiv).
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the second full catalog of LAT sources, based on the first 24 months of survey data. For a full explanation about the catalog and its construction see the LAT 2-year Catalog Paper (also available on arxiv).
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the second full catalog of LAT sources, based on the first 24 months of survey data. For a full explanation about the catalog and its construction see the LAT 2-year Catalog Paper (also available on arxiv).
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the second full catalog of LAT sources, based on the first 24 months of survey data. For a full explanation about the catalog and its construction see the LAT 2-year Catalog Paper (also available on arxiv).
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the second full catalog of LAT sources, based on the first 24 months of survey data. For a full explanation about the catalog and its construction see the LAT 2-year Catalog Paper (also available on arxiv).
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the second full catalog of LAT sources, based on the first 24 months of survey data. For a full explanation about the catalog and its construction see the LAT 2-year Catalog Paper (also available on arxiv).
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the second full catalog of LAT sources, based on the first 24 months of survey data. For a full explanation about the catalog and its construction see the LAT 2-year Catalog Paper (also available on arxiv).
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the second full catalog of LAT sources, based on the first 24 months of survey data. For a full explanation about the catalog and its construction see the LAT 2-year Catalog Paper (also available on arxiv).
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the second full catalog of LAT sources, based on the first 24 months of survey data. For a full explanation about the catalog and its construction see the LAT 2-year Catalog Paper (also available on arxiv).
Due to a glitch in the analysis pipeline there are apparent increases in flux around MJD 56810 for many sources. These increases are *not* real and should be disregarded. The problem is now believed to be fixed, and the most recent flux measurements are expected to be correct. At a later date the light curves will be reprocessed to remove these incorrect data points.
Due to a glitch in the analysis pipeline there are apparent increases in flux around MJD 56810 for many sources. These increases are *not* real and should be disregarded. The problem is now believed to be fixed, and the most recent flux measurements are expected to be correct. At a later date the light curves will be reprocessed to remove these incorrect data points.
This catalog of LAT sources above 10 GeV reports the locations, spectra, and variability properties of the 514 sources significantly detected in this range during the first three years of the Fermi mission. Many of these sources are already included in the 2FGL catalog, although in that catalog their characterization is dominated by the much larger numbers of gamma rays detected in the energy range 0.1 to 10 GeV.
This catalog of LAT sources above 10 GeV reports the locations, spectra, and variability properties of the 514 sources significantly detected in this range during the first three years of the Fermi mission. Many of these sources are already included in the 2FGL catalog, although in that catalog their characterization is dominated by the much larger numbers of gamma rays detected in the energy range 0.1 to 10 GeV.
This catalog of LAT sources above 10 GeV reports the locations, spectra, and variability properties of the 514 sources significantly detected in this range during the first three years of the Fermi mission. Many of these sources are already included in the 2FGL catalog, although in that catalog their characterization is dominated by the much larger numbers of gamma rays detected in the energy range 0.1 to 10 GeV.
This catalog of LAT sources above 10 GeV reports the locations, spectra, and variability properties of the 514 sources significantly detected in this range during the first three years of the Fermi mission. Many of these sources are already included in the 2FGL catalog, although in that catalog their characterization is dominated by the much larger numbers of gamma rays detected in the energy range 0.1 to 10 GeV.
This catalog of LAT sources above 10 GeV reports the locations, spectra, and variability properties of the 514 sources significantly detected in this range during the first three years of the Fermi mission. Many of these sources are already included in the 2FGL catalog, although in that catalog their characterization is dominated by the much larger numbers of gamma rays detected in the energy range 0.1 to 10 GeV.
This catalog of LAT sources above 10 GeV reports the locations, spectra, and variability properties of the 514 sources significantly detected in this range during the first three years of the Fermi mission. Many of these sources are already included in the 2FGL catalog, although in that catalog their characterization is dominated by the much larger numbers of gamma rays detected in the energy range 0.1 to 10 GeV.
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the first full catalog of LAT sources, based on the first eleven months of survey data. For a full explanation about the catalog and its construction see the LAT 1-year Catalog Paper.
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the first full catalog of LAT sources, based on the first eleven months of survey data. For a full explanation about the catalog and its construction see the LAT 1-year Catalog Paper.
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the first full catalog of LAT sources, based on the first eleven months of survey data. For a full explanation about the catalog and its construction see the LAT 1-year Catalog Paper.
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the first full catalog of LAT sources, based on the first eleven months of survey data. For a full explanation about the catalog and its construction see the LAT 1-year Catalog Paper.
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the first full catalog of LAT sources, based on the first eleven months of survey data. For a full explanation about the catalog and its construction see the LAT 1-year Catalog Paper.
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the first full catalog of LAT sources, based on the first eleven months of survey data. For a full explanation about the catalog and its construction see the LAT 1-year Catalog Paper.
The Fermi Gamma-ray Space Telescope (Fermi) Large Area Telescope (LAT) is a successor to EGRET, with greatly improved sensitivity, resolution, and energy range. This web page presents the first full catalog of LAT sources, based on the first eleven months of survey data. For a full explanation about the catalog and its construction see the LAT 1-year Catalog Paper.
The LAT Second Pulsar Catalog is available as a .tgz (tarred and zipped) archive file. The archive includes a main catalog FITS file with the data from the paper tables, images of the light curve and spectral energy distributions (SEDs) for each pulsar, FITS files containing the data points used in those images, and the timing parameters used in the analysis. A full description of the online archive is given in Appendix B of the preprint. Upon final publication, this catalog will also be generated as a BROWSE table that will be linked to this page.
The LAT Second Pulsar Catalog is available as a .tgz (tarred and zipped) archive file. The archive includes a main catalog FITS file with the data from the paper tables, images of the light curve and spectral energy distributions (SEDs) for each pulsar, FITS files containing the data points used in those images, and the timing parameters used in the analysis. A full description of the online archive is given in Appendix B of the preprint. Upon final publication, this catalog will also be generated as a BROWSE table that will be linked to this page.
The LAT Second Pulsar Catalog is available as a .tgz (tarred and zipped) archive file. The archive includes a main catalog FITS file with the data from the paper tables, images of the light curve and spectral energy distributions (SEDs) for each pulsar, FITS files containing the data points used in those images, and the timing parameters used in the analysis. A full description of the online archive is given in Appendix B of the preprint. Upon final publication, this catalog will also be generated as a BROWSE table that will be linked to this page.
The LAT Second Pulsar Catalog is available as a .tgz (tarred and zipped) archive file. The archive includes a main catalog FITS file with the data from the paper tables, images of the light curve and spectral energy distributions (SEDs) for each pulsar, FITS files containing the data points used in those images, and the timing parameters used in the analysis. A full description of the online archive is given in Appendix B of the preprint. Upon final publication, this catalog will also be generated as a BROWSE table that will be linked to this page.
The LAT Second Pulsar Catalog is available as a .tgz (tarred and zipped) archive file. The archive includes a main catalog FITS file with the data from the paper tables, images of the light curve and spectral energy distributions (SEDs) for each pulsar, FITS files containing the data points used in those images, and the timing parameters used in the analysis. A full description of the online archive is given in Appendix B of the preprint. Upon final publication, this catalog will also be generated as a BROWSE table that will be linked to this page.
The LAT Second Pulsar Catalog is available as a .tgz (tarred and zipped) archive file. The archive includes a main catalog FITS file with the data from the paper tables, images of the light curve and spectral energy distributions (SEDs) for each pulsar, FITS files containing the data points used in those images, and the timing parameters used in the analysis. A full description of the online archive is given in Appendix B of the preprint. Upon final publication, this catalog will also be generated as a BROWSE table that will be linked to this page.
The following is a compilation of all publicly-announced gamma-ray pulsars detected using the Fermi LAT. Each of the detections has been vetted by the LAT team, typically requiring a pulsed-detection significance of at least 5 sigma before announcement. We attempt to ensure that the information presented here is correct, but we strongly encourage users to consult the cited literature as the definitive source of information. Note that this list does not include all pulsars found in radio searches of LAT sources or other radio pulsars associated with LAT sources unless gamma-ray pulsations have been detected. To prevent inadvertent disclosure of private information, Edot column is only populated for pulsars whose discoveries have already been published, not just announced at a conference. Another warning: Edots in this list are NOT corrected for the Shklovskii effect.
Timing pulsars with the LAT requires the use of an ephemeris that covers the time period being analyzed. Below are several resources to provide this useful input to your analysis.
All analysis results presented here are preliminary and are not intended as an official catalog of Fermi-LAT detected GRBs. Please consult the table's caveat page for analysis details and other important information.
The Galactic model is a spatial and spectral template. The model for the Galactic diffuse emission was developed using spectral line surveys of HI and CO (as a tracer of H2) to derive the distribution of interstellar gas in Galactocentric rings. Infrared tracers of dust column density were used to correct column densities in directions where the optical depth of HI was either over or under-estimated. The model of the diffuse gamma-ray emission was then constructed by fitting the gamma-ray emissivities of the rings in several energy bands to the LAT observations.
Fermi is a powerful space observatory that will open a wide window on the universe. Gamma rays are the highest-energy form of light, and the gamma-ray sky is spectacularly different from the one we perceive with our own eyes. With a huge leap in all key capabilities, Fermi data will enable scientists to answer persistent questions across a broad range of topics, including supermassive black-hole systems, pulsars, the origin of cosmic rays, and searches for signals of new physics.
This table lists all of the triggers observed by one or more of the 14 GBM detectors (12 NaI and 2 BGO). Note that there are two Browse catalogs resulting from GBM triggers. All GBM triggers are entered in the Trigger Catalog, but only those triggers classified as bursts are entered in the Fermi GBM Burst Catalog. Thus, a burst will be found in both the Trigger and Burst Catalogs. The Burst Catalog analysis requires human intervention; therefore, GRBs will be entered in the Trigger Catalog before the Burst Catalog. The latency requirements are 1 day for triggers and 3 days for bursts.
This table lists all of the triggers observed by a subset of the 14 GBM detectors (12 NaI and 2 BGO) which have been classified as gamma-ray bursts (GRBs). Note that there are two Browse catalogs resulting from GBM triggers. All GBM triggers are entered in the Fermi GBM Trigger Catalog, while only those triggers classified as bursts are entered in the Burst Catalog. Thus, a burst will be found in both the Trigger and Burst Catalogs. The Burst Catalog analysis requires human intervention; therefore, GRBs will be entered in the Trigger Catalog before the Burst Catalog. The latency requirements are 1 day for triggers and 3 days for bursts.
The Fermi GBM Daily Data database table contains entries for each day for which GBM data has been processed.
The Fermi Gamma-Ray Burst Monitor (GBM) is not a pointed or imaging instrument. To determine fluxes for known sources, we measure the change in the count rate observed in the NaI (or BGO) detectors when the source enters or exits Earth occultation. The measured counts in each energy channel are converted to fluxes using an assumed spectrum for each source. For these measurements we currently use CTIME data, with 0.256-s resolution and 8 energy channels covering 8 keV to 1 MeV. Our technique uses all 8 energy channels, but for most sources the majority of the signal is in the 12-25 keV and 25-50 keV bands. The fluxes listed in the table are for the 12-25 keV band and are the mission long average, the 5-day average flux for the most recent 5 days, and the 2-day average flux for the most recent 2 days. The fluxes are normalized to units of mCrab based on the Crab flux over the period from MJD 54690 to 54790, during which the Crab flux is relatively constant as measured by GBM.
For each source we plot the history of pulse frequency and pulsed flux measured using the Fermi Gamma-Ray Burst Monitor (GBM) NaI detectors. For these measurements we use the CTIME data which normally has 0.256 s time bins, and eight energy channels. Our analysis normally uses channels 1 (12-25 keV) and 2 (25-50 keV). The integration interval used varies from source to source, ranging from one to four days. For eclipsing systems each egress to ingress interval is divided into an integral number of equal parts, with no measurement made during the eclipse. The measured frequencies are barycentered. For sources where the binary orbit is known, the frequencies are corrected for the binary motion. The R.M.S. pulsed flux is given in the energy band in which the pulse search was made.
This List is based on GCN Circulars issued by the GBM collaboration.
This utility permits you to download the most current version of the spacecraft (FT2) file predicting the LAT's pointing for a given mission week. The FT2 file is a FITS-formatted file describing Fermi's position and orientation, and thus the LAT's pointing, as a function of time. The FT2 files available here are created in planning Fermi's timeline, and thus provide the observatory's predicted pointing for a given mission week. Files with the string 'PRELIM' in the filename are produced approximately three weeks in advance, while files with 'FINAL' in the filename describe the timeline that will be uploaded to the spacecraft; thus you should use the latter if available. Note that the actual LAT pointing may differ from the predicted as a result of Target-of-Opportunity observations or Autonomous Repoints in response to a bright gamma-ray burst.
This is a compilation of sources in major blazar monitoring programs. This list contains all blazars known to be regularly monitored, plus all the MOJAVE- & Boston U.- monitored AGNs and known TeV blazars
The monitoring data shown on this site provides near real-time results from Swift observations of Fermi-LAT "sources of interest" and flaring sources. While this list is dominated by blazars, some X-ray binaries and Galactic transients are also included. The preliminary results on this page are intended to provide rapid feedback to the scientific community to aid in target of opportunity planning, multiwavelength campaigns, and planning of interesting scientific publications.
The VLBA Imaging and Polarimetry Survey, VIPS for short, is a combined 5 GHz and 15 GHz survey with the Very Long Baseline Array of ~1100 active galactic nuclei (AGN) with full polarization and high dynamic range. The parent sample is the CLASS survey in the region covered by the Sloan Digital Sky Survey in order to facilitate multi-wavelength science.
Since it is not possible to predict when a Gamma-Ray Burst (GRB) occurs, the follow-up ground telescopes must be distributed as uniform as possible all over the world in order to collect simultaneous data with the Swift detections. Based on the three-year operations of Swift, however, we noticed the distinct gap in follow-up coverage in the eastern U.S. region (Figure 1). This fact motivated us to construct a fully automated optical telescope here at GSFC.
This web page shows the light curves of a total of 163 AGNs that are monitored by KAIT with average cadence of 3 days. These are unfiltered observations; in practice, they correspond roughly to the R band (see Li et al. 2003, PASP, 115, 844).
Observations for the initial PSRPI sample of 60 pulsars have now concluded. 84.7 hours were observed on the VLBA (plus 12 hours from a pilot project) searching for in-beam calibrators around 245 pulsars, and 690.2 hours were utilised for 285 astrometric observations.
The Fermi Gamma-ray Space Telescope was launched in June 2008 to explore high-energy phenomena in the Universe.  This GI program is targeted specifically at Fermi observations of high-energy solar phenomena, primarily solar flares.  We provide quicklook products, data archives, and analysis software covering the solar X-ray and gamma-ray observations of both the Gamma-ray Burst Monitor (GBM) and Large Area Telescope (LAT), with the objective of facilitating and encouraging the broad use of Fermi data by the international solar physics community.
Autonomous flare finder identifies all flares ≥ GOES C-Class detected by GBM above 10 keV.  (FITS file)
Time periods when the >100 MeV fluxes computed via the light-bucket method deviate significantly from the mean level during a 4-day period.
Time histories of NaI, GBO, and GOES data, with flare and day/night markers. Orbital plots are on RHESSI orbit times.
Time histories of NaI, GBO, and GOES data, with flare and day/night markers. Orbital plots are on RHESSI orbit times.
Time histories of NaI, GBO, and GOES data, with flare and day/night markers. Orbital plots are on RHESSI orbit times.
Time-dependent detector response matrices for each GBM detector covering the duration of every GBM flare.  Needed in the spectral analysis software to relate observed count-rate spectra to model photon spectra. Suitable for analyzing CPEC and CTIME data.
LAT solar gamma-ray flux > 100 MeV, one point per solar exposure (i.e. average of the 20-40 minutes of solar observation every ~1.5 hours) calculated by two different methods.
LAT solar gamma-ray flux > 100 MeV, one point per solar exposure (i.e. average of the 20-40 minutes of solar observation every ~1.5 hours) calculated by two different methods.
LAT solar gamma-ray flux > 100 MeV, one point per solar exposure (i.e. average of the 20-40 minutes of solar observation every ~1.5 hours) calculated by two different methods.
LAT data between 100 MeV and 10 GeV filtered for solar counts in 1-minute time bins, no energy binning, using light-bucket method.  Contains exposure (cm^2 s) information.
For GBM, input is daily or trigger CSPEC or CTIME file from Fermi archive and corresponding response file from our archive.  For LAT, input is daily spectrum file and corresponding response file, both from our archive.
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ACRIMSAT studies the sun's energy output with uniform sensitivity to improve knowledge of the sun's role in global change.
ACRIMSAT studies the sun's energy output with uniform sensitivity to improve knowledge of the sun's role in global change.
Advanced Composition Explorer (ACE) observes particles of solar, interplanetary, interstellar, and galactic origins.
The Advanced Crew Escape Suit (ACES) is a full pressure vessel providing an atmosphere of protection. Polygons: 44656 Vertices: 44684
The Advanced Crew Escape Suit (ACES) is a full pressure vessel providing an atmosphere of protection. Polygons: 44656 Vertices: 44684
AIM is a two-year mission to study Polar Mesospheric Clouds (PMCs), the Earth's highest clouds, which form an icy membrane 50 miles (80.4 km) above the surface at the edge of space.
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Aqua, Latin for water, is a NASA Earth Science satellite mission named for the large amount of information that the mission is collecting about the Earth's water cycle, including evaporation from the oceans, water vapor in the atmosphere, clouds, precipitation, soil moisture, sea ice, land ice, and snow cover on the land and ice. Additional variables also being measured by Aqua include radiative energy fluxes, aerosols, vegetation cover on the land, phytoplankton and dissolved organic matter in the oceans, and air, land, and water temperatures.
Aqua, Latin for water, is a NASA Earth Science satellite mission named for the large amount of information that the mission is collecting about the Earth's water cycle, including evaporation from the oceans, water vapor in the atmosphere, clouds, precipitation, soil moisture, sea ice, land ice, and snow cover on the land and ice. Additional variables also being measured by Aqua include radiative energy fluxes, aerosols, vegetation cover on the land, phytoplankton and dissolved organic matter in the oceans, and air, land, and water temperatures.
Aqua carries six state-of-the-art instruments to observe the Earth's oceans, atmosphere, land, ice and snow covers, and vegetation, providing high measurement accuracy, spatial detail, and temporal frequency. This comprehensive approach to data collection enables scientists to study the interactions among the four spheres of the Earth system -- the oceans, land, atmosphere, and biosphere.
Polygons: 6012 Vertices: 8418
Aquarius is making NASA's first space-based global observations of ocean surface salinity, flying 657 kilometers (408 miles) above Earth in a sun-synchronous polar orbit that repeats every seven days. This NASA Earth System Science Pathfinder mission is mapping global changes in ocean surface salinity with a resolution of 150 kilometers (93 miles), showing how salinity changes from month to month, season to season and year to year. Scientists are combining Aquarius data with in-water measurements to generate operational maps of ocean salinity distribution.
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A model of an astronaut. Polygons: 6381 Vertices: 3739
A model of an astronaut’s glove. Polygons: 490 Vertices: 842
Aura observes the chemical content of the atmosphere to track the state of the ozone layer and the dispersion of airborne pollution. Polygons: 6 Vertices: 4
Aura observes the chemical content of the atmosphere to track the state of the ozone layer and the dispersion of airborne pollution.
Aura observes the chemical content of the atmosphere to track the state of the ozone layer and the dispersion of airborne pollution.
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The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite provides new insight into the role that clouds and atmospheric aerosols (airborne particles) play in regulating Earth's weather, climate, and air quality.
Polygons: 663 Vertices: 1080
Cassini spacecraft from SPACE rendering package, built by Michael Oberle under NASA contract at JPL. Includes orbiter only, Huygens probe detached. Accurate except no thermal blanketing is shown (this would cover most of the central structure of the spacecraft). Polygons: 9956 Vertices: 8130
Cassini spacecraft model.
Cassini spacecraft model.
Includes orbiter from CAD models. Accurate (to a fault) except no thermal blanketing is shown (this would cover most of the central structure of the spacecraft). Polygons: 478358 Vertices: 237633
Launched in April 2006, CloudSat monitors the state of the Earth’s atmosphere and weather with a sophisticated radar system. The instrument, jointly developed with the Canadian Space Agency, can predict which clouds produce rain, observe snowfall, and monitor the moisture content of clouds.
Polygons: 182 Vertices: 264
Originally designed to carry the towering Saturn V moon rocket from the Vehicle Assembly Building to the seaside launch site, the enormous transporters now carry the space shuttles to the launch pads for liftoff. Polygons: 146050 Vertices: 141658
Originally designed to carry the towering Saturn V moon rocket from the Vehicle Assembly Building to the seaside launch site, the enormous transporters now carry the space shuttles to the launch pads for liftoff. Polygons: 146050 Vertices: 141658
Crew lock bag. Polygons: 405 Vertices: 514
This .stl file was produced by scaling the original model and converting it directly to .stl format.
This .stl file was produced by scaling the original model and converting it directly to .stl format.
This .stl file was produced by scaling the original model and converting it directly to .stl format.
This .stl file was produced by scaling the original model and converting it directly to .stl format.
Dish Post. Polygons: 506 Vertices: 448
Dish Turntable. Polygons: 552 Vertices: 630
This .stl file was produced by scaling the original model and converting it directly to .stl format.
This .stl file was produced by scaling the original model and converting it directly to .stl format.
This .stl file was produced by scaling the original model and converting it directly to .stl format.
Earth Observing-1 (EO-1) is an advanced land-imaging mission that will demonstrate new instruments and spacecraft systems.
Polygons: 650 Vertices: 405
The current spacesuit is a complex garment. Not only does it protect from the extreme conditions of space, it is in itself a mobile life support system with an oxygen supply, electrical power, water-cooling equipment, ventilating fan, and an in-suit drink bag. Polygons: 172056 Vertices: 173044
The current spacesuit is a complex garment. Not only does it protect from the extreme conditions of space, it is in itself a mobile life support system with an oxygen supply, electrical power, water-cooling equipment, ventilating fan, and an in-suit drink bag. Polygons: 172056 Vertices: 173044
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Polygons: 164622 Vertices: 94843
Galileo spacecraft model.
Launch Complex 39's Pad A and Pad B were originally designed to support the Apollo program and were modified for Space Shuttle launch operations. Polygons: 99030 Vertices: 93625
Launch Complex 39's Pad A and Pad B were originally designed to support the Apollo program and were modified for Space Shuttle launch operations. Polygons: 99030 Vertices: 93625
Galileo spacecraft model. Polygons: 13414 Vertices: 6670
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The Gemini spacesuit had a combination of a pressure bladder and a link-net restraint layer that made the whole suit flexible when pressurized. Polygons: 57594 Vertices: 57638
The Gemini spacesuit had a combination of a pressure bladder and a link-net restraint layer that made the whole suit flexible when pressurized. Polygons: 57594 Vertices: 57638
The ability of the Global Hawk air vehicle to autonomously fly long distances and remain aloft for extended periods of time means that measuring, monitoring, and observing remote locations of the Earth's surface are now possible. Polygons: 19140 Vertices: 18620
The ability of the Global Hawk air vehicle to autonomously fly long distances and remain aloft for extended periods of time means that measuring, monitoring, and observing remote locations of the Earth's surface are now possible. Polygons: 19140 Vertices: 18620
GRACE (Gravity Recovery and Climate Experiment), twin satellites launched in March 2002, are making detailed measurements of Earth's gravity field which will lead to discoveries about gravity and Earth's natural systems. These discoveries could have far-reaching benefits to society and the world's population.
GRACE (Gravity Recovery and Climate Experiment), twin satellites launched in March 2002, are making detailed measurements of Earth's gravity field which will lead to discoveries about gravity and Earth's natural systems. These discoveries could have far-reaching benefits to society and the world's population.
Polygons: 38840 Vertices: 22394
Polygons: 38840 Vertices: 22394
Headquarters building model.
Astronaut’s helmet model.
Hubble Space Telescope (HST) Servicing Mission 4 (SM4) Carriers: For more information about the carriers see http://asd.gsfc.nasa.gov/archive/sm4/multimedia/gallery3.html#carriers
Hubble Space Telescope (HST).
Hubble Space Telescope (HST). Polygons: 7672 Vertices: 5122
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ICESat (Ice, Cloud, and land Elevation Satellite) is the benchmark Earth Observing System mission for measuring ice sheet mass balance, cloud and aerosol heights, as well as land topography and vegetation characteristics.
Polygons: 976 Vertices: 1142
Infrared camera.
Model of the ISS. Polygons: 6628 Vertices: 7239
Model of the ISS. Polygons: 175083 Vertices: 89501
A very high resolution model of the International Space Station in many parts. The download includes an image of the final configuration. This model is provided in its original Lightwave format, which preserves the configuration of the component parts. This model dates from February 2011.
The James Webb Space Telescope (JWST) will be a large infrared telescope with a 6.5-meter primary mirror. The project is working to a 2018 launch date. The JWST will study every phase in the history of our Universe, ranging from the first luminous glows after the Big Bang, to the formation of solar systems capable of supporting life on planets like Earth, to the evolution of our own Solar System. Interact with this 3D model of the James Webb Space Telescope and to explore all the different parts of it at http://www.nasa.gov/externalflash/webb3d/
Jason 1 is an oceanography mission to monitor global ocean circulation, study the ties between the oceans and atmosphere, improve global climate forecasts and predictions, and monitor events.
JSC Mission Control Room. Polygons: 11130 Vertices: 6068
Model of the Jupiter-C spacecraft. Polygons: 9299 Vertices: 5684
The Kepler Mission is specifically designed to survey a portion of our region of the Milky Way galaxy to discover Earth-sized planets in or near the habitable zones of their stars and determine how many of the billions of stars in our galaxy have such planets. Kepler was launched in March 2009.
Model of the Kepler spacecraft. Polygons: 372 Vertices: 418
The Kepler Mission is specifically designed to survey a portion of our region of the Milky Way galaxy to discover Earth-sized planets in or near the habitable zones of their stars and determine how many of the billions of stars in our galaxy have such planets. Kepler was launched in March 2009. This package includes models of Kepler, the photometer, and the solar array. By Ball Aerospace.
The Landsat Program is a series of Earth-observing satellite missions jointly managed by NASA and the U.S. Geological Survey. Since 1972, Landsat satellites have collected information about Earth from space.
Model of the Magellan spacecraft.
Both the JSC Mark III and the ARC AX-5 suit have been designed to operate at a pressure of 8.3 psi. Current space shuttle spacesuits operate at 4.3 psi and require a time-consuming pre-breathing operation prior to the beginning of any spacewalk. Polygons: 34892 Vertices: 35222
Both the JSC Mark III and the ARC AX-5 suit have been designed to operate at a pressure of 8.3 psi. Current space shuttle spacesuits operate at 4.3 psi and require a time-consuming pre-breathing operation prior to the beginning of any spacewalk. Polygons: 34892 Vertices: 35222
Model of the Mars Global Surveyor spacecraft. Polygons: 3543 Vertices: 4754
Model of the Mars Global Surveyor spacecraft. Polygons: 19314 Vertices: 10250
Model of the Mars Global Surveyor spacecraft. Polygons: 19314 Vertices: 10250
Model of the Mars Global Surveyor spacecraft. Polygons: 19314 Vertices: 10236
Model of the Mars Global Surveyor spacecraft. Polygons: 19314 Vertices: 10236
MER Opportunity. Polygons: 3766 Vertices: 4802
Mercury spacesuit. Polygons: 55366 Vertices: 55460
Mercury spacesuit. Polygons: 55366 Vertices: 55460
Mir. Polygons: 5836 Vertices: 3111
Mir. Polygons: 124 Vertices: 86
Mars Reconnaissance Orbiter Polygons: 1232 Vertices: 1478
Model of NEAR spacecraft.
Polygons: 3794 Vertices: 2776
OSTM/Jason-2's primary payload includes five instruments similar to those aboard Jason-1, along with three experimental instruments. Its main instrument is an altimeter that precisely measures the distance from the satellite to the ocean surface. Its radiometer measures the amount of water vapor in the atmosphere, which can distort the altimeter measurements. Three location systems combine to measure the satellite's precise position in orbit.
Polygons: 976 Vertices: 595
NASA's Quick Scatterometer (QuikSCAT) is equipped with a specialized microwave radar that measures near-surface wind speed and direction under all weather and cloud conditions over Earth's oceans.
Polygons: 272  Vertices: 248
Model of the ISS. Polygons: 6628 Vertices: 7239
A collection of interchangeable satellite parts: bodies, radios, and solar panels.
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A high resolution Shuttle made up of several models, allowing the user to animate the doors and gimbal the engines.
A high resolution Shuttle made up of several models, allowing the user to animate the doors and gimbal the engines.
Polygons: 2476  Vertices: 1353
Polygons: 2476  Vertices: 1353
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Includes External Tank, EVA Suit, Payload, and Solid Rocket Booster.
Skylab model. Polygons: 27533 Vertices: 15041
The Solar Radiation and Climate Experiment (SORCE) is a NASA-sponsored satellite mission that is providing state-of-the-art measurements of incoming x-ray, ultraviolet, visible, near-infrared, and total solar radiation.
Polygons: 11582 Vertices: 8040
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NASA launched the Earth Observing System's flagship satellite Terra, named for Earth, on December 18, 1999. Terra has been collecting data about Earth's changing climate.
Model of the Tether spacecraft.
Polygons: 6246 Vertices: 5992
The Tropical Rainfall Measuring Mission (TRMM) is a joint mission between NASA and the Japan Aerospace Exploration Agency (JAXA) designed to monitor and study tropical rainfall.
Model of the Ulysses spacecraft.
The Vehicle Assembly Building (VAB) is one of the largest buildings in the world. It was originally built for assembly of Apollo/Saturn vehicles and was later modified to support Space Shuttle operations. Polygons: 3528 Vertices: 3388
The Vehicle Assembly Building (VAB) is one of the largest buildings in the world. It was originally built for assembly of Apollo/Saturn vehicles and was later modified to support Space Shuttle operations. Polygons: 3528 Vertices: 3388
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Model of wrench.
The WMTS implementation standard provides a standards-based solution for serviing digital maps using predefined image tiles.  Through the constructs of the specification, a WMTS service advertises imagery layers (e.g. imagery product) and defines the coordinate reference system, scale, and tiling grid available for access.
The TWMS specification is a custom extension to the OGS WMS standard developed by the NASA Jet Propulsion Laboratory.  Similar to the OGC WMTS specification, TWMS introduces a 'tiled' approach to imagery requests so that tiles may be pre-generated and cached for fast response.  Unlike WMTS, the TWMS standard retains the usage of requests containing geographic coordinates for imagery.  However, it only responds to a limited number of predefined geographic regions, creating a gridded access pattern.
The KML documentation standard provides a solution for imagery integration into mapping tools that utilize support the KML standard, specifically Google Earth.  Using the constructs of the KML standard, GIBS infuses links to the TWMS web service endpoints to faclitate imagery viewing within supporting tools.  A custom KML generation endpoint is provided by GIBS to dynamically generate KML documents.
GDAL is an open source translator library for raster geospatial data formats that presents a single abstract data model to the calling application for all supported formats. By providing integration into the GDAL command line utilities, GIBS imagery can be easily included in imagery processing workflows, including bulk access.
PDS Data Dictionary.
CRaTER, DLRE, LAMP, LEND, LOLA, LROC
APXS, Atmospheric Opacity, HAZCAM, NAVCAM, MI, PANCAM, RAT, Rover Motion Counter, SPICE
EPPS, GRNS, MAG, MASCS, MDIS, MLA, RSS, SPICE, XRS
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SPICE
SHARAD
SHARAD
APXS, ChemCam, CheMin, DAN, Hazcam, MAHLI, MARDI, Mastcam, Navcam, RAD, REMS, SAM, SPICE
SHARAD
CIRS, HRD, INMS, ISS, MAG, MIMI, RADAR, RPWS, RSS, SPICE, UVIS, VIMS
CGRS, RADIO SCIENCE (Releases 142-144), SPICE, THEMIS
LGRS
CRaTER, DLRE, LAMP, LEND, LOLA, LROC, SPICE
APXS, HAZCAM, NAVCAM, MI, PANCAM, RAT, Rover Motion Counter, SPICE
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SPICE
Nasaview (3.11.0)
Data Dictionary and Index Files (1r92)
CIRS, HRD, INMS, ISS, MAG, MIMI, RADAR, RPWS, RSS, SPICE, VIMS
GRS, RADIO SCIENCE (Releases 139-141), SPICE, THEMIS
LGRS
APXS, ChemCam, CheMin, DAN, Hazcam, MAHLI, MARDI, Mastcam, Navcam, RAD, REMS, SAM, SPICE
CRaTER, DLRE, LAMP, LEND, LOLA, LROC, RSS
RSS
PDS Software Release Validation Tool (2.5.0)
PDS Software Release Validation Tool (2.5.0)
PDS Software Release Product Tools (3.4.0)
EPPS, GRNS, MAG, MASCS, MDIS, MLA, RSS, SPICE, XRS
APXS, Atmospheric Opacity, HAZCAM, NAVCAM, MI, PANCAM, RAT, Rover Motion Counter, SPICE
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SPICE
Data dictionary and index files version 1r91.
GRS, RADIO SCIENCE (Releases 136-138), SPICE, THEMIS
CIRS, ISS, RADAR, RSS, SPICE, VIMS
CRaTER, DLRE, LAMP, LEND, LOLA, LROC
APXS, ChemCam, DAN, Hazcam, MAHLI, MARDI, Mastcam, Navcam, RAD, REMS, SPICE, SAM
APXS, ENG, HAZCAM, NAVCAM, MI, PANCAM, RAT, SPICE
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SPICE
LGRS
CDA, CIRS, INMS, ISS, MAG, MIMI, RADAR, RPWS, RSS, SPICE, UVIS, VIMS
GRS, RADIO SCIENCE (Releases 133-135), SPICE, THEMIS
Software release 3.10.0
CRaTER, DLRE, LAMP, LEND, LOLA, LROC
EPPS, GRNS, MAG, MASCS, MDIS, MLA, XRS
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SPICE
APXS, ChemCam, DAN, Hazcam, MAHLI, MARDI, Mastcam, Navcam, RAD, REMS, SPICE, SAM
APXS, ENG, HAZCAM, NAVCAM, MI, PANCAM, RAT, SPICE
PDS Software Release Validation Tool (2.4.0)
PDS Software Release Product Tools (3.3.0)
PDS Data Dictionary (1r90)
CIRS, INMS, ISS, MAG, MIMI, RADAR, RSS, SPICE, UVIS, VIMS
GRS, RADIO SCIENCE (Releases 130-132), SPICE, THEMIS
CRaTER, DLRE, LAMP, LEND, LOLA, LROC, RSS
LGRS, RSS, SPICE
APXS, ChemCam, DAN, Hazcam, MAHLI, MARDI, Mastcam, Navcam, REMS, SPICE, SAM
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SPICE
APXS, Atmospheric Opacity, HAZCAM, NAVCAM, MI, PANCAM, RAT, Rover Motion Counter, SPICE
CAPS, CDA, CIRS, HRD, INMS, ISS, MAG, MIMI, RADAR, RPWS, RSS, SPICE, UVIS, VIMS
GRS, RADIO SCIENCE (Releases 127-129), SPICE, THEMIS
Data dictionary and index files.
APXS, ChemMin, Hazcam, Navcam, REMS, SAM
CRaTER, DLRE, LAMP, LEND, LOLA, LROC, SPICE
EPPS, GRNS, MAG, MASCS, MDIS, MLA, SPICE, XRS
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SPICE
APXS, ChemCam, DAN, Hazcam, Navcam, REMS, SPICE
APXS, Atmospheric Opacity, HAZCAM, NAVCAM, MI, PANCAM, RAT, Rover Motion Counter, SPICE
CIRS, ISS, RADAR, RPWS, SPICE, UVIS, VIMS
GRS, RADIO SCIENCE (Releases 124-126), SPICE, THEMIS
LGRS, RSS, SPICE
CRaTER, DLRE, LAMP, LEND, LOLA, LROC, Mini-RF, RSS
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
Data Dictionary and Index Files
APXS(EDRs), HAZCAM, NAVCAM, MI, MOESSBAUER (EDRs), PANCAM, Rover Motion Counter, SPICE
CIRS, ISS, RADAR, RPWS, RSS, SPICE, UVIS, VIMS
GRS, RADIO SCIENCE (Releases 121-123), SPICE, THEMIS
CRaTER, DLRE, LAMP, LEND, LOLA, LROC
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
Validation Tool (2.3.0)
Nasaview (3.9.0)
Data Dictionary and Index Files
CIPS, HRD, INMS, ISS, MAG, MIMI, RADAR, RPWS, RSS, SPICE, UVIS, VIMS
GRS, RADIO SCIENCE (Releases 118-120), SPICE, THEMIS
CRaTER, DLRE, LAMP, LEND, LOLA, LROC, Mini-RF, RSS
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
APXS, HAZCAM, NAVCAM, MI, MOESSBAUER (EDRs), PANCAM, Rock Abrasion Tool, Rover Motion Counter, SPICE
CAPS, HRD, INMS, ISS, MAG, MIMI, RADAR, SPICE, UVIS, VIMS
GRS, RADIO SCIENCE (Releases 115-117), SPICE, THEMIS
CRaTER, DLRE, LAMP, LEND, LOLA, LROC, Mini-RF, RSS
EPPS, GRNS, MAG, MASCS, MDIS, MLA, RSS, SPICE, XRS
PDS Data Dictionary and Index Files (1r86)
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
APXS, HAZCAM, NAVCAM, MI, PANCAM, Rock Abrasion Tool, Rover Motion Counter, SPICE
MRFFR, M3
GRS, RADIO SCIENCE (Releases 112-114), SPICE, THEMIS
ISS, RADAR, RPWS, RSS, SPICE, UVIS, VIMS
CRaTER, DLRE, LAMP, LEND, LOLA, LROC, Mini-RF
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
APXS, HAZCAM, NAVCAM, MI, PANCAM, Rock Abrasion Tool, Rover Motion Counter, SPICE
Data Dictionary and Index Files
M3
CAPS, CDA, INMS, ISS, MAG, MIMI, RPWS, RSS, SPICE, UVIS, VIMS
GRS, RADIO SCIENCE (Releases 109-111), SPICE, THEMIS
CRaTER, DLRE, LAMP, LEND, LOLA, LROC
EPPS, GRNS, MAG, MASCS, MDIS, MLA, RSS, SPICE, XRS
Data Dictionary and Index Files
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
Product Tools (3.2.0)
Product Tools (2.3.0)
APXS, HAZCAM, MI, Moessbauer, NAVCAM, PANCAM, Rock Abrasion Tool, Rover Motion Counter, SPICE
CAPS, HRD, INMS, ISS, MAG, MIMI, RADAR, RPWS, RSS, SPICE, UVIS, VIMS
GRS, RADIO SCIENCE (Releases 106-108), SPICE, THEMIS
CRaTER, DLRE, LAMP, LEND, LOLA, LROC, MRFLRO
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
Data Dictionary and Index Files
APXS, HAZCAM, MI, Moessbauer, NAVCAM, PANCAM, Rover Motion Counter, SPICE
PDS Software Release Tools Package (4.9)
CAPS, CDA, CIRS, HRD, INMS, ISS, MIMI, RADAR, RPWS, RSS, SPICE, UVIS, VIMS
GRS, Radio Science, SPICE, THEMIS
CRaTER, DLRE, LAMP, LEND, LOLA, LROC
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
APXS, HAZCAM, MI, NAVCAM, PANCAM, Rover Motion Counter, SPICE
Data Dictionary and Index Files
Catalog Ingest Tool (1.1.0)
Product Tools (3.1.0)
Validation Tools (2.2.0)
M3
CAPS, CIRS, HRD, INMS, ISS, MIMI, RADAR, RPWS, RSS, SPICE, UVIS, VIMS
CGRS, SPICE, THEMIS
CRAT, DLRE, LAMP, LEND, LOLA, LROC, MRFLRO
M3
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
Data Dictionary and Index Files
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
CDA, CIRS, HRD, ISS, MAG, RADAR, RPWS, RSS, SPICE, UVIS, VIMS
GRS, SPICE, THEMIS
RSS
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
RSS
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
Data Dictionary and Index Files
RDR
RSS
Agile, CCD47, Clio, MIR, NIR, NSP, PHOTDOC, PHOTGJON, TLP, VIS, VSP
CIRS, INMS, ISS, MAG, MIMI, RPWS, RSS, SPICE, VIMS
GRS, SPICE, THEMIS
RSS
CRAT, DLRE, LAMP, LEND, LOLA, LROC, MRFLRO
CRISM, HiRISE, MCS, RSS, SHARAD, SPICE
Nasaview (3.7.0)
RSS
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
Data Dictionary and Index Files
Data Dictionary and Index Files
GRS, SPICE, THEMIS
PDS Tools Package (4.8)
PDS Validation Tool (2.1.0)
EPPS, GRNS, MAG, MASCS, MDIS, MLA, RSS, SPICE, XRS
CRaTER, DLRE, LAMP, LEND, LOLA, LROC, Mini-RF
ACCELEROMETER, CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
Data Dictionary and Index Files (1r78)
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
Data Dictionary and Index Files
Nasaview (3.6.0)
HRD, ISS, RADAR, RPWS, RSS, SPICE, UVIS, VIMS
GRS, SPICE, THEMIS
Software Release Catalog Ingest Tool (1.0.0)
TES
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
Nasaview (3.5.0)
Nasaview (3.4.0)
Nasaview (3.3.0)
Nasaview (3.2.0)
Nasaview (3.1.0)
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
SHARAD
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
CRISM, CTX, HiRISE, MARCI, MCS, RSS, SHARAD, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, HAZCAM, MB, MI, MTES, NAVCAM, PANCAM, SPICE
APXS, DESCAM, HAZCAM, MB, MI, MTES, NAVCAM, tools
APXS, DESCAM, HAZCAM, MB, MI, MTES, NAVCAM, tools
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
Data Dictionary and Index Files
GRS
THEMIS, SPICE
GRS
ACCEL, THEMIS, SPICE
GRS, THEMIS, SPICE
GRS, THEMIS, SPICE
GRS, THEMIS, SPICE
GRS, THEMIS, SPICE
GRS, THEMIS, SPICE
GRS, THEMIS, SPICE
GRS, THEMIS, SPICE
GRS, THEMIS, SPICE
GRS, THEMIS, SPICE
GRS, THEMIS, SPICE
GRS, THEMIS, SPICE
GRS, THEMIS, SPICE
GRS, THEMIS, SPICE
GRS, THEMIS, SPICE
GRS (AND Data)
GRS, THEMIS, SPICE, RSS
GRS, THEMIS, SPICE
GRS, THEMIS, SPICE, RSS
THEMIS
GRS, SPICE, RSS
GRS, SPICE, THM
GRS
GRS, SPICE, THEMIS
GRS, MARIE, SPICE, THEMIS
GRS, MARIE, SPICE, THEMIS
GRS, MARIE, SPICE, THEMIS
CDA, CIRS, ISS, RADAR, RPWS, RSS, SPICE, UVIS, VIMS
CIRS, HRD, ISS, RPWS, RSS, SPICE, UVIS, VIMS
CDA, CIRS, ISS, RADAR, RPWS, RSS, SPICE, UVIS, VIMS
CDA, CIRS, ISS, RADAR, RSS, SPICE, UVIS, VIMS
CDA, CIRS, ISS, RADAR, RSS, SPICE, UVIS, VIMS
CDA, CIRS, HRD, INMS, ISS, RADAR, RSS, SPICE, UVIS, VIMS
CDA, CIRS, ISS, RADAR, RSS, SPICE, VIMS
CDA, CIRS, ISS, RADAR, RSS, SPICE, VIMS
CDA, CIRS, ISS, RADAR, RSS, UVIS, VIMS, SPICE
CDA, CIRS, ISS, RADAR, RSS, UVIS, VIMS, SPICE
CDA, CIRS, ISS, RADAR, RSS, UVIS, VIMS, SPICE
CDA, CIRS, RADAR, SPICE, UVIS
ISS, VIMS, RSS
CDA, ISS, UVIS, VIMS, RSS, RS
CDA, UVIS, RADAR
ISS, VIMS, RSS
ISS
CDA, SPICE, VIMS, RSS
RSS, MIMI, INMS, SPICE
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
RSS
ASE, MECA, MET, OM, RAC, SSI, TEGA, TT
ASE, MECA, MET, OM, RAC, SSI, TEGA, TT
ASE, MECA, MET, OM, RAC, SSI, TEGA, TT
EPPS, GRNS, MAG, MASCS, MDIS, MLA, RSS, SPICE, XRS
EPPS, GRNS, MAG, MASCS, MLA, RS, XRS
EPPS, GRNS, MAG, MASCS, MLA, RS, XRS
MRI, ITS
HRII, HRIV, MRI, ITS
ALICE, LEISA, LORRI, MVIC, PEPSSI, SDC, SWAP
PDS Validation Tool (2.0.1) and Product Tools (2.0.1)
PDS Validation Tool (1.2.0) and Product Tools (1.2.0)
PDS Validation Tool (1.1.0) and Product Tools (1.1.0)
PDS Validation Tool (1.0.0)
This data set includes 94 GHz co- and cross-polarized radar reflectivity. The Airborne Cloud Radar (ACR) sensor was mounted to a NASA P-3 aircraft flown over the Sea of Japan, the Western Pacific Ocean, and the Japanese Islands. The ACR data were acquired during the AMSR/AMSR-E Wakasa Bay Field Campaign in January and February 2003. Data are available in network Common Data Format (netCDF) from NSIDC via FTP.

