Global Multihazard Mortality Risks and Distribution is a 2.5 minute grid identifying and 

characterizing the nature of multihazard risk at the global scale. For this study, multihazard considers the hazards posed by 

cyclones, droughts, earthquakes, floods, landslides and volcanoes. The specific hazards are grouped into the following hazard 

categories: drought (drought), seismic (earthquakes and volcanoes), and hydro (cyclones, floods, and landslides). Each grid cell is 

assessed for each hazard category; and is considered at high risk or not at high risk. Treated as a binary value, the at-risk values 

of the hazards categories function as a 3-digit index of multihazard. For each of the hazard category combinations, aggregate 

analyses determine the total population, area, and length of major transportation features, as well as, the value of Gross Domestic 

Product (GDP) and agricultural GDP. This dataset is the result of collaboration among the Columbia University Center for Hazards and 

Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for 

International Earth Science Information Network (CIESIN).
Global Multihazard Mortality Risks and Distribution is a 2.5 minute grid identifying and 

characterizing the nature of multihazard risk at the global scale. For this study, multihazard considers the hazards posed by 

cyclones, droughts, earthquakes, floods, landslides and volcanoes. The specific hazards are grouped into the following hazard 

categories: drought (drought), seismic (earthquakes and volcanoes), and hydro (cyclones, floods, and landslides). Each grid cell is 

assessed for each hazard category; and is considered at high risk or not at high risk. Treated as a binary value, the at-risk values 

of the hazards categories function as a 3-digit index of multihazard. For each of the hazard category combinations, aggregate 

analyses determine the total population, area, and length of major transportation features, as well as, the value of Gross Domestic 

Product (GDP) and agricultural GDP. This dataset is the result of collaboration among the Columbia University Center for Hazards and 

Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for 

International Earth Science Information Network (CIESIN).
Global Multihazard Proportional Economic Loss Risks is a 2.5 minute grid of a multihazard-based 

economic loss risk as a proportion of the economic productivity of the analytical unit, the grid cell. Representation of multihazard 

risk is not based on a multihazard index but rather on combinations of hazard risk categories, drought, seismic, and hydro. The 

drought category includes drought only. The seismic category consists of earthquake and volcano hazards. Cyclones, floods, and 

landslides are included in the hydro category. For each of the six hazards considered, a binary risk surface is constructed utilizing 

the three most-at-risk deciles of each hazard's global proportional economic loss risks dataset (deciles 8-10). Each of the category 

risk surfaces are constructed by adding all the relevant hazard high-risk surfaces. These categorical risk surfaces are reclassified 

into binary high-risk surfaces. The combination of the category risk values forms a three digit identifier for determining those 

locations that are at higher-risk from multihazards. This dataset is the result of collaboration among the Columbia University Center 

for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University 

Center for International Earth Science Information Network (CIESIN).
Global Multihazard Proportional Economic Loss Risks is a 2.5 minute grid of a multihazard-based 

economic loss risk as a proportion of the economic productivity of the analytical unit, the grid cell. Representation of multihazard 

risk is not based on a multihazard index but rather on combinations of hazard risk categories, drought, seismic, and hydro. The 

drought category includes drought only. The seismic category consists of earthquake and volcano hazards. Cyclones, floods, and 

landslides are included in the hydro category. For each of the six hazards considered, a binary risk surface is constructed utilizing 

the three most-at-risk deciles of each hazard's global proportional economic loss risks dataset (deciles 8-10). Each of the category 

risk surfaces are constructed by adding all the relevant hazard high-risk surfaces. These categorical risk surfaces are reclassified 

into binary high-risk surfaces. The combination of the category risk values forms a three digit identifier for determining those 

locations that are at higher-risk from multihazards. This dataset is the result of collaboration among the Columbia University Center 

for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University 

Center for International Earth Science Information Network (CIESIN).
Global Multihazard Proportional Economic Loss Risks is a 2.5 minute grid of a multihazard-based 

economic loss risk as a proportion of the economic productivity of the analytical unit, the grid cell. Representation of multihazard 

risk is not based on a multihazard index but rather on combinations of hazard risk categories, drought, seismic, and hydro. The 

drought category includes drought only. The seismic category consists of earthquake and volcano hazards. Cyclones, floods, and 

landslides are included in the hydro category. For each of the six hazards considered, a binary risk surface is constructed utilizing 

the three most-at-risk deciles of each hazard's global proportional economic loss risks dataset (deciles 8-10). Each of the category 

risk surfaces are constructed by adding all the relevant hazard high-risk surfaces. These categorical risk surfaces are reclassified 

into binary high-risk surfaces. The combination of the category risk values forms a three digit identifier for determining those 

locations that are at higher-risk from multihazards. This dataset is the result of collaboration among the Columbia University Center 

for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University 

Center for International Earth Science Information Network (CIESIN).
Global Multihazard Total Economic Loss Risk Deciles is a 2.5 minute grid of global multihazard 

total economic loss risks. First, for each of the considered hazards (cyclones, droughts, earthquakes, floods, landslides, and 

volcanoes), subnational distributions of Gross Domestic Product (GDP) are computed using a methodology developed from Sachs et al. 

(2003). Where applicable, the contributions of subnational units to national GDP estimates, the contribution ratio, are determined 

using data of varied origin. World Bank Development Indicators are substituted for GDP estimates of varied origin and the subnational 

GDP is estimated using the fore mentioned contribution ratios. A subnational, per capita GDP is derived and a final GDP estimate per 

grid cell is made based on grid cell population density. A raw, total economic loss is computed per grid cell using a regional 

economic loss rate derived from EM-DAT records. To more accurately reflect the confidence surrounding the economic loss estimate, the 

range of losses are classified into deciles, 10 classes of an approximately equal number of grid cells. A multihazard index is 

generated by summing the top three deciles of the individual hazards. This dataset is the result of collaboration among the Columbia 

University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and 

Columbia University Center for International Earth Science Information Network (CIESIN).
Global Multihazard Total Economic Loss Risk Deciles is a 2.5 minute grid of global multihazard 

total economic loss risks. First, for each of the considered hazards (cyclones, droughts, earthquakes, floods, landslides, and 

volcanoes), subnational distributions of Gross Domestic Product (GDP) are computed using a methodology developed from Sachs et al. 

(2003). Where applicable, the contributions of subnational units to national GDP estimates, the contribution ratio, are determined 

using data of varied origin. World Bank Development Indicators are substituted for GDP estimates of varied origin and the subnational 

GDP is estimated using the fore mentioned contribution ratios. A subnational, per capita GDP is derived and a final GDP estimate per 

grid cell is made based on grid cell population density. A raw, total economic loss is computed per grid cell using a regional 

economic loss rate derived from EM-DAT records. To more accurately reflect the confidence surrounding the economic loss estimate, the 

range of losses are classified into deciles, 10 classes of an approximately equal number of grid cells. A multihazard index is 

generated by summing the top three deciles of the individual hazards. This dataset is the result of collaboration among the Columbia 

University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and 

Columbia University Center for International Earth Science Information Network (CIESIN).
Global Multihazard Total Economic Loss Risk Deciles is a 2.5 minute grid of global multihazard 

total economic loss risks. First, for each of the considered hazards (cyclones, droughts, earthquakes, floods, landslides, and 

volcanoes), subnational distributions of Gross Domestic Product (GDP) are computed using a methodology developed from Sachs et al. 

(2003). Where applicable, the contributions of subnational units to national GDP estimates, the contribution ratio, are determined 

using data of varied origin. World Bank Development Indicators are substituted for GDP estimates of varied origin and the subnational 

GDP is estimated using the fore mentioned contribution ratios. A subnational, per capita GDP is derived and a final GDP estimate per 

grid cell is made based on grid cell population density. A raw, total economic loss is computed per grid cell using a regional 

economic loss rate derived from EM-DAT records. To more accurately reflect the confidence surrounding the economic loss estimate, the 

range of losses are classified into deciles, 10 classes of an approximately equal number of grid cells. A multihazard index is 

generated by summing the top three deciles of the individual hazards. This dataset is the result of collaboration among the Columbia 

University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and 

Columbia University Center for International Earth Science Information Network (CIESIN).
Nitrogen is a major nutrient in terrestrial ecosystems and an important catalyst in tropospheric photochemistry. Over the last century human activities have dramatically increased inputs of reactive nitrogen (Nr, the combination of oxidized, reduced and organically bound nitrogen) to the Earth system. Nitrogen cycle perturbations have compromised air quality and human health, acidified ecosystems, and degraded and eutrophied  lakes and coastal estuaries [Vitousek et al., 1997a, 1997b; Rabalais, 2002; Howarth et al., 2003; Townsend et al., 2003; Galloway et al., 2004]. To begin to quantify the changes to the global N cycle, we have assembled key flux data and N2O mixing ratios from various sources.  The data assembled from different sources includes fertilizer production from 1920-2004;  manure production from 1860-2004; crop N fixation estimated for three time points, 1860, 1900, 1995; tropospheric N2O mixing ratios from ice core and firn measurements, and tropospheric concentrations to cover the time period from 1756-2004.  The changing N2O concentrations provide an independent index of changes to the global N cycle, in much the same way that changing carbon dioxide concentrations provide an important constraint on the global carbon cycle.  The changes to the global N cycle are driven by industrialization, as indicated by fossil fuel NOx emission, and by the intensification of agriculture, as indicted by fertilizer and manure production and crop N2 fixation. The data set and the science it reflects are by nature interdisciplinary.  Making the data set available through the ORNL DAAC is an attempt to make the data set available to the considerable interdisciplinary community studying the N cycle.
Nitrogen is a major nutrient in terrestrial ecosystems and an important catalyst in tropospheric photochemistry. Over the last century human activities have dramatically increased inputs of reactive nitrogen (Nr, the combination of oxidized, reduced and organically bound nitrogen) to the Earth system. Nitrogen cycle perturbations have compromised air quality and human health, acidified ecosystems, and degraded and eutrophied  lakes and coastal estuaries [Vitousek et al., 1997a, 1997b; Rabalais, 2002; Howarth et al., 2003; Townsend et al., 2003; Galloway et al., 2004]. To begin to quantify the changes to the global N cycle, we have assembled key flux data and N2O mixing ratios from various sources.  The data assembled from different sources includes fertilizer production from 1920-2004;  manure production from 1860-2004; crop N fixation estimated for three time points, 1860, 1900, 1995; tropospheric N2O mixing ratios from ice core and firn measurements, and tropospheric concentrations to cover the time period from 1756-2004.  The changing N2O concentrations provide an independent index of changes to the global N cycle, in much the same way that changing carbon dioxide concentrations provide an important constraint on the global carbon cycle.  The changes to the global N cycle are driven by industrialization, as indicated by fossil fuel NOx emission, and by the intensification of agriculture, as indicted by fertilizer and manure production and crop N2 fixation. The data set and the science it reflects are by nature interdisciplinary.  Making the data set available through the ORNL DAAC is an attempt to make the data set available to the considerable interdisciplinary community studying the N cycle.
ABSTRACT: Nitrogen is a major nutrient in terrestrial ecosystems and an important catalyst in tropospheric photochemistry. Over the last century human activities have dramatically increased inputs of reactive nitrogen (Nr, the combination of oxidized, reduced and organically bound nitrogen) to the Earth system. Nitrogen cycle perturbations have compromised air quality and human health, acidified ecosystems, and degraded and eutrophied  lakes and coastal estuaries [Vitousek et al., 1997a, 1997b; Rabalais, 2002; Howarth et al., 2003; Townsend et al., 2003; Galloway et al., 2004]. To begin to quantify the changes to the global N cycle, we have assembled key flux data and N2O mixing ratios from various sources.  The data assembled from different sources includes fertilizer production from 1920-2004;  manure production from 1860-2004; crop N fixation estimated for three time points, 1860, 1900, 1995; tropospheric N2O mixing ratios from ice core and firn measurements, and tropospheric concentrations to cover the time period from 1756-2004.  The changing N2O concentrations provide an independent index of changes to the global N cycle, in much the same way that changing carbon dioxide concentrations provide an important constraint on the global carbon cycle.  The changes to the global N cycle are driven by industrialization, as indicated by fossil fuel NOx emission, and by the intensification of agriculture, as indicted by fertilizer and manure production and crop N2 fixation. The data set and the science it reflects are by nature interdisciplinary.  Making the data set available through the ORNL DAAC is an attempt to make the data set available to the considerable interdisciplinary community studying the N cycle.
A compilation of worldwide soil carbon and nitrogen data for more than 3500 soil profiles.
A compilation of worldwide soil carbon and nitrogen data for more than 3500 soil profiles.
ABSTRACT: A compilation of worldwide soil carbon and nitrogen data for more than 3500 soil profiles.
The Global Reservoir and Dam Database, Version 1 (Revision 01) contains 6,862 records of reservoirs and their associated dams with a cumulative storage capacity of 6,197 cubic 

km. The dams were geospatially referenced and assigned to polygons depicting reservoir outlines at high spatial resolution. Dams have multiple attributes, such as name of the dam and 

impounded river, primary use, nearest city, height, area and volume of reservoir, and year of construction (or commissioning). While the main focus was to include all dams associated with 

reservoirs that have a storage capacity of more than 0.1 cubic kilometers, many smaller dams and reservoirs were added where data were available. The data were compiled by Lehner et al. 

(2011) and are distributed by the Global Water System Project (GWSP) and by the Columbia University Center for International Earth Science Information Network (CIESIN). For details please 

refer to the Technical Documentation which is provided with the data.
The Global Reservoir and Dam Database, Version 1 (Revision 01) contains 6,862 records of reservoirs and their associated dams with a cumulative storage capacity of 6,197 cubic 

km. The dams were geospatially referenced and assigned to polygons depicting reservoir outlines at high spatial resolution. Dams have multiple attributes, such as name of the dam and 

impounded river, primary use, nearest city, height, area and volume of reservoir, and year of construction (or commissioning). While the main focus was to include all dams associated with 

reservoirs that have a storage capacity of more than 0.1 cubic kilometers, many smaller dams and reservoirs were added where data were available. The data were compiled by Lehner et al. 

(2011) and are distributed by the Global Water System Project (GWSP) and by the Columbia University Center for International Earth Science Information Network (CIESIN). For details please 

refer to the Technical Documentation which is provided with the data.
The Global Reservoir and Dam Database, Version 1 (Revision 01) contains 6,862 records of reservoirs and their associated dams with a cumulative storage capacity of 6,197 cubic 

km. The dams were geospatially referenced and assigned to polygons depicting reservoir outlines at high spatial resolution. Dams have multiple attributes, such as name of the dam and 

impounded river, primary use, nearest city, height, area and volume of reservoir, and year of construction (or commissioning). While the main focus was to include all dams associated with 

reservoirs that have a storage capacity of more than 0.1 cubic kilometers, many smaller dams and reservoirs were added where data were available. The data were compiled by Lehner et al. 

(2011) and are distributed by the Global Water System Project (GWSP) and by the Columbia University Center for International Earth Science Information Network (CIESIN). For details please 

refer to the Technical Documentation which is provided with the data.
The Global Reservoir and Dam (GRanD) Database, Version 1.1 contains 6,862 records of reservoirs and their associated dams with a cumulative storage capacity of 6,197 cubic km. 

The reservoirs were delineated from high spatial resolution satellite imagery and are available as polygon shape files. The only attribute for the reservoirs is the area of the reservoir. 

The associated dams data set includes multiple attributes such as name of the dam and the impounded river, primary use, nearest city, area, and year of construction (or commissioning). 

While the main focus was to include all reservoirs with a storage capacity of more than 0.1 cubic kilometers, many smaller reservoirs were added where data were available. The data were 

compiled by Lehner et al. (2011) and are distributed by the Global Water System Project (GWSP) and by the Columbia University Center for International Earth Science Information Network 

(CIESIN). For details please refer to the Technical Documentation which is provided with the data.
The Global Reservoir and Dam (GRanD) Database, Version 1.1 contains 6,862 records of reservoirs and their associated dams with a cumulative storage capacity of 6,197 cubic km. 

The reservoirs were delineated from high spatial resolution satellite imagery and are available as polygon shape files. The only attribute for the reservoirs is the area of the reservoir. 

The associated dams data set includes multiple attributes such as name of the dam and the impounded river, primary use, nearest city, area, and year of construction (or commissioning). 

While the main focus was to include all reservoirs with a storage capacity of more than 0.1 cubic kilometers, many smaller reservoirs were added where data were available. The data were 

compiled by Lehner et al. (2011) and are distributed by the Global Water System Project (GWSP) and by the Columbia University Center for International Earth Science Information Network 

(CIESIN). For details please refer to the Technical Documentation which is provided with the data.
The Global Reservoir and Dam (GRanD) Database, Version 1.1 contains 6,862 records of reservoirs and their associated dams with a cumulative storage capacity of 6,197 cubic km. 

The reservoirs were delineated from high spatial resolution satellite imagery and are available as polygon shape files. The only attribute for the reservoirs is the area of the reservoir. 

The associated dams data set includes multiple attributes such as name of the dam and the impounded river, primary use, nearest city, area, and year of construction (or commissioning). 