The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) is a mission instrument launched aboard NASA's Aqua Satellite on 4 May 2002. The Wakasa Bay field campaign was designed to validate both AMSR and AMSR-E shallow rainfall and snowfall retrieval capabilities.
This data set includes 94 GHz co- and cross-polarized radar reflectivity. The Airborne Cloud Radar (ACR) sensor was mounted to a NASA P-3 aircraft flown over the Sea of Japan, the Western Pacific Ocean, and the Japanese Islands. The ACR data were acquired during the AMSR/AMSR-E Wakasa Bay Field Campaign in January and February 2003. Data are available in network Common Data Format (netCDF) from NSIDC via FTP.

The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) is a mission instrument launched aboard NASA's Aqua Satellite on 4 May 2002. The Wakasa Bay field campaign was designed to validate both AMSR and AMSR-E shallow rainfall and snowfall retrieval capabilities.
This data set includes 94 GHz co- and cross-polarized radar reflectivity. The Airborne Cloud Radar (ACR) sensor was mounted to a NASA P-3 aircraft flown over the Sea of Japan, the Western Pacific Ocean, and the Japanese Islands. The ACR data were acquired during the AMSR/AMSR-E Wakasa Bay Field Campaign in January and February 2003. Data are available in network Common Data Format (netCDF) from NSIDC via FTP.

The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) is a mission instrument launched aboard NASA's Aqua Satellite on 4 May 2002. The Wakasa Bay field campaign was designed to validate both AMSR and AMSR-E shallow rainfall and snowfall retrieval capabilities.
The Wakasa Bay Field Campaign was conducted in January and February 2003 to validate rainfall algorithms developed for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). The primary objective was to validate both AMSR and AMSR-E shallow rainfall and snowfall retrievals. An Airborne Multichannel Microwave Radiometer (AMMR) aboard a NASA P-3 Orion collected 37 GHz and 21 GHz brightness temperatures (TBs) and air temperatures on 14 January, 19 January, 21 January, and 03 February 2003. All measurements fall within 30.6763 deg N to 41.476 deg N, 134.0313 deg E to 150.3528 deg E. Data are in tab-delimited ASCII text format and are available via FTP.
The Wakasa Bay Field Campaign was conducted in January and February 2003 to validate rainfall algorithms developed for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). The primary objective was to validate both AMSR and AMSR-E shallow rainfall and snowfall retrievals. An Airborne Multichannel Microwave Radiometer (AMMR) aboard a NASA P-3 Orion collected 37 GHz and 21 GHz brightness temperatures (TBs) and air temperatures on 14 January, 19 January, 21 January, and 03 February 2003. All measurements fall within 30.6763 deg N to 41.476 deg N, 134.0313 deg E to 150.3528 deg E. Data are in tab-delimited ASCII text format and are available via FTP.
The Wakasa Bay Field Campaign was conducted in January and February 2003 to validate rainfall algorithms developed for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). The primary objective was to validate both AMSR and AMSR-E shallow rainfall and snowfall retrievals. An Airborne Multichannel Microwave Radiometer (AMMR) aboard a NASA P-3 Orion collected 37 GHz and 21 GHz brightness temperatures (TBs) and air temperatures on 14 January, 19 January, 21 January, and 03 February 2003. All measurements fall within 30.6763 deg N to 41.476 deg N, 134.0313 deg E to 150.3528 deg E. Data are in tab-delimited ASCII text format and are available via FTP.
The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) instrument on the NASA EOS Aqua satellite provides global passive microwave measurements of the Earth. NSIDC produces AMSR-E gridded brightness temperature data by interpolating AMSR-E data (6.9 GHz, 10.7 GHz, 18.7 GHz, 23.8 GHz, 36.5 GHz, and 89.0 GHz) to the output grids from swath space using an inverse-distance squared method. AMSR-E/Aqua L2A Global Swath Spatially-Resampled Brightness Temperatures (AE_L2A) input source data are used to create the gridded brightness temperature data.

These data are provided in one global cylindrical, equidistant latitude-longitude projection at 0.25 degree (quarter-degree) resolution. Spatial coverage is global, data are daily, and coverage begins 19 June 2002, and ends 27 September 2011.

Data are provided via FTP. Brightness temperature data (in tenths of kelvins) are two-byte unsigned integers and time files are two-byte signed integers.
The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) instrument on the NASA EOS Aqua satellite provides global passive microwave measurements of the Earth. NSIDC produces AMSR-E gridded brightness temperature data by interpolating AMSR-E data (6.9 GHz, 10.7 GHz, 18.7 GHz, 23.8 GHz, 36.5 GHz, and 89.0 GHz) to the output grids from swath space using an inverse-distance squared method. AMSR-E/Aqua L2A Global Swath Spatially-Resampled Brightness Temperatures (AE_L2A) input source data are used to create the gridded brightness temperature data.

These data are provided in one global cylindrical, equidistant latitude-longitude projection at 0.25 degree (quarter-degree) resolution. Spatial coverage is global, data are daily, and coverage begins 19 June 2002, and ends 27 September 2011.

Data are provided via FTP. Brightness temperature data (in tenths of kelvins) are two-byte unsigned integers and time files are two-byte signed integers.
The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) instrument on the NASA EOS Aqua satellite provides global passive microwave measurements of the Earth. NSIDC produces AMSR-E gridded brightness temperature data by interpolating AMSR-E data (6.9 GHz, 10.7 GHz, 18.7 GHz, 23.8 GHz, 36.5 GHz, and 89.0 GHz) to the output grids from swath space using an inverse-distance squared method. AMSR-E/Aqua L2A Global Swath Spatially-Resampled Brightness Temperatures (AE_L2A) input source data are used to create the gridded brightness temperature data.

These data are provided in one global cylindrical, equidistant latitude-longitude projection at 0.25 degree (quarter-degree) resolution. Spatial coverage is global, data are daily, and coverage begins 19 June 2002, and ends 27 September 2011.

Data are provided via FTP. Brightness temperature data (in tenths of kelvins) are two-byte unsigned integers and time files are two-byte signed integers.
This data set is a global land emissivity product using passive microwave observations from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). The data set complements existing land emissivity products from the Special Sensor Microwave Imager (SSM/I) and Advanced Microwave Sounding Unit (AMSU) by adding land emissivity estimates at two lower frequencies, 6.9 and 10.65 GHz (C- and X-band, respectively). Observations at these low frequencies penetrate deeper into the soil layer. Land surface emissivity estimates for this data set were collected at the following vertically and horizontally polarized (V-pol and H-pol) frequencies: 6.9, 10.65, 18.7, 23.8, 36.5, and 89.0 GHz. Ancillary data used in the analysis, such as surface skin temperature and cloud mask, were obtained from International Satellite Cloud Climatology Project (ISCCP). Atmospheric properties were obtained from TIROS Operational Vertical Sounder (TOVS) observations to determine the small upwelling and downwelling atmospheric emissions as well as the atmospheric transmission. The data set is in monthly format that is extracted from instantaneous emissivity estimates. Data are stored in HDF4 files and are available via FTP.
This data set is a global land emissivity product using passive microwave observations from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). The data set complements existing land emissivity products from the Special Sensor Microwave Imager (SSM/I) and Advanced Microwave Sounding Unit (AMSU) by adding land emissivity estimates at two lower frequencies, 6.9 and 10.65 GHz (C- and X-band, respectively). Observations at these low frequencies penetrate deeper into the soil layer. Land surface emissivity estimates for this data set were collected at the following vertically and horizontally polarized (V-pol and H-pol) frequencies: 6.9, 10.65, 18.7, 23.8, 36.5, and 89.0 GHz. Ancillary data used in the analysis, such as surface skin temperature and cloud mask, were obtained from International Satellite Cloud Climatology Project (ISCCP). Atmospheric properties were obtained from TIROS Operational Vertical Sounder (TOVS) observations to determine the small upwelling and downwelling atmospheric emissions as well as the atmospheric transmission. The data set is in monthly format that is extracted from instantaneous emissivity estimates. Data are stored in HDF4 files and are available via FTP.
This data set is a global land emissivity product using passive microwave observations from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). The data set complements existing land emissivity products from the Special Sensor Microwave Imager (SSM/I) and Advanced Microwave Sounding Unit (AMSU) by adding land emissivity estimates at two lower frequencies, 6.9 and 10.65 GHz (C- and X-band, respectively). Observations at these low frequencies penetrate deeper into the soil layer. Land surface emissivity estimates for this data set were collected at the following vertically and horizontally polarized (V-pol and H-pol) frequencies: 6.9, 10.65, 18.7, 23.8, 36.5, and 89.0 GHz. Ancillary data used in the analysis, such as surface skin temperature and cloud mask, were obtained from International Satellite Cloud Climatology Project (ISCCP). Atmospheric properties were obtained from TIROS Operational Vertical Sounder (TOVS) observations to determine the small upwelling and downwelling atmospheric emissions as well as the atmospheric transmission. The data set is in monthly format that is extracted from instantaneous emissivity estimates. Data are stored in HDF4 files and are available via FTP.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains Landsat-7 Enhanced Thematic Mapper Plus (ETM+) satellite imagery of the Bering Sea and Chukchi Sea areas to complement the joint in situ and aircraft Advanced Microwave Scanning Radiometer Sea Ice Product Validation (AMSRIce03) campaign conducted in March 2003.  The 150 m resolution images correspond to the panchromatic band (band 8), and were collected on 13, 15, 20, and 22 March 2003.  The total volume of this data set is approximately 161 megabytes.  Data are provided in binary image files with corresponding ENVI header files, and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains Landsat-7 Enhanced Thematic Mapper Plus (ETM+) satellite imagery of the Bering Sea and Chukchi Sea areas to complement the joint in situ and aircraft Advanced Microwave Scanning Radiometer Sea Ice Product Validation (AMSRIce03) campaign conducted in March 2003.  The 150 m resolution images correspond to the panchromatic band (band 8), and were collected on 13, 15, 20, and 22 March 2003.  The total volume of this data set is approximately 161 megabytes.  Data are provided in binary image files with corresponding ENVI header files, and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains Landsat-7 Enhanced Thematic Mapper Plus (ETM+) satellite imagery of the Bering Sea and Chukchi Sea areas to complement the joint in situ and aircraft Advanced Microwave Scanning Radiometer Sea Ice Product Validation (AMSRIce03) campaign conducted in March 2003.  The 150 m resolution images correspond to the panchromatic band (band 8), and were collected on 13, 15, 20, and 22 March 2003.  The total volume of this data set is approximately 161 megabytes.  Data are provided in binary image files with corresponding ENVI header files, and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains Moderate Resolution Imaging Spectroradiometer (MODIS) imagery of the Alaska, USA area, complementing the joint in situ and aircraft Advanced Microwave Scanning Radiometer Sea Ice Product Validation (AMSRIce03) campaign conducted in March 2003.  The images are visible imagery collected 13, 15, 16, 19, 20 and 22 March 2003.  The total volume of this data set is approximately 3 gigabytes.  Data are provided in binary image files with corresponding Environment for Visualizing Images (ENVI) header files, and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains Moderate Resolution Imaging Spectroradiometer (MODIS) imagery of the Alaska, USA area, complementing the joint in situ and aircraft Advanced Microwave Scanning Radiometer Sea Ice Product Validation (AMSRIce03) campaign conducted in March 2003.  The images are visible imagery collected 13, 15, 16, 19, 20 and 22 March 2003.  The total volume of this data set is approximately 3 gigabytes.  Data are provided in binary image files with corresponding Environment for Visualizing Images (ENVI) header files, and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains Moderate Resolution Imaging Spectroradiometer (MODIS) imagery of the Alaska, USA area, complementing the joint in situ and aircraft Advanced Microwave Scanning Radiometer Sea Ice Product Validation (AMSRIce03) campaign conducted in March 2003.  The images are visible imagery collected 13, 15, 16, 19, 20 and 22 March 2003.  The total volume of this data set is approximately 3 gigabytes.  Data are provided in binary image files with corresponding Environment for Visualizing Images (ENVI) header files, and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains photographic mosaics of sea ice in the Barrow, Alaska USA area as part of the joint in situ and aircraft AMSRIce03.  Photographs were taken from a Cessna 185 aircraft on 07 March 2003 and on 11 March 2003 using a Nikon digital camera.  Data are provided in four Adobe Photoshop files (.psd), and four corresponding Joint Photographic Experts Group (JPEG) files (.jpg) converted from the Photoshop files.  The total volume of the Photoshop set of files is approximately 133 MB and the total volume of the JPEG set of files is approximately 5 MB.  All files are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains photographic mosaics of sea ice in the Barrow, Alaska USA area as part of the joint in situ and aircraft AMSRIce03.  Photographs were taken from a Cessna 185 aircraft on 07 March 2003 and on 11 March 2003 using a Nikon digital camera.  Data are provided in four Adobe Photoshop files (.psd), and four corresponding Joint Photographic Experts Group (JPEG) files (.jpg) converted from the Photoshop files.  The total volume of the Photoshop set of files is approximately 133 MB and the total volume of the JPEG set of files is approximately 5 MB.  All files are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains photographic mosaics of sea ice in the Barrow, Alaska USA area as part of the joint in situ and aircraft AMSRIce03.  Photographs were taken from a Cessna 185 aircraft on 07 March 2003 and on 11 March 2003 using a Nikon digital camera.  Data are provided in four Adobe Photoshop files (.psd), and four corresponding Joint Photographic Experts Group (JPEG) files (.jpg) converted from the Photoshop files.  The total volume of the Photoshop set of files is approximately 133 MB and the total volume of the JPEG set of files is approximately 5 MB.  All files are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains ice thickness measurements collected over sea ice in the Barrow, Alaska area and at the Navy Ice Camp in the main pack ice of the Arctic Ocean as part of the joint in situ and aircraft AMSRIce03 campaign conducted in March 2003.  The ice thickness data were collected 09 March 2003 to 21 March 2003 using a Geonics EM31 electromagnetic induction device.  Data set parameters include sea ice conductivity, ocean salinity, snow depth, snow and ice thickness, and ice thickness.  The total volume of this data set is approximately 101 KB.  Data are provided in eight American Standard Code for Information Interchange (ASCII) text files, and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains ice thickness measurements collected over sea ice in the Barrow, Alaska area and at the Navy Ice Camp in the main pack ice of the Arctic Ocean as part of the joint in situ and aircraft AMSRIce03 campaign conducted in March 2003.  The ice thickness data were collected 09 March 2003 to 21 March 2003 using a Geonics EM31 electromagnetic induction device.  Data set parameters include sea ice conductivity, ocean salinity, snow depth, snow and ice thickness, and ice thickness.  The total volume of this data set is approximately 101 KB.  Data are provided in eight American Standard Code for Information Interchange (ASCII) text files, and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains ice thickness measurements collected over sea ice in the Barrow, Alaska area and at the Navy Ice Camp in the main pack ice of the Arctic Ocean as part of the joint in situ and aircraft AMSRIce03 campaign conducted in March 2003.  The ice thickness data were collected 09 March 2003 to 21 March 2003 using a Geonics EM31 electromagnetic induction device.  Data set parameters include sea ice conductivity, ocean salinity, snow depth, snow and ice thickness, and ice thickness.  The total volume of this data set is approximately 101 KB.  Data are provided in eight American Standard Code for Information Interchange (ASCII) text files, and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains snow depth measurements collected over sea ice in the Barrow, Alaska area and at the Navy Ice Camp in the main pack ice of the Arctic Ocean as part of the joint in situ and aircraft AMSRIce03 campaign conducted in March 2003.  The snow depth data, measured in situ using a self-recording depth probe, were collected 04 March 2003 to 19 March 2003.  The total volume of this data set is approximately 139 kilobytes.  Data are provided in four American Standard Code for Information Interchange (ASCII) text files, and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains snow depth measurements collected over sea ice in the Barrow, Alaska area and at the Navy Ice Camp in the main pack ice of the Arctic Ocean as part of the joint in situ and aircraft AMSRIce03 campaign conducted in March 2003.  The snow depth data, measured in situ using a self-recording depth probe, were collected 04 March 2003 to 19 March 2003.  The total volume of this data set is approximately 139 kilobytes.  Data are provided in four American Standard Code for Information Interchange (ASCII) text files, and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains snow depth measurements collected over sea ice in the Barrow, Alaska area and at the Navy Ice Camp in the main pack ice of the Arctic Ocean as part of the joint in situ and aircraft AMSRIce03 campaign conducted in March 2003.  The snow depth data, measured in situ using a self-recording depth probe, were collected 04 March 2003 to 19 March 2003.  The total volume of this data set is approximately 139 kilobytes.  Data are provided in four American Standard Code for Information Interchange (ASCII) text files, and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains snow ice temperature measurements collected over sea ice in the Barrow, Alaska USA area as part of the joint in situ and aircraft AMSRIce03 campaign conducted in March 2003.  The snow ice temperature data were collected on 13 March 2003 and on 20 March 2003.  Data set parameters are ice temperature, air temperature, snow/ice interface temperature, and snow depth.  Temperatures were measured using a thermistor probe.  Snow depth was measured with a self-recording depth probe.  The total volume of this data set is approximately 11 kilobytes.  Data are provided in five American Standard Code for Information Interchange (ASCII) text files and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains snow ice temperature measurements collected over sea ice in the Barrow, Alaska USA area as part of the joint in situ and aircraft AMSRIce03 campaign conducted in March 2003.  The snow ice temperature data were collected on 13 March 2003 and on 20 March 2003.  Data set parameters are ice temperature, air temperature, snow/ice interface temperature, and snow depth.  Temperatures were measured using a thermistor probe.  Snow depth was measured with a self-recording depth probe.  The total volume of this data set is approximately 11 kilobytes.  Data are provided in five American Standard Code for Information Interchange (ASCII) text files and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains snow ice temperature measurements collected over sea ice in the Barrow, Alaska USA area as part of the joint in situ and aircraft AMSRIce03 campaign conducted in March 2003.  The snow ice temperature data were collected on 13 March 2003 and on 20 March 2003.  Data set parameters are ice temperature, air temperature, snow/ice interface temperature, and snow depth.  Temperatures were measured using a thermistor probe.  Snow depth was measured with a self-recording depth probe.  The total volume of this data set is approximately 11 kilobytes.  Data are provided in five American Standard Code for Information Interchange (ASCII) text files and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains snow pit data collected over sea ice in the Barrow, Alaska, USA area and nearby at the Navy Ice Camp in the main pack ice of the Arctic Ocean. Measurements were collected as part of the joint in situ and aircraft AMSRIce03 campaign from 03 March to 23 March 2003.  Snow pit parameters include number of layers, average layer thickness, total thickness, Snow Water Equivalent (SWE), bulk density, hoar fraction, slab fraction, wet/icy fraction, new/recent fraction, and other fraction.  Data are provided in a single American Standard Code for Information Interchange (ASCII) text file, and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains snow pit data collected over sea ice in the Barrow, Alaska, USA area and nearby at the Navy Ice Camp in the main pack ice of the Arctic Ocean. Measurements were collected as part of the joint in situ and aircraft AMSRIce03 campaign from 03 March to 23 March 2003.  Snow pit parameters include number of layers, average layer thickness, total thickness, Snow Water Equivalent (SWE), bulk density, hoar fraction, slab fraction, wet/icy fraction, new/recent fraction, and other fraction.  Data are provided in a single American Standard Code for Information Interchange (ASCII) text file, and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains snow pit data collected over sea ice in the Barrow, Alaska, USA area and nearby at the Navy Ice Camp in the main pack ice of the Arctic Ocean. Measurements were collected as part of the joint in situ and aircraft AMSRIce03 campaign from 03 March to 23 March 2003.  Snow pit parameters include number of layers, average layer thickness, total thickness, Snow Water Equivalent (SWE), bulk density, hoar fraction, slab fraction, wet/icy fraction, new/recent fraction, and other fraction.  Data are provided in a single American Standard Code for Information Interchange (ASCII) text file, and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains surface roughness measurements collected over sea ice in the Barrow, Alaska USA area as part the joint in situ and aircraft AMSRIce03 campaign conducted in March 2003.  The surface roughness data were collected 16 March 2003.  Data set parameters are snow base, surface elevation, and snow depth measured in centimeters using a SmartStik rotating laser and self-reading rod.  The total volume of this data set is approximately 58 kilobytes.  Data are provided in two American Standard Code for Information Interchange (ASCII) text files, and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains surface roughness measurements collected over sea ice in the Barrow, Alaska USA area as part the joint in situ and aircraft AMSRIce03 campaign conducted in March 2003.  The surface roughness data were collected 16 March 2003.  Data set parameters are snow base, surface elevation, and snow depth measured in centimeters using a SmartStik rotating laser and self-reading rod.  The total volume of this data set is approximately 58 kilobytes.  Data are provided in two American Standard Code for Information Interchange (ASCII) text files, and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains surface roughness measurements collected over sea ice in the Barrow, Alaska USA area as part the joint in situ and aircraft AMSRIce03 campaign conducted in March 2003.  The surface roughness data were collected 16 March 2003.  Data set parameters are snow base, surface elevation, and snow depth measured in centimeters using a SmartStik rotating laser and self-reading rod.  The total volume of this data set is approximately 58 kilobytes.  Data are provided in two American Standard Code for Information Interchange (ASCII) text files, and are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument launched aboard NASA's Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains photographs of sea ice in the Chukchi and Beaufort Seas of the Arctic Ocean, and of snow cover off the northern coast of Alaska, USA. Photographs were taken from a P3 aircraft during six days in March 2006 using two Kodak digital DC4800 cameras. The images are available in Joint Photographic Experts Group (JPEG) file format. Also included are ASCII text files containing processing scripts, Global Positioning System (GPS) time data, and GPS data stream information. This data set is part of the joint in situ and aircraft AMSRIce06 campaign. The total volume of this data set is approximately 12 gigabytes. All files are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument that was launched aboard the NASA Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains photographs of sea ice in the Chukchi and Beaufort Seas of the Arctic Ocean, and of snow cover off the northern coast of Alaska, USA. Photographs were taken from a P3 aircraft during six days in March 2006 using two Kodak digital DC4800 cameras. The images are available in Joint Photographic Experts Group (JPEG) file format. Also included are ASCII text files containing processing scripts, Global Positioning System (GPS) time data, and GPS data stream information. This data set is part of the joint in situ and aircraft AMSRIce06 campaign. The total volume of this data set is approximately 12 gigabytes. All files are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument that was launched aboard the NASA Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains photographs of sea ice in the Chukchi and Beaufort Seas of the Arctic Ocean, and of snow cover off the northern coast of Alaska, USA. Photographs were taken from a P3 aircraft during six days in March 2006 using two Kodak digital DC4800 cameras. The images are available in Joint Photographic Experts Group (JPEG) file format. Also included are ASCII text files containing processing scripts, Global Positioning System (GPS) time data, and GPS data stream information. This data set is part of the joint in situ and aircraft AMSRIce06 campaign. The total volume of this data set is approximately 12 gigabytes. All files are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument that was launched aboard the NASA Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains Lidar measurements of sea ice in the Chukchi and Beaufort Seas of the Arctic Ocean, and of snow cover off the northern coast of Alaska, USA. The Lidar data were obtained by the Airborne Topographic Mapper (ATM) instrument mounted on a P3 aircraft during three days in March 2006. The data set includes airborne laser-ranging data, aircraft attitude, and GPS positioning information organized in 32-bit (4-byte) scaled binary format. Also included are ASCII text files containing processing scripts, latitude/longitude coordinates, and surface elevation corresponding to the ATM data. These data were collected as part of the joint in situ and aircraft AMSRIce06 campaign. The total volume of this data set is approximately 11 gigabytes. All files are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument that was launched aboard the NASA Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains Lidar measurements of sea ice in the Chukchi and Beaufort Seas of the Arctic Ocean, and of snow cover off the northern coast of Alaska, USA. The Lidar data were obtained by the Airborne Topographic Mapper (ATM) instrument mounted on a P3 aircraft during three days in March 2006. The data set includes airborne laser-ranging data, aircraft attitude, and GPS positioning information organized in 32-bit (4-byte) scaled binary format. Also included are ASCII text files containing processing scripts, latitude/longitude coordinates, and surface elevation corresponding to the ATM data. These data were collected as part of the joint in situ and aircraft AMSRIce06 campaign. The total volume of this data set is approximately 11 gigabytes. All files are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument that was launched aboard the NASA Aqua Satellite on 04 May 2002.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains Lidar measurements of sea ice in the Chukchi and Beaufort Seas of the Arctic Ocean, and of snow cover off the northern coast of Alaska, USA. The Lidar data were obtained by the Airborne Topographic Mapper (ATM) instrument mounted on a P3 aircraft during three days in March 2006. The data set includes airborne laser-ranging data, aircraft attitude, and GPS positioning information organized in 32-bit (4-byte) scaled binary format. Also included are ASCII text files containing processing scripts, latitude/longitude coordinates, and surface elevation corresponding to the ATM data. These data were collected as part of the joint in situ and aircraft AMSRIce06 campaign. The total volume of this data set is approximately 11 gigabytes. All files are available via FTP.

These data were collected as part of a validation study for the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). AMSR-E is a mission instrument that was launched aboard the NASA Aqua Satellite on 04 May 2002.
This data set provides a digital elevation model (DEM) for Antarctica to 81.5 degrees south latitude, at a resolution of 5 km. Approximately twenty million data points were used to generate this data set.  Data points were derived from ERS-1 radar altimetry during the geodetic phase from March 1994 to May 1995. The improved density in coverage and resolution, compared with past satellite altimetry missions, provides better detection of topographic detail such as surface undulations, ice streams, grounding zones, and interstream ridges.  DEM data are in a polar stereographic projection with the origin at the south pole, and are referenced to the OSU91A geoid.

The ERS-1 satellite radar altimeter measurements are highly useful for determining precise ice sheet elevations in Antarctica.  The orthometric heights derived from the ERS-1 data contribute to a more accurate and complete mapping of the Antarctic Ice Sheets than previously possible, and therefore to ongoing studies of ice mass balance studies in Antarctica.

The DEM is provided as a single ASCII text file, accessible by ftp. Data access is unrestricted, but we recommend that users register with us. Registered users automatically receive e-mail notification of product updates and changes to processing.
This data set provides a digital elevation model (DEM) for Antarctica to 81.5 degrees south latitude, at a resolution of 5 km. Approximately twenty million data points were used to generate this data set.  Data points were derived from ERS-1 radar altimetry during the geodetic phase from March 1994 to May 1995. The improved density in coverage and resolution, compared with past satellite altimetry missions, provides better detection of topographic detail such as surface undulations, ice streams, grounding zones, and interstream ridges.  DEM data are in a polar stereographic projection with the origin at the south pole, and are referenced to the OSU91A geoid.

The ERS-1 satellite radar altimeter measurements are highly useful for determining precise ice sheet elevations in Antarctica.  The orthometric heights derived from the ERS-1 data contribute to a more accurate and complete mapping of the Antarctic Ice Sheets than previously possible, and therefore to ongoing studies of ice mass balance studies in Antarctica.

The DEM is provided as a single ASCII text file, accessible by ftp. Data access is unrestricted, but we recommend that users register with us. Registered users automatically receive e-mail notification of product updates and changes to processing.
This data set provides a digital elevation model (DEM) for Antarctica to 81.5 degrees south latitude, at a resolution of 5 km. Approximately twenty million data points were used to generate this data set.  Data points were derived from ERS-1 radar altimetry during the geodetic phase from March 1994 to May 1995. The improved density in coverage and resolution, compared with past satellite altimetry missions, provides better detection of topographic detail such as surface undulations, ice streams, grounding zones, and interstream ridges.  DEM data are in a polar stereographic projection with the origin at the south pole, and are referenced to the OSU91A geoid.

The ERS-1 satellite radar altimeter measurements are highly useful for determining precise ice sheet elevations in Antarctica.  The orthometric heights derived from the ERS-1 data contribute to a more accurate and complete mapping of the Antarctic Ice Sheets than previously possible, and therefore to ongoing studies of ice mass balance studies in Antarctica.

The DEM is provided as a single ASCII text file, accessible by ftp. Data access is unrestricted, but we recommend that users register with us. Registered users automatically receive e-mail notification of product updates and changes to processing.
This compilation of recent ice velocity data of the Antarctic ice sheet is intended for use by the polar scientific community. The data are presented in tabular form (ASCII), containing latitude, longitude, speed, bearing, and error ranges. A metadata header describes the source of the data, the time of measurement, and gives details on measurement accuracy and precision. The tables are available for ftp transfer.

Web pages developed specifically for this data set provide detailed information for viewing and selecting the velocity data. These pages contain large satellite image maps (available as jpeg files). The data sets used to create these images were contributed by several investigators, generally from already published work. Both in situ and image-based methods are used.

References for the data sets are included with the data tables. If you have well-characterized Antarctic ice velocity data you would like to contribute to this site, please contact teds@icehouse.colorado.edu. If you have any questions concerning the relevance of these data to your work please contact NSIDC User Services.
This compilation of recent ice velocity data of the Antarctic ice sheet is intended for use by the polar scientific community. The data are presented in tabular form (ASCII), containing latitude, longitude, speed, bearing, and error ranges. A metadata header describes the source of the data, the time of measurement, and gives details on measurement accuracy and precision. The tables are available for ftp transfer.

Web pages developed specifically for this data set provide detailed information for viewing and selecting the velocity data. These pages contain large satellite image maps (available as jpeg files). The data sets used to create these images were contributed by several investigators, generally from already published work. Both in situ and image-based methods are used.

References for the data sets are included with the data tables. If you have well-characterized Antarctic ice velocity data you would like to contribute to this site, please contact teds@icehouse.colorado.edu. If you have any questions concerning the relevance of these data to your work please contact NSIDC User Services.
This compilation of recent ice velocity data of the Antarctic ice sheet is intended for use by the polar scientific community. The data are presented in tabular form (ASCII), containing latitude, longitude, speed, bearing, and error ranges. A metadata header describes the source of the data, the time of measurement, and gives details on measurement accuracy and precision. The tables are available for ftp transfer.

Web pages developed specifically for this data set provide detailed information for viewing and selecting the velocity data. These pages contain large satellite image maps (available as jpeg files). The data sets used to create these images were contributed by several investigators, generally from already published work. Both in situ and image-based methods are used.

References for the data sets are included with the data tables. If you have well-characterized Antarctic ice velocity data you would like to contribute to this site, please contact teds@icehouse.colorado.edu. If you have any questions concerning the relevance of these data to your work please contact NSIDC User Services.
In January and February 2003, the Airborne Second Generation Precipitation Radar (APR-2) collected data in the Wakasa Bay AMSR-E validation campaign over the sea of Japan on board a NASA P-3 aircraft. Data were collected on all P-3 flights that encountered precipitation. APR-2 collected data at 13.405 and 35.605 GHz in a downward-looking, cross-track scanning geometry. The experiment was designed to validate the AMSR-E shallow rain and snow retrievals, and to extend the precipitation database needed to implement a physical validation strategy.

The Level 1 data product consists of the calibrated reflectivity at both 13.405 and 35.605 GHz, as well as the Doppler and linear depolarization ratio (LDR) at 13.405 GHz. Data are available via FTP in binary Hierarchical Data Format (HDF) and browse images.