While the main focus was to include all reservoirs with a storage capacity of more than 0.1 cubic kilometers, many smaller reservoirs were added where data were available. The data were 

compiled by Lehner et al. (2011) and are distributed by the Global Water System Project (GWSP) and by the Columbia University Center for International Earth Science Information Network 

(CIESIN). For details please refer to the Technical Documentation which is provided with the data.
The Global Monthly River Discharge Data Set (RivDIS) contains monthly averaged discharge measurements for 1,018 stations located throughout the world from 1807-1991. The period of record varies widely from station to station with a mean of 21.5 years. The data are derived from the published UNESCO archives for river discharge, and checked against information obtained from the Global Runoff Center in Koblenz, Germany through the U.S. National Geophysical Data Center in Boulder, Colorado.
The Global Monthly River Discharge Data Set (RivDIS) contains monthly averaged discharge measurements for 1,018 stations located throughout the world from 1807-1991. The period of record varies widely from station to station with a mean of 21.5 years. The data are derived from the published UNESCO archives for river discharge, and checked against information obtained from the Global Runoff Center in Koblenz, Germany through the U.S. National Geophysical Data Center in Boulder, Colorado.
ABSTRACT: The Global Monthly River Discharge Data Set (RivDIS) contains monthly averaged discharge measurements for 1,018 stations located throughout the world from 1807-1991. The period of record varies widely from station to station with a mean of 21.5 years. The data are derived from the published UNESCO archives for river discharge, and checked against information obtained from the Global Runoff Center in Koblenz, Germany through the U.S. National Geophysical Data Center in Boulder, Colorado.
The Global Roads Open Access Data Set, Version 1 (gROADSv1) was developed under the auspices of the CODATA Global Roads Data Development Task Group. The data set combines the best available roads data by country into a global roads coverage, using the UN Spatial Data Infrastructure Transport (UNSDI-T) version 2 as a common data model. All country road networks have been joined topologically at the borders, and many countries have been edited for internal topology. Source data for each country are provided in the documentation, and users are encouraged to refer to the readme file for use constraints that apply to a small number of countries. Because the data are compiled from multiple sources, the date range for road network representations ranges from the 1980s to 2010 depending on the country (most countries have no confirmed date), and spatial accuracy varies. The baseline global data set was compiled by the Information Technology Outreach Services (ITOS) of the University of Georgia. Updated data for 27 countries and 6 smaller geographic entities were assembled by Columbia University's Center for International Earth Science Information Network (CIESIN), with a focus largely on developing countries with the poorest data coverage.
The Global Roads Open Access Data Set, Version 1 (gROADSv1) was developed under the auspices of the CODATA Global Roads Data Development Task Group. The data set combines the best available roads data by country into a global roads coverage, using the UN Spatial Data Infrastructure Transport (UNSDI-T) version 2 as a common data model. All country road networks have been joined topologically at the borders, and many countries have been edited for internal topology. Source data for each country are provided in the documentation, and users are encouraged to refer to the readme file for use constraints that apply to a small number of countries. Because the data are compiled from multiple sources, the date range for road network representations ranges from the 1980s to 2010 depending on the country (most countries have no confirmed date), and spatial accuracy varies. The baseline global data set was compiled by the Information Technology Outreach Services (ITOS) of the University of Georgia. Updated data for 27 countries and 6 smaller geographic entities were assembled by Columbia University's Center for International Earth Science Information Network (CIESIN), with a focus largely on developing countries with the poorest data coverage.
The Global Roads Open Access Data Set, Version 1 (gROADSv1) was developed under the auspices of the CODATA Global Roads Data Development Task Group. The data set combines the best available roads data by country into a global roads coverage, using the UN Spatial Data Infrastructure Transport (UNSDI-T) version 2 as a common data model. All country road networks have been joined topologically at the borders, and many countries have been edited for internal topology. Source data for each country are provided in the documentation, and users are encouraged to refer to the readme file for use constraints that apply to a small number of countries. Because the data are compiled from multiple sources, the date range for road network representations ranges from the 1980s to 2010 depending on the country (most countries have no confirmed date), and spatial accuracy varies. The baseline global data set was compiled by the Information Technology Outreach Services (ITOS) of the University of Georgia. Updated data for 27 countries and 6 smaller geographic entities were assembled by Columbia University's Center for International Earth Science Information Network (CIESIN), with a focus largely on developing countries with the poorest data coverage.
The Global Roads Open Access Data Set, Version 1 (gROADSv1) was developed under the auspices of the CODATA Global Roads Data Development Task Group. The data set combines the best available roads data by country into a global roads coverage, using the UN Spatial Data Infrastructure Transport (UNSDI-T) version 2 as a common data model. All country road networks have been joined topologically at the borders, and many countries have been edited for internal topology. Source data for each country are provided in the documentation, and users are encouraged to refer to the readme file for use constraints that apply to a small number of countries. Because the data are compiled from multiple sources, the date range for road network representations ranges from the 1980s to 2010 depending on the country (most countries have no confirmed date), and spatial accuracy varies. The baseline global data set was compiled by the Information Technology Outreach Services (ITOS) of the University of Georgia. Updated data for 27 countries and 6 smaller geographic entities were assembled by Columbia University's Center for International Earth Science Information Network (CIESIN), with a focus largely on developing countries with the poorest data coverage.
The Global Rural-Urban Mapping Project (GRUMP), Alpha Version consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated datasets dated circa 2000. The data products include population count grids (raw counts), population density grids (per square km), land area grids (actual area net of ice and water), mean geographic unit area grids, urban extents grids, centroids, a national identifier grid, national boundaries, coastlines, and settlement points. These products vary in GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). A proportional allocation gridding algorithm, utilizing more than 1,000,000 national and sub-national geographic units, is used to assign population values to grid cells. Additional global grids are created from the 30 arc-second grid at 1/4, 1/2, and 1 degree resolutions. The Spatial Reference metadata section information applies only to global extent, 30 arc-second resolution. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT). (Suggested Usage: To allow analysis of urban and rural population figures based on a consistent global dataset.)
The Global Rural-Urban Mapping Project (GRUMP), Alpha Version consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated datasets dated circa 2000. The data products include population count grids (raw counts), population density grids (per square km), land area grids (actual area net of ice and water), mean geographic unit area grids, urban extents grids, centroids, a national identifier grid, national boundaries, coastlines, and settlement points. These products vary in GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). A proportional allocation gridding algorithm, utilizing more than 1,000,000 national and sub-national geographic units, is used to assign population values to grid cells. Additional global grids are created from the 30 arc-second grid at 1/4, 1/2, and 1 degree resolutions. The Spatial Reference metadata section information applies only to global extent, 30 arc-second resolution. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT). (Suggested Usage: To allow analysis of urban and rural population figures based on a consistent global dataset.)
The Global Rural-Urban Mapping Project (GRUMP), Alpha Version consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated datasets dated circa 2000. The data products include population count grids (raw counts), population density grids (per square km), land area grids (actual area net of ice and water), mean geographic unit area grids, urban extents grids, centroids, a national identifier grid, national boundaries, coastlines, and settlement points. These products vary in GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). A proportional allocation gridding algorithm, utilizing more than 1,000,000 national and sub-national geographic units, is used to assign population values to grid cells. Additional global grids are created from the 30 arc-second grid at 1/4, 1/2, and 1 degree resolutions. The Spatial Reference metadata section information applies only to global extent, 30 arc-second resolution. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT). (Suggested Usage: To allow analysis of urban and rural population figures based on a consistent global dataset.)
The Global Rural-Urban Mapping Project (GRUMP), Alpha Version consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated datasets dated circa 2000. The data products include population count grids (raw counts), population density grids (per square km), land area grids (actual area net of ice and water), mean geographic unit area grids, urban extents grids, centroids, a national identifier grid, national boundaries, coastlines, and settlement points. These products vary in GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). A proportional allocation gridding algorithm, utilizing more than 1,000,000 national and sub-national geographic units, is used to assign population values to grid cells. Additional global grids are created from the 30 arc-second grid at 1/4, 1/2, and 1 degree resolutions. The Spatial Reference metadata section information applies only to global extent, 30 arc-second resolution. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT). (Suggested Usage: To allow analysis of urban and rural population figures based on a consistent global dataset.)
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated datasets dated circa 2000. Coastlines are derived from the land area grids to show the outlines of pixels (cells) that contain administrative units in GRUMPv1 and that fall along waterbodies. The coastlines are designed for cartographic use with the GRUMPv1 population raster datasets. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated datasets dated circa 2000. Coastlines are derived from the land area grids to show the outlines of pixels (cells) that contain administrative units in GRUMPv1 and that fall along waterbodies. The coastlines are designed for cartographic use with the GRUMPv1 population raster datasets. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated datasets dated circa 2000. Coastlines are derived from the land area grids to show the outlines of pixels (cells) that contain administrative units in GRUMPv1 and that fall along waterbodies. The coastlines are designed for cartographic use with the GRUMPv1 population raster datasets. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT). (Suggested Usage:  To permit cartographic display of coastlines that exactly match the GRUMPv1 population surfaces.)
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid. The area grids measure land areas in square kilometers and the mean unit size (population-weighted) in square kilometers. The land area grid permits the summation of areas (net of permanent ice and water) at the same resolution as the population density, count, and urban-rural grids. The mean unit size grids provide a quantitative surface that indicates the size of the input unit(s) from which population count and density grids are derived. Additional global grids are created from the 30 arc-second grid at 1/4, 1/2, and 1 degree resolutions. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid. The area grids measure land areas in square kilometers and the mean unit size (population-weighted) in square kilometers. The land area grid permits the summation of areas (net of permanent ice and water) at the same resolution as the population density, count, and urban-rural grids. The mean unit size grids provide a quantitative surface that indicates the size of the input unit(s) from which population count and density grids are derived. Additional global grids are created from the 30 arc-second grid at 1/4, 1/2, and 1 degree resolutions. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid. The area grids measure land areas in square kilometers and the mean unit size (population-weighted) in square kilometers. The land area grid permits the summation of areas (net of permanent ice and water) at the same resolution as the population density, count, and urban-rural grids. The mean unit size grids provide a quantitative surface that indicates the size of the input unit(s) from which population count and density grids are derived. Additional global grids are created from the 30 arc-second grid at 1/4, 1/2, and 1 degree resolutions. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated datasets dated circa 2000. National Administrative boundaries are derived from the land area grid to show the outlines of pixels (cells) that contain administrative units in GRUMPv1 on a per-country/territory basis. The National boundaries data are derived from the pixels as polygons and thus have rectilinear boundaries at large scale. Note that the polygons that outline the countries and territories are not official representations; rather they represent the area covered by the statistical data as provided. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated datasets dated circa 2000. National Administrative boundaries are derived from the land area grid to show the outlines of pixels (cells) that contain administrative units in GRUMPv1 on a per-country/territory basis. The National boundaries data are derived from the pixels as polygons and thus have rectilinear boundaries at large scale. Note that the polygons that outline the countries and territories are not official representations; rather they represent the area covered by the statistical data as provided. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated datasets dated circa 2000. National Administrative boundaries are derived from the land area grid to show the outlines of pixels (cells) that contain administrative units in GRUMPv1 on a per-country/territory basis. The National boundaries data are derived from the pixels as polygons and thus have rectilinear boundaries at large scale. Note that the polygons that outline the countries and territories are not official representations; rather they represent the area covered by the statistical data as provided. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT). (Suggested Usage:  To permit cartographic display of coastlines that exactly match the GRUMPv1 population surfaces.)
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated datasets dated circa 2000. National Identifier Grid is derived from the land area grid to create a raster surface where pixels (cells) that cover the same nation or territory have the same value. Note that the countries and territories are not official representations of country boundaries; rather, they represent the area covered by the statistical data as provided. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated datasets dated circa 2000. National Identifier Grid is derived from the land area grid to create a raster surface where pixels (cells) that cover the same nation or territory have the same value. Note that the countries and territories are not official representations of country boundaries; rather, they represent the area covered by the statistical data as provided. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated datasets dated circa 2000. National Identifier Grid is derived from the land area grid to create a raster surface where pixels (cells) that cover the same nation or territory have the same value. Note that the countries and territories are not official representations of country boundaries; rather, they represent the area covered by the statistical data as provided. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT). (Suggested Usage:  To permit the summation of population values by country/territory and, in combination with other data layers, the summation of population values by irregular areas represented in the other data layers and country/territory.)
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated datasets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 1,000,000 national and sub-national geographic units, is used to assign population values (counts, in persons) to grid cells. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated datasets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 1,000,000 national and sub-national geographic units, is used to assign population values (counts, in persons) to grid cells. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated datasets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 1,000,000 national and sub-national geographic units, is used to assign population values (counts, in persons) to grid cells. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT). (Suggested Usage:  To provide a time series of raster population data for ntegration with other data sets.)
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid. The 

population density grids measure population per square km. A proportional allocation gridding algorithm, utilizing more than 1,000,000 national and sub-national geographic units, is used to 

assign population values to grid cells. The population count grids are divided by the land area grid to produce population densities. This dataset is produced by the Columbia University 

Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional 

de Agricultura Tropical (CIAT).
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid. The 

population density grids measure population per square km. A proportional allocation gridding algorithm, utilizing more than 1,000,000 national and sub-national geographic units, is used to 

assign population values to grid cells. The population count grids are divided by the land area grid to produce population densities. This dataset is produced by the Columbia University 

Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional 

de Agricultura Tropical (CIAT).
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid. The 

population density grids measure population per square km. A proportional allocation gridding algorithm, utilizing more than 1,000,000 national and sub-national geographic units, is used to 

assign population values to grid cells. The population count grids are divided by the land area grid to produce population densities. This dataset is produced by the Columbia University 

Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional 

de Agricultura Tropical (CIAT).
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and 

associated datasets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 1,000,000 national and sub-national geographic units, is used to assign population 

values (counts, in persons) to grid cells. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the 

International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT)..
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and 

associated datasets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 1,000,000 national and sub-national geographic units, is used to assign population 

values (counts, in persons) to grid cells. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the 

International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT)..
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and 

associated datasets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 1,000,000 national and sub-national geographic units, is used to assign population 

values (counts, in persons) to grid cells. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the 

International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT)..
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid. The urban extent grids distinguish urban and rural areas based on a combination of population counts (persons), settlement points, and the presence of Nighttime Lights . Areas are defined as urban where contiguous lighted cells from the Nighttime Lights or approximated urban extents based on buffered settlement points for which the total population is greater than 5,000 persons. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT)
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid. The urban extent grids distinguish urban and rural areas based on a combination of population counts (persons), settlement points, and the presence of Nighttime Lights . Areas are defined as urban where contiguous lighted cells from the Nighttime Lights or approximated urban extents based on buffered settlement points for which the total population is greater than 5,000 persons. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT)
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid. The urban extent grids distinguish urban and rural areas based on a combination of population counts (persons), settlement points, and the presence of Nighttime Lights . Areas are defined as urban where contiguous lighted cells from the Nighttime Lights or approximated urban extents based on buffered settlement points for which the total population is greater than 5,000 persons. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT)
The ISRIC-WISE International soil profile data set consists of a homogenized, global set of 1,125 soil profiles for use by global modelers. These profiles provided the basis for the Global Pedon Database (GPDB) of the International Geosphere-Biosphere Programme (IGBP) - Data and Information System (DIS). The data set includes information on soil classification, site data, soil horizon data, source of data, and methods used for determining analytical data.
The ISRIC-WISE International soil profile data set consists of a homogenized, global set of 1,125 soil profiles for use by global modelers. These profiles provided the basis for the Global Pedon Database (GPDB) of the International Geosphere-Biosphere Programme (IGBP) - Data and Information System (DIS). The data set includes information on soil classification, site data, soil horizon data, source of data, and methods used for determining analytical data.
ABSTRACT: The ISRIC-WISE International soil profile data set consists of a homogenized, global set of 1,125 soil profiles for use by global modelers. These profiles provided the basis for the Global Pedon Database (GPDB) of the International Geosphere-Biosphere Programme (IGBP) - Data and Information System (DIS). The data set includes information on soil classification, site data, soil horizon data, source of data, and methods used for determining analytical data.
A standardized global data set of soil horizon thicknesses and textures (particle size distributions).
A standardized global data set of soil horizon thicknesses and textures (particle size distributions).
ABSTRACT: A standardized global data set of soil horizon thicknesses and textures (particle size distributions).
A global 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.
A global 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.
ABSTRACT: A global 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.
A global digital data base of soil properties is available at 1 degree longitude resolution.  For each land cell, the data base includes major and associated soil units, surface texture, and slope; phase and miscellaneous land units are included where available. The data base was compiled as part of an effort to improve modeling of the hydrologic cycle in the GISS Genreal Circulation Model.
A global digital data base of soil properties is available at 1 degree longitude resolution.  For each land cell, the data base includes major and associated soil units, surface texture, and slope; phase and miscellaneous land units are included where available. The data base was compiled as part of an effort to improve modeling of the hydrologic cycle in the GISS Genreal Circulation Model.
ABSTRACT: A global digital data base of soil properties is available at 1 degree longitude resolution.  For each land cell, the data base includes major and associated soil units, surface texture, and slope; phase and miscellaneous land units are included where available. The data base was compiled as part of an effort to improve modeling of the hydrologic cycle in the GISS Genreal Circulation Model.
A global digital data base of vegetation was compiled at 1 degree latitude by 1 degree longitude resolution, drawing on approximately 100 published sources.  Vegetation data from varied sources were consistently recorded using the hierarchical UNESCO classification system.  The raw data base distinguishes about 180 vegetation types that have been collapsed to 32.
A global digital data base of vegetation was compiled at 1 degree latitude by 1 degree longitude resolution, drawing on approximately 100 published sources.  Vegetation data from varied sources were consistently recorded using the hierarchical UNESCO classification system.  The raw data base distinguishes about 180 vegetation types that have been collapsed to 32.
ABSTRACT: A global digital data base of vegetation was compiled at 1 degree latitude by 1 degree longitude resolution, drawing on approximately 100 published sources.  Vegetation data from varied sources were consistently recorded using the hierarchical UNESCO classification system.  The raw data base distinguishes about 180 vegetation types that have been collapsed to 32.
Global Volcano Hazard Frequency and Distribution is a 2.5 minute gridded data set based upon the 

National Geophysical Data Center (NGDC) Volcano Database spanning the period of 1979 through 2000. This database includes nearly 

4,000 volcanic events categorized as moderate or above (values 2 through 8) according to the Volcano Explosivity Index (VEI). Most 

volcanoes are georeferenced to the nearest tenth or hundredth of a degree with a few to the nearest thousandth of a degree. To 

produce the final output, the frequency of a volcanic hazard is computed for each grid cell, with the data set consequently being 

classified into deciles (10 classes of approximately equal number of grid cells). The higher the grid cell value in the final output, 

the higher the relative frequency of hazard posed by volcanoes. This dataset is the result of collaboration among the Columbia 

University Center for Hazards and Risk Research (CHRR) and Columbia University Center for International Earth Science Information 

Network (CIESIN).
Global Volcano Hazard Frequency and Distribution is a 2.5 minute gridded data set based upon the 