The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) is a mission instrument launched aboard NASA's Aqua Satellite on 4 May 2002. AMSR-E validation studies linked to rainfall experiments are designed to evaluate the accuracy of AMSR-E precipitation data.
In January and February 2003, the Airborne Second Generation Precipitation Radar (APR-2) collected data in the Wakasa Bay AMSR-E validation campaign over the sea of Japan on board a NASA P-3 aircraft. Data were collected on all P-3 flights that encountered precipitation. APR-2 collected data at 13.405 and 35.605 GHz in a downward-looking, cross-track scanning geometry. The experiment was designed to validate the AMSR-E shallow rain and snow retrievals, and to extend the precipitation database needed to implement a physical validation strategy.

The Level 1 data product consists of the calibrated reflectivity at both 13.405 and 35.605 GHz, as well as the Doppler and linear depolarization ratio (LDR) at 13.405 GHz. Data are available via FTP in binary Hierarchical Data Format (HDF) and browse images.

The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) is a mission instrument launched aboard NASA's Aqua Satellite on 4 May 2002. AMSR-E validation studies linked to rainfall experiments are designed to evaluate the accuracy of AMSR-E precipitation data.
In January and February 2003, the Airborne Second Generation Precipitation Radar (APR-2) collected data in the Wakasa Bay AMSR-E validation campaign over the sea of Japan on board a NASA P-3 aircraft. Data were collected on all P-3 flights that encountered precipitation. APR-2 collected data at 13.405 and 35.605 GHz in a downward-looking, cross-track scanning geometry. The experiment was designed to validate the AMSR-E shallow rain and snow retrievals, and to extend the precipitation database needed to implement a physical validation strategy.

The Level 1 data product consists of the calibrated reflectivity at both 13.405 and 35.605 GHz, as well as the Doppler and linear depolarization ratio (LDR) at 13.405 GHz. Data are available via FTP in binary Hierarchical Data Format (HDF) and browse images.

The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) is a mission instrument launched aboard NASA's Aqua Satellite on 4 May 2002. AMSR-E validation studies linked to rainfall experiments are designed to evaluate the accuracy of AMSR-E precipitation data.
This data set provides measurements of sea ice freeboard and sea ice thickness for the Arctic region. The data were derived from measurements made by from the Ice, Cloud, and land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) instrument, the Special Sensor Microwave/Imager (SSM/I), and climatologies of snow and drift of ice. The data span fifteen GLAS campaigns, laser 1 through 3k, from 20 February 2003 to 19 October 2008. Data parameters include sea ice freeboard and thickness measured in meters derived from GLAS Release 28 data. The data are provided in four formats: ASCII track data derived from binary track data, binary gridded polar stereographic data derived from ASCII gridded polar stereographic files, GeoTIFF images files, and Portable Network Graphic (PNG) image files. Also included are mask files used in preparation of the image files, a Mapx grid definition file, and grid cell center latitude and longitude files. The ASCII track data vectors of position and ice thickness have a resolution of about 170 meters in the along-track direction. The binary gridded polar stereographic data have a resolution of 25 km.
This data set provides measurements of sea ice freeboard and sea ice thickness for the Arctic region. The data were derived from measurements made by from the Ice, Cloud, and land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) instrument, the Special Sensor Microwave/Imager (SSM/I), and climatologies of snow and drift of ice. The data span fifteen GLAS campaigns, laser 1 through 3k, from 20 February 2003 to 19 October 2008. Data parameters include sea ice freeboard and thickness measured in meters derived from GLAS Release 28 data. The data are provided in four formats: ASCII track data derived from binary track data, binary gridded polar stereographic data derived from ASCII gridded polar stereographic files, GeoTIFF images files, and Portable Network Graphic (PNG) image files. Also included are mask files used in preparation of the image files, a Mapx grid definition file, and grid cell center latitude and longitude files. The ASCII track data vectors of position and ice thickness have a resolution of about 170 meters in the along-track direction. The binary gridded polar stereographic data have a resolution of 25 km.
This data set provides measurements of sea ice freeboard and sea ice thickness for the Arctic region. The data were derived from measurements made by from the Ice, Cloud, and land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) instrument, the Special Sensor Microwave/Imager (SSM/I), and climatologies of snow and drift of ice. The data span fifteen GLAS campaigns, laser 1 through 3k, from 20 February 2003 to 19 October 2008. Data parameters include sea ice freeboard and thickness measured in meters derived from GLAS Release 28 data. The data are provided in four formats: ASCII track data derived from binary track data, binary gridded polar stereographic data derived from ASCII gridded polar stereographic files, GeoTIFF images files, and Portable Network Graphic (PNG) image files. Also included are mask files used in preparation of the image files, a Mapx grid definition file, and grid cell center latitude and longitude files. The ASCII track data vectors of position and ice thickness have a resolution of about 170 meters in the along-track direction. The binary gridded polar stereographic data have a resolution of 25 km.
A gridded climatological monthly-mean data base of Arctic water vapor characteristics has been assembled by combining fixed station data
with data from soundings taken over the Arctic Ocean from ships and
Russian drifting stations. Variables provided include temperature,
specific humidity, zonal vapor flux, meridional vapor flux, zonal wind
speed, and meridional wind speed, available for 15 levels extending
from the surface and then at every 50 mb from 950 mb to 300 mb; sea
level pressure and geopotential height, available at 850 mb, 700 mb,
500 mb and 300 mb; and precipitable water, vertically integrated zonal
vapor flux and vertically integrated meridional vapor flux, available
for five layers, surface to 850 mb, 850 to 700 mb, 700 to 500 mb, 500
to 400 mb and 400 to 300 mb. Coverage of the rawinsonde archives
extends from 1945 through 1990 for data from the Russian North Pole
series of drifting ice stations over the Arctic Ocean; from 1976
through 1991 for fixed-station data obtained from the National Center
for Atmospheric Research; and from about 1958 through 1991 for
fixed-station data obtained from the Historical Arctic Rawinsonde
Archive.
 All variables were obtained through interpolation of the raw sounding
data, with the exception of sea level pressure and geopotential
height. The file, available via ftp, is structured in monthly data
arrays over a subsection of the National Meteorological Center grid
(octagonal grid format) centered over the pole, extending to
approximately 65 degrees North on each side and about 55 degrees North
at the corners.
A gridded climatological monthly-mean data base of Arctic water vapor characteristics has been assembled by combining fixed station data
with data from soundings taken over the Arctic Ocean from ships and
Russian drifting stations. Variables provided include temperature,
specific humidity, zonal vapor flux, meridional vapor flux, zonal wind
speed, and meridional wind speed, available for 15 levels extending
from the surface and then at every 50 mb from 950 mb to 300 mb; sea
level pressure and geopotential height, available at 850 mb, 700 mb,
500 mb and 300 mb; and precipitable water, vertically integrated zonal
vapor flux and vertically integrated meridional vapor flux, available
for five layers, surface to 850 mb, 850 to 700 mb, 700 to 500 mb, 500
to 400 mb and 400 to 300 mb. Coverage of the rawinsonde archives
extends from 1945 through 1990 for data from the Russian North Pole
series of drifting ice stations over the Arctic Ocean; from 1976
through 1991 for fixed-station data obtained from the National Center
for Atmospheric Research; and from about 1958 through 1991 for
fixed-station data obtained from the Historical Arctic Rawinsonde
Archive.
 All variables were obtained through interpolation of the raw sounding
data, with the exception of sea level pressure and geopotential
height. The file, available via ftp, is structured in monthly data
arrays over a subsection of the National Meteorological Center grid
(octagonal grid format) centered over the pole, extending to
approximately 65 degrees North on each side and about 55 degrees North
at the corners.
A gridded climatological monthly-mean data base of Arctic water vapor characteristics has been assembled by combining fixed station data
with data from soundings taken over the Arctic Ocean from ships and
Russian drifting stations. Variables provided include temperature,
specific humidity, zonal vapor flux, meridional vapor flux, zonal wind
speed, and meridional wind speed, available for 15 levels extending
from the surface and then at every 50 mb from 950 mb to 300 mb; sea
level pressure and geopotential height, available at 850 mb, 700 mb,
500 mb and 300 mb; and precipitable water, vertically integrated zonal
vapor flux and vertically integrated meridional vapor flux, available
for five layers, surface to 850 mb, 850 to 700 mb, 700 to 500 mb, 500
to 400 mb and 400 to 300 mb. Coverage of the rawinsonde archives
extends from 1945 through 1990 for data from the Russian North Pole
series of drifting ice stations over the Arctic Ocean; from 1976
through 1991 for fixed-station data obtained from the National Center
for Atmospheric Research; and from about 1958 through 1991 for
fixed-station data obtained from the Historical Arctic Rawinsonde
Archive.
 All variables were obtained through interpolation of the raw sounding
data, with the exception of sea level pressure and geopotential
height. The file, available via ftp, is structured in monthly data
arrays over a subsection of the National Meteorological Center grid
(octagonal grid format) centered over the pole, extending to
approximately 65 degrees North on each side and about 55 degrees North
at the corners.
<font color="#FF0000">This data set is no longer available because of errors in the data. See the <a href="http://nsidc.org/data/docs/daac/nsidc0094_avhrr_25km_abstract.gd.html#errorsource">Error Sources</a> section of the data set documentation for details. If you have further questions, please contact NSIDC User Services by e-mail at <a href="mailto:nsidc@nsidc.org">nsidc@nsidc.org</a> or telephone at +1 303.492.6199.</font>

The AVHRR Polar Pathfinder Twice-Daily 25 km EASE-Grid Composites are a collection of products for both poles, consisting of twice-daily gridded and calibrated satellite channel data and derived parameters. Data include five Advanced Very High Resolution Radiometer (AVHRR) channels, clear sky surface broadband albedo and skin temperature, average albedo and temperature, valid fraction file, solar zenith angle, satellite elevation angle, sun-satellite relative azimuth angle, surface type mask, cloud mask, cloud fraction files, and Universal Coordinated Time (UTC) of acquisition. The 25 km data are derived from the AVHRR Polar Pathfinder Twice-Daily 5 km EASE-Grid Composites, and extend poleward from 48.4 degrees north and 53.2 degrees south latitudes, spanning July 1981 through December 2000. Data are in 1-byte and 2-byte integer grid format and are available by FTP. 

Note: NSIDC reccommends the use of the Extended AVHRR Polar Pathfinder (APP-x) Product instead of our AVHRR Polar Pathfinder Twice-Daily 25 km EASE-Grid Composites. The APP-x 25 km product has albedo and temperature calculations for all sky conditions. Cloud properties are modeled to estimate the albedo and temperature under the clouds. An improved cloud detection algorithm is also used in the APP-x product.
<font color="#FF0000">This data set is no longer available because of errors in the data. See the <a href="http://nsidc.org/data/docs/daac/nsidc0094_avhrr_25km_abstract.gd.html#errorsource">Error Sources</a> section of the data set documentation for details. If you have further questions, please contact NSIDC User Services by e-mail at <a href="mailto:nsidc@nsidc.org">nsidc@nsidc.org</a> or telephone at +1 303.492.6199.</font>

The AVHRR Polar Pathfinder Twice-Daily 25 km EASE-Grid Composites are a collection of products for both poles, consisting of twice-daily gridded and calibrated satellite channel data and derived parameters. Data include five Advanced Very High Resolution Radiometer (AVHRR) channels, clear sky surface broadband albedo and skin temperature, average albedo and temperature, valid fraction file, solar zenith angle, satellite elevation angle, sun-satellite relative azimuth angle, surface type mask, cloud mask, cloud fraction files, and Universal Coordinated Time (UTC) of acquisition. The 25 km data are derived from the AVHRR Polar Pathfinder Twice-Daily 5 km EASE-Grid Composites, and extend poleward from 48.4 degrees north and 53.2 degrees south latitudes, spanning July 1981 through December 2000. Data are in 1-byte and 2-byte integer grid format and are available by FTP. 

Note: NSIDC reccommends the use of the Extended AVHRR Polar Pathfinder (APP-x) Product instead of our AVHRR Polar Pathfinder Twice-Daily 25 km EASE-Grid Composites. The APP-x 25 km product has albedo and temperature calculations for all sky conditions. Cloud properties are modeled to estimate the albedo and temperature under the clouds. An improved cloud detection algorithm is also used in the APP-x product.
<font color="#FF0000">This data set is no longer available because of errors in the data. See the <a href="http://nsidc.org/data/docs/daac/nsidc0094_avhrr_25km_abstract.gd.html#errorsource">Error Sources</a> section of the data set documentation for details. If you have further questions, please contact NSIDC User Services by e-mail at <a href="mailto:nsidc@nsidc.org">nsidc@nsidc.org</a> or telephone at +1 303.492.6199.</font>

The AVHRR Polar Pathfinder Twice-Daily 25 km EASE-Grid Composites are a collection of products for both poles, consisting of twice-daily gridded and calibrated satellite channel data and derived parameters. Data include five Advanced Very High Resolution Radiometer (AVHRR) channels, clear sky surface broadband albedo and skin temperature, average albedo and temperature, valid fraction file, solar zenith angle, satellite elevation angle, sun-satellite relative azimuth angle, surface type mask, cloud mask, cloud fraction files, and Universal Coordinated Time (UTC) of acquisition. The 25 km data are derived from the AVHRR Polar Pathfinder Twice-Daily 5 km EASE-Grid Composites, and extend poleward from 48.4 degrees north and 53.2 degrees south latitudes, spanning July 1981 through December 2000. Data are in 1-byte and 2-byte integer grid format and are available by FTP. 

Note: NSIDC reccommends the use of the Extended AVHRR Polar Pathfinder (APP-x) Product instead of our AVHRR Polar Pathfinder Twice-Daily 25 km EASE-Grid Composites. The APP-x 25 km product has albedo and temperature calculations for all sky conditions. Cloud properties are modeled to estimate the albedo and temperature under the clouds. An improved cloud detection algorithm is also used in the APP-x product.
<span style="color:#FF0000;">This data set is no longer available due to errors in the data. See the <a href="http://nsidc.org/data/docs/daac/nsidc0066_avhrr_5km.gd.html#errorsource">Error Sources</a> section of the data set documentation for details. If you have further questions, please contact NSIDC User Services by <a href="mailto:nsidc@nsidc.org">e-mail</a> or telephone at +1 303.492.6199.</span>

The Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder Twice-Daily 5 km EASE-Grid Composites are a collection of products for both poles, consisting of twice-daily calibrated and gridded satellite channel data and derived parameters. Data include five AVHRR channels, clear sky surface broadband albedo and skin temperature, solar zenith angle, satellite elevation angle, sun-satellite relative azimuth angle, surface type mask, cloud mask, and Universal Coordinated Time (UTC) of acquisition. AVHRR Polar Pathfinder data extend pole ward from 48.4 degrees north and 53.2 degrees south latitudes, from 24 July 1981 through 30 June 2005. Data are in 1-byte and 2-byte integer grid format and are available by FTP. 

Note: Due to a problem with the NOAA-16 scan motor, all the channel data is shifted sporadically between 2001 and 2005, causing the channels to contain data from another channel; thus, the derived parameters also contain errors during this time-period. See Table 12 in the Error Sources section of this document for specific dates.
<span style="color:#FF0000;">This data set is no longer available due to errors in the data. See the <a href="http://nsidc.org/data/docs/daac/nsidc0066_avhrr_5km.gd.html#errorsource">Error Sources</a> section of the data set documentation for details. If you have further questions, please contact NSIDC User Services by <a href="mailto:nsidc@nsidc.org">e-mail</a> or telephone at +1 303.492.6199.</span>

The Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder Twice-Daily 5 km EASE-Grid Composites are a collection of products for both poles, consisting of twice-daily calibrated and gridded satellite channel data and derived parameters. Data include five AVHRR channels, clear sky surface broadband albedo and skin temperature, solar zenith angle, satellite elevation angle, sun-satellite relative azimuth angle, surface type mask, cloud mask, and Universal Coordinated Time (UTC) of acquisition. AVHRR Polar Pathfinder data extend pole ward from 48.4 degrees north and 53.2 degrees south latitudes, from 24 July 1981 through 30 June 2005. Data are in 1-byte and 2-byte integer grid format and are available by FTP. 

Note: Due to a problem with the NOAA-16 scan motor, all the channel data is shifted sporadically between 2001 and 2005, causing the channels to contain data from another channel; thus, the derived parameters also contain errors during this time-period. See Table 12 in the Error Sources section of this document for specific dates.
<span style="color:#FF0000;">This data set is no longer available due to errors in the data. See the <a href="http://nsidc.org/data/docs/daac/nsidc0066_avhrr_5km.gd.html#errorsource">Error Sources</a> section of the data set documentation for details. If you have further questions, please contact NSIDC User Services by <a href="mailto:nsidc@nsidc.org">e-mail</a> or telephone at +1 303.492.6199.</span>

The Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder Twice-Daily 5 km EASE-Grid Composites are a collection of products for both poles, consisting of twice-daily calibrated and gridded satellite channel data and derived parameters. Data include five AVHRR channels, clear sky surface broadband albedo and skin temperature, solar zenith angle, satellite elevation angle, sun-satellite relative azimuth angle, surface type mask, cloud mask, and Universal Coordinated Time (UTC) of acquisition. AVHRR Polar Pathfinder data extend pole ward from 48.4 degrees north and 53.2 degrees south latitudes, from 24 July 1981 through 30 June 2005. Data are in 1-byte and 2-byte integer grid format and are available by FTP. 

Note: Due to a problem with the NOAA-16 scan motor, all the channel data is shifted sporadically between 2001 and 2005, causing the channels to contain data from another channel; thus, the derived parameters also contain errors during this time-period. See Table 12 in the Error Sources section of this document for specific dates.
This data set includes non-Doppler polar volume reflectivity data from the Baltic Sea Experiment (BALTEX). Data were collected on Sweden's Gotland Island, using an Ericsson radar mounted at 56 m above sea level. The radar provided 12 scanning angles. Measurements were taken between 1 September 2002 and 31 May 2003. BALTEX data sets will be used for validation of AMSR-E and Advanced Microwave Sounding Unit (AMSU)/Humidity Sounder for Brazil (HSB) Level 1 brightness temperatures and Level 2 cloud and precipitation parameters. Data are available in network Common Data Format (netCDF) from NSIDC via FTP.

The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) is a mission instrument launched aboard NASA's Aqua Satellite on 4 May 2002. The Baltic Sea Experiment's (BALTEX) Radar Data Centre (BRDC), operated by the Swedish Meteorological and Hydrological Institute (SMHI), collects data from as many radars in or near the Baltic region as possible. During the Main Observational Phase (October 1999 - February 2002), data from 25 radars in six countries have covered the Baltic region every 15 minutes. High-latitude data are recorded from 50 to 70 degrees North, and they complement pre-existing efforts in the mid-latitudes and tropics.
This data set includes non-Doppler polar volume reflectivity data from the Baltic Sea Experiment (BALTEX). Data were collected on Sweden's Gotland Island, using an Ericsson radar mounted at 56 m above sea level. The radar provided 12 scanning angles. Measurements were taken between 1 September 2002 and 31 May 2003. BALTEX data sets will be used for validation of AMSR-E and Advanced Microwave Sounding Unit (AMSU)/Humidity Sounder for Brazil (HSB) Level 1 brightness temperatures and Level 2 cloud and precipitation parameters. Data are available in network Common Data Format (netCDF) from NSIDC via FTP.

The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) is a mission instrument launched aboard NASA's Aqua Satellite on 4 May 2002. The Baltic Sea Experiment's (BALTEX) Radar Data Centre (BRDC), operated by the Swedish Meteorological and Hydrological Institute (SMHI), collects data from as many radars in or near the Baltic region as possible. During the Main Observational Phase (October 1999 - February 2002), data from 25 radars in six countries have covered the Baltic region every 15 minutes. High-latitude data are recorded from 50 to 70 degrees North, and they complement pre-existing efforts in the mid-latitudes and tropics.
This data set includes non-Doppler polar volume reflectivity data from the Baltic Sea Experiment (BALTEX). Data were collected on Sweden's Gotland Island, using an Ericsson radar mounted at 56 m above sea level. The radar provided 12 scanning angles. Measurements were taken between 1 September 2002 and 31 May 2003. BALTEX data sets will be used for validation of AMSR-E and Advanced Microwave Sounding Unit (AMSU)/Humidity Sounder for Brazil (HSB) Level 1 brightness temperatures and Level 2 cloud and precipitation parameters. Data are available in network Common Data Format (netCDF) from NSIDC via FTP.

The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) is a mission instrument launched aboard NASA's Aqua Satellite on 4 May 2002. The Baltic Sea Experiment's (BALTEX) Radar Data Centre (BRDC), operated by the Swedish Meteorological and Hydrological Institute (SMHI), collects data from as many radars in or near the Baltic region as possible. During the Main Observational Phase (October 1999 - February 2002), data from 25 radars in six countries have covered the Baltic region every 15 minutes. High-latitude data are recorded from 50 to 70 degrees North, and they complement pre-existing efforts in the mid-latitudes and tropics.
This sea ice concentration data set was derived using measurements from the Scanning Multichannel Microwave Radiometer (SMMR) on the Nimbus-7 satellite and from the Special Sensor Microwave/Imager (SSM/I) sensors on the Defense Meteorological Satellite Program's (DMSP) -F8, -F11, and -F13 satellites. Measurements from the Special Sensor Microwave Imager/Sounder (SSMIS) aboard DMSP-F17 are also included. The data set has been generated using the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) Bootstrap Algorithm with daily varying tie-points. Daily (every other day prior to July 1987) and monthly data are available for both the north and south polar regions. Data are gridded on the SSM/I polar stereographic grid (25 x 25 km) and provided in two-byte integer format. Data are available via FTP.
This sea ice concentration data set was derived using measurements from the Scanning Multichannel Microwave Radiometer (SMMR) on the Nimbus-7 satellite and from the Special Sensor Microwave/Imager (SSM/I) sensors on the Defense Meteorological Satellite Program's (DMSP) -F8, -F11, and -F13 satellites. Measurements from the Special Sensor Microwave Imager/Sounder (SSMIS) aboard DMSP-F17 are also included. The data set has been generated using the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) Bootstrap Algorithm with daily varying tie-points. Daily (every other day prior to July 1987) and monthly data are available for both the north and south polar regions. Data are gridded on the SSM/I polar stereographic grid (25 x 25 km) and provided in two-byte integer format. Data are available via FTP.
This sea ice concentration data set was derived using measurements from the Scanning Multichannel Microwave Radiometer (SMMR) on the Nimbus-7 satellite and from the Special Sensor Microwave/Imager (SSM/I) sensors on the Defense Meteorological Satellite Program's (DMSP) -F8, -F11, and -F13 satellites. Measurements from the Special Sensor Microwave Imager/Sounder (SSMIS) aboard DMSP-F17 are also included. The data set has been generated using the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) Bootstrap Algorithm with daily varying tie-points. Daily (every other day prior to July 1987) and monthly data are available for both the north and south polar regions. Data are gridded on the SSM/I polar stereographic grid (25 x 25 km) and provided in two-byte integer format. Data are available via FTP.
This data set consists of Northern Hemisphere snow depth analysis data processed by the Canadian Meteorological Centre (CMC). Snow depth data obtained from surface synoptic observations (synops), meteorological aviation reports (metars), and special aviation reports (SAs) were acquired from the World Meteorological Organization (WMO) information system for use in the CMC analyses. This CMC data set includes daily observations from 1998 through 2013 and will be updated annually. Monthly averages and monthly climatologies of snow depth and estimated Snow Water Equivalent (SWE) are provided, where SWE was estimated using a density look-up table. The volume of the data set is approximately four gigabytes. Data are provided in tab-delimited ASCII text files and are available via FTP.
This data set consists of Northern Hemisphere snow depth analysis data processed by the Canadian Meteorological Centre (CMC). Snow depth data obtained from surface synoptic observations (synops), meteorological aviation reports (metars), and special aviation reports (SAs) were acquired from the World Meteorological Organization (WMO) information system for use in the CMC analyses. This CMC data set includes daily observations from 1998 through 2013 and will be updated annually. Monthly averages and monthly climatologies of snow depth and estimated Snow Water Equivalent (SWE) are provided, where SWE was estimated using a density look-up table. The volume of the data set is approximately four gigabytes. Data are provided in tab-delimited ASCII text files and are available via FTP.
This data set consists of Northern Hemisphere snow depth analysis data processed by the Canadian Meteorological Centre (CMC). Snow depth data obtained from surface synoptic observations (synops), meteorological aviation reports (metars), and special aviation reports (SAs) were acquired from the World Meteorological Organization (WMO) information system for use in the CMC analyses. This CMC data set includes daily observations from 1998 through 2013 and will be updated annually. Monthly averages and monthly climatologies of snow depth and estimated Snow Water Equivalent (SWE) are provided, where SWE was estimated using a density look-up table. The volume of the data set is approximately four gigabytes. Data are provided in tab-delimited ASCII text files and are available via FTP.
Airborne gamma surveys were conducted over each of the three Cold Land Processes Field Experiment (CLPX) Meso-cell Study Areas (MSAs) in northern Colorado, USA, during September 2001 and 2002, and during the three Intensive Observation Periods (IOPs) in February 2002 (IOP1), February 2003 (IOP3) and March 2003 (IOP4). Data collected in September 2001 and 2002 provided background gamma radiation measurements necessary to calculate measurements of snow water equivalent (SWE) and soil moisture during subsequent winters. Airborne gamma radiation measurements of SWE and soil moisture are based on the attenuation of natural terrestrial gamma radiation by the mass of water contained in the soil and snow. Measurements were collected at 500 feet AGL along flight lines of variable length and 300 m width. Measurements are integrated along the entire length of a flight line. Flight lines in the North Park MSA were each 9 km in length, with a series of three lines (27 km total length) flown in a regular N-S parallel pattern spaced 1 km apart. Flight lines in the Fraser and Rabbit Ears MSAs are of variable length and direction. 

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
Airborne gamma surveys were conducted over each of the three Cold Land Processes Field Experiment (CLPX) Meso-cell Study Areas (MSAs) in northern Colorado, USA, during September 2001 and 2002, and during the three Intensive Observation Periods (IOPs) in February 2002 (IOP1), February 2003 (IOP3) and March 2003 (IOP4). Data collected in September 2001 and 2002 provided background gamma radiation measurements necessary to calculate measurements of snow water equivalent (SWE) and soil moisture during subsequent winters. Airborne gamma radiation measurements of SWE and soil moisture are based on the attenuation of natural terrestrial gamma radiation by the mass of water contained in the soil and snow. Measurements were collected at 500 feet AGL along flight lines of variable length and 300 m width. Measurements are integrated along the entire length of a flight line. Flight lines in the North Park MSA were each 9 km in length, with a series of three lines (27 km total length) flown in a regular N-S parallel pattern spaced 1 km apart. Flight lines in the Fraser and Rabbit Ears MSAs are of variable length and direction. 

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
Airborne gamma surveys were conducted over each of the three Cold Land Processes Field Experiment (CLPX) Meso-cell Study Areas (MSAs) in northern Colorado, USA, during September 2001 and 2002, and during the three Intensive Observation Periods (IOPs) in February 2002 (IOP1), February 2003 (IOP3) and March 2003 (IOP4). Data collected in September 2001 and 2002 provided background gamma radiation measurements necessary to calculate measurements of snow water equivalent (SWE) and soil moisture during subsequent winters. Airborne gamma radiation measurements of SWE and soil moisture are based on the attenuation of natural terrestrial gamma radiation by the mass of water contained in the soil and snow. Measurements were collected at 500 feet AGL along flight lines of variable length and 300 m width. Measurements are integrated along the entire length of a flight line. Flight lines in the North Park MSA were each 9 km in length, with a series of three lines (27 km total length) flown in a regular N-S parallel pattern spaced 1 km apart. Flight lines in the Fraser and Rabbit Ears MSAs are of variable length and direction. 

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set consists of apparent surface reflectance, subpixel snow-covered area and grain size inferred from data acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The AVIRIS has a spectral range of 400-2500 nm, a spectral resolution of 10 nm, instantaneous field of view of 1 mrad, and a scan angle of 15 degrees. Sampling is scene based (~ 815 samples, 512 lines).

The AVIRIS provides spectral resolution into hundreds of spectral bands versus the seven multispectral bands flown on traditional Landsat imaging missions. Through this large number of spectral bands, complex land ecosystems can be imaged and accurately classified. 

This data set is part of the NASA Cold Land Processes Field Experiment (CLPX). The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread. Data are available via FTP. Users are requested to register with NSIDC User Services to obtain access to the data.
This data set consists of apparent surface reflectance, subpixel snow-covered area and grain size inferred from data acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The AVIRIS has a spectral range of 400-2500 nm, a spectral resolution of 10 nm, instantaneous field of view of 1 mrad, and a scan angle of 15 degrees. Sampling is scene based (~ 815 samples, 512 lines).

The AVIRIS provides spectral resolution into hundreds of spectral bands versus the seven multispectral bands flown on traditional Landsat imaging missions. Through this large number of spectral bands, complex land ecosystems can be imaged and accurately classified. 

This data set is part of the NASA Cold Land Processes Field Experiment (CLPX). The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread. Data are available via FTP. Users are requested to register with NSIDC User Services to obtain access to the data. 

PLEASE NOTE: These data have not been reviewed for quality. Known issues exist in the processing of these data. Until this disclaimer has been removed, users should send questions and comments about this data set to nsidc@nsidc.org. NSIDC will forward these inquiries to the PI for resolution.
This data set consists of apparent surface reflectance, subpixel snow-covered area and grain size inferred from data acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The AVIRIS has a spectral range of 400-2500 nm, a spectral resolution of 10 nm, instantaneous field of view of 1 mrad, and a scan angle of 15 degrees. Sampling is scene based (~ 815 samples, 512 lines).

The AVIRIS provides spectral resolution into hundreds of spectral bands versus the seven multispectral bands flown on traditional Landsat imaging missions. Through this large number of spectral bands, complex land ecosystems can be imaged and accurately classified. 

This data set is part of the NASA Cold Land Processes Field Experiment (CLPX). The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread. Data are available via FTP. Users are requested to register with NSIDC User Services to obtain access to the data. 

PLEASE NOTE: These data have not been reviewed for quality. Known issues exist in the processing of these data. Until this disclaimer has been removed, users should send questions and comments about this data set to nsidc@nsidc.org. NSIDC will forward these inquiries to the PI for resolution.
The purpose of this project was to generate a research-quality, scientifically-sound, best-as-reasonably possible, three-dimensional meteorological analysis for the entire cold season 2002-2003 for the three CLPX Meteorological Study Areas (MSAs) in northern Colorado (North Park, Fraser
and Rabbit Ears) using high-resolution (500 m horizontal grid spacing). This
complex terrain meteorological dataset is to be used to complete publishable
research from CLPX across the disciplines of atmospheric science, snow
science, ecology and forestry. All simulations were completed through the
provision of supercomputer time at the National Center for Atmospheric
Research.  Data are available via FTP. 

The NASA Cold Land Processes Field Experiment (CLPX) is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1 ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
The purpose of this project was to generate a research-quality, scientifically-sound, best-as-reasonably possible, three-dimensional meteorological analysis for the entire cold season 2002-2003 for the three CLPX Meteorological Study Areas (MSAs) in northern Colorado (North Park, Fraser
and Rabbit Ears) using high-resolution (500 m horizontal grid spacing). This
complex terrain meteorological dataset is to be used to complete publishable
research from CLPX across the disciplines of atmospheric science, snow
science, ecology and forestry. All simulations were completed through the
provision of supercomputer time at the National Center for Atmospheric
Research.  Data are available via FTP. 

The NASA Cold Land Processes Field Experiment (CLPX) is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1 ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
The purpose of this project was to generate a research-quality, scientifically-sound, best-as-reasonably possible, three-dimensional meteorological analysis for the entire cold season 2002-2003 for the three CLPX Meteorological Study Areas (MSAs) in northern Colorado (North Park, Fraser
and Rabbit Ears) using high-resolution (500 m horizontal grid spacing). This
complex terrain meteorological dataset is to be used to complete publishable
research from CLPX across the disciplines of atmospheric science, snow
science, ecology and forestry. All simulations were completed through the
provision of supercomputer time at the National Center for Atmospheric
Research.  Data are available via FTP. 

The NASA Cold Land Processes Field Experiment (CLPX) is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1 ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
The Rapid Update Cycle analysis/model system at a 20-km horizontal resolution (RUC20) provides short-range numerical weather guidance for general forecasting, as well as for the special short-term needs of aviation and severe-weather forecasting. This data set consists of 60 meteorological and soil parameters at 50 computational levels. Data are available from 1 October 2002 to 1 October 2003. RUC20 is a further development on the RUC40 model that produced output at a 40 km horizontal resolution. 

The NASA Cold Land Processes Experiment (CLPX) is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
The Rapid Update Cycle analysis/model system at a 20-km horizontal resolution (RUC20) provides short-range numerical weather guidance for general forecasting, as well as for the special short-term needs of aviation and severe-weather forecasting. This data set consists of 60 meteorological and soil parameters at 50 computational levels. Data are available from 1 October 2002 to 1 October 2003. RUC20 is a further development on the RUC40 model that produced output at a 40 km horizontal resolution. 

The NASA Cold Land Processes Experiment (CLPX) is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
The Rapid Update Cycle analysis/model system at a 20-km horizontal resolution (RUC20) provides short-range numerical weather guidance for general forecasting, as well as for the special short-term needs of aviation and severe-weather forecasting. This data set consists of 60 meteorological and soil parameters at 50 computational levels. Data are available from 1 October 2002 to 1 October 2003. RUC20 is a further development on the RUC40 model that produced output at a 40 km horizontal resolution. 

The NASA Cold Land Processes Experiment (CLPX) is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set consists of measurements of GPS signals reflected from the Earth's surface and collected on an airborne platform. A modified GPS Delay Mapping Receiver (DMR) tracks and measures the direct, line-of-sight, right hand circulary polarized (RHCP) signal of a GPS satellite. It also simultaneously measures the delayed, Earth-reflected, near-specular, LHCP GPS signal. These measurements are a form of bistatic radar. The measurements can be used to estimate the surface scattering coefficient and path delays between the direct and reflected GPS signals. Over land, scattering coefficients can be used to estimate changes in surface soil moisture. Over water surfaces, the reflected pulses can be used to sense roughness and derive wind speeds. The bistatic range measurements can also be used to estimate the receiver height above the surface in a form of aircraft altimetry. 

Data were collected throughout each Meso-cell Study Area (MSA) within the Cold Land Processes Field Experiment (CLPX) Small Regional Study Area (SRSA, 39.5 N-41 N, 105 W-107.5 W). Spatial resolution of these data is variable depending on airborne height and scattering regime (specular or rough). Data were collected 19 and 21 February 2002, and 22-24 February and 25, 30, 31 March 2003. Data are available via FTP.
This data set consists of measurements of GPS signals reflected from the Earth's surface and collected on an airborne platform. A modified GPS Delay Mapping Receiver (DMR) tracks and measures the direct, line-of-sight, right hand circulary polarized (RHCP) signal of a GPS satellite. It also simultaneously measures the delayed, Earth-reflected, near-specular, LHCP GPS signal. These measurements are a form of bistatic radar. The measurements can be used to estimate the surface scattering coefficient and path delays between the direct and reflected GPS signals. Over land, scattering coefficients can be used to estimate changes in surface soil moisture. Over water surfaces, the reflected pulses can be used to sense roughness and derive wind speeds. The bistatic range measurements can also be used to estimate the receiver height above the surface in a form of aircraft altimetry. 

Data were collected throughout each Meso-cell Study Area (MSA) within the Cold Land Processes Field Experiment (CLPX) Small Regional Study Area (SRSA, 39.5 N-41 N, 105 W-107.5 W). Spatial resolution of these data is variable depending on airborne height and scattering regime (specular or rough). Data were collected 19 and 21 February 2002, and 22-24 February and 25, 30, 31 March 2003. Data are available via FTP.
This data set consists of measurements of GPS signals reflected from the Earth's surface and collected on an airborne platform. A modified GPS Delay Mapping Receiver (DMR) tracks and measures the direct, line-of-sight, right hand circulary polarized (RHCP) signal of a GPS satellite. It also simultaneously measures the delayed, Earth-reflected, near-specular, LHCP GPS signal. These measurements are a form of bistatic radar. The measurements can be used to estimate the surface scattering coefficient and path delays between the direct and reflected GPS signals. Over land, scattering coefficients can be used to estimate changes in surface soil moisture. Over water surfaces, the reflected pulses can be used to sense roughness and derive wind speeds. The bistatic range measurements can also be used to estimate the receiver height above the surface in a form of aircraft altimetry. 

Data were collected throughout each Meso-cell Study Area (MSA) within the Cold Land Processes Field Experiment (CLPX) Small Regional Study Area (SRSA, 39.5 N-41 N, 105 W-107.5 W). Spatial resolution of these data is variable depending on airborne height and scattering regime (specular or rough). Data were collected 19 and 21 February 2002, and 22-24 February and 25, 30, 31 March 2003. Data are available via FTP.
Airborne Synthetic Aperture Radar (AIRSAR) is a side-looking imaging radar that is able to collect data irrespective of daylight or cloud cover. The AIRSAR instrument was operated in two modes over each Cold Land Processes Field Experiment (CLPX) Meso-cell Study Area (MSA). In the first mode (POLSAR), polarimetric radar data were collected at P-, L-, and C-bands. In the second mode (TOPSAR), cross-track interferometry data were collected at C-band and L-band. The CLPX AIRSAR mission flew on a DC-8 aircraft at 8 km altitude over the three MSAs at Rabbit Ears, North Park, and Fraser. 171 flight lines (87 TOPSAR and 84 POLSAR) were flown in February, March, and September of 2002 and in March 2003.

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
Airborne Synthetic Aperture Radar (AIRSAR) is a side-looking imaging radar that is able to collect data irrespective of daylight or cloud cover. The AIRSAR instrument was operated in two modes over each Cold Land Processes Field Experiment (CLPX) Meso-cell Study Area (MSA). In the first mode (POLSAR), polarimetric radar data were collected at P-, L-, and C-bands. In the second mode (TOPSAR), cross-track interferometry data were collected at C-band and L-band. The CLPX AIRSAR mission flew on a DC-8 aircraft at 8 km altitude over the three MSAs at Rabbit Ears, North Park, and Fraser. 171 flight lines (87 TOPSAR and 84 POLSAR) were flown in February, March, and September of 2002 and in March 2003.

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
Airborne Synthetic Aperture Radar (AIRSAR) is a side-looking imaging radar that is able to collect data irrespective of daylight or cloud cover. The AIRSAR instrument was operated in two modes over each Cold Land Processes Field Experiment (CLPX) Meso-cell Study Area (MSA). In the first mode (POLSAR), polarimetric radar data were collected at P-, L-, and C-bands. In the second mode (TOPSAR), cross-track interferometry data were collected at C-band and L-band. The CLPX AIRSAR mission flew on a DC-8 aircraft at 8 km altitude over the three MSAs at Rabbit Ears, North Park, and Fraser. 171 flight lines (87 TOPSAR and 84 POLSAR) were flown in February, March, and September of 2002 and in March 2003.

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set was collected to test the concept of measuring snow depth using aerial lidar. The data set consists of color infrared orthophotography (TerrainVision® - High resolution Topographic Mapping & Aerial Photography, with 6-inch pixel resolution), lidar elevation returns (raw/combined, filtered to bare ground/snow, and filtered to top of vegetation), elevation contours (0.5 meter) and snow depth contours (0.1 meter). Data were collected within the Small Regional Study Area (SRSA) as part of the Cold Land Processes Field Experiment (CLPX) in Northern Colorado. Observations were made in each Intensive Study Area (ISA), the Local Scale Observation Site (LSOS) and at a site adjacent to the NCAR (National Center for Atmospheric Research) flux tower (close to the southeast corner of Potter Creek ISA). Data were collected on 8-9 April and 18-19 September 2003. Data are available for all sites except for snow depth contours at the site adjacent to the NCAR flux tower. Elevation data were acquired at approximately 4200 ft via Airborne lidar, normalized to ground controls and processed to remove noise and redundancies.
This data set was collected to test the concept of measuring snow depth using aerial lidar. The data set consists of color infrared orthophotography (TerrainVision® - High resolution Topographic Mapping & Aerial Photography, with 6-inch pixel resolution), lidar elevation returns (raw/combined, filtered to bare ground/snow, and filtered to top of vegetation), elevation contours (0.5 meter) and snow depth contours (0.1 meter). Data were collected within the Small Regional Study Area (SRSA) as part of the Cold Land Processes Field Experiment (CLPX) in Northern Colorado. Observations were made in each Intensive Study Area (ISA), the Local Scale Observation Site (LSOS) and at a site adjacent to the NCAR (National Center for Atmospheric Research) flux tower (close to the southeast corner of Potter Creek ISA). Data were collected on 8-9 April and 18-19 September 2003. Data are available for all sites except for snow depth contours at the site adjacent to the NCAR flux tower. Elevation data were acquired at approximately 4200 ft via Airborne lidar, normalized to ground controls and processed to remove noise and redundancies.
This data set was collected to test the concept of measuring snow depth using aerial lidar. The data set consists of color infrared orthophotography (TerrainVision® - High resolution Topographic Mapping & Aerial Photography, with 6-inch pixel resolution), lidar elevation returns (raw/combined, filtered to bare ground/snow, and filtered to top of vegetation), elevation contours (0.5 meter) and snow depth contours (0.1 meter). Data were collected within the Small Regional Study Area (SRSA) as part of the Cold Land Processes Field Experiment (CLPX) in Northern Colorado. Observations were made in each Intensive Study Area (ISA), the Local Scale Observation Site (LSOS) and at a site adjacent to the NCAR (National Center for Atmospheric Research) flux tower (close to the southeast corner of Potter Creek ISA). Data were collected on 8-9 April and 18-19 September 2003. Data are available for all sites except for snow depth contours at the site adjacent to the NCAR flux tower. Elevation data were acquired at approximately 4200 ft via Airborne lidar, normalized to ground controls and processed to remove noise and redundancies.
This data set presents micrometeorological data from the Flux over Snow Surfaces (FLOSS) project carried out during the Cold Land Processes Field Experiment (CLPX) at North Park, Colorado, USA.  The project measured air temperature, air pressure, relative humidity, water vapor, cloud particles, carbon dioxide, longwave and shortwave radiation, and precipitation. Measurements were collected between November 2002 and March 2003. Sensors were installed on a Raytheon King Air 200T, which flew at low atlitude over the study area.
This data set presents micrometeorological data from the Flux over Snow Surfaces (FLOSS) project carried out during the Cold Land Processes Field Experiment (CLPX) at North Park, Colorado, USA.  The project measured air temperature, air pressure, relative humidity, water vapor, cloud particles, carbon dioxide, longwave and shortwave radiation, and precipitation. Measurements were collected between November 2002 and March 2003. Sensors were installed on a Raytheon King Air 200T, which flew at low atlitude over the study area.
This data set presents micrometeorological data from the Flux over Snow Surfaces (FLOSS) project carried out during the Cold Land Processes Field Experiment (CLPX) at North Park, Colorado, USA.  The project measured air temperature, air pressure, relative humidity, water vapor, cloud particles, carbon dioxide, longwave and shortwave radiation, and precipitation. Measurements were collected between November 2002 and March 2003. Sensors were installed on a Raytheon King Air 200T, which flew at low atlitude over the study area.
This data set provides multiband polarimetric brightness temperature images over three 25 x 25 km Meso-cell Study Areas (MSAs) in Northern Colorado. The purpose of collecting these data within the overall aims of the NASA Cold Land Processes Field Experiment (CLPX) is to 1) provide multiband polarimetric dry snow microwave images using AMSR-E bands at a spatial resolution representative of the topography and vegetation cover, and 2) provide a simulated AMSR-E microwave data set coincident with the CLPX AIRSAR imagery for joint snow algorithm retrieval studies. Data were collected using the NOAA Environmental Technology Laboratory (ETL) Polarimetric Scanning Radiometer (PSR), an airborne multiband, conical-scanning, imaging radiometer system. PSR/A data were collected from a series of flight lines flown over the MSAs in February and March 2002 and 2003. PSR/A data are available via FTP as binary files (*.bin) and MATLAB files (*.mat).

NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations were collected. Data collection focused on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set provides multiband polarimetric brightness temperature images over three 25 x 25 km Meso-cell Study Areas (MSAs) in Northern Colorado. The purpose of collecting these data within the overall aims of the NASA Cold Land Processes Field Experiment (CLPX) is to 1) provide multiband polarimetric dry snow microwave images using AMSR-E bands at a spatial resolution representative of the topography and vegetation cover, and 2) provide a simulated AMSR-E microwave data set coincident with the CLPX AIRSAR imagery for joint snow algorithm retrieval studies. Data were collected using the NOAA Environmental Technology Laboratory (ETL) Polarimetric Scanning Radiometer (PSR), an airborne multiband, conical-scanning, imaging radiometer system. PSR/A data were collected from a series of flight lines flown over the MSAs in February and March 2002 and 2003. PSR/A data are available via FTP as binary files (*.bin) and MATLAB files (*.mat).

NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations were collected. Data collection focused on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set provides multiband polarimetric brightness temperature images over three 25 x 25 km Meso-cell Study Areas (MSAs) in Northern Colorado. The purpose of collecting these data within the overall aims of the NASA Cold Land Processes Field Experiment (CLPX) is to 1) provide multiband polarimetric dry snow microwave images using AMSR-E bands at a spatial resolution representative of the topography and vegetation cover, and 2) provide a simulated AMSR-E microwave data set coincident with the CLPX AIRSAR imagery for joint snow algorithm retrieval studies. Data were collected using the NOAA Environmental Technology Laboratory (ETL) Polarimetric Scanning Radiometer (PSR), an airborne multiband, conical-scanning, imaging radiometer system. PSR/A data were collected from a series of flight lines flown over the MSAs in February and March 2002 and 2003. PSR/A data are available via FTP as binary files (*.bin) and MATLAB files (*.mat).

NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations were collected. Data collection focused on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set contains Ku-band polarimetric scatterometer (POLSCAT) data collected as part of the Cold Land Processes Field Experiment (CLPX) to enable the development of a retrieval algorithm for snow water equivalent (SWE). POLSCAT is a Ku-band polarimetric scatterometer operating at 13.95 GHz. Flights were flown on 19, 21, and 23 February 2002 (during IOP1), 25 March 2002 (IOP2), and 25, 28 and 30 March 2003 (IOP 4). 205 flight lines of data were collected over Fraser, North Park and Rabbit Ears MSAs. 

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set contains Ku-band polarimetric scatterometer (POLSCAT) data collected as part of the Cold Land Processes Field Experiment (CLPX) to enable the development of a retrieval algorithm for snow water equivalent (SWE). POLSCAT is a Ku-band polarimetric scatterometer operating at 13.95 GHz. Flights were flown on 19, 21, and 23 February 2002 (during IOP1), 25 March 2002 (IOP2), and 25, 28 and 30 March 2003 (IOP 4). 205 flight lines of data were collected over Fraser, North Park and Rabbit Ears MSAs. 

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set contains Ku-band polarimetric scatterometer (POLSCAT) data collected as part of the Cold Land Processes Field Experiment (CLPX) to enable the development of a retrieval algorithm for snow water equivalent (SWE). POLSCAT is a Ku-band polarimetric scatterometer operating at 13.95 GHz. Flights were flown on 19, 21, and 23 February 2002 (during IOP1), 25 March 2002 (IOP2), and 25, 28 and 30 March 2003 (IOP 4). 205 flight lines of data were collected over Fraser, North Park and Rabbit Ears MSAs. 

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set contains brightness temperature observations of the snow cover at the Local Scale Observation Site (LSOS) of the Cold Land Processes Field Experiment (CLPX) in Fraser, Colorado, USA. Measurements were taken at 18.7, 23.8, 36.5, and 89 GHz (vertical/horizontal polarization) using a ground-based passive microwave radiometer (GBMR-7). Three different measurement techniques were used: 1) scans of undisturbed total snow cover, 2) angular scans with varying incidence angles (30 to 70 degrees), and 3) scans of bare soil and new snow accumulation. In addition to observed snow brightness temperatures, the data set includes snow pit characteristics (density, snow temperature, stratigraphy, snow crystal size, soil moisture) and meteorological forcing data observations (wind speed, wind direction, air temperature, relative humidity, downward long-wave radiation, downward short-wave radiation and precipitation). Snow cover brightness measurements were made 19-21 January 2002, 10-13 December 2002, 18-26 February 2003 and 25 March 2003. Snow pit and meteorological measurements were made between 1 October 2002 and 29 March 2003.

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km<sup>2</sup>, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set contains brightness temperature observations of the snow cover at the Local Scale Observation Site (LSOS) of the Cold Land Processes Field Experiment (CLPX) in Fraser, Colorado, USA. Measurements were taken at 18.7, 23.8, 36.5, and 89 GHz (vertical/horizontal polarization) using a ground-based passive microwave radiometer (GBMR-7). Three different measurement techniques were used: 1) scans of undisturbed total snow cover, 2) angular scans with varying incidence angles (30 to 70 degrees), and 3) scans of bare soil and new snow accumulation. In addition to observed snow brightness temperatures, the data set includes snow pit characteristics (density, snow temperature, stratigraphy, snow crystal size, soil moisture) and meteorological forcing data observations (wind speed, wind direction, air temperature, relative humidity, downward long-wave radiation, downward short-wave radiation and precipitation). Snow cover brightness measurements were made 19-21 January 2002, 10-13 December 2002, 18-26 February 2003 and 25 March 2003. Snow pit and meteorological measurements were made between 1 October 2002 and 29 March 2003.

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km<sup>2</sup>, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set contains brightness temperature observations of the snow cover at the Local Scale Observation Site (LSOS) of the Cold Land Processes Field Experiment (CLPX) in Fraser, Colorado, USA. Measurements were taken at 18.7, 23.8, 36.5, and 89 GHz (vertical/horizontal polarization) using a ground-based passive microwave radiometer (GBMR-7). Three different measurement techniques were used: 1) scans of undisturbed total snow cover, 2) angular scans with varying incidence angles (30 to 70 degrees), and 3) scans of bare soil and new snow accumulation. In addition to observed snow brightness temperatures, the data set includes snow pit characteristics (density, snow temperature, stratigraphy, snow crystal size, soil moisture) and meteorological forcing data observations (wind speed, wind direction, air temperature, relative humidity, downward long-wave radiation, downward short-wave radiation and precipitation). Snow cover brightness measurements were made 19-21 January 2002, 10-13 December 2002, 18-26 February 2003 and 25 March 2003. Snow pit and meteorological measurements were made between 1 October 2002 and 29 March 2003.

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km<sup>2</sup>, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set presents more than 400 sub-canopy digital thermograms collected at the Fraser Experimental Forest (Fraser, Colorado, USA) using an Infrared Solutions IR SnapShot&trade; thermoelectric thermal infrared (IR) imaging radiometer that was cold-weather modified. To view the data it is necessary to have the Infrared Solutions SnapView software, which is available from Infrared Solutions.

The NASA Cold Land Processes Field Experiment (CLPX) is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1 ha to 160,000 km<sup>2</sup>, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set presents more than 400 sub-canopy digital thermograms collected at the Fraser Experimental Forest (Fraser, Colorado, USA) using an Infrared Solutions IR SnapShot&trade; thermoelectric thermal infrared (IR) imaging radiometer that was cold-weather modified. To view the data it is necessary to have the Infrared Solutions SnapView software, which is available from Infrared Solutions.