National Geophysical Data Center (NGDC) Volcano Database spanning the period of 1979 through 2000. This database includes nearly 

4,000 volcanic events categorized as moderate or above (values 2 through 8) according to the Volcano Explosivity Index (VEI). Most 

volcanoes are georeferenced to the nearest tenth or hundredth of a degree with a few to the nearest thousandth of a degree. To 

produce the final output, the frequency of a volcanic hazard is computed for each grid cell, with the data set consequently being 

classified into deciles (10 classes of approximately equal number of grid cells). The higher the grid cell value in the final output, 

the higher the relative frequency of hazard posed by volcanoes. This dataset is the result of collaboration among the Columbia 

University Center for Hazards and Risk Research (CHRR) and Columbia University Center for International Earth Science Information 

Network (CIESIN).
Global Volcano Hazard Frequency and Distribution is a 2.5 minute gridded data set based upon the 

National Geophysical Data Center (NGDC) Volcano Database spanning the period of 1979 through 2000. This database includes nearly 

4,000 volcanic events categorized as moderate or above (values 2 through 8) according to the Volcano Explosivity Index (VEI). Most 

volcanoes are georeferenced to the nearest tenth or hundredth of a degree with a few to the nearest thousandth of a degree. To 

produce the final output, the frequency of a volcanic hazard is computed for each grid cell, with the data set consequently being 

classified into deciles (10 classes of approximately equal number of grid cells). The higher the grid cell value in the final output, 

the higher the relative frequency of hazard posed by volcanoes. This dataset is the result of collaboration among the Columbia 

University Center for Hazards and Risk Research (CHRR) and Columbia University Center for International Earth Science Information 

Network (CIESIN).
Global Volcano Mortality Risks and Distribution is a 2.5 minute grid representing global volcano mortality risks. The data set was constructed using historical hazard-specific mortality loss data from the Emergency Events Database (EM-DAT) maintained by the Centre for Research on the Epidemiology of Disasters (CRED), subnational year 2000 population estimates from Gridded Population of the World, Version 3 (GPWv3), and volcano hazard data from the Global Volcano Hazard Frequency and Distribution dataset. Estimates were made as to the mortality numbers associated with volcano hazard. In turn, these mortality estimates were classified into deciles, 10 class of an approximately equal number of grid cells of increasing mortality risk. This dataset is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).
Global Volcano Mortality Risks and Distribution is a 2.5 minute grid representing global volcano mortality risks. The data set was constructed using historical hazard-specific mortality loss data from the Emergency Events Database (EM-DAT) maintained by the Centre for Research on the Epidemiology of Disasters (CRED), subnational year 2000 population estimates from Gridded Population of the World, Version 3 (GPWv3), and volcano hazard data from the Global Volcano Hazard Frequency and Distribution dataset. Estimates were made as to the mortality numbers associated with volcano hazard. In turn, these mortality estimates were classified into deciles, 10 class of an approximately equal number of grid cells of increasing mortality risk. This dataset is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).
Global Volcano Mortality Risks and Distribution is a 2.5 minute grid representing global volcano mortality risks. The data set was constructed using historical hazard-specific mortality loss data from the Emergency Events Database (EM-DAT) maintained by the Centre for Research on the Epidemiology of Disasters (CRED), subnational year 2000 population estimates from Gridded Population of the World, Version 3 (GPWv3), and volcano hazard data from the Global Volcano Hazard Frequency and Distribution dataset. Estimates were made as to the mortality numbers associated with volcano hazard. In turn, these mortality estimates were classified into deciles, 10 class of an approximately equal number of grid cells of increasing mortality risk. This dataset is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).
Global Volcano Proportional Economic Loss Risk Deciles is a 2.5 minute grid of volcano hazard 

economic loss as proportions of Gross Domestic Product (GDP) per analytical unit. Estimates of GDP at risk are based on regional 

economic loss rates derived from historical records of the Emergency Events Database (EM-DAT). Loss rates are weighted by the 

hazard's frequency and distribution. The methodology of Sachs et al. (2003) is followed to determine baseline estimates of GDP per 

grid cell. To better reflect the confidence surrounding the data and procedures, the range of proportionalities is classified into 

deciles, 10 class of an approximately equal number of grid cells of increasing risk. This dataset is the result of collaboration 

among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The 

World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).
Global Volcano Proportional Economic Loss Risk Deciles is a 2.5 minute grid of volcano hazard 

economic loss as proportions of Gross Domestic Product (GDP) per analytical unit. Estimates of GDP at risk are based on regional 

economic loss rates derived from historical records of the Emergency Events Database (EM-DAT). Loss rates are weighted by the 

hazard's frequency and distribution. The methodology of Sachs et al. (2003) is followed to determine baseline estimates of GDP per 

grid cell. To better reflect the confidence surrounding the data and procedures, the range of proportionalities is classified into 

deciles, 10 class of an approximately equal number of grid cells of increasing risk. This dataset is the result of collaboration 

among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The 

World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).
Global Volcano Proportional Economic Loss Risk Deciles is a 2.5 minute grid of volcano hazard 

economic loss as proportions of Gross Domestic Product (GDP) per analytical unit. Estimates of GDP at risk are based on regional 

economic loss rates derived from historical records of the Emergency Events Database (EM-DAT). Loss rates are weighted by the 

hazard's frequency and distribution. The methodology of Sachs et al. (2003) is followed to determine baseline estimates of GDP per 

grid cell. To better reflect the confidence surrounding the data and procedures, the range of proportionalities is classified into 

deciles, 10 class of an approximately equal number of grid cells of increasing risk. This dataset is the result of collaboration 

among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The 

World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).
distributions of Gross Domestic Product (GDP) are computed using a two-fold process. Where 

applicable, the proportional contribution of subnational units are determined following the methodology of Sachs et al. (2003) and 

these proportions are used against World Bank Development Indicators to determine a GDP value for the subnational unit. Once a 

national GDP has been spatially stratified into the smallest administrative units available, it is further distributed based upon 

Gridded Population of the World, Version 3 (GPWv3) population distributions. A per capita contribution value is determined for each 

unit, and this value is multiplied by the population per grid cell. Once the GDP has been determined on a per grid cell basis, then 

the spatially variable loss rate as derived from EM-DAT historical records is used to determine the total economic loss posed to a 

grid cell by volcano hazards. The final surface does not present absolute values of total economic loss, but rather a relative decile 

(1-10) ranking of grid cells based upon the calculated economic loss risks. This dataset is the result of collaboration among the 

Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World 

Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).
distributions of Gross Domestic Product (GDP) are computed using a two-fold process. Where 

applicable, the proportional contribution of subnational units are determined following the methodology of Sachs et al. (2003) and 

these proportions are used against World Bank Development Indicators to determine a GDP value for the subnational unit. Once a 

national GDP has been spatially stratified into the smallest administrative units available, it is further distributed based upon 

Gridded Population of the World, Version 3 (GPWv3) population distributions. A per capita contribution value is determined for each 

unit, and this value is multiplied by the population per grid cell. Once the GDP has been determined on a per grid cell basis, then 

the spatially variable loss rate as derived from EM-DAT historical records is used to determine the total economic loss posed to a 

grid cell by volcano hazards. The final surface does not present absolute values of total economic loss, but rather a relative decile 

(1-10) ranking of grid cells based upon the calculated economic loss risks. This dataset is the result of collaboration among the 

Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World 

Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).
distributions of Gross Domestic Product (GDP) are computed using a two-fold process. Where 

applicable, the proportional contribution of subnational units are determined following the methodology of Sachs et al. (2003) and 

these proportions are used against World Bank Development Indicators to determine a GDP value for the subnational unit. Once a 

national GDP has been spatially stratified into the smallest administrative units available, it is further distributed based upon 

Gridded Population of the World, Version 3 (GPWv3) population distributions. A per capita contribution value is determined for each 

unit, and this value is multiplied by the population per grid cell. Once the GDP has been determined on a per grid cell basis, then 

the spatially variable loss rate as derived from EM-DAT historical records is used to determine the total economic loss posed to a 

grid cell by volcano hazards. The final surface does not present absolute values of total economic loss, but rather a relative decile 

(1-10) ranking of grid cells based upon the calculated economic loss risks. This dataset is the result of collaboration among the 

Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World 

Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).
These data are part of the Goddard Satellite-based Surface Turbulent Fluxes Version 3 (GSSTF3) Dataset recently produced through a MEaSURES funded project led by Dr. Chung-Lin Shie (UMBC/GEST, NASA/GSFC), converted to HDF-EOS5 format. The stewardship of this HDF-EOS5 dataset is part of the MEaSUREs project, http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects/surface-turbulent-fluxes-esdr
http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects

This is a Daily (24-hour) product; data are projected to equidistant Grid that covers the globe at 0.25x0.25 degree cell size, resulting in data arrays of 1440x720 size.

The daily fluxes  are produced for each individual available SSM/I satellite tapes (e.g., F11, F13, F14 and F15), and then serve as input to the Combined daily fluxes (GES_DISC_GSSTF_3).

These HDF-EOS5 files contain one grid that have 8 variables:

&quot;E&quot;    &apos;latent heat flux&apos; (W/m**2),
&quot;STu&quot;  &apos;zonal wind stress&apos; (N/m**2),
&quot;STv&quot;  &apos;meridional wind stress&apos; (N/m**2),
&quot;H&quot;    &apos;sensible heat flux&apos; (W/m**2),
&quot;Qair&quot; &apos;surface air (~10-m) specific humidity&apos; (g/kg),
&quot;U&quot;    &apos;10-m wind speed&apos; (m/s),
&quot;DQ&quot;   &apos;sea-air humidity difference&apos; (g/kg)
&quot;Tot_Precip_Water&quot; &apos;total precipitable water&apos; (g/cm**2)

The double-quoted labels are the short names of the data fields in the HDF-EOS5 files.
 
The short name of this data set is GSSTF_F11

Parameters contained in the data files include the following:
Variable Name|Description|Units 
 DQ|sea-air humidity difference|(g/kg)
 E|latent heat flux|(W/m^^2)
 H|sensible heat flux|(W/m^^2)
 Qair|surface air (~10-m) specific humidity|(g/kg)
 STu|zonal wind stress|(N/m^^2)
 STv|meridional wind stress|(N/m^^2)
 Tot_Precip_Water|Total Precipitable Water|(g/cm^^2)
 U|10-m wind speed|(m/s)
End of parameter information
These data are part of the Goddard Satellite-based Surface Turbulent Fluxes Version 3 (GSSTF3) Dataset recently produced through a MEaSURES funded project led by Dr. Chung-Lin Shie (UMBC/GEST, NASA/GSFC), converted to HDF-EOS5 format. The stewardship of this HDF-EOS5 dataset is part of the MEaSUREs project, http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects/surface-turbulent-fluxes-esdr
http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects

This is a Daily (24-hour) product; data are projected to equidistant Grid that covers the globe at 0.25x0.25 degree cell size, resulting in data arrays of 1440x720 size.

The daily fluxes  are produced for each individual available SSM/I satellite tapes (e.g., F11, F13, F14 and F15), and then serve as input to the Combined daily fluxes (GES_DISC_GSSTF_3).

These HDF-EOS5 files contain one grid that have 8 variables:

&quot;E&quot;    &apos;latent heat flux&apos; (W/m**2),
&quot;STu&quot;  &apos;zonal wind stress&apos; (N/m**2),
&quot;STv&quot;  &apos;meridional wind stress&apos; (N/m**2),
&quot;H&quot;    &apos;sensible heat flux&apos; (W/m**2),
&quot;Qair&quot; &apos;surface air (~10-m) specific humidity&apos; (g/kg),
&quot;U&quot;    &apos;10-m wind speed&apos; (m/s),
&quot;DQ&quot;   &apos;sea-air humidity difference&apos; (g/kg)
&quot;Tot_Precip_Water&quot; &apos;total precipitable water&apos; (g/cm**2)

The double-quoted labels are the short names of the data fields in the HDF-EOS5 files.
 
The short name of this data set is GSSTF_F13

Parameters contained in the data files include the following:
Variable Name|Description|Units 
 DQ|sea-air humidity difference|(g/kg)
 E|latent heat flux|(W/m^^2)
 H|sensible heat flux|(W/m^^2)
 Qair|surface air (~10-m) specific humidity|(g/kg)
 STu|zonal wind stress|(N/m^^2)
 STv|meridional wind stress|(N/m^^2)
 Tot_Precip_Water|Total Precipitable Water|(g/cm^^2)
 U|10-m wind speed|(m/s)
End of parameter information
These data are part of the Goddard Satellite-based Surface Turbulent Fluxes Version 3 (GSSTF3) Dataset recently produced through a MEaSURES funded project led by Dr. Chung-Lin Shie (UMBC/GEST, NASA/GSFC), converted to HDF-EOS5 format. The stewardship of this HDF-EOS5 dataset is part of the MEaSUREs project, http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects/surface-turbulent-fluxes-esdr
http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects

This is a Daily (24-hour) product; data are projected to equidistant Grid that covers the globe at 0.25x0.25 degree cell size, resulting in data arrays of 1440x720 size.

The daily fluxes  are produced for each individual available SSM/I satellite tapes (e.g., F11, F13, F14 and F15), and then serve as input to the Combined daily fluxes (GES_DISC_GSSTF_3).

These HDF-EOS5 files contain one grid that have 8 variables:

&quot;E&quot;    &apos;latent heat flux&apos; (W/m**2),
&quot;STu&quot;  &apos;zonal wind stress&apos; (N/m**2),
&quot;STv&quot;  &apos;meridional wind stress&apos; (N/m**2),
&quot;H&quot;    &apos;sensible heat flux&apos; (W/m**2),
&quot;Qair&quot; &apos;surface air (~10-m) specific humidity&apos; (g/kg),
&quot;U&quot;    &apos;10-m wind speed&apos; (m/s),
&quot;DQ&quot;   &apos;sea-air humidity difference&apos; (g/kg)
&quot;Tot_Precip_Water&quot; &apos;total precipitable water&apos; (g/cm**2)

The double-quoted labels are the short names of the data fields in the HDF-EOS5 files.
 
The short name of this data set is GSSTF_F14

Parameters contained in the data files include the following:
Variable Name|Description|Units 
 DQ|sea-air humidity difference|(g/kg)
 E|latent heat flux|(W/m^^2)
 H|sensible heat flux|(W/m^^2)
 Qair|surface air (~10-m) specific humidity|(g/kg)
 STu|zonal wind stress|(N/m^^2)
 STv|meridional wind stress|(N/m^^2)
 Tot_Precip_Water|Total Precipitable Water|(g/cm^^2)
 U|10-m wind speed|(m/s)
End of parameter information
These data are part of the Goddard Satellite-based Surface Turbulent Fluxes Version 3 (GSSTF3) Dataset recently produced through a MEaSURES funded project led by Dr. Chung-Lin Shie (UMBC/GEST, NASA/GSFC), converted to HDF-EOS5 format. The stewardship of this HDF-EOS5 dataset is part of the MEaSUREs project, http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects/surface-turbulent-fluxes-esdr
http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects

This is a Daily (24-hour) product; data are projected to equidistant Grid that covers the globe at 0.25x0.25 degree cell size, resulting in data arrays of 1440x720 size.

The daily fluxes  are produced for each individual available SSM/I satellite tapes (e.g., F11, F13, F14 and F15), and then serve as input to the Combined daily fluxes (GES_DISC_GSSTF_3).

These HDF-EOS5 files contain one grid that have 8 variables:

&quot;E&quot;    &apos;latent heat flux&apos; (W/m**2),
&quot;STu&quot;  &apos;zonal wind stress&apos; (N/m**2),
&quot;STv&quot;  &apos;meridional wind stress&apos; (N/m**2),
&quot;H&quot;    &apos;sensible heat flux&apos; (W/m**2),
&quot;Qair&quot; &apos;surface air (~10-m) specific humidity&apos; (g/kg),
&quot;U&quot;    &apos;10-m wind speed&apos; (m/s),
&quot;DQ&quot;   &apos;sea-air humidity difference&apos; (g/kg)
&quot;Tot_Precip_Water&quot; &apos;total precipitable water&apos; (g/cm**2)

The double-quoted labels are the short names of the data fields in the HDF-EOS5 files.
 
The short name of this data set is GSSTF_F15

Parameters contained in the data files include the following:
Variable Name|Description|Units 
 DQ|sea-air humidity difference|(g/kg)
 E|latent heat flux|(W/m^^2)
 H|sensible heat flux|(W/m^^2)
 Qair|surface air (~10-m) specific humidity|(g/kg)
 STu|zonal wind stress|(N/m^^2)
 STv|meridional wind stress|(N/m^^2)
 Tot_Precip_Water|Total Precipitable Water|(g/cm^^2)
 U|10-m wind speed|(m/s)
End of parameter information
These data are part of the Goddard Satellite-based Surface Turbulent Fluxes Version 3 (GSSTF3) Dataset recently produced through a MEaSURES funded project led by Dr. Chung-Lin Shie (UMBC/GEST, NASA/GSFC), converted to HDF-EOS5 format. The stewardship of this HDF-EOS5 dataset is part of the MEaSUREs project, http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects/surface-turbulent-fluxes-esdr
http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects

This is a Daily (24-hour) product; data are projected to equidistant Grid that covers the globe at 0.25x0.25 degree cell size, resulting in data arrays of 1440x720 size.

The daily fluxes  are produced for each individual available SSM/I satellite tapes (e.g., F08, F10, F11, F13, F14 and F15), and then serve as input to the Combined daily fluxes (GES_DISC_GSSTF_3).

These HDF-EOS5 files contain one grid that have 8 variables:

"E"    'latent heat flux' (W/m**2),
"STu"  'zonal wind stress' (N/m**2),
"STv"  'meridional wind stress' (N/m**2),
"H"    'sensible heat flux' (W/m**2),
"Qair" 'surface air (~10-m) specific humidity' (g/kg),
"U"    '10-m wind speed' (m/s),
"DQ"   'sea-air humidity difference' (g/kg)
"Tot_Precip_Water" 'total precipitable water' (g/cm**2)

The double-quoted labels are the short names of the data fields in the HDF-EOS5 files.
 