The NASA Cold Land Processes Field Experiment (CLPX) is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1 ha to 160,000 km<sup>2</sup>, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set presents more than 400 sub-canopy digital thermograms collected at the Fraser Experimental Forest (Fraser, Colorado, USA) using an Infrared Solutions IR SnapShot&trade; thermoelectric thermal infrared (IR) imaging radiometer that was cold-weather modified. To view the data it is necessary to have the Infrared Solutions SnapView software, which is available from Infrared Solutions.

The NASA Cold Land Processes Field Experiment (CLPX) is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1 ha to 160,000 km<sup>2</sup>, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set includes ground-based radar observations carried out at the Fraser Experimental Forest Headquarters, Colorado, USA (39.95 N, 105.9 W), between 17-26 February and 26-30 March 2003. Truck-mounted L- and Ku-band scatterometers were used to collect fully polarimetric backscattering coefficients of snow. The calibrated radar systems measured the amplitude and phase of backscattered signal over a relatively wide bandwidth at L-band (1.1-1.4 GHz) and Ku-band (15.25-15.75 GHz). Backscatter measurements of an open snow pack were collected at three different incidence angles (20, 35, and 50 degrees) several times a day. This data set is part of the NASA Cold Land Processes Field Experiment (CLPX).

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set includes ground-based radar observations carried out at the Fraser Experimental Forest Headquarters, Colorado, USA (39.95 N, 105.9 W), between 17-26 February and 26-30 March 2003. Truck-mounted L- and Ku-band scatterometers were used to collect fully polarimetric backscattering coefficients of snow. The calibrated radar systems measured the amplitude and phase of backscattered signal over a relatively wide bandwidth at L-band (1.1-1.4 GHz) and Ku-band (15.25-15.75 GHz). Backscatter measurements of an open snow pack were collected at three different incidence angles (20, 35, and 50 degrees) several times a day. This data set is part of the NASA Cold Land Processes Field Experiment (CLPX).

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set includes ground-based radar observations carried out at the Fraser Experimental Forest Headquarters, Colorado, USA (39.95 N, 105.9 W), between 17-26 February and 26-30 March 2003. Truck-mounted L- and Ku-band scatterometers were used to collect fully polarimetric backscattering coefficients of snow. The calibrated radar systems measured the amplitude and phase of backscattered signal over a relatively wide bandwidth at L-band (1.1-1.4 GHz) and Ku-band (15.25-15.75 GHz). Backscatter measurements of an open snow pack were collected at three different incidence angles (20, 35, and 50 degrees) several times a day. This data set is part of the NASA Cold Land Processes Field Experiment (CLPX).

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set contains meteorological observations at 36 sites throughout the Small Regional Study Area (SRSA) of the NASA Cold Land Processes Field Experiment (CLPX) in Colorado, USA. Identical meteorological towers were located close to the four corners of nine 1 km x 1 km Intensive Study Areas (ISAs). At each site, measurements of air temperature, relative humidity, wind speed, and wind direction were made at 2 m (North Park) or 4 m (Frasier and Buffalo Pass) above ground level. Snow depth, soil moisture, and soil temperatures were also measured. Hourly meteorological observations were recorded between 20 September 2002 and 1 October 2003, although data were not necessarily continuous throughout this time period for all towers.

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km^2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry; and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set contains meteorological observations at 36 sites throughout the Small Regional Study Area (SRSA) of the NASA Cold Land Processes Field Experiment (CLPX) in Colorado, USA. Identical meteorological towers were located close to the four corners of nine 1 km x 1 km Intensive Study Areas (ISAs). At each site, measurements of air temperature, relative humidity, wind speed, and wind direction were made at 2 m (North Park) or 4 m (Frasier and Buffalo Pass) above ground level. Snow depth, soil moisture, and soil temperatures were also measured. Hourly meteorological observations were recorded between 20 September 2002 and 1 October 2003, although data were not necessarily continuous throughout this time period for all towers.

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km^2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry; and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set contains meteorological observations at 36 sites throughout the Small Regional Study Area (SRSA) of the NASA Cold Land Processes Field Experiment (CLPX) in Colorado, USA. Identical meteorological towers were located close to the four corners of nine 1 km x 1 km Intensive Study Areas (ISAs). At each site, measurements of air temperature, relative humidity, wind speed, and wind direction were made at 2 m (North Park) or 4 m (Frasier and Buffalo Pass) above ground level. Snow depth, soil moisture, and soil temperatures were also measured. Hourly meteorological observations were recorded between 20 September 2002 and 1 October 2003, although data were not necessarily continuous throughout this time period for all towers.

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km^2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry; and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set contains meteorological observations at ten sites throughout the Small Regional Study Area (SRSA) of the Cold Land Processes Field Experiment (CLPX) in Fraser, Colorado, USA. Nine identical meteorological towers were located close to the center of each Intensive Study Area (ISA). Another meteorological tower was located close to the Local-Scale Observation Site (LSOS) within the Fraser Meso-Cell Study Area (MSA). At each site, measurements were made at 10 m above ground level (air temperature, relative humidity, radiation, leaf wetness, wind speed, and direction); approximately 1 m above maximum anticipated snow depth (air temperature, relative humidity, wind speed, wind direction and, in the North Park MSA only, precipitation); and snow depth, snow surface temperature, snow temperature profile, soil moisture, and soil temperatures. Snow pits were also dug at the meteorological sites, and snow density, temperature, and stratigraphy were recorded. Meteorological observations were recorded at a 10-minute temporal resolution between 20 September 2002 and 1 October 2003, although data were not necessarily continuous throughout this time period for all towers. Meteorological measurements were made to support investigations of spatial and temporal variations in accumulation and ablation of the seasonal snowpack within the study areas. 

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set contains meteorological observations at ten sites throughout the Small Regional Study Area (SRSA) of the Cold Land Processes Field Experiment (CLPX) in Fraser, Colorado, USA. Nine identical meteorological towers were located close to the center of each Intensive Study Area (ISA). Another meteorological tower was located close to the Local-Scale Observation Site (LSOS) within the Fraser Meso-Cell Study Area (MSA). At each site, measurements were made at 10 m above ground level (air temperature, relative humidity, radiation, leaf wetness, wind speed, and direction); approximately 1 m above maximum anticipated snow depth (air temperature, relative humidity, wind speed, wind direction and, in the North Park MSA only, precipitation); and snow depth, snow surface temperature, snow temperature profile, soil moisture, and soil temperatures. Snow pits were also dug at the meteorological sites, and snow density, temperature, and stratigraphy were recorded. Meteorological observations were recorded at a 10-minute temporal resolution between 20 September 2002 and 1 October 2003, although data were not necessarily continuous throughout this time period for all towers. Meteorological measurements were made to support investigations of spatial and temporal variations in accumulation and ablation of the seasonal snowpack within the study areas. 

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set contains meteorological observations at ten sites throughout the Small Regional Study Area (SRSA) of the Cold Land Processes Field Experiment (CLPX) in Fraser, Colorado, USA. Nine identical meteorological towers were located close to the center of each Intensive Study Area (ISA). Another meteorological tower was located close to the Local-Scale Observation Site (LSOS) within the Fraser Meso-Cell Study Area (MSA). At each site, measurements were made at 10 m above ground level (air temperature, relative humidity, radiation, leaf wetness, wind speed, and direction); approximately 1 m above maximum anticipated snow depth (air temperature, relative humidity, wind speed, wind direction and, in the North Park MSA only, precipitation); and snow depth, snow surface temperature, snow temperature profile, soil moisture, and soil temperatures. Snow pits were also dug at the meteorological sites, and snow density, temperature, and stratigraphy were recorded. Meteorological observations were recorded at a 10-minute temporal resolution between 20 September 2002 and 1 October 2003, although data were not necessarily continuous throughout this time period for all towers. Meteorological measurements were made to support investigations of spatial and temporal variations in accumulation and ablation of the seasonal snowpack within the study areas. 

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set is part of the NASA Cold Land Processes Field Experiment (CLPX). Parameters include snow depth, surface wetness, surface roughness, canopy, and soil temperature, measured at Fraser, North Park, and Rabbit Ears MSAs on 19-24 February and 25-30 March 2002.

CLPX consists of ground, airborne, and satellite measurements of snow and frozen ground. The CLPX uses a set of nested study areas to permit a detailed examination of cold land processes, modeling, and measurement over a wide range of physiographic conditions and spatial scales. The nested study areas are the Large Regional Study Area (LSA) consisting of 4.5 x 3.5 degrees in north-central Colorado and south-central Wyoming, Meso-cell Study Areas (MSAs) that are 25 km x 25 km, Intensive Study Areas (ISAs) that are 1 km2, and Sectors (four sectors per ISA, with 100-m grid spacing per sector). Temporally, the data collection focuses on two seasons, between 2001 and 2004: mid-winter (when conditions are generally frozen and dry) and early spring (a transitional period when both frozen and thawed, dry and wet, conditions are widespread).
This data set is part of the NASA Cold Land Processes Field Experiment (CLPX). Parameters include snow depth, surface wetness, surface roughness, canopy, and soil temperature, measured at Fraser, North Park, and Rabbit Ears MSAs on 19-24 February and 25-30 March 2002.

CLPX consists of ground, airborne, and satellite measurements of snow and frozen ground. The CLPX uses a set of nested study areas to permit a detailed examination of cold land processes, modeling, and measurement over a wide range of physiographic conditions and spatial scales. The nested study areas are the Large Regional Study Area (LSA) consisting of 4.5 x 3.5 degrees in north-central Colorado and south-central Wyoming, Meso-cell Study Areas (MSAs) that are 25 km x 25 km, Intensive Study Areas (ISAs) that are 1 km2, and Sectors (four sectors per ISA, with 100-m grid spacing per sector). Temporally, the data collection focuses on two seasons, between 2001 and 2004: mid-winter (when conditions are generally frozen and dry) and early spring (a transitional period when both frozen and thawed, dry and wet, conditions are widespread).
This data set is part of the NASA Cold Land Processes Field Experiment (CLPX). Parameters include snow depth, surface wetness, surface roughness, canopy, and soil temperature, measured at Fraser, North Park, and Rabbit Ears MSAs on 19-24 February and 25-30 March 2002.

CLPX consists of ground, airborne, and satellite measurements of snow and frozen ground. The CLPX uses a set of nested study areas to permit a detailed examination of cold land processes, modeling, and measurement over a wide range of physiographic conditions and spatial scales. The nested study areas are the Large Regional Study Area (LSA) consisting of 4.5 x 3.5 degrees in north-central Colorado and south-central Wyoming, Meso-cell Study Areas (MSAs) that are 25 km x 25 km, Intensive Study Areas (ISAs) that are 1 km2, and Sectors (four sectors per ISA, with 100-m grid spacing per sector). Temporally, the data collection focuses on two seasons, between 2001 and 2004: mid-winter (when conditions are generally frozen and dry) and early spring (a transitional period when both frozen and thawed, dry and wet, conditions are widespread).
This data set consists of snow depth data from nine study areas, within 
three larger-scale areas in northern Colorado (Fraser, North Park, and 
Rabbit Ears Meso-cell Study Areas (MSAs)). The study areas range from low-relief (flat topography) 
unforested areas with shallow snow covers, to high-relief (complex topography)
densely forested areas with deep snow covers. Parameters measured include 
snow depth, snow wetness, snow temperature, soil temperature, and canopy cover. Photos were taken of 
surface roughness and terrain. Data were collected during February and March 2002 and 2003. This data 
set is part of the NASA Cold Land Processes Field Experiment (CLPX).
This data set consists of snow depth data from nine study areas, within 
three larger-scale areas in northern Colorado (Fraser, North Park, and 
Rabbit Ears Meso-cell Study Areas (MSAs)). The study areas range from low-relief (flat topography) 
unforested areas with shallow snow covers, to high-relief (complex topography)
densely forested areas with deep snow covers. Parameters measured include 
snow depth, snow wetness, snow temperature, soil temperature, and canopy cover. Photos were taken of 
surface roughness and terrain. Data were collected during February and March 2002 and 2003. This data 
set is part of the NASA Cold Land Processes Field Experiment (CLPX).
This data set consists of snow depth data from nine study areas, within 
three larger-scale areas in northern Colorado (Fraser, North Park, and 
Rabbit Ears Meso-cell Study Areas (MSAs)). The study areas range from low-relief (flat topography) 
unforested areas with shallow snow covers, to high-relief (complex topography)
densely forested areas with deep snow covers. Parameters measured include 
snow depth, snow wetness, snow temperature, soil temperature, and canopy cover. Photos were taken of 
surface roughness and terrain. Data were collected during February and March 2002 and 2003. This data 
set is part of the NASA Cold Land Processes Field Experiment (CLPX).
This data set consists of snow pit data from nine study areas, within three larger-scale areas in northern 
Colorado (Fraser, North Park, and Rabbit 
Ears Meso-cell Study Areas (MSAs)). The study areas range from low-relief (flat topography) 
unforested areas with shallow snow covers, to high-relief (complex topography) densely forested areas 
with deep snow covers. Parameters 
measured include snow density, snow temperature, snow stratigraphy, and 
snow grain size. Data were collected during February 
and March 2002 and 2003. This data set is part of the NASA Cold Land Processes Field Experiment (CLPX).
This data set consists of snow pit data from nine study areas, within three larger-scale areas in northern 
Colorado (Fraser, North Park, and Rabbit 
Ears Meso-cell Study Areas (MSAs)). The study areas range from low-relief (flat topography) 
unforested areas with shallow snow covers, to high-relief (complex topography) densely forested areas 
with deep snow covers. Parameters 
measured include snow density, snow temperature, snow stratigraphy, and 
snow grain size. Data were collected during February 
and March 2002 and 2003. This data set is part of the NASA Cold Land Processes Field Experiment (CLPX).
This data set consists of snow pit data from nine study areas, within three larger-scale areas in northern 
Colorado (Fraser, North Park, and Rabbit 
Ears Meso-cell Study Areas (MSAs)). The study areas range from low-relief (flat topography) 
unforested areas with shallow snow covers, to high-relief (complex topography) densely forested areas 
with deep snow covers. Parameters 
measured include snow density, snow temperature, snow stratigraphy, and 
snow grain size. Data were collected during February 
and March 2002 and 2003. This data set is part of the NASA Cold Land Processes Field Experiment (CLPX).
This data set consists of in-situ point measurements of soil moisture within three 25-km by 25-km Meso-cell Study Areas (MSAs) in northern Colorado (Fraser, North Park , and Rabbit Ears). Measurements were made between September 2001 and April 2003. Spatial and temporal variations in soil moisture described by these data may be used to support remotely sensed airborne (e.g., Gamma flights) and satellite (e.g., AMSR-E) surveys of soil moisture at increasing spatial scales. Gravimetric measurements, as well as some volumetric measurements, of soil moisture were made at each measurement site. 

The NASA Cold Land Processes Field Experiment (CLPX) is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set consists of in-situ point measurements of soil moisture within three 25-km by 25-km Meso-cell Study Areas (MSAs) in northern Colorado (Fraser, North Park , and Rabbit Ears). Measurements were made between September 2001 and April 2003. Spatial and temporal variations in soil moisture described by these data may be used to support remotely sensed airborne (e.g., Gamma flights) and satellite (e.g., AMSR-E) surveys of soil moisture at increasing spatial scales. Gravimetric measurements, as well as some volumetric measurements, of soil moisture were made at each measurement site. 

The NASA Cold Land Processes Field Experiment (CLPX) is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set consists of in-situ point measurements of soil moisture within three 25-km by 25-km Meso-cell Study Areas (MSAs) in northern Colorado (Fraser, North Park , and Rabbit Ears). Measurements were made between September 2001 and April 2003. Spatial and temporal variations in soil moisture described by these data may be used to support remotely sensed airborne (e.g., Gamma flights) and satellite (e.g., AMSR-E) surveys of soil moisture at increasing spatial scales. Gravimetric measurements, as well as some volumetric measurements, of soil moisture were made at each measurement site. 

The NASA Cold Land Processes Field Experiment (CLPX) is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set presents micrometeorological data from the Flux over Snow Surfaces (FLOSS) project carried out during the Cold Land Processes Field Experiment (CLPX) at North Park, Colorado, USA. The project measured air temperature, air pressure, relative humidity, wind speed, water vapor flux, carbon dioxide, longwave and shortwave radiation, soil temperature, soil moisture, soil heat flux, precipitation, snow depth, and eddy correlation. Measurements were collected between 1 Dec 2001 and 27 March 2002, and between 20 November 2002 and 24 March 2003. Sensors were installed on 2-meter and 4-meter platforms.
This data set presents micrometeorological data from the Flux over Snow Surfaces (FLOSS) project carried out during the Cold Land Processes Field Experiment (CLPX) at North Park, Colorado, USA. The project measured air temperature, air pressure, relative humidity, wind speed, water vapor flux, carbon dioxide, longwave and shortwave radiation, soil temperature, soil moisture, soil heat flux, precipitation, snow depth, and eddy correlation. Measurements were collected between 1 Dec 2001 and 27 March 2002, and between 20 November 2002 and 24 March 2003. Sensors were installed on 2-meter and 4-meter platforms.
This data set presents micrometeorological data from the Flux over Snow Surfaces (FLOSS) project carried out during the Cold Land Processes Field Experiment (CLPX) at North Park, Colorado, USA. The project measured air temperature, air pressure, relative humidity, wind speed, water vapor flux, carbon dioxide, longwave and shortwave radiation, soil temperature, soil moisture, soil heat flux, precipitation, snow depth, and eddy correlation. Measurements were collected between 1 Dec 2001 and 27 March 2002, and between 20 November 2002 and 24 March 2003. Sensors were installed on 2-meter and 4-meter platforms.
This data set presents micrometeorological data from the Flux over Snow Surfaces (FLOSS) project carried out during the Cold Land Processes Field Experiment (CLPX) at North Park, Colorado, USA. The project measured air temperature, air pressure, relative humidity, wind speed, water vapor flux, carbon dioxide, longwave and shortwave radiation, soil temperature, soil moisture, soil heat flux, precipitation, snow depth, and eddy correlation. Measurements were collected between 1 Dec 2001 and 27 March 2002, and between 20 November 2002 and 24 March 2003. Sensors were installed on a 24-meter tower, and on 2-meter and 4-meter platforms.
This data set presents micrometeorological data from the Flux over Snow Surfaces (FLOSS) project carried out during the Cold Land Processes Field Experiment (CLPX) at North Park, Colorado, USA. The project measured air temperature, air pressure, relative humidity, wind speed, water vapor flux, carbon dioxide, longwave and shortwave radiation, soil temperature, soil moisture, soil heat flux, precipitation, snow depth, and eddy correlation. Measurements were collected between 1 Dec 2001 and 27 March 2002, and between 20 November 2002 and 24 March 2003. Sensors were installed on a 24-meter tower, and on 2-meter and 4-meter platforms.
This data set presents micrometeorological data from the Flux over Snow Surfaces (FLOSS) project carried out during the Cold Land Processes Field Experiment (CLPX) at North Park, Colorado, USA. The project measured air temperature, air pressure, relative humidity, wind speed, water vapor flux, carbon dioxide, longwave and shortwave radiation, soil temperature, soil moisture, soil heat flux, precipitation, snow depth, and eddy correlation. Measurements were collected between 1 Dec 2001 and 27 March 2002, and between 20 November 2002 and 24 March 2003. Sensors were installed on a 24-meter tower, and on 2-meter and 4-meter platforms.
This data set presents snow depth, snow water equivalence (SWE), snow wetness data, and snow pit data from two pine sites and a small clearing at the Local Scale Observation Site (LSOS) of the Cold Land Processes Field Experiment (CLPX) in northern Colorado. The LSOS is a 0.8 ha study site located within the Fraser Intensive Study Area (ISA). The study area has flat topography with a uniform pine forest, a discontinuous pine forest, and a small clearing. Data were collected during February and March 2003. 

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set presents snow depth, snow water equivalence (SWE), snow wetness data, and snow pit data from two pine sites and a small clearing at the Local Scale Observation Site (LSOS) of the Cold Land Processes Field Experiment (CLPX) in northern Colorado. The LSOS is a 0.8 ha study site located within the Fraser Intensive Study Area (ISA). The study area has flat topography with a uniform pine forest, a discontinuous pine forest, and a small clearing. Data were collected during February and March 2003. 

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set presents snow depth, snow water equivalence (SWE), snow wetness data, and snow pit data from two pine sites and a small clearing at the Local Scale Observation Site (LSOS) of the Cold Land Processes Field Experiment (CLPX) in northern Colorado. The LSOS is a 0.8 ha study site located within the Fraser Intensive Study Area (ISA). The study area has flat topography with a uniform pine forest, a discontinuous pine forest, and a small clearing. Data were collected during February and March 2003. 

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set consists of solar and longwave radiation data from beneath two pine canopies (one uniform, one discontinuous) at the Local Scale Observation Site (LSOS) of the Cold Land Processes Field Experiment (CLPX) in northern Colorado. The LSOS is a 100 x 100-m study site located within the Fraser Intensive Study Area (ISA). The study area has flat topography with both a dense pine stand and an open pine stand. Data were collected during February and March 2002 and 2003. 

This work addresses two of the overall CLPX questions: (1) How do the extent and evolution of snow and frozen landscapes affect fluxes, storage, and transformations of water, energy, and carbon? (2) At what scales does spatial variability of key state variables in the cryosphere (including snow characteristics, soil moisture, the extent of frozen soils, and the transition between frozen and thawed conditions) control fluxes and transformations of water, energy, and carbon, and can remote sensing resolve this variability at these scales? 

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set consists of solar and longwave radiation data from beneath two pine canopies (one uniform, one discontinuous) at the Local Scale Observation Site (LSOS) of the Cold Land Processes Field Experiment (CLPX) in northern Colorado. The LSOS is a 100 x 100-m study site located within the Fraser Intensive Study Area (ISA). The study area has flat topography with both a dense pine stand and an open pine stand. Data were collected during February and March 2002 and 2003. 

This work addresses two of the overall CLPX questions: (1) How do the extent and evolution of snow and frozen landscapes affect fluxes, storage, and transformations of water, energy, and carbon? (2) At what scales does spatial variability of key state variables in the cryosphere (including snow characteristics, soil moisture, the extent of frozen soils, and the transition between frozen and thawed conditions) control fluxes and transformations of water, energy, and carbon, and can remote sensing resolve this variability at these scales? 

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set consists of solar and longwave radiation data from beneath two pine canopies (one uniform, one discontinuous) at the Local Scale Observation Site (LSOS) of the Cold Land Processes Field Experiment (CLPX) in northern Colorado. The LSOS is a 100 x 100-m study site located within the Fraser Intensive Study Area (ISA). The study area has flat topography with both a dense pine stand and an open pine stand. Data were collected during February and March 2002 and 2003. 

This work addresses two of the overall CLPX questions: (1) How do the extent and evolution of snow and frozen landscapes affect fluxes, storage, and transformations of water, energy, and carbon? (2) At what scales does spatial variability of key state variables in the cryosphere (including snow characteristics, soil moisture, the extent of frozen soils, and the transition between frozen and thawed conditions) control fluxes and transformations of water, energy, and carbon, and can remote sensing resolve this variability at these scales? 

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set contains microwave radiometry data collected at the Local Scale Observation Site (LSOS) of the Cold Land Processes Field Experiment (CLPX) in Colorado, USA, during IOP4 (March-April 2003). The LSOS is a 100 x 100 m study site located within the Fraser Intensive Study Area (ISA). The LSOS has flat topography with areas of both uniform and discontinuous pine forest, and a small clearing. The majority of the data consist of brightness temperatures at a 54 degree incidence angle of the accumulated snowpack at the small clearing in the LSOS. Other observations include upwelling brightness temperatures from short and tall trees, and downwelling brightness temperatures from tall trees. Snowpack ranged from 0 to 80 cm in depth.The microwave radiometers operated at 6.7, 19, and 37 GHz. 

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set contains microwave radiometry data collected at the Local Scale Observation Site (LSOS) of the Cold Land Processes Field Experiment (CLPX) in Colorado, USA, during IOP4 (March-April 2003). The LSOS is a 100 x 100 m study site located within the Fraser Intensive Study Area (ISA). The LSOS has flat topography with areas of both uniform and discontinuous pine forest, and a small clearing. The majority of the data consist of brightness temperatures at a 54 degree incidence angle of the accumulated snowpack at the small clearing in the LSOS. Other observations include upwelling brightness temperatures from short and tall trees, and downwelling brightness temperatures from tall trees. Snowpack ranged from 0 to 80 cm in depth.The microwave radiometers operated at 6.7, 19, and 37 GHz. 

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set contains microwave radiometry data collected at the Local Scale Observation Site (LSOS) of the Cold Land Processes Field Experiment (CLPX) in Colorado, USA, during IOP4 (March-April 2003). The LSOS is a 100 x 100 m study site located within the Fraser Intensive Study Area (ISA). The LSOS has flat topography with areas of both uniform and discontinuous pine forest, and a small clearing. The majority of the data consist of brightness temperatures at a 54 degree incidence angle of the accumulated snowpack at the small clearing in the LSOS. Other observations include upwelling brightness temperatures from short and tall trees, and downwelling brightness temperatures from tall trees. Snowpack ranged from 0 to 80 cm in depth.The microwave radiometers operated at 6.7, 19, and 37 GHz. 

The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
The Local Analysis and Prediction System (LAPS), run by the NOAA's Forecast Systems Laboratory (FSL), combines numerous observed meteorological data sets into a collection of atmospheric analyses. LAPS analyses data include hourly three-dimensional and surface distributions of temperature, surface u and v winds, vertical velocity, dew-point temperature, relative humidity, specific humidity, pressure, MSL pressure, cloud type, mean cloud drop diameter, cloud base, cloud top, fractional cloud cover, cloud liquid water, cloud ice, surface precipitation type, rain concentration, snow concentration, soil moisture, snow accumulation, snow water equivalent, and snowmelt over the Cold Land Processes Experiment (CLPX) study areas in Colorado and Wyoming, USA (approximately 36.1°N through 45.8°N latitude, and 113.8°W through 97.2°W longitude). The CLPX LAPS analyses archive spans the period 1 September 2001 through 31 August 2003. Data are separated into a 2-D surface field group and a 3-D upper air group. Data are available at an hourly resolution on a 10-km horizontal grid (125 x 105), with the 3-D upper air group comprising 21 vertical levels. All data files are delivered in netCDF format.
The Local Analysis and Prediction System (LAPS), run by the NOAA's Forecast Systems Laboratory (FSL), combines numerous observed meteorological data sets into a collection of atmospheric analyses. LAPS analyses data include hourly three-dimensional and surface distributions of temperature, surface u and v winds, vertical velocity, dew-point temperature, relative humidity, specific humidity, pressure, MSL pressure, cloud type, mean cloud drop diameter, cloud base, cloud top, fractional cloud cover, cloud liquid water, cloud ice, surface precipitation type, rain concentration, snow concentration, soil moisture, snow accumulation, snow water equivalent, and snowmelt over the Cold Land Processes Experiment (CLPX) study areas in Colorado and Wyoming, USA (approximately 36.1°N through 45.8°N latitude, and 113.8°W through 97.2°W longitude). The CLPX LAPS analyses archive spans the period 1 September 2001 through 31 August 2003. Data are separated into a 2-D surface field group and a 3-D upper air group. Data are available at an hourly resolution on a 10-km horizontal grid (125 x 105), with the 3-D upper air group comprising 21 vertical levels. All data files are delivered in netCDF format.
The Local Analysis and Prediction System (LAPS), run by the NOAA's Forecast Systems Laboratory (FSL), combines numerous observed meteorological data sets into a collection of atmospheric analyses. LAPS analyses data include hourly three-dimensional and surface distributions of temperature, surface u and v winds, vertical velocity, dew-point temperature, relative humidity, specific humidity, pressure, MSL pressure, cloud type, mean cloud drop diameter, cloud base, cloud top, fractional cloud cover, cloud liquid water, cloud ice, surface precipitation type, rain concentration, snow concentration, soil moisture, snow accumulation, snow water equivalent, and snowmelt over the Cold Land Processes Experiment (CLPX) study areas in Colorado and Wyoming, USA (approximately 36.1°N through 45.8°N latitude, and 113.8°W through 97.2°W longitude). The CLPX LAPS analyses archive spans the period 1 September 2001 through 31 August 2003. Data are separated into a 2-D surface field group and a 3-D upper air group. Data are available at an hourly resolution on a 10-km horizontal grid (125 x 105), with the 3-D upper air group comprising 21 vertical levels. All data files are delivered in netCDF format.
The Rapid Update Cycle, version 2 at 40km (RUC-2, known to the Cold Land Processes community as RUC40) model is a Mesoscale Analysis and Prediction System (MAPS) data set that uses the Model Output Reduced Data Set (MORDS) version. This data set has been subsetted for use in the Cold Land Processes Field Experiment (CLPX). The data are in a 40 km (approximate) Lambertian latitude/longitude grid covering the Large-Regional Study Area (LRSA).The data set covers the period from 1 October 2002 through 30 June 2003, with a time step of 60 seconds. RUC40 data are stored in individual ASCII data files, with one file per hour. Within each hourly file, 42 data variables are stored in row-major order. The RUC40 model uses the Arakawa-C staggered horizontal grid, with u and v horizontal wind points offset from mass points to improve numerical accuracy, and there is no vertical staggering. Positive definite advection schemes are used for the continuity equation (advection of pressure thickness between levels) and for horizontal advection of virtual potential temperature, and all vapor and hydrometer moisture variables.
The Rapid Update Cycle, version 2 at 40km (RUC-2, known to the Cold Land Processes community as RUC40) model is a Mesoscale Analysis and Prediction System (MAPS) data set that uses the Model Output Reduced Data Set (MORDS) version. This data set has been subsetted for use in the Cold Land Processes Field Experiment (CLPX). The data are in a 40 km (approximate) Lambertian latitude/longitude grid covering the Large-Regional Study Area (LRSA).The data set covers the period from 1 October 2002 through 30 June 2003, with a time step of 60 seconds. RUC40 data are stored in individual ASCII data files, with one file per hour. Within each hourly file, 42 data variables are stored in row-major order. The RUC40 model uses the Arakawa-C staggered horizontal grid, with u and v horizontal wind points offset from mass points to improve numerical accuracy, and there is no vertical staggering. Positive definite advection schemes are used for the continuity equation (advection of pressure thickness between levels) and for horizontal advection of virtual potential temperature, and all vapor and hydrometer moisture variables.
The Rapid Update Cycle, version 2 at 40km (RUC-2, known to the Cold Land Processes community as RUC40) model is a Mesoscale Analysis and Prediction System (MAPS) data set that uses the Model Output Reduced Data Set (MORDS) version. This data set has been subsetted for use in the Cold Land Processes Field Experiment (CLPX). The data are in a 40 km (approximate) Lambertian latitude/longitude grid covering the Large-Regional Study Area (LRSA).The data set covers the period from 1 October 2002 through 30 June 2003, with a time step of 60 seconds. RUC40 data are stored in individual ASCII data files, with one file per hour. Within each hourly file, 42 data variables are stored in row-major order. The RUC40 model uses the Arakawa-C staggered horizontal grid, with u and v horizontal wind points offset from mass points to improve numerical accuracy, and there is no vertical staggering. Positive definite advection schemes are used for the continuity equation (advection of pressure thickness between levels) and for horizontal advection of virtual potential temperature, and all vapor and hydrometer moisture variables.
This data set includes Aqua Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) passive microwave brightness temperatures gridded to the geographic (lat-lon) and UTM grids of the Cold Land Processes Field Experiment (CLPX) Large Regional Study Area (LRSA).  Data are provided for passive microwave frequencies at 6.9, 10.7, 18.7,23.8, 36.5 and 89.0 GHz, separated by ascending and descending satellite passes, and include time files. These data are interpolated from swath space using inverse distance squared resampling.  Grid resolution is approximately 25 km.  Temporal coverage is 1 February - 31 May, 2003.  Satellite passive microwave brightness temperatures can be used to derive snow water equivalent.
This data set includes Aqua Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) passive microwave brightness temperatures gridded to the geographic (lat-lon) and UTM grids of the Cold Land Processes Field Experiment (CLPX) Large Regional Study Area (LRSA).  Data are provided for passive microwave frequencies at 6.9, 10.7, 18.7,23.8, 36.5 and 89.0 GHz, separated by ascending and descending satellite passes, and include time files. These data are interpolated from swath space using inverse distance squared resampling.  Grid resolution is approximately 25 km.  Temporal coverage is 1 February - 31 May, 2003.  Satellite passive microwave brightness temperatures can be used to derive snow water equivalent.
This data set includes Aqua Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) passive microwave brightness temperatures gridded to the geographic (lat-lon) and UTM grids of the Cold Land Processes Field Experiment (CLPX) Large Regional Study Area (LRSA).  Data are provided for passive microwave frequencies at 6.9, 10.7, 18.7,23.8, 36.5 and 89.0 GHz, separated by ascending and descending satellite passes, and include time files. These data are interpolated from swath space using inverse distance squared resampling.  Grid resolution is approximately 25 km.  Temporal coverage is 1 February - 31 May, 2003.  Satellite passive microwave brightness temperatures can be used to derive snow water equivalent.
This data set includes AVHRR/HRPT (Advanced Very High Resolution Radiometer/High Resolution Picture Transmission) brightness temperatures and reflectances over the NASA Cold Land Processes Field Experiment (CLPX) Large Regional Study Area (LRSA) (NW corner: 42°N, 108.5°W, SE corner: 38.5°N 104°W). Data are gridded to the LRSA at 1.1 km (or 30 arc-second) resolution. Data were collected between November 2001 and May 2003. Reflectance files contain flat binary rasters of 2-byte unsigned integers representing albedo. The brightness temperature files contain 2-byte unsigned integers representing interpolated temperatures in tenths of degrees Kelvin.
This data set includes AVHRR/HRPT (Advanced Very High Resolution Radiometer/High Resolution Picture Transmission) brightness temperatures and reflectances over the NASA Cold Land Processes Field Experiment (CLPX) Large Regional Study Area (LRSA) (NW corner: 42°N, 108.5°W, SE corner: 38.5°N 104°W). Data are gridded to the LRSA at 1.1 km (or 30 arc-second) resolution. Data were collected between November 2001 and May 2003. Reflectance files contain flat binary rasters of 2-byte unsigned integers representing albedo. The brightness temperature files contain 2-byte unsigned integers representing interpolated temperatures in tenths of degrees Kelvin.
This data set includes AVHRR/HRPT (Advanced Very High Resolution Radiometer/High Resolution Picture Transmission) brightness temperatures and reflectances over the NASA Cold Land Processes Field Experiment (CLPX) Large Regional Study Area (LRSA) (NW corner: 42°N, 108.5°W, SE corner: 38.5°N 104°W). Data are gridded to the LRSA at 1.1 km (or 30 arc-second) resolution. Data were collected between November 2001 and May 2003. Reflectance files contain flat binary rasters of 2-byte unsigned integers representing albedo. The brightness temperature files contain 2-byte unsigned integers representing interpolated temperatures in tenths of degrees Kelvin.
This data set consists of apparent surface reflectance, subpixel snow-covered area and grain size collected from the Hyperion hyperspectral imager. The Hyperion imager has a spectral range of 400-2500 nm, a spectral resolution of 10 nm, spatial resolution of 30 m, and a swath width of 7.8 km. Sampling is scene based (256 samples, 512 lines).

The Hyperion capabilities provide resolution of surface properties into hundreds of spectral bands versus the six optical multispectral bands flown on traditional Landsat imaging missions. Through these large number of spectral bands, complex land ecosystems can be imaged and accurately classified. Data are available via FTP. Users must register with NSIDC User Services to obtain access to the data. 

This data set is part of the NASA Cold Land Processes Field Experiment (CLPX). The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set consists of apparent surface reflectance, subpixel snow-covered area and grain size collected from the Hyperion hyperspectral imager. The Hyperion imager has a spectral range of 400-2500 nm, a spectral resolution of 10 nm, spatial resolution of 30 m, and a swath width of 7.8 km. Sampling is scene based (256 samples, 512 lines).

The Hyperion capabilities provide resolution of surface properties into hundreds of spectral bands versus the six optical multispectral bands flown on traditional Landsat imaging missions. Through these large number of spectral bands, complex land ecosystems can be imaged and accurately classified. Data are available via FTP. Users must register with NSIDC User Services to obtain access to the data. 

This data set is part of the NASA Cold Land Processes Field Experiment (CLPX). The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set consists of apparent surface reflectance, subpixel snow-covered area and grain size collected from the Hyperion hyperspectral imager. The Hyperion imager has a spectral range of 400-2500 nm, a spectral resolution of 10 nm, spatial resolution of 30 m, and a swath width of 7.8 km. Sampling is scene based (256 samples, 512 lines).

The Hyperion capabilities provide resolution of surface properties into hundreds of spectral bands versus the six optical multispectral bands flown on traditional Landsat imaging missions. Through these large number of spectral bands, complex land ecosystems can be imaged and accurately classified. Data are available via FTP. Users must register with NSIDC User Services to obtain access to the data. 

This data set is part of the NASA Cold Land Processes Field Experiment (CLPX). The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set consists of Lansat thematic mapper imagergy collected over 
the Cold Land Processes Field Experiment (CLPX) Large Regional Study Area (LRSA), located between 104-108.5 W and 
38.5-42 N. Data were collected between 10 November 2001 and 9 January 2003,  using the Enhanced Thematic Mapper Plus sensor (ETM+) on Landsat 7 and the Thematic Mapper (TM) sensor on Landsat 5. Data consist of Level 1G imagery 
products (radiance) that have been radiometrically and geometrically 
corrected.   Each band of Landsat data in the GeoTIFF format is delivered 
as a greyscale, uncompressed, 8-bit string of unsigned integers. This data 
set is part of the NASA CLPX

NASA CLPX is a multi-sensor, multi-scale 
experiment that focuses on extending a local-scale understanding of water 
fluxes, storage, and transformations to regional and global scales. Within 
a framework of nested study areas in the central Rocky Mountains of the 
western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses 
on two seasons: mid-winter, when conditions are generally frozen and dry, 
and early spring, a transitional period when both frozen and thawed, dry 
and wet conditions are widespread.
This data set consists of Lansat thematic mapper imagergy collected over 
the Cold Land Processes Field Experiment (CLPX) Large Regional Study Area (LRSA), located between 104-108.5 W and 
38.5-42 N. Data were collected between 10 November 2001 and 9 January 2003,  using the Enhanced Thematic Mapper Plus sensor (ETM+) on Landsat 7 and the Thematic Mapper (TM) sensor on Landsat 5. Data consist of Level 1G imagery 
products (radiance) that have been radiometrically and geometrically 
corrected.   Each band of Landsat data in the GeoTIFF format is delivered 
as a greyscale, uncompressed, 8-bit string of unsigned integers. This data 
set is part of the NASA CLPX

NASA CLPX is a multi-sensor, multi-scale 
experiment that focuses on extending a local-scale understanding of water 
fluxes, storage, and transformations to regional and global scales. Within 
a framework of nested study areas in the central Rocky Mountains of the 
western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses 
on two seasons: mid-winter, when conditions are generally frozen and dry, 
and early spring, a transitional period when both frozen and thawed, dry 
and wet conditions are widespread.
This data set consists of Lansat thematic mapper imagergy collected over 
the Cold Land Processes Field Experiment (CLPX) Large Regional Study Area (LRSA), located between 104-108.5 W and 
38.5-42 N. Data were collected between 10 November 2001 and 9 January 2003,  using the Enhanced Thematic Mapper Plus sensor (ETM+) on Landsat 7 and the Thematic Mapper (TM) sensor on Landsat 5. Data consist of Level 1G imagery 
products (radiance) that have been radiometrically and geometrically 
corrected.   Each band of Landsat data in the GeoTIFF format is delivered 
as a greyscale, uncompressed, 8-bit string of unsigned integers. This data 
set is part of the NASA CLPX

NASA CLPX is a multi-sensor, multi-scale 
experiment that focuses on extending a local-scale understanding of water 
fluxes, storage, and transformations to regional and global scales. Within 
a framework of nested study areas in the central Rocky Mountains of the 
western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses 
on two seasons: mid-winter, when conditions are generally frozen and dry, 
and early spring, a transitional period when both frozen and thawed, dry 
and wet conditions are widespread.
This data set provides Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Cold Land Processes Field Experiment (CLPX). These data are delivered in geographic (GEO) and Universal Tranverse Mercator (UTM) grids covering the Large-Regional Study Area (LRSA) in Colorado, USA. The data cover the time period Feb 15 (day 046) through May 15 (day 135), a total of 90 days, for both study years (2002-2003). Data were resampled from the original HDF-EOS product files containing either swath data or gridded data. Parameters include calibrated radiances, surface refelctance, snow cover, surface temperature/emissivity, and vegetation indices. Gridded data are provided in two formats: raw binary (including an ASCII header) and GeoTiff. Both formats are provided as output from the MODIS Reprojection Tool which is used to 
regrid MODIS gridded data.
This data set provides Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Cold Land Processes Field Experiment (CLPX). These data are delivered in geographic (GEO) and Universal Tranverse Mercator (UTM) grids covering the Large-Regional Study Area (LRSA) in Colorado, USA. The data cover the time period Feb 15 (day 046) through May 15 (day 135), a total of 90 days, for both study years (2002-2003). Data were resampled from the original HDF-EOS product files containing either swath data or gridded data. Parameters include calibrated radiances, surface refelctance, snow cover, surface temperature/emissivity, and vegetation indices. Gridded data are provided in two formats: raw binary (including an ASCII header) and GeoTiff. Both formats are provided as output from the MODIS Reprojection Tool which is used to 
regrid MODIS gridded data.
This data set provides Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Cold Land Processes Field Experiment (CLPX). These data are delivered in geographic (GEO) and Universal Tranverse Mercator (UTM) grids covering the Large-Regional Study Area (LRSA) in Colorado, USA. The data cover the time period Feb 15 (day 046) through May 15 (day 135), a total of 90 days, for both study years (2002-2003). Data were resampled from the original HDF-EOS product files containing either swath data or gridded data. Parameters include calibrated radiances, surface refelctance, snow cover, surface temperature/emissivity, and vegetation indices. Gridded data are provided in two formats: raw binary (including an ASCII header) and GeoTiff. Both formats are provided as output from the MODIS Reprojection Tool which is used to 
regrid MODIS gridded data.
This data set includes Level-1B1radiance (all angles), Level-1B2 georectified terrain, and Level-2 land surface, and an ancillary geographic product for the Large Regional Study Area (LRSA) of the Cold Land Processes Field Experiment (CLPX) in northern Colorado and southern Wyoming. Data were collected between 15 February and 15 May 2002 and the same time period in 2003.  Data are available via FTP.

The Multi-angle Imaging SpectroRadiometer (MISR) views Earth at nine widely spaced angles via radiometrically and geometrically calibrated images in four spectral bands at each of the nine angles, to provide global images with high spatial detail. Global spatial sampling is provided at 275 and 1100 meters. These images provide accurate measures of the brightness, contrast, and color of reflected sunlight.
This data set includes Level-1B1radiance (all angles), Level-1B2 georectified terrain, and Level-2 land surface, and an ancillary geographic product for the Large Regional Study Area (LRSA) of the Cold Land Processes Field Experiment (CLPX) in northern Colorado and southern Wyoming. Data were collected between 15 February and 15 May 2002 and the same time period in 2003.  Data are available via FTP.

The Multi-angle Imaging SpectroRadiometer (MISR) views Earth at nine widely spaced angles via radiometrically and geometrically calibrated images in four spectral bands at each of the nine angles, to provide global images with high spatial detail. Global spatial sampling is provided at 275 and 1100 meters. These images provide accurate measures of the brightness, contrast, and color of reflected sunlight.
This data set includes Level-1B1radiance (all angles), Level-1B2 georectified terrain, and Level-2 land surface, and an ancillary geographic product for the Large Regional Study Area (LRSA) of the Cold Land Processes Field Experiment (CLPX) in northern Colorado and southern Wyoming. Data were collected between 15 February and 15 May 2002 and the same time period in 2003.  Data are available via FTP.

The Multi-angle Imaging SpectroRadiometer (MISR) views Earth at nine widely spaced angles via radiometrically and geometrically calibrated images in four spectral bands at each of the nine angles, to provide global images with high spatial detail. Global spatial sampling is provided at 275 and 1100 meters. These images provide accurate measures of the brightness, contrast, and color of reflected sunlight.
This data set consists of time-series spaceborne Synthetic Aperture Radar (SAR) imagery of the three Cold Land Processes Field Experiment (CLPX) Meso-cell Study Areas (MSAs) (Fraser, Rabbit Ears, and North Park) acquired by the RADARSAT-1 Synthetic Aperture Radar (SAR). Images are derived from C-band (5.3 GHz frequency, 5.66 cm wavelength) HH-polarization Standard Beam data for multiple incidence angles. SAR data were acquired through the Alaska Satellite Facility (ASF) and post-processed at the Jet Propulsion Laboratory, California Institute of Technology, for derivation of ancillary data and assembly of the database. The data series consists of 195 individual radar scenes acquired from 17 February to 23 June 2003. Calibrated radar backscatter images are provided in binary format together with header and facility data record information for each image. 

Note that the Canadian Space Agency (CSA) holds copyrights over all RADARSAT-1 SAR data. NASA/NOAA-approved SAR researchers are can obtain these data directly from ASF, as per agreements between NASA/NOAA and CSA. No commercial use is allowed of the data or any products derived there from. Users of this data must submit a <A HREF='/data/docs/daac/nsidc0146_clpx_radarsat/ASF_Res_Agreement.doc'>Research Agreement</A> to ASF.


The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set consists of time-series spaceborne Synthetic Aperture Radar (SAR) imagery of the three Cold Land Processes Field Experiment (CLPX) Meso-cell Study Areas (MSAs) (Fraser, Rabbit Ears, and North Park) acquired by the RADARSAT-1 Synthetic Aperture Radar (SAR). Images are derived from C-band (5.3 GHz frequency, 5.66 cm wavelength) HH-polarization Standard Beam data for multiple incidence angles. SAR data were acquired through the Alaska Satellite Facility (ASF) and post-processed at the Jet Propulsion Laboratory, California Institute of Technology, for derivation of ancillary data and assembly of the database. The data series consists of 195 individual radar scenes acquired from 17 February to 23 June 2003. Calibrated radar backscatter images are provided in binary format together with header and facility data record information for each image. 

Note that the Canadian Space Agency (CSA) holds copyrights over all RADARSAT-1 SAR data. NASA/NOAA-approved SAR researchers are can obtain these data directly from ASF, as per agreements between NASA/NOAA and CSA. No commercial use is allowed of the data or any products derived there from. Users of this data must submit a <A HREF='/data/docs/daac/nsidc0146_clpx_radarsat/ASF_Res_Agreement.doc'>Research Agreement</A> to ASF.


The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set consists of time-series spaceborne Synthetic Aperture Radar (SAR) imagery of the three Cold Land Processes Field Experiment (CLPX) Meso-cell Study Areas (MSAs) (Fraser, Rabbit Ears, and North Park) acquired by the RADARSAT-1 Synthetic Aperture Radar (SAR). Images are derived from C-band (5.3 GHz frequency, 5.66 cm wavelength) HH-polarization Standard Beam data for multiple incidence angles. SAR data were acquired through the Alaska Satellite Facility (ASF) and post-processed at the Jet Propulsion Laboratory, California Institute of Technology, for derivation of ancillary data and assembly of the database. The data series consists of 195 individual radar scenes acquired from 17 February to 23 June 2003. Calibrated radar backscatter images are provided in binary format together with header and facility data record information for each image. 

Note that the Canadian Space Agency (CSA) holds copyrights over all RADARSAT-1 SAR data. NASA/NOAA-approved SAR researchers are can obtain these data directly from ASF, as per agreements between NASA/NOAA and CSA. No commercial use is allowed of the data or any products derived there from. Users of this data must submit a <A HREF='/data/docs/daac/nsidc0146_clpx_radarsat/ASF_Res_Agreement.doc'>Research Agreement</A> to ASF.


The NASA CLPX is a multi-sensor, multi-scale experiment that focuses on extending a local-scale understanding of water fluxes, storage, and transformations to regional and global scales. Within a framework of nested study areas in the central Rocky Mountains of the western United States, ranging from 1-ha to 160,000 km2, intensive ground, airborne, and spaceborne observations are collected. Data collection focuses on two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, dry and wet conditions are widespread.
This data set includes Defense Meteorological Satellite Program (DMSP) F-13 passive microwave brightness temperatures gridded to the geographic (lat/long) and UTM grids of the Cold Land Processes Field Experiment (CLPX) Large Regional Study Area (LRSA). Data are provided for passive microwave frequencies at 19, 22, 37 and 85 GHz, separated by ascending and descending satellite passes, and include time files. Grid resolution is 25 km, which approximates the sampling resolution of the original swath data. Backus-Gilbert optimal interpolation is used to artificially increase (16 times) the density of brightness temperature measurements in the satellite swath reference frame. This process uses actual antenna patterns to create the oversampled array, and the net effect is as if the additional samples had been made by the satellite radiometer itself, i.e., the beam patterns and spatial resolutions of the interpolated data approximate those 
of the original samples. This method is based on the earlier work of Galantowicz and England (1991) and Poe (1990). Please see the documentation 
for the global version of this data set for complete details. Please see the documentation for the global version of this data set at http://nsidc.org/data/nsidc-0032.html for complete details. 

Several things about this data set that are different:
1) Temporal coverage is limited to 1 February - 31 March 2002 and 
   1 February - 31 March 2003.
2) The projection/grid is not EASE-Grid, it is CLPX lrsa_geo720.0 and lrsa_utm25000. However, interpolation is Backus-Gilbert, so all the benefits of this interpolation are shared with the global data set.
3) Filenames are different. 4) CLPX grid dimensions are:
GEO720.0: 23 cols by 18 rows UTM25000: 17 cols by 17 rows
5) Grid resolution for CLPX is limited to the CLPX grids that approximate 25 km.
This data set includes Defense Meteorological Satellite Program (DMSP) F-13 passive microwave brightness temperatures gridded to the geographic (lat/long) and UTM grids of the Cold Land Processes Field Experiment (CLPX) Large Regional Study Area (LRSA). Data are provided for passive microwave frequencies at 19, 22, 37 and 85 GHz, separated by ascending and descending satellite passes, and include time files. Grid resolution is 25 km, which approximates the sampling resolution of the original swath data. Backus-Gilbert optimal interpolation is used to artificially increase (16 times) the density of brightness temperature measurements in the satellite swath reference frame. This process uses actual antenna patterns to create the oversampled array, and the net effect is as if the additional samples had been made by the satellite radiometer itself, i.e., the beam patterns and spatial resolutions of the interpolated data approximate those 
of the original samples. This method is based on the earlier work of Galantowicz and England (1991) and Poe (1990). Please see the documentation 
for the global version of this data set for complete details. Please see the documentation for the global version of this data set at http://nsidc.org/data/nsidc-0032.html for complete details. 