The short name of this data set is GSSTF_F08

Parameters contained in the data files include the following:
Variable Name|Description|Units 
 DQ|sea-air humidity difference|(g/kg)
 E|latent heat flux|(W/m^^2)
 H|sensible heat flux|(W/m^^2)
 Qair|surface air (~10-m) specific humidity|(g/kg)
 STu|zonal wind stress|(N/m^^2)
 STv|meridional wind stress|(N/m^^2)
 Tot_Precip_Water|Total Precipitable Water|(g/cm^^2)
 U|10-m wind speed|(m/s)
End of parameter information
These data are part of the Goddard Satellite-based Surface Turbulent Fluxes Version 3 (GSSTF3) Dataset recently produced through a MEaSURES funded project led by Dr. Chung-Lin Shie (UMBC/GEST, NASA/GSFC), converted to HDF-EOS5 format. The stewardship of this HDF-EOS5 dataset is part of the MEaSUREs project, http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects/surface-turbulent-fluxes-esdr
http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects

This is a Daily (24-hour) product; data are projected to equidistant Grid that covers the globe at 0.25x0.25 degree cell size, resulting in data arrays of 1440x720 size.

The daily fluxes  are produced for each individual available SSM/I satellite tapes (e.g., F08, F10, F11, F13, F14 and F15), and then serve as input to the Combined daily fluxes (GES_DISC_GSSTF_3).

These HDF-EOS5 files contain one grid that have 8 variables:

"E"    'latent heat flux' (W/m**2),
"STu"  'zonal wind stress' (N/m**2),
"STv"  'meridional wind stress' (N/m**2),
"H"    'sensible heat flux' (W/m**2),
"Qair" 'surface air (~10-m) specific humidity' (g/kg),
"U"    '10-m wind speed' (m/s),
"DQ"   'sea-air humidity difference' (g/kg)
"Tot_Precip_Water" 'total precipitable water' (g/cm**2)

The double-quoted labels are the short names of the data fields in the HDF-EOS5 files.
 
The short name of this data set is GSSTF_F10

Parameters contained in the data files include the following:
Variable Name|Description|Units 
 DQ|sea-air humidity difference|(g/kg)
 E|latent heat flux|(W/m^^2)
 H|sensible heat flux|(W/m^^2)
 Qair|surface air (~10-m) specific humidity|(g/kg)
 STu|zonal wind stress|(N/m^^2)
 STv|meridional wind stress|(N/m^^2)
 Tot_Precip_Water|Total Precipitable Water|(g/cm^^2)
 U|10-m wind speed|(m/s)
End of parameter information
The GOES Water Vapor Transport CD contains nineteen months of geostationary satellite-derived products spanning the 1987/1988 El Nino Southern Oscillation (ENSO) cycle.  Water vapor transport variables derived from GOES data are provided in daily and monthly gridded and non-gridded formats.
The GOZCARDS Merged Data for Hydrogen Chloride Monthly Zonal Averages on a Geodetic Latitude and Pressure Grid product (GozMmlpHCl) contains zonal means and related information (standard deviation, minimum/maximum value, etc.), calculated as a result of a merging process that ties together the source datasets, after bias removal and averaging. The merged HCl data are from the following satellite instruments: HALOE (v19; 1991 - 2005), ACE-FTS (v2.2u; 2004 - onward), and Aura MLS (v3.3; 2004 - onward). The vertical pressure range for HCl is from 147 to 0.5 hPa. The input source data used to create this merged product are contained in a separate data product with the short name GozSmlpHCl.

The GozMmlpHCl merged data are written using the new netCDF4 enhanced model using CF-1 metadata attributes. The data variables are organized into a Group hierarchy structure. Global Attributes describing the data file (e.g. data start/end time, spatial extent, etc.) are located at the file/root level. Users can use netCDF enabled tools to view the data. Since netCDF4 is based on the HDF5 format, HDF5 readers will also work with these data files.

Parameters contained in the data files include the following:
Variable Name    |Description                                  |Units
/Merged/average  |Hydrogen Chloride Merged Zonal Average       |(mol/mol)
End of parameter informationGOZCARDS (Global OZone Chemistry And Related trace gas Data records for the Stratosphere) refers to a commonly-formatted Earth system data record (ESDR) for stratospheric composition, of high relevance to the issue of ozone decline and recovery. High-quality long-term ozone and related trace gas data records are needed to (a) evaluate and understand composition changes in the atmosphere and (b) constrain model representations of atmospheric dynamics and photochemistry.
The GOZCARDS Merged Data for Nitric Acid Monthly Zonal Averages on a Geodetic Latitude and Pressure Grid product (GozMmlpHNO3) contains zonal means and related information (standard deviation, minimum/maximum value, etc.), calculated as a result of a merging process that ties together the source datasets, after bias removal and averaging. The merged HNO3 data are from the following satellite instruments: UARS MLS (v6; 1991 - 1997), ACE-FTS (v2.2u; 2004 - onward), and Aura MLS (v3.3; 2004 - onward). The vertical pressure range for HNO3 is from 147 to 1 hPa. The input source data used to create this merged product are contained in a separate data product with the short name GozSmlpHNO3.

The GozMmlpHNO3 merged data are written using the new netCDF4 enhanced model using CF-1 metadata attributes. The data variables are organized into a Group hierarchy structure. Global Attributes describing the data file (e.g. data start/end time, spatial extent, etc.) are located at the file/root level. Users can use netCDF enabled tools to view the data. Since netCDF4 is based on the HDF5 format, HDF5 readers will also work with these data files.

Parameters contained in the data files include the following:
Variable Name    |Description                                  |Units
/Merged/average  |Nitric Acid Merged Zonal Average             |(mol/mol)
End of parameter information
GOZCARDS (Global OZone Chemistry And Related trace gas Data records for the Stratosphere) refers to a commonly-formatted Earth system data record (ESDR) for stratospheric composition, of high relevance to the issue of ozone decline and recovery. High-quality long-term ozone and related trace gas data records are needed to (a) evaluate and understand composition changes in the atmosphere and (b) constrain model representations of atmospheric dynamics and photochemistry.
The GOZCARDS Merged Data for Nitrous Oxide Monthly Zonal Averages on a Geodetic Latitude and Pressure Grid product (GozMmlpN2O) contains zonal means and related information (standard deviation, minimum/maximum value, etc.), calculated as a result of a merging process that ties together the source datasets, after bias removal and averaging. The merged N2O data are from the following satellite instruments: ACE-FTS (v2.2u; 2004 - onward), and Aura MLS (v3.3; 2004 - onward). The vertical pressure range for N2O is from 147 to 0.5 hPa. The input source data used to create this merged product are contained in a separate data product with the short name GozSmlpN2O.

The GozMmlpN2O merged data are written using the new netCDF4 enhanced model using CF-1 metadata attributes. The data variables are organized into a Group hierarchy structure. Global Attributes describing the data file (e.g. data start/end time, spatial extent, etc.) are located at the file/root level. Users can use netCDF enabled tools to view the data. Since netCDF4 is based on the HDF5 format, HDF5 readers will also work with these data files.

Parameters contained in the data files include the following:
Variable Name    |Description                                  |Units
/Merged/average  |Nitrous Oxide Merged Zonal Average           |(mol/mol)
End of parameter information
GOZCARDS (Global OZone Chemistry And Related trace gas Data records for the Stratosphere) refers to a commonly-formatted Earth system data record (ESDR) for stratospheric composition, of high relevance to the issue of ozone decline and recovery. High-quality long-term ozone and related trace gas data records are needed to (a) evaluate and understand composition changes in the atmosphere and (b) constrain model representations of atmospheric dynamics and photochemistry.
The GOZCARDS Merged Data for Ozone Monthly Zonal Averages on a Geodetic Latitude and Pressure Grid product (GozMmlpO3) contains zonal means and related information (standard deviation, minimum/maximum value, etc.), calculated as a result of a merging process that ties together the source datasets, after bias removal and averaging. The merged O3 data are from the following satellite instruments: SAGE I (v5.9_rev; 1979-1981), SAGE II (v6.2; 1984-2005), HALOE (v19; 1991-2005), UARS MLS (v5; 1991-1997), ACE-FTS (v2.2; 2004-onward), Aura MLS (v2.2; 2004 onward) + others as validation (e.g., SAGE III, v4.0; 2002-2005). The vertical pressure range for O3 is from 147 to 0.5 hPa. The input source data used to create this merged product are contained in a separate data product with the short name GozSmlpO3.

The GozMmlpO3 merged data are written using the new netCDF4 enhanced model using CF-1 metadata attributes. The data variables are organized into a Group hierarchy structure. Global Attributes describing the data file (e.g. data start/end time, spatial extent, etc.) are located at the file/root level. Users can use netCDF enabled tools to view the data. Since netCDF4 is based on the HDF5 format, HDF5 readers will also work with these data files.

Parameters contained in the data files include the following:
Variable Name    |Description                                  |Units
/Merged/average  |Ozone Merged Zonal Average                   |(mol/mol)
End of parameter informationGOZCARDS (Global OZone Chemistry And Related trace gas Data records for the Stratosphere) refers to a commonly-formatted Earth system data record (ESDR) for stratospheric composition, of high relevance to the issue of ozone decline and recovery. High-quality long-term ozone and related trace gas data records are needed to (a) evaluate and understand composition changes in the atmosphere and (b) constrain model representations of atmospheric dynamics and photochemistry.
The GOZCARDS Merged Data for Water Vapor Monthly Zonal Averages on a Geodetic Latitude and Pressure Grid product (GozMmlpH2O) contains zonal means and related information (standard deviation, minimum/maximum value, etc.), calculated as a result of a merging process that ties together the source datasets, after bias removal and averaging. The merged H2O data are from the following satellite instruments: HALOE (v19; 1991 - 2005), ACE-FTS (v2.2u; 2004 - onward), and Aura MLS (v3.3; 2004 - onward). The vertical pressure range for H2O is from 147 to 0.01 hPa. The input source data used to create this merged product are contained in a separate data product with the short name GozSmlpH2O.

The GozMmlpH2O merged data are written using the new netCDF4 enhanced model using CF-1 metadata attributes. The data variables are organized into a Group hierarchy structure. Global Attributes describing the data file (e.g. data start/end time, spatial extent, etc.) are located at the file/root level. Users can use netCDF enabled tools to view the data. Since netCDF4 is based on the HDF5 format, HDF5 readers will also work with these data files.

Parameters contained in the data files include the following:
Variable Name    |Description                                  |Units
/Merged/average  |Water Merged Zonal Average                   |(mol/mol)
End of parameter informationGOZCARDS (Global OZone Chemistry And Related trace gas Data records for the Stratosphere) refers to a commonly-formatted Earth system data record (ESDR) for stratospheric composition, of high relevance to the issue of ozone decline and recovery. High-quality long-term ozone and related trace gas data records are needed to (a) evaluate and understand composition changes in the atmosphere and (b) constrain model representations of atmospheric dynamics and photochemistry.
The GOZCARDS Source Data for Hydrogen Chloride Monthly Zonal Averages on a Geodetic Latitude and Pressure Grid product (GozSmlpHCl) contains zonal means and related information (standard deviation, minimum/maximum value, etc.), calculated from original (‘Level 2’ type) satellite instruments and products. The source HCl data are from the following satellite instruments: HALOE (v19; 1991 - 2005), ACE-FTS (v2.2u; 2004 - onward), and Aura MLS (v3.3; 2004 - onward). The vertical pressure range for HCl is from 147 to 0.5 hPa. The source data are used to create a merged product contained in a separate data product with the short name GozMmlpHCl.

The GozSmlpHCl source data are written using the new netCDF4 enhanced model using CF-1 metadata attributes. The data variables are organized into a Group hierarchy structure. Global Attributes describing the data file (e.g. data start/end time, spatial extent, etc.) are located at the file/root level. Users can use netCDF enabled tools to view the data. Since netCDF4 is based on the HDF5 format, HDF5 readers will also work with these data files.

Parameters contained in the data files include the following:
Variable Name    |Description                                  |Units
/HALOE/average   |Hydrogen Chloride Zonal Average from HALOE   |(mol/mol)
/ACE-FTS/average |Hydrogen Chloride Zonal Average from ACE-FTS |(mol/mol)
/Aura MLS/average|Hydrogen Chloride Zonal Average from Aura MLS|(mol/mol)
End of parameter informationGOZCARDS (Global OZone Chemistry And Related trace gas Data records for the Stratosphere) refers to a commonly-formatted Earth system data record (ESDR) for stratospheric composition, of high relevance to the issue of ozone decline and recovery. High-quality long-term ozone and related trace gas data records are needed to (a) evaluate and understand composition changes in the atmosphere and (b) constrain model representations of atmospheric dynamics and photochemistry.
The GOZCARDS Source Data for Nitric Acid Monthly Zonal Averages on a Geodetic Latitude and Pressure Grid product (GozSmlpHNO3) contains zonal means and related information (standard deviation, minimum/maximum value, etc.), calculated from original (‘Level 2’ type) satellite instruments and products. The source HNO3 data are from the following satellite instruments: UARS MLS (v6; 1991 - 1997), ACE-FTS (v2.2u; 2004 - onward), and Aura MLS (v3.3; 2004 - onward). The vertical pressure range for HNO3 is from 147 to 1 hPa. source data are used to create a merged product contained in a separate data product with the short name GozMmlpHNO3.

The GozSmlpHNO3 source data are written using the new netCDF4 enhanced model using CF-1 metadata attributes. The data variables are organized into a Group hierarchy structure. Global Attributes describing the data file (e.g. data start/end time, spatial extent, etc.) are located at the file/root level. Users can use netCDF enabled tools to view the data. Since netCDF4 is based on the HDF5 format, HDF5 readers will also work with these data files.

Parameters contained in the data files include the following:
Variable Name    |Description                                  |Units
/ACE-FTS/average |Nitric Acid Zonal Average from ACE-FTS       |(mol/mol)
/Aura MLS/average|Nitric Acid Zonal Average from Aura MLS      |(mol/mol)
End of parameter information
GOZCARDS (Global OZone Chemistry And Related trace gas Data records for the Stratosphere) refers to a commonly-formatted Earth system data record (ESDR) for stratospheric composition, of high relevance to the issue of ozone decline and recovery. High-quality long-term ozone and related trace gas data records are needed to (a) evaluate and understand composition changes in the atmosphere and (b) constrain model representations of atmospheric dynamics and photochemistry.
The GOZCARDS Source Data for Nitrous Oxide Monthly Zonal Averages on a Geodetic Latitude and Pressure Grid product (GozSmlpN2O) contains zonal means and related information (standard deviation, minimum/maximum value, etc.), calculated from original (‘Level 2’ type) satellite instruments and products. The source N2O data are from the following satellite instruments: ACE-FTS (v2.2; 2004-onward) and Aura MLS (v2.2; 2004 onward). The vertical pressure range for N2O is from 147 to 0.5 hPa. The source data are used to create a merged product contained in a separate data product with the short name GozMmlpN2O.

The GozSmlpN2O source data are written using the new netCDF4 enhanced model using CF-1 metadata attributes. The data variables are organized into a Group hierarchy structure. Global Attributes describing the data file (e.g. data start/end time, spatial extent, etc.) are located at the file/root level. Users can use netCDF enabled tools to view the data. Since netCDF4 is based on the HDF5 format, HDF5 readers will also work with these data files.

Parameters contained in the data files include the following:
Variable Name    |Description                                  |Units
/ACE-FTS/average |Nitrous Oxide Zonal Average from ACE-FTS     |(mol/mol)
/Aura MLS/average|Nitrous Oxide Zonal Average from Aura MLS    |(mol/mol)
End of parameter informationGOZCARDS (Global OZone Chemistry And Related trace gas Data records for the Stratosphere) refers to a commonly-formatted Earth system data record (ESDR) for stratospheric composition, of high relevance to the issue of ozone decline and recovery. High-quality long-term ozone and related trace gas data records are needed to (a) evaluate and understand composition changes in the atmosphere and (b) constrain model representations of atmospheric dynamics and photochemistry.
The GOZCARDS Source Data for Temperature Monthly Zonal Averages on a Geodetic Latitude and Pressure Grid product (GozSmlpT) contains zonal means and related information (standard deviation, minimum/maximum value, etc.), calculated from the original products. The source Temperature data are from the GMAO MERRA model product DAS 3d analyzed state MAI6NVANA (v5.2.0; 1979 - onward). The vertical pressure range for Temperature are from 1000 – 0.015 hPa.

The GozSmlpT source data are written using the new netCDF4 enhanced model using CF-1 metadata attributes. The data variables are organized into a Group hierarchy structure. Global Attributes describing the data file (e.g. data start/end time, spatial extent, etc.) are located at the file/root level. Users can use netCDF enabled tools to view the data. Since netCDF4 is based on the HDF5 format, HDF5 readers will also work with these data files.