Several things about this data set that are different:
1) Temporal coverage is limited to 1 February - 31 March 2002 and 
   1 February - 31 March 2003.
2) The projection/grid is not EASE-Grid, it is CLPX lrsa_geo720.0 and lrsa_utm25000. However, interpolation is Backus-Gilbert, so all the benefits of this interpolation are shared with the global data set.
3) Filenames are different. 4) CLPX grid dimensions are:
GEO720.0: 23 cols by 18 rows UTM25000: 17 cols by 17 rows
5) Grid resolution for CLPX is limited to the CLPX grids that approximate 25 km.
This data set includes Defense Meteorological Satellite Program (DMSP) F-13 passive microwave brightness temperatures gridded to the geographic (lat/long) and UTM grids of the Cold Land Processes Field Experiment (CLPX) Large Regional Study Area (LRSA). Data are provided for passive microwave frequencies at 19, 22, 37 and 85 GHz, separated by ascending and descending satellite passes, and include time files. Grid resolution is 25 km, which approximates the sampling resolution of the original swath data. Backus-Gilbert optimal interpolation is used to artificially increase (16 times) the density of brightness temperature measurements in the satellite swath reference frame. This process uses actual antenna patterns to create the oversampled array, and the net effect is as if the additional samples had been made by the satellite radiometer itself, i.e., the beam patterns and spatial resolutions of the interpolated data approximate those 
of the original samples. This method is based on the earlier work of Galantowicz and England (1991) and Poe (1990). Please see the documentation 
for the global version of this data set for complete details. Please see the documentation for the global version of this data set at http://nsidc.org/data/nsidc-0032.html for complete details. 

Several things about this data set that are different:
1) Temporal coverage is limited to 1 February - 31 March 2002 and 
   1 February - 31 March 2003.
2) The projection/grid is not EASE-Grid, it is CLPX lrsa_geo720.0 and lrsa_utm25000. However, interpolation is Backus-Gilbert, so all the benefits of this interpolation are shared with the global data set.
3) Filenames are different. 4) CLPX grid dimensions are:
GEO720.0: 23 cols by 18 rows UTM25000: 17 cols by 17 rows
5) Grid resolution for CLPX is limited to the CLPX grids that approximate 25 km.
Notice to Data Users:
The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains the following spatially and temporally co-registered data: Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) brightness temperatures for all channels; Quick Scatterometer (QuikSCAT) backscattering coefficients; and World Meteorological Organization (WMO) ground observations acquired from more than two thousand stations. There is a large, increasing interest in the potential arising from the combination of active and passive microwave data for the extraction of geophysical parameters from spaceborne platforms. Often, one of the major obstacles is the generation of spatially and temporally co-registered data sets for testing hypotheses, validating models, and developing retrieval approaches. The temporal coverage of this data set spans from 01 January 2002 through 19 March 2009 with AMSR-E data included for the 19 June 2002 through 19 March 2009 time period. The volume of the data set is approximately two gigabytes. Data are provided in tab-delimited ASCII text files and are available via FTP.
Notice to Data Users:
The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains the following spatially and temporally co-registered data: Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) brightness temperatures for all channels; Quick Scatterometer (QuikSCAT) backscattering coefficients; and World Meteorological Organization (WMO) ground observations acquired from more than two thousand stations. There is a large, increasing interest in the potential arising from the combination of active and passive microwave data for the extraction of geophysical parameters from spaceborne platforms. Often, one of the major obstacles is the generation of spatially and temporally co-registered data sets for testing hypotheses, validating models, and developing retrieval approaches. The temporal coverage of this data set spans from 01 January 2002 through 19 March 2009 with AMSR-E data included for the 19 June 2002 through 19 March 2009 time period. The volume of the data set is approximately two gigabytes. Data are provided in tab-delimited ASCII text files and are available via FTP.
Notice to Data Users:
The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains the following spatially and temporally co-registered data: Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) brightness temperatures for all channels; Quick Scatterometer (QuikSCAT) backscattering coefficients; and World Meteorological Organization (WMO) ground observations acquired from more than two thousand stations. There is a large, increasing interest in the potential arising from the combination of active and passive microwave data for the extraction of geophysical parameters from spaceborne platforms. Often, one of the major obstacles is the generation of spatially and temporally co-registered data sets for testing hypotheses, validating models, and developing retrieval approaches. The temporal coverage of this data set spans from 01 January 2002 through 19 March 2009 with AMSR-E data included for the 19 June 2002 through 19 March 2009 time period. The volume of the data set is approximately two gigabytes. Data are provided in tab-delimited ASCII text files and are available via FTP.
The Comprehensive Ocean - Atmosphere Data Set (COADS) LMRF Arctic
subset contains marine surface weather reports for the region north of
65 degrees N from ships, drifting ice stations, and buoys. COADS is
the result of an ongoing project to assemble and reduce
machine-readable portions of the available historical ocean-atmosphere
record into a regular, compact, easy-to-use database. The COADS LMRF
Arctic subset contains data collected over the years 1950 to 1995. The
following parameters are included in this data set: air and sea
temperature, cloudiness, humidity, and winds. The scientists
assembling COADS have attempted to integrate all available digitized,
directly sensed surface-marine data sets that would contribute
information of reasonable quality. Most of the early data were
gathered by ships-of-opportunity. More recent data also come from
fixed research vessels, buoys, and other observing devices. Data
archived at NSIDC is for the region North of 65 degrees N. for the years 1950-1995. Updates will be made available as they are received
at NSIDC.
 The COADS LMRF Arctic subset consists of 46 data files (one for each
year) which are in LMRF (Long Marine Report Fixed-Length, packed
binary format), and has a total volume of approximately 201 MB UNIX
compressed, and 632 MB uncompressed. The data are in the form of
individual marine reports with a given latitude and longitude. A
UNIX-based Fortran program is distributed with the data files.
The Comprehensive Ocean - Atmosphere Data Set (COADS) LMRF Arctic
subset contains marine surface weather reports for the region north of
65 degrees N from ships, drifting ice stations, and buoys. COADS is
the result of an ongoing project to assemble and reduce
machine-readable portions of the available historical ocean-atmosphere
record into a regular, compact, easy-to-use database. The COADS LMRF
Arctic subset contains data collected over the years 1950 to 1995. The
following parameters are included in this data set: air and sea
temperature, cloudiness, humidity, and winds. The scientists
assembling COADS have attempted to integrate all available digitized,
directly sensed surface-marine data sets that would contribute
information of reasonable quality. Most of the early data were
gathered by ships-of-opportunity. More recent data also come from
fixed research vessels, buoys, and other observing devices. Data
archived at NSIDC is for the region North of 65 degrees N. for the years 1950-1995. Updates will be made available as they are received
at NSIDC.
 The COADS LMRF Arctic subset consists of 46 data files (one for each
year) which are in LMRF (Long Marine Report Fixed-Length, packed
binary format), and has a total volume of approximately 201 MB UNIX
compressed, and 632 MB uncompressed. The data are in the form of
individual marine reports with a given latitude and longitude. A
UNIX-based Fortran program is distributed with the data files.
The Comprehensive Ocean - Atmosphere Data Set (COADS) LMRF Arctic
subset contains marine surface weather reports for the region north of
65 degrees N from ships, drifting ice stations, and buoys. COADS is
the result of an ongoing project to assemble and reduce
machine-readable portions of the available historical ocean-atmosphere
record into a regular, compact, easy-to-use database. The COADS LMRF
Arctic subset contains data collected over the years 1950 to 1995. The
following parameters are included in this data set: air and sea
temperature, cloudiness, humidity, and winds. The scientists
assembling COADS have attempted to integrate all available digitized,
directly sensed surface-marine data sets that would contribute
information of reasonable quality. Most of the early data were
gathered by ships-of-opportunity. More recent data also come from
fixed research vessels, buoys, and other observing devices. Data
archived at NSIDC is for the region North of 65 degrees N. for the years 1950-1995. Updates will be made available as they are received
at NSIDC.
 The COADS LMRF Arctic subset consists of 46 data files (one for each
year) which are in LMRF (Long Marine Report Fixed-Length, packed
binary format), and has a total volume of approximately 201 MB UNIX
compressed, and 632 MB uncompressed. The data are in the form of
individual marine reports with a given latitude and longitude. A
UNIX-based Fortran program is distributed with the data files.
CEAREX was a multi-platform field program conducted in the Norwegian
Seas and Greenland north to Svalbard from September 1988 through May
1989. Canada, Denmark, France, Norway and the United States
participated in the experiment. Primary data from CEAREX are available
on FTP in ASCII format along with some data from the Marginal Ice
Zone Experiment (MIZEX) and the Eurasian Basin Experiment (EUBEX).

Meteorology data from CEAREX and the MIZEX (1983, 1984, 1987) include near-surface time series and rawinsonde (upper-air sounding) profiles of wind, pressure, temperature, and humidity collected on ship platforms and ice floe stations. A collection of hydrography data include CTD, STD, and bottle data 
from a ship and two operations camps. Hydrography data also include data from the MIZEX, the EUBEX, NODC archives, and a merged set of data from five other cruises. Sea ice data consist of compressive stress measurements made in a multi-year floe, stress sensor data for time series of stress invariants, 
and ice accelerometer data for movements associated with the deformation of multi-year ice floes. Noise data consist of acoustic measurements from a variety of hydrophone and geophone arrays, and ambient noise observations from a ship using omni-directional hydrophones tethered beneath the ice cover. Biophysical data include bottle sample, zooplankton sampling, and 
bioluminescence data. Bathymetry data consist of gridded trackline data collected from the two operations camps, and digital bottom bathymetry and continental topography data for the Fram Strait region and a portion of the Arctic Ocean. Sample position data consist of hourly listings of position and 
velocity for both manned stations and unmanned drifting buoys. Data are available via FTP.
CEAREX was a multi-platform field program conducted in the Norwegian
Seas and Greenland north to Svalbard from September 1988 through May
1989. Canada, Denmark, France, Norway and the United States
participated in the experiment. Primary data from CEAREX are available
on FTP in ASCII format along with some data from the Marginal Ice
Zone Experiment (MIZEX) and the Eurasian Basin Experiment (EUBEX).

Meteorology data from CEAREX and the MIZEX (1983, 1984, 1987) include near-surface time series and rawinsonde (upper-air sounding) profiles of wind, pressure, temperature, and humidity collected on ship platforms and ice floe stations. A collection of hydrography data include CTD, STD, and bottle data 
from a ship and two operations camps. Hydrography data also include data from the MIZEX, the EUBEX, NODC archives, and a merged set of data from five other cruises. Sea ice data consist of compressive stress measurements made in a multi-year floe, stress sensor data for time series of stress invariants, 
and ice accelerometer data for movements associated with the deformation of multi-year ice floes. Noise data consist of acoustic measurements from a variety of hydrophone and geophone arrays, and ambient noise observations from a ship using omni-directional hydrophones tethered beneath the ice cover. Biophysical data include bottle sample, zooplankton sampling, and 
bioluminescence data. Bathymetry data consist of gridded trackline data collected from the two operations camps, and digital bottom bathymetry and continental topography data for the Fram Strait region and a portion of the Arctic Ocean. Sample position data consist of hourly listings of position and 
velocity for both manned stations and unmanned drifting buoys. Data are available via FTP.
CEAREX was a multi-platform field program conducted in the Norwegian
Seas and Greenland north to Svalbard from September 1988 through May
1989. Canada, Denmark, France, Norway and the United States
participated in the experiment. Primary data from CEAREX are available
on FTP in ASCII format along with some data from the Marginal Ice
Zone Experiment (MIZEX) and the Eurasian Basin Experiment (EUBEX).

Meteorology data from CEAREX and the MIZEX (1983, 1984, 1987) include near-surface time series and rawinsonde (upper-air sounding) profiles of wind, pressure, temperature, and humidity collected on ship platforms and ice floe stations. A collection of hydrography data include CTD, STD, and bottle data 
from a ship and two operations camps. Hydrography data also include data from the MIZEX, the EUBEX, NODC archives, and a merged set of data from five other cruises. Sea ice data consist of compressive stress measurements made in a multi-year floe, stress sensor data for time series of stress invariants, 
and ice accelerometer data for movements associated with the deformation of multi-year ice floes. Noise data consist of acoustic measurements from a variety of hydrophone and geophone arrays, and ambient noise observations from a ship using omni-directional hydrophones tethered beneath the ice cover. Biophysical data include bottle sample, zooplankton sampling, and 
bioluminescence data. Bathymetry data consist of gridded trackline data collected from the two operations camps, and digital bottom bathymetry and continental topography data for the Fram Strait region and a portion of the Arctic Ocean. Sample position data consist of hourly listings of position and 
velocity for both manned stations and unmanned drifting buoys. Data are available via FTP.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains satellite-retrieved geophysical parameter files generated from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) instrument on the National Aeronautics and Space Administration (NASA) Aqua satellite. The daily parameter retrievals extend from 19 June 2002 to 27 September 2011 and include daily air temperature minima and maxima (ta) at approximately 2 m in height; fractional cover of open water on land (fw); vegetation canopy microwave transmittance (tc); surface soil moisture (mv) at &#8804; 2 cm soil depth; and integrated water vapor content of the intervening atmosphere (V) for the total column. The global retrievals were derived over land for non-precipitating, non-snow, and non-ice covered conditions. The primary input data were daily AMSR-E dual polarized multi-frequency, ascending and descending overpass brightness temperature data. The total volume for this data set is approximately seven gigabytes. Data are provided in zipped binary files and are available via FTP.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains satellite-retrieved geophysical parameter files generated from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) instrument on the National Aeronautics and Space Administration (NASA) Aqua satellite. The daily parameter retrievals extend from 19 June 2002 to 27 September 2011 and include daily air temperature minima and maxima (ta) at approximately 2 m in height; fractional cover of open water on land (fw); vegetation canopy microwave transmittance (tc); surface soil moisture (mv) at &#8804; 2 cm soil depth; and integrated water vapor content of the intervening atmosphere (V) for the total column. The global retrievals were derived over land for non-precipitating, non-snow, and non-ice covered conditions. The primary input data were daily AMSR-E dual polarized multi-frequency, ascending and descending overpass brightness temperature data. The total volume for this data set is approximately seven gigabytes. Data are provided in zipped binary files and are available via FTP.
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.

This data set contains satellite-retrieved geophysical parameter files generated from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) instrument on the National Aeronautics and Space Administration (NASA) Aqua satellite. The daily parameter retrievals extend from 19 June 2002 to 27 September 2011 and include daily air temperature minima and maxima (ta) at approximately 2 m in height; fractional cover of open water on land (fw); vegetation canopy microwave transmittance (tc); surface soil moisture (mv) at &#8804; 2 cm soil depth; and integrated water vapor content of the intervening atmosphere (V) for the total column. The global retrievals were derived over land for non-precipitating, non-snow, and non-ice covered conditions. The primary input data were daily AMSR-E dual polarized multi-frequency, ascending and descending overpass brightness temperature data. The total volume for this data set is approximately seven gigabytes. Data are provided in zipped binary files and are available via FTP.
NSIDC produces daily gridded brightness temperature data from orbital swath data generated by the Special Sensor Microwave/Imager (SSM/I) aboard the Defense Meteorological Satellite Program (DMSP) F8, F11, and F13 platforms and the Special Sensor Microwave Imager/Sounder (SSMIS) aboard DMSP-F17. The SSM/I and SSMIS channels used to calculate brightness temperatures include 19.3 GHz vertical and horizontal, 22.2 GHz vertical, 37.0 GHz vertical and horizontal, 85.5 GHz vertical and horizontal (on SSM/I), and 91.7 GHz vertical and horizontal (on SSMIS). Thus, a total of nine channels result from vertical and horizontal polarization for each of five frequencies, with the exception of 22.2 GHz, which is vertical only. The gridded brightness temperatures are distributed in polar stereographic projection. Orbital data for each 24-hour period are mapped to respective grid cells using a simple sum and average method (drop-in-the-bucket method). 85.5 GHz and 91.7 GHz data are gridded at a resolution of 12.5 km, with all other frequencies at a resolution of 25 km. All SSM/I and SSMIS gridded brightness temperature data are stored as scaled 2-byte integers in flat binary arrays and are available via FTP.
NSIDC produces daily gridded brightness temperature data from orbital swath data generated by the Special Sensor Microwave/Imager (SSM/I) aboard the Defense Meteorological Satellite Program (DMSP) F8, F11, and F13 platforms and the Special Sensor Microwave Imager/Sounder (SSMIS) aboard DMSP-F17. The SSM/I and SSMIS channels used to calculate brightness temperatures include 19.3 GHz vertical and horizontal, 22.2 GHz vertical, 37.0 GHz vertical and horizontal, 85.5 GHz vertical and horizontal (on SSM/I), and 91.7 GHz vertical and horizontal (on SSMIS). Thus, a total of nine channels result from vertical and horizontal polarization for each of five frequencies, with the exception of 22.2 GHz, which is vertical only. The gridded brightness temperatures are distributed in polar stereographic projection. Orbital data for each 24-hour period are mapped to respective grid cells using a simple sum and average method (drop-in-the-bucket method). 85.5 GHz and 91.7 GHz data are gridded at a resolution of 12.5 km, with all other frequencies at a resolution of 25 km. All SSM/I and SSMIS gridded brightness temperature data are stored as scaled 2-byte integers in flat binary arrays and are available via FTP.
NSIDC produces daily gridded brightness temperature data from orbital swath data generated by the Special Sensor Microwave/Imager (SSM/I) aboard the Defense Meteorological Satellite Program (DMSP) F8, F11, and F13 platforms and the Special Sensor Microwave Imager/Sounder (SSMIS) aboard DMSP-F17. The SSM/I and SSMIS channels used to calculate brightness temperatures include 19.3 GHz vertical and horizontal, 22.2 GHz vertical, 37.0 GHz vertical and horizontal, 85.5 GHz vertical and horizontal (on SSM/I), and 91.7 GHz vertical and horizontal (on SSMIS). Thus, a total of nine channels result from vertical and horizontal polarization for each of five frequencies, with the exception of 22.2 GHz, which is vertical only. The gridded brightness temperatures are distributed in polar stereographic projection. Orbital data for each 24-hour period are mapped to respective grid cells using a simple sum and average method (drop-in-the-bucket method). 85.5 GHz and 91.7 GHz data are gridded at a resolution of 12.5 km, with all other frequencies at a resolution of 25 km. All SSM/I and SSMIS gridded brightness temperature data are stored as scaled 2-byte integers in flat binary arrays and are available via FTP.
This Level-3 Equal-Area Scalable Earth-Grid (EASE-Grid) Brightness Temperature data set, collected since 09 July 1987, is a part of the NOAA/NASA Pathfinder Program. The data set consists of gridded data from the Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager/Sounder (SSMIS) in three equal-area projections: Northern Hemisphere, Southern Hemisphere, and full global. The data gridding technique maximizes the radiometric integrity of the original brightness temperature values, maintains high spatial and temporal precision, and involves no averaging of original swath data. Spatial coverage is global and a spatial resolution of 25 km is available for all channels. Channels at 85 and 91 GHz are also provided at 12.5 km. For a given projection, there are 18 brightness temperature files per day and two corresponding time files. Data are contained in flat binary files and are available via FTP as processing is completed.
This Level-3 Equal-Area Scalable Earth-Grid (EASE-Grid) Brightness Temperature data set, collected since 09 July 1987, is a part of the NOAA/NASA Pathfinder Program. The data set consists of gridded data from the Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager/Sounder (SSMIS) in three equal-area projections: Northern Hemisphere, Southern Hemisphere, and full global. The data gridding technique maximizes the radiometric integrity of the original brightness temperature values, maintains high spatial and temporal precision, and involves no averaging of original swath data. Spatial coverage is global and a spatial resolution of 25 km is available for all channels. Channels at 85 and 91 GHz are also provided at 12.5 km. For a given projection, there are 18 brightness temperature files per day and two corresponding time files. Data are contained in flat binary files and are available via FTP as processing is completed.
This Level-3 Equal-Area Scalable Earth-Grid (EASE-Grid) Brightness Temperature data set, collected since 09 July 1987, is a part of the NOAA/NASA Pathfinder Program. The data set consists of gridded data from the Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager/Sounder (SSMIS) in three equal-area projections: Northern Hemisphere, Southern Hemisphere, and full global. The data gridding technique maximizes the radiometric integrity of the original brightness temperature values, maintains high spatial and temporal precision, and involves no averaging of original swath data. Spatial coverage is global and a spatial resolution of 25 km is available for all channels. Channels at 85 and 91 GHz are also provided at 12.5 km. For a given projection, there are 18 brightness temperature files per day and two corresponding time files. Data are contained in flat binary files and are available via FTP as processing is completed.
These sea ice concentrations have been generated by applying the NASA
Team algorithm to DMSP F8 SSM/I brightness temperature observations
from 19 GHz (vertical and horizontal), 37- and 22 GHz vertical
frequencies, calculating two gradients for use as weather
filters. Global coverage is provided, but sea ice concentrations are
only derived for ocean, ice, and possible ice surfaces poleward of 35
degrees latitude, from 1 August 1987 through 30 November 1988. In the
Northern Hemisphere, where data are not filtered due to weather
effects, first-year and multi-year concentrations (in percent) are
calculated; total ice concentration is taken as the sum of these
two. Only total ice is calculated for the Southern Hemisphere.
25 km swath data are in HDF, available via FTP.
These sea ice concentrations have been generated by applying the NASA
Team algorithm to DMSP F8 SSM/I brightness temperature observations
from 19 GHz (vertical and horizontal), 37- and 22 GHz vertical
frequencies, calculating two gradients for use as weather
filters. Global coverage is provided, but sea ice concentrations are
only derived for ocean, ice, and possible ice surfaces poleward of 35
degrees latitude, from 1 August 1987 through 30 November 1988. In the
Northern Hemisphere, where data are not filtered due to weather
effects, first-year and multi-year concentrations (in percent) are
calculated; total ice concentration is taken as the sum of these
two. Only total ice is calculated for the Southern Hemisphere.
25 km swath data are in HDF, available via FTP.
These sea ice concentrations have been generated by applying the NASA
Team algorithm to DMSP F8 SSM/I brightness temperature observations
from 19 GHz (vertical and horizontal), 37- and 22 GHz vertical
frequencies, calculating two gradients for use as weather
filters. Global coverage is provided, but sea ice concentrations are
only derived for ocean, ice, and possible ice surfaces poleward of 35
degrees latitude, from 1 August 1987 through 30 November 1988. In the
Northern Hemisphere, where data are not filtered due to weather
effects, first-year and multi-year concentrations (in percent) are
calculated; total ice concentration is taken as the sum of these
two. Only total ice is calculated for the Southern Hemisphere.
25 km swath data are in HDF, available via FTP.
The Pathfinder Program, sponsored by the National Oceanic and Atmospheric Administration (NOAA) and the National Aeronautics and Space Administration (NASA), is tasked to produce long-term data sets for global change research. The Special Sensor Microwave/Imager (SSM/I) Pathfinder Level 2 Land Products data set has been generated using the land classification algorithms developed by Neale, and the land surface temperature algorithms developed by McFarland. This data set includes both the land classification and land surface temperature products.  The Pathfinder Level 2 Land Products data set is in swath format. Coverage is global land surface, and covers 1 August 1987 through 31 March 1988. Data are available via ftp on request.

The SSM/I Pathfinder Level 3 Land Products data set has been generated using the Level 2 data described above. The Level 2 data were interpolated to a longitude-latitude grid with a resolution of one degree. For the Benchmark Period, the data were averaged over periods of five days (a pentad) or one month, although, for the land classification product, the most commonly occurring land class (the mode of the distribution within each bin) was chosen as the class for that bin and for the period. The data set, including both pentad and monthly grids, covers 1 August 1987 through 31 December 1988.
The Pathfinder Program, sponsored by the National Oceanic and Atmospheric Administration (NOAA) and the National Aeronautics and Space Administration (NASA), is tasked to produce long-term data sets for global change research. The Special Sensor Microwave/Imager (SSM/I) Pathfinder Level 2 Land Products data set has been generated using the land classification algorithms developed by Neale, and the land surface temperature algorithms developed by McFarland. This data set includes both the land classification and land surface temperature products.  The Pathfinder Level 2 Land Products data set is in swath format. Coverage is global land surface, and covers 1 August 1987 through 31 March 1988. Data are available via ftp on request.

The SSM/I Pathfinder Level 3 Land Products data set has been generated using the Level 2 data described above. The Level 2 data were interpolated to a longitude-latitude grid with a resolution of one degree. For the Benchmark Period, the data were averaged over periods of five days (a pentad) or one month, although, for the land classification product, the most commonly occurring land class (the mode of the distribution within each bin) was chosen as the class for that bin and for the period. The data set, including both pentad and monthly grids, covers 1 August 1987 through 31 December 1988.
The Pathfinder Program, sponsored by the National Oceanic and Atmospheric Administration (NOAA) and the National Aeronautics and Space Administration (NASA), is tasked to produce long-term data sets for global change research. The Special Sensor Microwave/Imager (SSM/I) Pathfinder Level 2 Land Products data set has been generated using the land classification algorithms developed by Neale, and the land surface temperature algorithms developed by McFarland. This data set includes both the land classification and land surface temperature products.  The Pathfinder Level 2 Land Products data set is in swath format. Coverage is global land surface, and covers 1 August 1987 through 31 March 1988. Data are available via ftp on request.

The SSM/I Pathfinder Level 3 Land Products data set has been generated using the Level 2 data described above. The Level 2 data were interpolated to a longitude-latitude grid with a resolution of one degree. For the Benchmark Period, the data were averaged over periods of five days (a pentad) or one month, although, for the land classification product, the most commonly occurring land class (the mode of the distribution within each bin) was chosen as the class for that bin and for the period. The data set, including both pentad and monthly grids, covers 1 August 1987 through 31 December 1988.