Parameters contained in the data files include the following:
Variable Name    |Description                                  |Units
/MERRA/average   |Temperature Zonal Average from MERRA         |(K)
End of parameter informationGOZCARDS (Global OZone Chemistry And Related trace gas Data records for the Stratosphere) refers to a commonly-formatted Earth system data record (ESDR) for stratospheric composition, of high relevance to the issue of ozone decline and recovery. High-quality long-term ozone and related trace gas data records are needed to (a) evaluate and understand composition changes in the atmosphere and (b) constrain model representations of atmospheric dynamics and photochemistry.
The Advanced Microwave Precipitation Radiometer (AMPR) instrument played a key role in the Midlatitude Continental Convective Clouds Experiment (MC3E).  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 are collected at a combination of four microwave frequencies (10.7, 19.35, 37.1, and 85.5 GHz) with two orientations each (Vpol-to-Hpol and Hpol-to-Vpol) which are complimentary to current aircraft and satellite instrumentation.  These frequencies are best suited to the study of rain systems, but are also useful to studies of other atmospheric, oceanic, and land surface processes.
The Advanced Microwave Precipitation Radiometer (AMPR) instrument played a key role in the Midlatitude Continental Convective Clouds Experiment (MC3E).  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 are collected at a combination of four microwave frequencies (10.7, 19.35, 37.1, and 85.5 GHz) with two orientations each (Vpol-to-Hpol and Hpol-to-Vpol) which are complimentary to current aircraft and satellite instrumentation.  These frequencies are best suited to the study of rain systems, but are also useful to studies of other atmospheric, oceanic, and land surface processes.
The Advanced Microwave Precipitation Radiometer (AMPR) instrument played a key role in the Midlatitude Continental Convective Clouds Experiment (MC3E).  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 are collected at a combination of four microwave frequencies (10.7, 19.35, 37.1, and 85.5 GHz) with two orientations each (Vpol-to-Hpol and Hpol-to-Vpol) which are complimentary to current aircraft and satellite instrumentation.  These frequencies are best suited to the study of rain systems, but are also useful to studies of other atmospheric, oceanic, and land surface processes.
The GPM Ground Validation Advanced Microwave Radiometer Rain Identification (ADMIRARI) GCPEx dataset measures brightness temperatures at three frequencies (10.7, 21.0 and 36.5 GHz) and at two polarized planes (H & V).  The ADMIRARI is a scanning radiometer like its auxiliary active instruments, i.e., Micro rain radar and cloud lidar which provide reflectivity profiles and cloud base altitude at the same scanning angle as the radiometer.  The radiometer retrieval typically provides rain/cloud liquid water path (LWP) and integrated water vapor, and for low water content cases it provides the total LWP and integrated water vapor.  This data was collected during the GPM Cold-season Precipitation Experiment (GCPEx) located in Ontario, Canada, January 14, 2012 through February 29, 2012.  Reference: http://www2.meteo.uni-bonn.de/admirari.
The GPM Ground Validation Advanced Microwave Radiometer Rain Identification (ADMIRARI) GCPEx dataset measures brightness temperatures at three frequencies (10.7, 21.0 and 36.5 GHz) and at two polarized planes (H & V).  The ADMIRARI is a scanning radiometer like its auxiliary active instruments, i.e., Micro rain radar and cloud lidar which provide reflectivity profiles and cloud base altitude at the same scanning angle as the radiometer.  The radiometer retrieval typically provides rain/cloud liquid water path (LWP) and integrated water vapor, and for low water content cases it provides the total LWP and integrated water vapor.  This data was collected during the GPM Cold-season Precipitation Experiment (GCPEx) located in Ontario, Canada, January 14, 2012 through February 29, 2012.  Reference: http://www2.meteo.uni-bonn.de/admirari.
The GPM Ground Validation Advanced Microwave Radiometer Rain Identification (ADMIRARI) GCPEx dataset measures brightness temperatures at three frequencies (10.7, 21.0 and 36.5 GHz) and at two polarized planes (H & V).  The ADMIRARI is a scanning radiometer like its auxiliary active instruments, i.e., Micro rain radar and cloud lidar which provide reflectivity profiles and cloud base altitude at the same scanning angle as the radiometer.  The radiometer retrieval typically provides rain/cloud liquid water path (LWP) and integrated water vapor, and for low water content cases it provides the total LWP and integrated water vapor.  This data was collected during the GPM Cold-season Precipitation Experiment (GCPEx) located in Ontario, Canada, January 14, 2012 through February 29, 2012.  Reference: http://www2.meteo.uni-bonn.de/admirari.
The Second Generation Airborne Precipitation Radar (APR-2) is a dual-frequency (13 GHz and 35 GHz), Doppler, dual-polarization radar system.  It has a downward looking antenna that performs cross track scans, covering a swath that is +/- 25 to each side of the aircraft path.  Additional features include: simultaneous dual-frequency, matched beam operation at 13.4 and 35.6 GHz (same as GPM Dual-Frequency Precipitation Radar), simultaneous measurement of both like- and cross-polarized signals at both frequencies, Doppler operation, and real-time pulse compression (calibrated reflectivity data can be produced for large areas in the field during flight, if necessary.  The APR-2 flew aboard the NASA DC-8 for the GPM Cold-season Precipitation Experiment (GCPEx) from 11 January to 25 February, 2012.
The Second Generation Airborne Precipitation Radar (APR-2) is a dual-frequency (13 GHz and 35 GHz), Doppler, dual-polarization radar system.  It has a downward looking antenna that performs cross track scans, covering a swath that is +/- 25 to each side of the aircraft path.  Additional features include: simultaneous dual-frequency, matched beam operation at 13.4 and 35.6 GHz (same as GPM Dual-Frequency Precipitation Radar), simultaneous measurement of both like- and cross-polarized signals at both frequencies, Doppler operation, and real-time pulse compression (calibrated reflectivity data can be produced for large areas in the field during flight, if necessary.  The APR-2 flew aboard the NASA DC-8 for the GPM Cold-season Precipitation Experiment (GCPEx) from 11 January to 25 February, 2012.
The Second Generation Airborne Precipitation Radar (APR-2) is a dual-frequency (13 GHz and 35 GHz), Doppler, dual-polarization radar system.  It has a downward looking antenna that performs cross track scans, covering a swath that is +/- 25 to each side of the aircraft path.  Additional features include: simultaneous dual-frequency, matched beam operation at 13.4 and 35.6 GHz (same as GPM Dual-Frequency Precipitation Radar), simultaneous measurement of both like- and cross-polarized signals at both frequencies, Doppler operation, and real-time pulse compression (calibrated reflectivity data can be produced for large areas in the field during flight, if necessary.  The APR-2 flew aboard the NASA DC-8 for the GPM Cold-season Precipitation Experiment (GCPEx) from 11 January to 25 February, 2012.
The Autonomous Parsivel Unit (APU) is an optical disdrometer based on single particle extinction that measures particle size and fall velocity.  This APU consists of the Parsivel, which was developed by OTT in Germany, and its support systems, which were designed and built by the University of Alabama in Huntsville.  The APU dataset for the GPM Cold-season Precipitation Experiment (GCPEx) provides precipitation data including raindrop size and counts, precipitation drop size, rate and amount and snowflake size, counts and distribution.  The GCPEx APU data was collected from several sites in Canada during the Winter 2011-2012 period.
The Autonomous Parsivel Unit (APU) is an optical disdrometer based on single particle extinction that measures particle size and fall velocity.  This APU consists of the Parsivel, which was developed by OTT in Germany, and its support systems, which were designed and built by the University of Alabama in Huntsville.  The APU dataset for the GPM Cold-season Precipitation Experiment (GCPEx) provides precipitation data including raindrop size and counts, precipitation drop size, rate and amount and snowflake size, counts and distribution.  The GCPEx APU data was collected from several sites in Canada during the Winter 2011-2012 period.
The Autonomous Parsivel Unit (APU) is an optical disdrometer based on single particle extinction that measures particle size and fall velocity.  This APU consists of the Parsivel, which was developed by OTT in Germany, and its support systems, which were designed and built by the University of Alabama in Huntsville.  The APU dataset for the GPM Cold-season Precipitation Experiment (GCPEx) provides precipitation data including raindrop size and counts, precipitation drop size, rate and amount and snowflake size, counts and distribution.  The GCPEx APU data was collected from several sites in Canada during the Winter 2011-2012 period.
The GPM Ground Validation Autonomous Parsivel Unit (APU) IFLOODS dataset collected data from several sites in eastern Iowa during the spring of 2013.  The APU dataset for the Iowa Flood Studies (IFloodS) Field Experiment provides precipitation data including precipitation drop size, counts, and distribution.  The APU is an optical disdrometer based on single particle extinction that measures particle size and fall velocity.  This APU consists of the Parsivel, which was developed by OTT in Germany, and its support systems, which were designed and built by the University of Alabama in Huntsville.
The GPM Ground Validation Autonomous Parsivel Unit (APU) IFLOODS dataset collected data from several sites in eastern Iowa during the spring of 2013.  The APU dataset for the Iowa Flood Studies (IFloodS) Field Experiment provides precipitation data including precipitation drop size, counts, and distribution.  The APU is an optical disdrometer based on single particle extinction that measures particle size and fall velocity.  This APU consists of the Parsivel, which was developed by OTT in Germany, and its support systems, which were designed and built by the University of Alabama in Huntsville.
The GPM Ground Validation Autonomous Parsivel Unit (APU) IFLOODS dataset collected data from several sites in eastern Iowa during the spring of 2013.  The APU dataset for the Iowa Flood Studies (IFloodS) Field Experiment provides precipitation data including precipitation drop size, counts, and distribution.  The APU is an optical disdrometer based on single particle extinction that measures particle size and fall velocity.  This APU consists of the Parsivel, which was developed by OTT in Germany, and its support systems, which were designed and built by the University of Alabama in Huntsville.
This dataset provides rainfall data for the Global Precipitation Measurement (GPM) Misson Ground Validation Experiment collected at four sites in Finland: Harmaja, Emasalo, and Jarvenpaa, and the Gulf of Finland (Aranda) during the Light Precipitation Validation Experiment September-October 2010.
This dataset provides rainfall data for the Global Precipitation Measurement (GPM) Misson Ground Validation Experiment collected at four sites in Finland: Harmaja, Emasalo, and Jarvenpaa, and the Gulf of Finland (Aranda) during the Light Precipitation Validation Experiment September-October 2010.
This dataset provides rainfall data for the Global Precipitation Measurement (GPM) Misson Ground Validation Experiment collected at four sites in Finland: Harmaja, Emasalo, and Jarvenpaa, and the Gulf of Finland (Aranda) during the Light Precipitation Validation Experiment September-October 2010.
The Autonomous Parsivel Unit (APU) is an optical disdrometer based on single particle extinction that measures particle size and fall velocity.  This APU consists of the Parsivel, which was developed by OTT in Germany, and its support systems, which were designed and built by the University of Alabama in Huntsville.  The APU dataset for the Midlatitude Continental Convective Clouds Experiment (MC3E) provides precipitation data including raindrop size, precipitation drop size, precipitation rate and amount.  The Midlatitude Continental Convective Clouds Experiment (MC3E) took place in central Oklahoma during the April-June 2011 period.  The experiment was a collaborative effort between the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility and the National Aeronautics and Space Administration's (NASA) Global Precipitation Measurement (GPM) mission Ground Validation (GV) program.  The field campaign leveraged the unprecedented observing infrastructure currently available in the central United States, combined with an extensive sounding array, remote sensing and in situ aircraft observations, NASA GPM ground validation remote sensors, and new ARM instrumentation purchased with American Recovery and Reinvestment Act funding.  The overarching goal was to provide the most complete characterization of convective cloud systems, precipitation, and the environment that has ever been obtained, providing constraints for model cumulus parameterizations and space-based rainfall retrieval algorithms over land that had never before been available.
The Autonomous Parsivel Unit (APU) is an optical disdrometer based on single particle extinction that measures particle size and fall velocity.  This APU consists of the Parsivel, which was developed by OTT in Germany, and its support systems, which were designed and built by the University of Alabama in Huntsville.  The APU dataset for the Midlatitude Continental Convective Clouds Experiment (MC3E) provides precipitation data including raindrop size, precipitation drop size, precipitation rate and amount.  The Midlatitude Continental Convective Clouds Experiment (MC3E) took place in central Oklahoma during the April-June 2011 period.  The experiment was a collaborative effort between the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility and the National Aeronautics and Space Administration's (NASA) Global Precipitation Measurement (GPM) mission Ground Validation (GV) program.  The field campaign leveraged the unprecedented observing infrastructure currently available in the central United States, combined with an extensive sounding array, remote sensing and in situ aircraft observations, NASA GPM ground validation remote sensors, and new ARM instrumentation purchased with American Recovery and Reinvestment Act funding.  The overarching goal was to provide the most complete characterization of convective cloud systems, precipitation, and the environment that has ever been obtained, providing constraints for model cumulus parameterizations and space-based rainfall retrieval algorithms over land that had never before been available.
The Autonomous Parsivel Unit (APU) is an optical disdrometer based on single particle extinction that measures particle size and fall velocity.  This APU consists of the Parsivel, which was developed by OTT in Germany, and its support systems, which were designed and built by the University of Alabama in Huntsville.  The APU dataset for the Midlatitude Continental Convective Clouds Experiment (MC3E) provides precipitation data including raindrop size, precipitation drop size, precipitation rate and amount.  The Midlatitude Continental Convective Clouds Experiment (MC3E) took place in central Oklahoma during the April-June 2011 period.  The experiment was a collaborative effort between the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility and the National Aeronautics and Space Administration's (NASA) Global Precipitation Measurement (GPM) mission Ground Validation (GV) program.  The field campaign leveraged the unprecedented observing infrastructure currently available in the central United States, combined with an extensive sounding array, remote sensing and in situ aircraft observations, NASA GPM ground validation remote sensors, and new ARM instrumentation purchased with American Recovery and Reinvestment Act funding.  The overarching goal was to provide the most complete characterization of convective cloud systems, precipitation, and the environment that has ever been obtained, providing constraints for model cumulus parameterizations and space-based rainfall retrieval algorithms over land that had never before been available.
The Autonomous Parsivel Unit (APU) is an optical disdrometer based on single particle extinction that measures particle size and fall velocity.  This APU consists of the Parsivel, which was developed by OTT in Germany, and its support systems, which were designed and built by the University of Alabama in Huntsville.  This dataset provides rainfall data for the Global Precipitation Measurement (GPM) Mission Ground Validation Experiment collected at the National Space Science Technology Center (NSSTC), Huntsville, AL.  There may be occasional gaps in the data when the instrument is not resident at the NSSTC and is sent to participate in field campaigns.
The Autonomous Parsivel Unit (APU) is an optical disdrometer based on single particle extinction that measures particle size and fall velocity.  This APU consists of the Parsivel, which was developed by OTT in Germany, and its support systems, which were designed and built by the University of Alabama in Huntsville.  This dataset provides rainfall data for the Global Precipitation Measurement (GPM) Mission Ground Validation Experiment collected at the National Space Science Technology Center (NSSTC), Huntsville, AL.  There may be occasional gaps in the data when the instrument is not resident at the NSSTC and is sent to participate in field campaigns.
The Autonomous Parsivel Unit (APU) is an optical disdrometer based on single particle extinction that measures particle size and fall velocity.  This APU consists of the Parsivel, which was developed by OTT in Germany, and its support systems, which were designed and built by the University of Alabama in Huntsville.  This dataset provides rainfall data for the Global Precipitation Measurement (GPM) Mission Ground Validation Experiment collected at the National Space Science Technology Center (NSSTC), Huntsville, AL.  There may be occasional gaps in the data when the instrument is not resident at the NSSTC and is sent to participate in field campaigns.
The GPM Ground Validation Campaign Reports MC3E dataset consists of various reports filed by the scientists during the MC3E campaign which took place from mid April thru 3rd June 2011.  Several of the reports are from the planning, test flights, and preparation as early as March 22, 2011.  Reports included in this dataset are for the Mission Scientist, Mission Manager, Instrument Scientists, and Weather Forecasts.  Many reports have additional information included as attachments.
The GPM Ground Validation Campaign Reports MC3E dataset consists of various reports filed by the scientists during the MC3E campaign which took place from mid April thru 3rd June 2011.  Several of the reports are from the planning, test flights, and preparation as early as March 22, 2011.  Reports included in this dataset are for the Mission Scientist, Mission Manager, Instrument Scientists, and Weather Forecasts.  Many reports have additional information included as attachments.
The GPM Ground Validation Campaign Reports MC3E dataset consists of various reports filed by the scientists during the MC3E campaign which took place from mid April thru 3rd June 2011.  Several of the reports are from the planning, test flights, and preparation as early as March 22, 2011.  Reports included in this dataset are for the Mission Scientist, Mission Manager, Instrument Scientists, and Weather Forecasts.  Many reports have additional information included as attachments.
The GPM Ground Validation CARE Satellite Overpass Images GCPEx are the satellite overpass images for the GPM Cold-season Precipitation Experiment (GCPEx) which occurred in Ontario, Canada, January 15, 2012 through February 28, 2012.  The satellites tracks include the DMSP satellites numbers 15, 16, 17, 18, and 19.  A list of starting overpass times per satellite and day is included.
The GPM Ground Validation CARE Satellite Overpass Images GCPEx are the satellite overpass images for the GPM Cold-season Precipitation Experiment (GCPEx) which occurred in Ontario, Canada, January 15, 2012 through February 28, 2012.  The satellites tracks include the DMSP satellites numbers 15, 16, 17, 18, and 19.  A list of starting overpass times per satellite and day is included.
The GPM Ground Validation CARE Satellite Overpass Images GCPEx are the satellite overpass images for the GPM Cold-season Precipitation Experiment (GCPEx) which occurred in Ontario, Canada, January 15, 2012 through February 28, 2012.  The satellites tracks include the DMSP satellites numbers 15, 16, 17, 18, and 19.  A list of starting overpass times per satellite and day is included.
The CHILL radar data for the Midlatitude Continental Convective Clouds Experiment (MC3E) held in Oklahoma were collected while the NASA ER-2 aircraft conducted a series of four legs along the 090 and 120 degree CHILL azimuths on May 24, 2011.  Dual linear polarization variables as well as Doppler velocity, radial velocity, and normalized coherent power are contained in this dataset.  In an effort to expand the MC3E sampling to a wider geographical area, the NASA ER2 aircraft was directed to Northeastern Colorado while widespread rain was in progress on May 24 2011.  The aircraft flew a series of pre-defined ground tracks that coincided with radials from the CSU-CHILL radar.  This aided in keeping the aircraft in the plane of a series of RHI scans done by CSU-CHILL.  The single polarization CSU-Pawnee radar maintained volume coverage of the echo system while the radial flight legs were in progress.  During aircraft course reversals at the ends of the radial legs, the CHILL and Pawnee radars started volume scans in synchronization to support dual Doppler wind syntheses.  CHILL and Pawnee radar data are available as separate datasets.
The CHILL radar data for the Midlatitude Continental Convective Clouds Experiment (MC3E) held in Oklahoma were collected while the NASA ER-2 aircraft conducted a series of four legs along the 090 and 120 degree CHILL azimuths on May 24, 2011.  Dual linear polarization variables as well as Doppler velocity, radial velocity, and normalized coherent power are contained in this dataset.  In an effort to expand the MC3E sampling to a wider geographical area, the NASA ER2 aircraft was directed to Northeastern Colorado while widespread rain was in progress on May 24 2011.  The aircraft flew a series of pre-defined ground tracks that coincided with radials from the CSU-CHILL radar.  This aided in keeping the aircraft in the plane of a series of RHI scans done by CSU-CHILL.  The single polarization CSU-Pawnee radar maintained volume coverage of the echo system while the radial flight legs were in progress.  During aircraft course reversals at the ends of the radial legs, the CHILL and Pawnee radars started volume scans in synchronization to support dual Doppler wind syntheses.  CHILL and Pawnee radar data are available as separate datasets.
The CHILL radar data for the Midlatitude Continental Convective Clouds Experiment (MC3E) held in Oklahoma were collected while the NASA ER-2 aircraft conducted a series of four legs along the 090 and 120 degree CHILL azimuths on May 24, 2011.  Dual linear polarization variables as well as Doppler velocity, radial velocity, and normalized coherent power are contained in this dataset.  In an effort to expand the MC3E sampling to a wider geographical area, the NASA ER2 aircraft was directed to Northeastern Colorado while widespread rain was in progress on May 24 2011.  The aircraft flew a series of pre-defined ground tracks that coincided with radials from the CSU-CHILL radar.  This aided in keeping the aircraft in the plane of a series of RHI scans done by CSU-CHILL.  The single polarization CSU-Pawnee radar maintained volume coverage of the echo system while the radial flight legs were in progress.  During aircraft course reversals at the ends of the radial legs, the CHILL and Pawnee radars started volume scans in synchronization to support dual Doppler wind syntheses.  CHILL and Pawnee radar data are available as separate datasets.
This Cloud Microphysic dataset provides particle size spectra for the Global Precipitation Measurement (GPM) Misson Ground Validation Experiment collected by the Cloud spectrometer and impactor (CIP) and 2DP (2-dimensional probe) aboard the University of Wyoming King Air flown in Finland during the Light Precipitation Validation Experiment September-October 2010.  Lat, Lon, Altitude, Presssure, Temperature are provided with the total concentration of particles with diameter greater than 100 microns.
This Cloud Microphysic dataset provides particle size spectra for the Global Precipitation Measurement (GPM) Misson Ground Validation Experiment collected by the Cloud spectrometer and impactor (CIP) and 2DP (2-dimensional probe) aboard the University of Wyoming King Air flown in Finland during the Light Precipitation Validation Experiment September-October 2010.  Lat, Lon, Altitude, Presssure, Temperature are provided with the total concentration of particles with diameter greater than 100 microns.
This Cloud Microphysic dataset provides particle size spectra for the Global Precipitation Measurement (GPM) Misson Ground Validation Experiment collected by the Cloud spectrometer and impactor (CIP) and 2DP (2-dimensional probe) aboard the University of Wyoming King Air flown in Finland during the Light Precipitation Validation Experiment September-October 2010.  Lat, Lon, Altitude, Presssure, Temperature are provided with the total concentration of particles with diameter greater than 100 microns.
The GPM Ground Validation Composite Satellite Overpasses GCPEx dataset provides satellite overpasses from the SSMIS satellites (F-16, 17, 18) during the GPM Cold-season Precipitation Experiment (GCPEx) which took place in Ontario, Canada, January 15, 2012 through February 29, 2012.  The radiometric data was matched up with other datasets necessary to carry out land surface emissivity studies.  These other datasets include the NEXRAD NMQ radar mosaic for knowledge of rain structure and intensity at the time of the overpass, as well as the previous accumulated precipitation prior to the satellite overpass time), the NOAA IMS snow mapping system (to identify surface snow or ice cover), and the NASA/GMAO MERRA land and  atmospheric reanalysis (for background land and atmospheric state needed for microwave radiative transfer calculations). The identified SSMIS satellite overpasses passed within 700-km of the central field site.
The GPM Ground Validation Composite Satellite Overpasses GCPEx dataset provides satellite overpasses from the SSMIS satellites (F-16, 17, 18) during the GPM Cold-season Precipitation Experiment (GCPEx) which took place in Ontario, Canada, January 15, 2012 through February 29, 2012.  The radiometric data was matched up with other datasets necessary to carry out land surface emissivity studies.  These other datasets include the NEXRAD NMQ radar mosaic for knowledge of rain structure and intensity at the time of the overpass, as well as the previous accumulated precipitation prior to the satellite overpass time), the NOAA IMS snow mapping system (to identify surface snow or ice cover), and the NASA/GMAO MERRA land and  atmospheric reanalysis (for background land and atmospheric state needed for microwave radiative transfer calculations). The identified SSMIS satellite overpasses passed within 700-km of the central field site.
The GPM Ground Validation Composite Satellite Overpasses GCPEx dataset provides satellite overpasses from the SSMIS satellites (F-16, 17, 18) during the GPM Cold-season Precipitation Experiment (GCPEx) which took place in Ontario, Canada, January 15, 2012 through February 29, 2012.  The radiometric data was matched up with other datasets necessary to carry out land surface emissivity studies.  These other datasets include the NEXRAD NMQ radar mosaic for knowledge of rain structure and intensity at the time of the overpass, as well as the previous accumulated precipitation prior to the satellite overpass time), the NOAA IMS snow mapping system (to identify surface snow or ice cover), and the NASA/GMAO MERRA land and  atmospheric reanalysis (for background land and atmospheric state needed for microwave radiative transfer calculations). The identified SSMIS satellite overpasses passed within 700-km of the central field site.
The GPM Ground Validation Composite Satellite Overpasses MC3E dataset provides satellite overpasses from the AQUA satellite during the Midlatitude Continental Convective Clouds Experiment (MC3E) which took place in central Oklahoma April 22 - June 5, 2011.  The radiometric data was matched up with other datasets necessary to carry out land surface emissivity studies.  These other datasets include the NEXRAD NMQ radar mosaic for knowledge of rain structure and intensity at the time of the overpass, as well as the previous accumulated precip prior to the satellite overpass time), the NOAA IMS snow mapping system (to identify surface snow or ice cover), and the NASA/GMAO MERRA land and atmospheric reanalysis (for background land and atmospheric state needed for microwave radiative transfer calculations).  The identified AQUA satellite overpasses included passed within 700-km of the central field site.
The GPM Ground Validation Composite Satellite Overpasses MC3E dataset provides satellite overpasses from the AQUA satellite during the Midlatitude Continental Convective Clouds Experiment (MC3E) which took place in central Oklahoma April 22 - June 5, 2011.  The radiometric data was matched up with other datasets necessary to carry out land surface emissivity studies.  These other datasets include the NEXRAD NMQ radar mosaic for knowledge of rain structure and intensity at the time of the overpass, as well as the previous accumulated precip prior to the satellite overpass time), the NOAA IMS snow mapping system (to identify surface snow or ice cover), and the NASA/GMAO MERRA land and atmospheric reanalysis (for background land and atmospheric state needed for microwave radiative transfer calculations).  The identified AQUA satellite overpasses included passed within 700-km of the central field site.
The GPM Ground Validation Composite Satellite Overpasses MC3E dataset provides satellite overpasses from the AQUA satellite during the Midlatitude Continental Convective Clouds Experiment (MC3E) which took place in central Oklahoma April 22 - June 5, 2011.  The radiometric data was matched up with other datasets necessary to carry out land surface emissivity studies.  These other datasets include the NEXRAD NMQ radar mosaic for knowledge of rain structure and intensity at the time of the overpass, as well as the previous accumulated precip prior to the satellite overpass time), the NOAA IMS snow mapping system (to identify surface snow or ice cover), and the NASA/GMAO MERRA land and atmospheric reanalysis (for background land and atmospheric state needed for microwave radiative transfer calculations).  The identified AQUA satellite overpasses included passed within 700-km of the central field site.
The Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) dataset for the GPM Cold-season Precipitation Experiment (GCPEx) plays the role as an airborne high-frequency simulator for the GPM Microwave Imager (GMI), which will launch in 2014.  The CoSMIR was modified with a new scan mode to acquire both conical and cross-track scan data simultaneously in a given flight satisfying the requirements of the Precipitation Measurement Mission (PMM) algorithm development team.  The dataset provides well-calibrated radiometric data from 9 channels between 50-183GHz with the accuracy on the order of +-1K.  All channels besides the 89 and 165.5 GHz are horizontally polarized.
The Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) dataset for the GPM Cold-season Precipitation Experiment (GCPEx) plays the role as an airborne high-frequency simulator for the GPM Microwave Imager (GMI), which will launch in 2014.  The CoSMIR was modified with a new scan mode to acquire both conical and cross-track scan data simultaneously in a given flight satisfying the requirements of the Precipitation Measurement Mission (PMM) algorithm development team.  The dataset provides well-calibrated radiometric data from 9 channels between 50-183GHz with the accuracy on the order of +-1K.  All channels besides the 89 and 165.5 GHz are horizontally polarized.
The Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) dataset for the GPM Cold-season Precipitation Experiment (GCPEx) plays the role as an airborne high-frequency simulator for the GPM Microwave Imager (GMI), which will launch in 2014.  The CoSMIR was modified with a new scan mode to acquire both conical and cross-track scan data simultaneously in a given flight satisfying the requirements of the Precipitation Measurement Mission (PMM) algorithm development team.  The dataset provides well-calibrated radiometric data from 9 channels between 50-183GHz with the accuracy on the order of +-1K.  All channels besides the 89 and 165.5 GHz are horizontally polarized.
The Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) dataset for the Midlatitude Continental Convective Clouds Experiment (MC3E) plays the role as an airborne high-frequency simulator for the GPM Microwave Imager (GMI), which will launch in 2014.  The CoSMIR was modified with a new scan mode to acquire both conical and cross-track scan data simultaneously in a given flight satisfying the requirements of the Precipitation Measurement Mission (PMM) algorithm development team.  The dataset provides well-calibrated radiometric data from 9 channels between 50-183GHz with the accuracy on the order of +-1K.  All channels besides the 89 and 165.5 GHz are horizontally polarized.
The Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) dataset for the Midlatitude Continental Convective Clouds Experiment (MC3E) plays the role as an airborne high-frequency simulator for the GPM Microwave Imager (GMI), which will launch in 2014.  The CoSMIR was modified with a new scan mode to acquire both conical and cross-track scan data simultaneously in a given flight satisfying the requirements of the Precipitation Measurement Mission (PMM) algorithm development team.  The dataset provides well-calibrated radiometric data from 9 channels between 50-183GHz with the accuracy on the order of +-1K.  All channels besides the 89 and 165.5 GHz are horizontally polarized.
The Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) dataset for the Midlatitude Continental Convective Clouds Experiment (MC3E) plays the role as an airborne high-frequency simulator for the GPM Microwave Imager (GMI), which will launch in 2014.  The CoSMIR was modified with a new scan mode to acquire both conical and cross-track scan data simultaneously in a given flight satisfying the requirements of the Precipitation Measurement Mission (PMM) algorithm development team.  The dataset provides well-calibrated radiometric data from 9 channels between 50-183GHz with the accuracy on the order of +-1K.  All channels besides the 89 and 165.5 GHz are horizontally polarized.
The GPM Ground Validation DC-8 Camera Nadir GCPEx dataset contains geo-located visible-wavelength imagery of the ground obtained from the nadir camera aboard the NASA DC-8 in Canada during the Cold-season Precipitation experiment.  The data is available only for February 20, 2012, a clear-air flight day.  DC-8 Camera nadir data may be useful for determining snow cover and lake ice cover for emissivity studies in conjunction with CoSMIR data, for example.  The dataset also includes, for convenience and reproducibility, aircraft navigation information and ground temperatures to aid in emissivity retrievals.
The GPM Ground Validation DC-8 Camera Nadir GCPEx dataset contains geo-located visible-wavelength imagery of the ground obtained from the nadir camera aboard the NASA DC-8 in Canada during the Cold-season Precipitation experiment.  The data is available only for February 20, 2012, a clear-air flight day.  DC-8 Camera nadir data may be useful for determining snow cover and lake ice cover for emissivity studies in conjunction with CoSMIR data, for example.  The dataset also includes, for convenience and reproducibility, aircraft navigation information and ground temperatures to aid in emissivity retrievals.
The GPM Ground Validation DC-8 Camera Nadir GCPEx dataset contains geo-located visible-wavelength imagery of the ground obtained from the nadir camera aboard the NASA DC-8 in Canada during the Cold-season Precipitation experiment.  The data is available only for February 20, 2012, a clear-air flight day.  DC-8 Camera nadir data may be useful for determining snow cover and lake ice cover for emissivity studies in conjunction with CoSMIR data, for example.  The dataset also includes, for convenience and reproducibility, aircraft navigation information and ground temperatures to aid in emissivity retrievals.
The GCPEX Navigation dataset is composed of two types of files.  National Suborbital Education and Research Center (NSERC) of the University of North Dakota (UND) provided the geo-located housekeeping data containing the altitude, pressure, air speed, wind speed and other attributes.  The NASA DC-8 Navigation data in comma delimited IWG1 format were collected and utilized in-flight during the GCPEx mission and retrieved from the Real-Time Mission Monitor.  Both file types are available for most of the dataset dates, however please note that there are a few dates where only the IWG1 formatted data is available.
The GCPEX Navigation dataset is composed of two types of files.  National Suborbital Education and Research Center (NSERC) of the University of North Dakota (UND) provided the geo-located housekeeping data containing the altitude, pressure, air speed, wind speed and other attributes.  The NASA DC-8 Navigation data in comma delimited IWG1 format were collected and utilized in-flight during the GCPEx mission and retrieved from the Real-Time Mission Monitor.  Both file types are available for most of the dataset dates, however please note that there are a few dates where only the IWG1 formatted data is available.
The GCPEX Navigation dataset is composed of two types of files.  National Suborbital Education and Research Center (NSERC) of the University of North Dakota (UND) provided the geo-located housekeeping data containing the altitude, pressure, air speed, wind speed and other attributes.  The NASA DC-8 Navigation data in comma delimited IWG1 format were collected and utilized in-flight during the GCPEx mission and retrieved from the Real-Time Mission Monitor.  Both file types are available for most of the dataset dates, however please note that there are a few dates where only the IWG1 formatted data is available.
The GPM Ground Validation Dual Polarization Radiometer GCPEx dataset provides brightness temperature measurements at frequencies 90 GHz (not polarized) and 150 GHz (HV-polarized) for the GPM Cold-season Precipitation Experiment (GCPEx) which occurred in Ontario, Canada, during January and February 2012.  This Dual polarization radiometer (DPR) is sensitive to particle orientation since it observes the brightness temperature difference between the vertical and horizontal polarization channels at 150 GHz, and it is especially important for the retrievals of particle shape and orientation with polarization observations.  DPR also has a high sensitivity to the supercooled liquid water in clouds due to the high-frequency window channels.  Even though the netCDF data has regular scans, the browse is only shown at 30 and 150 degrees.  Ancillary data is captured for the internal calibration of the instrument.
The GPM Ground Validation Dual Polarization Radiometer GCPEx dataset provides brightness temperature measurements at frequencies 90 GHz (not polarized) and 150 GHz (HV-polarized) for the GPM Cold-season Precipitation Experiment (GCPEx) which occurred in Ontario, Canada, during January and February 2012.  This Dual polarization radiometer (DPR) is sensitive to particle orientation since it observes the brightness temperature difference between the vertical and horizontal polarization channels at 150 GHz, and it is especially important for the retrievals of particle shape and orientation with polarization observations.  DPR also has a high sensitivity to the supercooled liquid water in clouds due to the high-frequency window channels.  Even though the netCDF data has regular scans, the browse is only shown at 30 and 150 degrees.  Ancillary data is captured for the internal calibration of the instrument.
The GPM Ground Validation Dual Polarization Radiometer GCPEx dataset provides brightness temperature measurements at frequencies 90 GHz (not polarized) and 150 GHz (HV-polarized) for the GPM Cold-season Precipitation Experiment (GCPEx) which occurred in Ontario, Canada, during January and February 2012.  This Dual polarization radiometer (DPR) is sensitive to particle orientation since it observes the brightness temperature difference between the vertical and horizontal polarization channels at 150 GHz, and it is especially important for the retrievals of particle shape and orientation with polarization observations.  DPR also has a high sensitivity to the supercooled liquid water in clouds due to the high-frequency window channels.  Even though the netCDF data has regular scans, the browse is only shown at 30 and 150 degrees.  Ancillary data is captured for the internal calibration of the instrument.
The GPM Ground Validation Dual Polarized C-Band Doppler Radar King City GCPEx dataset has special RHI and sector scans of several dual polarization parameters created by the C-Band radar during the GPM Cold-season Precipitation Experiment (GCPEx) in Ontario, Canada.  Additionally, specially configured CARE-centric composites were also generated.  Standard WKR IRIS volume and PPI scans, along with corresponding standard PPI imagery, are also included.  Data was collected from January 15, 2012 through March 3, 2012.
The GPM Ground Validation Dual Polarized C-Band Doppler Radar King City GCPEx dataset has special RHI and sector scans of several dual polarization parameters created by the C-Band radar during the GPM Cold-season Precipitation Experiment (GCPEx) in Ontario, Canada.  Additionally, specially configured CARE-centric composites were also generated.  Standard WKR IRIS volume and PPI scans, along with corresponding standard PPI imagery, are also included.  Data was collected from January 15, 2012 through March 3, 2012.
The GPM Ground Validation Dual Polarized C-Band Doppler Radar King City GCPEx dataset has special RHI and sector scans of several dual polarization parameters created by the C-Band radar during the GPM Cold-season Precipitation Experiment (GCPEx) in Ontario, Canada.  Additionally, specially configured CARE-centric composites were also generated.  Standard WKR IRIS volume and PPI scans, along with corresponding standard PPI imagery, are also included.  Data was collected from January 15, 2012 through March 3, 2012.
The GPM Ground Validation Dual-frequency Dual-polarized Doppler Radar (D3R) GCPEx dataset was collected from January 13, 2012 to February 29, 2012 at the CARE site in Ontario, Canada as a part of the GPM Cold-season Precipitation Experiment (GCPEx).  The D3R is a fully polarimetric, scanning weather radar system operating at the nominal frequencies of 13.91 GHz and 35.56 GHz covering a maximum range of 30 km.  The GPM Ground Validation Dual-frequency Dual-polarized Doppler Radar (D3R) GCPEx dataset is available in netCDF format.  Browse images are also available in .png format.
The GPM Ground Validation Dual-frequency Dual-polarized Doppler Radar (D3R) GCPEx dataset was collected from January 13, 2012 to February 29, 2012 at the CARE site in Ontario, Canada as a part of the GPM Cold-season Precipitation Experiment (GCPEx).  The D3R is a fully polarimetric, scanning weather radar system operating at the nominal frequencies of 13.91 GHz and 35.56 GHz covering a maximum range of 30 km.  The GPM Ground Validation Dual-frequency Dual-polarized Doppler Radar (D3R) GCPEx dataset is available in netCDF format.  Browse images are also available in .png format.
The GPM Ground Validation Dual-frequency Dual-polarized Doppler Radar (D3R) GCPEx dataset was collected from January 13, 2012 to February 29, 2012 at the CARE site in Ontario, Canada as a part of the GPM Cold-season Precipitation Experiment (GCPEx).  The D3R is a fully polarimetric, scanning weather radar system operating at the nominal frequencies of 13.91 GHz and 35.56 GHz covering a maximum range of 30 km.  The GPM Ground Validation Dual-frequency Dual-polarized Doppler Radar (D3R) GCPEx dataset is available in netCDF format.  Browse images are also available in .png format.
The GPM Ground Validation Dual-frequency Dual-polarized Doppler Radar (D3R) IFloodS dataset was collected from May 9, 2013 to June 13, 2013 as a part of the GPM Cold-season Precipitation Experiment (GCPEx).  The D3R is a fully polarimetric, scanning weather radar system operating at the nominal frequencies of 13.91 GHz and 35.56 GHz covering a maximum range of 30 km.  The GPM Ground Validation Dual-frequency Dual-polarized Doppler Radar (D3R) IFloodS dataset is available in netCDF format.  Browse images are also available in .png format.
The GPM Ground Validation Dual-frequency Dual-polarized Doppler Radar (D3R) IFloodS dataset was collected from May 9, 2013 to June 13, 2013 as a part of the GPM Cold-season Precipitation Experiment (GCPEx).  The D3R is a fully polarimetric, scanning weather radar system operating at the nominal frequencies of 13.91 GHz and 35.56 GHz covering a maximum range of 30 km.  The GPM Ground Validation Dual-frequency Dual-polarized Doppler Radar (D3R) IFloodS dataset is available in netCDF format.  Browse images are also available in .png format.
The GPM Ground Validation Dual-frequency Dual-polarized Doppler Radar (D3R) IFloodS dataset was collected from May 9, 2013 to June 13, 2013 as a part of the GPM Cold-season Precipitation Experiment (GCPEx).  The D3R is a fully polarimetric, scanning weather radar system operating at the nominal frequencies of 13.91 GHz and 35.56 GHz covering a maximum range of 30 km.  The GPM Ground Validation Dual-frequency Dual-polarized Doppler Radar (D3R) IFloodS dataset is available in netCDF format.  Browse images are also available in .png format.
The Earth Networks Total Lightning Network (ENTLN) is an integrated in-cloud (IC) lightning and cloud-to-ground (CG) detection network deployed on a global basis capable of detecting long range in-cloud lightning at high efficiencies critical for the advanced prediction of severe weather phenomena.  This dataset consists of a subset of data for the period of the Midlatitude Continental Convective Clouds Experiment (MC3E), 1 April 2011 - 15 June 2011.
The GPM Ground Validation Environment Canada (EC) Manual Precipitation Measurements GCPEx dataset was collected during the GPM Cold-season Precipitation Experiment (GCPEx) in Ontario, Canada with data collections from January 18 - March 28, 2012.  Precipitation amount, weight, snow water equivalent and present weather condition were recorded using a Tretyakov gauge inside a double fence intercomparison reference (DFIR) shield.
The GPM Ground Validation Environment Canada (EC) Manual Precipitation Measurements GCPEx dataset was collected during the GPM Cold-season Precipitation Experiment (GCPEx) in Ontario, Canada with data collections from January 18 - March 28, 2012.  Precipitation amount, weight, snow water equivalent and present weather condition were recorded using a Tretyakov gauge inside a double fence intercomparison reference (DFIR) shield.
The GPM Ground Validation Environment Canada (EC) Manual Precipitation Measurements GCPEx dataset was collected during the GPM Cold-season Precipitation Experiment (GCPEx) in Ontario, Canada with data collections from January 18 - March 28, 2012.  Precipitation amount, weight, snow water equivalent and present weather condition were recorded using a Tretyakov gauge inside a double fence intercomparison reference (DFIR) shield.
Environment Canada (EC) collected data from the Micro Rain Radar (MRR) during the GPM Cold-season Precipitation Experiment (GCPEx) in Ontario, Canada during the winter season 2012.  Operating at 24 GHz the MRR, a vertically pointing Doppler radar, retrieved quantitative rain rates, drop size distributions, radar reflectivity, fall velocities on vertical profiles up to several kilometers above the unit.  The MRR used during GCPEX is the second generation of the instrument manufactured by METEK (URL: http://www.metek.de/product-details/mrr-2.html).
Environment Canada (EC) collected data from the Micro Rain Radar (MRR) during the GPM Cold-season Precipitation Experiment (GCPEx) in Ontario, Canada during the winter season 2012.  Operating at 24 GHz the MRR, a vertically pointing Doppler radar, retrieved quantitative rain rates, drop size distributions, radar reflectivity, fall velocities on vertical profiles up to several kilometers above the unit.  The MRR used during GCPEX is the second generation of the instrument manufactured by METEK (URL: http://www.metek.de/product-details/mrr-2.html).
Environment Canada (EC) collected data from the Micro Rain Radar (MRR) during the GPM Cold-season Precipitation Experiment (GCPEx) in Ontario, Canada during the winter season 2012.  Operating at 24 GHz the MRR, a vertically pointing Doppler radar, retrieved quantitative rain rates, drop size distributions, radar reflectivity, fall velocities on vertical profiles up to several kilometers above the unit.  The MRR used during GCPEX is the second generation of the instrument manufactured by METEK (URL: http://www.metek.de/product-details/mrr-2.html).
The GPM Ground Validation Environment Canada (EC) Passive Microwave Radiometer and Soil Moisture-Temperature Data GCPEx dataset gathered data during the GPM Cold-season Precipitation Experiment (GCPEx) at the CARE site in Ontario, Canada during the winter season 2011-2012.  Data collected includes microwave brightness temperatures, snow and soil/snow-air interface (ground surface temperatures), soil surface temperatures, and soil volumetric water content.  These data were acquired by multiple instruments: a passive microwave radiometer, a water content reflectometer, thermistors, soil moisture probe.
The GPM Ground Validation Environment Canada (EC) Passive Microwave Radiometer and Soil Moisture-Temperature Data GCPEx dataset gathered data during the GPM Cold-season Precipitation Experiment (GCPEx) at the CARE site in Ontario, Canada during the winter season 2011-2012.  Data collected includes microwave brightness temperatures, snow and soil/snow-air interface (ground surface temperatures), soil surface temperatures, and soil volumetric water content.  These data were acquired by multiple instruments: a passive microwave radiometer, a water content reflectometer, thermistors, soil moisture probe.
The GPM Ground Validation Environment Canada (EC) Passive Microwave Radiometer and Soil Moisture-Temperature Data GCPEx dataset gathered data during the GPM Cold-season Precipitation Experiment (GCPEx) at the CARE site in Ontario, Canada during the winter season 2011-2012.  Data collected includes microwave brightness temperatures, snow and soil/snow-air interface (ground surface temperatures), soil surface temperatures, and soil volumetric water content.  These data were acquired by multiple instruments: a passive microwave radiometer, a water content reflectometer, thermistors, soil moisture probe.
The GPM Ground Validation Environment Canada (EC) Precipitation Occurrence Sensor System (POSS) GCPEx dataset has data gathered during the GPM Cold-season Precipitation Experiment which took place in Ontario, Canada, January 15 - March 1, 2012. The POSS is a bi-static X-band Doppler radar designed by Environment Canada The POSS measures a signal whose frequency is proportional to the particle Doppler velocity and whose amplitude is proportional to the particle scattering cross-section.  Its measurements can be used to provide information regarding precipitation occurrence, type, rate, and raindrop size distribution.
The GPM Ground Validation Environment Canada (EC) Precipitation Occurrence Sensor System (POSS) GCPEx dataset has data gathered during the GPM Cold-season Precipitation Experiment which took place in Ontario, Canada, January 15 - March 1, 2012. The POSS is a bi-static X-band Doppler radar designed by Environment Canada The POSS measures a signal whose frequency is proportional to the particle Doppler velocity and whose amplitude is proportional to the particle scattering cross-section.  Its measurements can be used to provide information regarding precipitation occurrence, type, rate, and raindrop size distribution.
The GPM Ground Validation Environment Canada (EC) Precipitation Occurrence Sensor System (POSS) GCPEx dataset has data gathered during the GPM Cold-season Precipitation Experiment which took place in Ontario, Canada, January 15 - March 1, 2012. The POSS is a bi-static X-band Doppler radar designed by Environment Canada The POSS measures a signal whose frequency is proportional to the particle Doppler velocity and whose amplitude is proportional to the particle scattering cross-section.  Its measurements can be used to provide information regarding precipitation occurrence, type, rate, and raindrop size distribution.
The GPM Ground Validation Environment Canada (EC) Radiometer GCPEx dataset contains retrievals of temperature, water vapor, relative humidity, liquid water profiles and surface parameters acquired by a passive microwave radiometer during the GPM Cold-season Precipitation Experiment (GCPEx) in Ontario, Canada, February 2012 through March 1, 2012.  Data plots are available in the browse files.
The GPM Ground Validation Environment Canada (EC) Radiometer GCPEx dataset contains retrievals of temperature, water vapor, relative humidity, liquid water profiles and surface parameters acquired by a passive microwave radiometer during the GPM Cold-season Precipitation Experiment (GCPEx) in Ontario, Canada, February 2012 through March 1, 2012.  Data plots are available in the browse files.
The GPM Ground Validation Environment Canada (EC) Radiometer GCPEx dataset contains retrievals of temperature, water vapor, relative humidity, liquid water profiles and surface parameters acquired by a passive microwave radiometer during the GPM Cold-season Precipitation Experiment (GCPEx) in Ontario, Canada, February 2012 through March 1, 2012.  Data plots are available in the browse files.
The GPM Ground Validation Environment Canada (EC) Radiosonde GCPEx dataset provides measurements of pressure, temperature, humidity, and winds collected by Vaisala RS92 Radiosondes during the GPM Cold-season Precipitation Experiment (GCPEx) at the CARE site in Ontario, Canada, 17 January through 29 February 2012.
The GPM Ground Validation Environment Canada (EC) Radiosonde GCPEx dataset provides measurements of pressure, temperature, humidity, and winds collected by Vaisala RS92 Radiosondes during the GPM Cold-season Precipitation Experiment (GCPEx) at the CARE site in Ontario, Canada, 17 January through 29 February 2012.
The GPM Ground Validation Environment Canada (EC) Radiosonde GCPEx dataset provides measurements of pressure, temperature, humidity, and winds collected by Vaisala RS92 Radiosondes during the GPM Cold-season Precipitation Experiment (GCPEx) at the CARE site in Ontario, Canada, 17 January through 29 February 2012.
The GPM Ground Validation Environment Canada Snow Depth Surveys GCPEx dataset was manually collected during the GPM Cold-season Precipitation Experiment (GCPEx) which occurred in Ontario, Canada, January 20, 2012 through February 27, 2012 across four sites (CARE, Steamshow, Huronia Airport, and Skydive-Jump).  Snow depth, water equivalent and density transects were surveyed weekly at each of the GCPEx sites in order to provide baseline information on the distribution of snow on the ground.  Pairs of bulk density and snow water equivalent measurements were made every 25 m along the same transect using an ESC-30 (30 cm2 cross sectional area) snow corer.  Snow depth measurements were made every 50 cm along a 100 m transect using a GPS equipped snow depth probe.
The GPM Ground Validation Environment Canada Snow Depth Surveys GCPEx dataset was manually collected during the GPM Cold-season Precipitation Experiment (GCPEx) which occurred in Ontario, Canada, January 20, 2012 through February 27, 2012 across four sites (CARE, Steamshow, Huronia Airport, and Skydive-Jump).  Snow depth, water equivalent and density transects were surveyed weekly at each of the GCPEx sites in order to provide baseline information on the distribution of snow on the ground.  Pairs of bulk density and snow water equivalent measurements were made every 25 m along the same transect using an ESC-30 (30 cm2 cross sectional area) snow corer.  Snow depth measurements were made every 50 cm along a 100 m transect using a GPS equipped snow depth probe.
The GPM Ground Validation Environment Canada Snow Depth Surveys GCPEx dataset was manually collected during the GPM Cold-season Precipitation Experiment (GCPEx) which occurred in Ontario, Canada, January 20, 2012 through February 27, 2012 across four sites (CARE, Steamshow, Huronia Airport, and Skydive-Jump).  Snow depth, water equivalent and density transects were surveyed weekly at each of the GCPEx sites in order to provide baseline information on the distribution of snow on the ground.  Pairs of bulk density and snow water equivalent measurements were made every 25 m along the same transect using an ESC-30 (30 cm2 cross sectional area) snow corer.  Snow depth measurements were made every 50 cm along a 100 m transect using a GPS equipped snow depth probe.
Environment Canada (EC) collected ceilometer data during the GPM Cold-season Precipitation Experiment (GCPEx) in Huronia, Canada from January 15, 2012 through March 1, 2012.  The CT25K ceilometer uses pulsed diode laser LIDAR technology to derive backscatter profiles, cloud heights and vertical visibilities.  It is also able to detect 3 cloud layers simultaneously.
Environment Canada (EC) collected ceilometer data during the GPM Cold-season Precipitation Experiment (GCPEx) in Huronia, Canada from January 15, 2012 through March 1, 2012.  The CT25K ceilometer uses pulsed diode laser LIDAR technology to derive backscatter profiles, cloud heights and vertical visibilities.  It is also able to detect 3 cloud layers simultaneously.
Environment Canada (EC) collected ceilometer data during the GPM Cold-season Precipitation Experiment (GCPEx) in Huronia, Canada from January 15, 2012 through March 1, 2012.  The CT25K ceilometer uses pulsed diode laser LIDAR technology to derive backscatter profiles, cloud heights and vertical visibilities.  It is also able to detect 3 cloud layers simultaneously.
The GPM Ground Validation Environment Canada (EC) Visibility Sensor FD12P and Present Weather Detector GCPEx dataset collected data January 15 through March 1, 2012 in Huronia, Canada for the GPM Cold-season Precipitation Experiment (GCPEx).  The FD12P combines the functions of a forward scatter visibility meter and a present weather detector.  It also measures the intensity and the amount of both liquid and solid precipitation.
The GPM Ground Validation Environment Canada (EC) Visibility Sensor FD12P and Present Weather Detector GCPEx dataset collected data January 15 through March 1, 2012 in Huronia, Canada for the GPM Cold-season Precipitation Experiment (GCPEx).  The FD12P combines the functions of a forward scatter visibility meter and a present weather detector.  It also measures the intensity and the amount of both liquid and solid precipitation.
The GPM Ground Validation Environment Canada (EC) Visibility Sensor FD12P and Present Weather Detector GCPEx dataset collected data January 15 through March 1, 2012 in Huronia, Canada for the GPM Cold-season Precipitation Experiment (GCPEx).  The FD12P combines the functions of a forward scatter visibility meter and a present weather detector.  It also measures the intensity and the amount of both liquid and solid precipitation.
The GPM Ground Validation Environment Canada (EC) Web Camera Images GCPEx were taken at 5 site locations in Ontario, Canada during the GPM Cold-season Precipitation Experiment (GCPEx) which occurred January 15 through March 1, 2012.  Mounted as a fixed outdoor camera, the AXIS P1343-E network camera has day/night functionality with an automatically controlled IR filter, adapting to both daylight and dark lighting conditions.  These images provided visual records throughout the day of the weather conditions at the site.
The GPM Ground Validation Environment Canada (EC) Web Camera Images GCPEx were taken at 5 site locations in Ontario, Canada during the GPM Cold-season Precipitation Experiment (GCPEx) which occurred January 15 through March 1, 2012.  Mounted as a fixed outdoor camera, the AXIS P1343-E network camera has day/night functionality with an automatically controlled IR filter, adapting to both daylight and dark lighting conditions.  These images provided visual records throughout the day of the weather conditions at the site.
The GPM Ground Validation Environment Canada (EC) Web Camera Images GCPEx were taken at 5 site locations in Ontario, Canada during the GPM Cold-season Precipitation Experiment (GCPEx) which occurred January 15 through March 1, 2012.  Mounted as a fixed outdoor camera, the AXIS P1343-E network camera has day/night functionality with an automatically controlled IR filter, adapting to both daylight and dark lighting conditions.  These images provided visual records throughout the day of the weather conditions at the site.
The GPM Ground Validation Environment Canada (EC) Wind Profiler GCPEx dataset provides post-processed consensus winds and daily quick look plots from the Vaisala Wind Profiler LAP 3000.  The daily plots depict wind information from the profiler and from the GEM model data.  The LAP 3000 is a pulsed Doppler radar that operates in clean air, reporting data from the atmosphere 3 kilometres or more above ground level.  The Wind profiler data was collected January 15, 2012 through March 1, 2012 for the GPM Cold-season Precipitation Experiment (GCPEx) at the CARE site in Ontario, Canada.
The GPM Ground Validation Environment Canada (EC) Wind Profiler GCPEx dataset provides post-processed consensus winds and daily quick look plots from the Vaisala Wind Profiler LAP 3000.  The daily plots depict wind information from the profiler and from the GEM model data.  The LAP 3000 is a pulsed Doppler radar that operates in clean air, reporting data from the atmosphere 3 kilometres or more above ground level.  The Wind profiler data was collected January 15, 2012 through March 1, 2012 for the GPM Cold-season Precipitation Experiment (GCPEx) at the CARE site in Ontario, Canada.
The GPM Ground Validation Environment Canada (EC) Wind Profiler GCPEx dataset provides post-processed consensus winds and daily quick look plots from the Vaisala Wind Profiler LAP 3000.  The daily plots depict wind information from the profiler and from the GEM model data.  The LAP 3000 is a pulsed Doppler radar that operates in clean air, reporting data from the atmosphere 3 kilometres or more above ground level.  The Wind profiler data was collected January 15, 2012 through March 1, 2012 for the GPM Cold-season Precipitation Experiment (GCPEx) at the CARE site in Ontario, Canada.
The Flight Summaries and Flight Tracks Imagery dataset for MC3E provides processed summaries from University of North Dakota including sonde maps, a radar animation, parameter versus time charts, radar track graphs, and a summary including aircraft and instrument operational times.  The Flight Tracks imagery includes one animation for May 11, 2011 and the KICT 5 minute snapshots from the Real Time Mission Monitor (RTMM).  This dataset is distributed with the MC3E ER-2 Navigation and the Citation Navigation datasets.
The Flight Summaries and Flight Tracks Imagery dataset for MC3E provides processed summaries from University of North Dakota including sonde maps, a radar animation, parameter versus time charts, radar track graphs, and a summary including aircraft and instrument operational times.  The Flight Tracks imagery includes one animation for May 11, 2011 and the KICT 5 minute snapshots from the Real Time Mission Monitor (RTMM).  This dataset is distributed with the MC3E ER-2 Navigation and the Citation Navigation datasets.
The Flight Summaries and Flight Tracks Imagery dataset for MC3E provides processed summaries from University of North Dakota including sonde maps, a radar animation, parameter versus time charts, radar track graphs, and a summary including aircraft and instrument operational times.  The Flight Tracks imagery includes one animation for May 11, 2011 and the KICT 5 minute snapshots from the Real Time Mission Monitor (RTMM).  This dataset is distributed with the MC3E ER-2 Navigation and the Citation Navigation datasets.
The GOES 13 imagery files (ir3, ir4, vis) were produced and archived in near real time here at the Global Hydrology and Climate Center (http://ghcc.nsstc.nasa.gov) throughout the GPM Cold-Season Precipitation Experiment (GCPEx).  These image files were created for use with the Real Time Mission Monitor (RTMM).  Generally, GOES-13 images are available for all dates between January 1, 2012 and March 13, 2012 at 15 minute intervals throughout this time period.
The GOES 13 imagery files (ir3, ir4, vis) were produced and archived in near real time here at the Global Hydrology and Climate Center (http://ghcc.nsstc.nasa.gov) throughout the GPM Cold-Season Precipitation Experiment (GCPEx).  These image files were created for use with the Real Time Mission Monitor (RTMM).  Generally, GOES-13 images are available for all dates between January 1, 2012 and March 13, 2012 at 15 minute intervals throughout this time period.
The GOES 13 imagery files (ir3, ir4, vis) were produced and archived in near real time here at the Global Hydrology and Climate Center (http://ghcc.nsstc.nasa.gov) throughout the GPM Cold-Season Precipitation Experiment (GCPEx).  These image files were created for use with the Real Time Mission Monitor (RTMM).  Generally, GOES-13 images are available for all dates between January 1, 2012 and March 13, 2012 at 15 minute intervals throughout this time period.
These GOES 13 imagery files (ir3, ir4, vis) were produced and archived in near real time here at the Global Hydrology and Climate Center (http://ghcc.nsstc.nasa.gov) throughout the GPM Midlatitude Continental Convective Clouds Experiment (MC3E).  These image files were created for use with the Real Time Mission Monitor (RTMM).  Generally, GOES-13 images are available for all dates between May 6, 2011 and June 30, 2011 at 15 minute intervals throughout this time period.
These GOES 13 imagery files (ir3, ir4, vis) were produced and archived in near real time here at the Global Hydrology and Climate Center (http://ghcc.nsstc.nasa.gov) throughout the GPM Midlatitude Continental Convective Clouds Experiment (MC3E).  These image files were created for use with the Real Time Mission Monitor (RTMM).  Generally, GOES-13 images are available for all dates between May 6, 2011 and June 30, 2011 at 15 minute intervals throughout this time period.
These GOES 13 imagery files (ir3, ir4, vis) were produced and archived in near real time here at the Global Hydrology and Climate Center (http://ghcc.nsstc.nasa.gov) throughout the GPM Midlatitude Continental Convective Clouds Experiment (MC3E).  These image files were created for use with the Real Time Mission Monitor (RTMM).  Generally, GOES-13 images are available for all dates between May 6, 2011 and June 30, 2011 at 15 minute intervals throughout this time period.
The High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) is a dual-frequency (Ka- and Ku-band) conical scan system, configured with a nadir viewing antenna on the high-altitude (20 km) NASA ER-2 aircraft.  It provides calibrated reflectivity and unfolded Doppler velocity.  These dual-frequency radar measurements have similar frequencies to the GPM.
The High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) is a dual-frequency (Ka- and Ku-band) conical scan system, configured with a nadir viewing antenna on the high-altitude (20 km) NASA ER-2 aircraft.  It provides calibrated reflectivity and unfolded Doppler velocity.  These dual-frequency radar measurements have similar frequencies to the GPM.
The High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) is a dual-frequency (Ka- and Ku-band) conical scan system, configured with a nadir viewing antenna on the high-altitude (20 km) NASA ER-2 aircraft.  It provides calibrated reflectivity and unfolded Doppler velocity.  These dual-frequency radar measurements have similar frequencies to the GPM.
The Joss-Waldvogel (JW) disdrometer is an impact-type electromechanical counter designed to measure the drop size distribution (DSD).  This dataset provides rainfall data for the Global Precipitation Measurement (GPM) Mission Ground Validation Experiment collected at the National Space Science Technology Center (NSSTC), Huntsville, AL.  There may be occasional gaps in the data when the instrument is not resident at the NSSTC and is sent to participate in field campaigns.
The Joss-Waldvogel (JW) disdrometer is an impact-type electromechanical counter designed to measure the drop size distribution (DSD).  This dataset provides rainfall data for the Global Precipitation Measurement (GPM) Mission Ground Validation Experiment collected at the National Space Science Technology Center (NSSTC), Huntsville, AL.  There may be occasional gaps in the data when the instrument is not resident at the NSSTC and is sent to participate in field campaigns.
The Joss-Waldvogel (JW) disdrometer is an impact-type electromechanical counter designed to measure the drop size distribution (DSD).  This dataset provides rainfall data for the Global Precipitation Measurement (GPM) Mission Ground Validation Experiment collected at the National Space Science Technology Center (NSSTC), Huntsville, AL.  There may be occasional gaps in the data when the instrument is not resident at the NSSTC and is sent to participate in field campaigns.
The GPM Ground Validation McGill Vertical Pointing X-Band (VertiX) Radar GCPEx dataset was collected from January 15, 2012 to February 29, 2012 at the CARE site in Ontario, Canada as a part of the GPM Cold-season Precipitation Experiment (GCPEx).  The VertiX, a vertically pointing X-band radar, can detect all precipitation targets and some ice clouds.  The VertiX can also measure the Doppler velocity of precipitation targets.  The GPM Ground Validation McGill Vertical Pointing X-Band (VertiX) Radar GCPEx dataset is available in netCDF format.
The GPM Ground Validation McGill Vertical Pointing X-Band (VertiX) Radar GCPEx dataset was collected from January 15, 2012 to February 29, 2012 at the CARE site in Ontario, Canada as a part of the GPM Cold-season Precipitation Experiment (GCPEx).  The VertiX, a vertically pointing X-band radar, can detect all precipitation targets and some ice clouds.  The VertiX can also measure the Doppler velocity of precipitation targets.  The GPM Ground Validation McGill Vertical Pointing X-Band (VertiX) Radar GCPEx dataset is available in netCDF format.
The GPM Ground Validation McGill Vertical Pointing X-Band (VertiX) Radar GCPEx dataset was collected from January 15, 2012 to February 29, 2012 at the CARE site in Ontario, Canada as a part of the GPM Cold-season Precipitation Experiment (GCPEx).  The VertiX, a vertically pointing X-band radar, can detect all precipitation targets and some ice clouds.  The VertiX can also measure the Doppler velocity of precipitation targets.  The GPM Ground Validation McGill Vertical Pointing X-Band (VertiX) Radar GCPEx dataset is available in netCDF format.
The GPM Ground Validation McGill W-Band Radar GCPEx dataset was collected from February 1, 2012 to February 29, 2012 at the CARE site in Ontario, Canada as a part of the GPM Cold-season Precipitation Experiment (GCPEx).  The W-Band radar is a single antenna, 94-GHz pulsed Doppler, vertical pointing radar system.  Data products from the W-Band radar include radar reflectivity, Doppler moments, and Doppler spectra of variable lengths.  The W-Band radar is primarily used to research cloud properties.  The GPM Ground Validation McGill W-Band Radar GCPEx dataset is available in netCDF format.
The GPM Ground Validation McGill W-Band Radar GCPEx dataset was collected from February 1, 2012 to February 29, 2012 at the CARE site in Ontario, Canada as a part of the GPM Cold-season Precipitation Experiment (GCPEx).  The W-Band radar is a single antenna, 94-GHz pulsed Doppler, vertical pointing radar system.  Data products from the W-Band radar include radar reflectivity, Doppler moments, and Doppler spectra of variable lengths.  The W-Band radar is primarily used to research cloud properties.  The GPM Ground Validation McGill W-Band Radar GCPEx dataset is available in netCDF format.
The GPM Ground Validation McGill W-Band Radar GCPEx dataset was collected from February 1, 2012 to February 29, 2012 at the CARE site in Ontario, Canada as a part of the GPM Cold-season Precipitation Experiment (GCPEx).  The W-Band radar is a single antenna, 94-GHz pulsed Doppler, vertical pointing radar system.  Data products from the W-Band radar include radar reflectivity, Doppler moments, and Doppler spectra of variable lengths.  The W-Band radar is primarily used to research cloud properties.  The GPM Ground Validation McGill W-Band Radar GCPEx dataset is available in netCDF format.
Sixteen tipping bucket rain gauge pairs were deployed alongside each Autonomous Parsivel Unit (APU) during the Mid-latitude Continental Convective Cloud Experiment (MC3E) in northern Oklahoma.  Along with the disdrometers, these rain gauges provided an additional means for directly measuring rainfall during the MC3E campaign.  Two different models of these rain gauges, which are manufactured by MetOne Instruments, Inc., were used during MC3E.  The Model 380 gauges have a 30.5 cm diameter catchment funnel and a resolution of 0.2 mm of liquid water for each tip.  The Model 370 gauges have a 20.3 cm diameter catchment funnel and a resolution of 0.01 inches of liquid water for each tip.  The 0.2 mm resolution rain gauges were sited alongside APU01,02,10-16, whereas the 0.01 inches resolution rain gauges were sited alongside APU03-08.  The data for each rain gauge was collected at 1-minute intervals.  Data was collected from 22 April 2011 through 06 June 2011.
Sixteen tipping bucket rain gauge pairs were deployed alongside each Autonomous Parsivel Unit (APU) during the Mid-latitude Continental Convective Cloud Experiment (MC3E) in northern Oklahoma.  Along with the disdrometers, these rain gauges provided an additional means for directly measuring rainfall during the MC3E campaign.  Two different models of these rain gauges, which are manufactured by MetOne Instruments, Inc., were used during MC3E.  The Model 380 gauges have a 30.5 cm diameter catchment funnel and a resolution of 0.2 mm of liquid water for each tip.  The Model 370 gauges have a 20.3 cm diameter catchment funnel and a resolution of 0.01 inches of liquid water for each tip.  The 0.2 mm resolution rain gauges were sited alongside APU01,02,10-16, whereas the 0.01 inches resolution rain gauges were sited alongside APU03-08.  The data for each rain gauge was collected at 1-minute intervals.  Data was collected from 22 April 2011 through 06 June 2011.
Sixteen tipping bucket rain gauge pairs were deployed alongside each Autonomous Parsivel Unit (APU) during the Mid-latitude Continental Convective Cloud Experiment (MC3E) in northern Oklahoma.  Along with the disdrometers, these rain gauges provided an additional means for directly measuring rainfall during the MC3E campaign.  Two different models of these rain gauges, which are manufactured by MetOne Instruments, Inc., were used during MC3E.  The Model 380 gauges have a 30.5 cm diameter catchment funnel and a resolution of 0.2 mm of liquid water for each tip.  The Model 370 gauges have a 20.3 cm diameter catchment funnel and a resolution of 0.01 inches of liquid water for each tip.  The 0.2 mm resolution rain gauges were sited alongside APU01,02,10-16, whereas the 0.01 inches resolution rain gauges were sited alongside APU03-08.  The data for each rain gauge was collected at 1-minute intervals.  Data was collected from 22 April 2011 through 06 June 2011.
The GPM Ground Validation Meteorological Tower Environment Canada GCPEx dataset provides temperature, relative humidity, 10m winds, pressure and solar radiation data collected by a suite of standard meteorological instruments attached to a 10m met tower.  Browse images are available on-line.  The observation station was assembled by Automated Transportable Meteorological Observation Station (ATMOS).  Data was gathered over the Ontario region of Canada in 2012 from Jan 15 through March 1.
The GPM Ground Validation Meteorological Tower Environment Canada GCPEx dataset provides temperature, relative humidity, 10m winds, pressure and solar radiation data collected by a suite of standard meteorological instruments attached to a 10m met tower.  Browse images are available on-line.  The observation station was assembled by Automated Transportable Meteorological Observation Station (ATMOS).  Data was gathered over the Ontario region of Canada in 2012 from Jan 15 through March 1.
The GPM Ground Validation Meteorological Tower Environment Canada GCPEx dataset provides temperature, relative humidity, 10m winds, pressure and solar radiation data collected by a suite of standard meteorological instruments attached to a 10m met tower.  Browse images are available on-line.  The observation station was assembled by Automated Transportable Meteorological Observation Station (ATMOS).  Data was gathered over the Ontario region of Canada in 2012 from Jan 15 through March 1.
The MC3E ER-2 Navigation data files contain information recorded by an on board navigation recorder (NavRec).  In addition to typical navigation data (e.g. date, time, lat/lon and altitude) it contains outside meteorological parameters such as wind speed and direction and temperature.  These ASCII text files are recorded every second for the length of the sortie.  The Flight Summaries and Flight Track Imagery dataset which includes sonde maps, radar animation, 5-minute KICT track snapshots is distributed with this dataset.
The MC3E ER-2 Navigation data files contain information recorded by an on board navigation recorder (NavRec).  In addition to typical navigation data (e.g. date, time, lat/lon and altitude) it contains outside meteorological parameters such as wind speed and direction and temperature.  These ASCII text files are recorded every second for the length of the sortie.  The Flight Summaries and Flight Track Imagery dataset which includes sonde maps, radar animation, 5-minute KICT track snapshots is distributed with this dataset.
The MC3E ER-2 Navigation data files contain information recorded by an on board navigation recorder (NavRec).  In addition to typical navigation data (e.g. date, time, lat/lon and altitude) it contains outside meteorological parameters such as wind speed and direction and temperature.  These ASCII text files are recorded every second for the length of the sortie.  The Flight Summaries and Flight Track Imagery dataset which includes sonde maps, radar animation, 5-minute KICT track snapshots is distributed with this dataset.
The GPM Ground Validation NASA Micro Rain Radar (MRR) is a vertically pointing Doppler radar which provides measurements of vertical velocity, drop size distribution, rainfall rate, attenuation, liquid water content, and reflectivity factor obtained during the GPM Cold-season Precipitation Experiment (GCPEx), which took place in Canada during Winter 2011-2012.  The MRR is a frequency-modulated continuous wave (FMCW) vertically pointing Doppler radar, which operates at 24.24GHz, and it is the second generation of the instrument manufactured by METEK (http://www.metek.de/product-details/mrr-2.html).  NASA MRR data was collected from late October 2011 through March 2013.
The GPM Ground Validation NASA Micro Rain Radar (MRR) is a vertically pointing Doppler radar which provides measurements of vertical velocity, drop size distribution, rainfall rate, attenuation, liquid water content, and reflectivity factor obtained during the GPM Cold-season Precipitation Experiment (GCPEx), which took place in Canada during Winter 2011-2012.  The MRR is a frequency-modulated continuous wave (FMCW) vertically pointing Doppler radar, which operates at 24.24GHz, and it is the second generation of the instrument manufactured by METEK (http://www.metek.de/product-details/mrr-2.html).  NASA MRR data was collected from late October 2011 through March 2013.
The GPM Ground Validation NASA Micro Rain Radar (MRR) is a vertically pointing Doppler radar which provides measurements of vertical velocity, drop size distribution, rainfall rate, attenuation, liquid water content, and reflectivity factor obtained during the GPM Cold-season Precipitation Experiment (GCPEx), which took place in Canada during Winter 2011-2012.  The MRR is a frequency-modulated continuous wave (FMCW) vertically pointing Doppler radar, which operates at 24.24GHz, and it is the second generation of the instrument manufactured by METEK (http://www.metek.de/product-details/mrr-2.html).  NASA MRR data was collected from late October 2011 through March 2013.
The GPM Ground Validation Micro Rain Radar (MRR) is a vertically pointing Doppler radar which provides measurements of vertical velocity, drop size distribution, rainfall rate, attenuation, liquid water content, and reflectivity factor obtained during the Midlatitude Continental Convective Clouds Experiment (MC3E), which took place in Oklahoma during Spring 2011.  The MRR is a frequency-modulated continuous wave (FMCW) vertically pointing Doppler radar, which operates at 24.24GHz, and it is the second generation of the instrument manufactured by METEK (URL: http://www.metek.de/product-details/mrr-2.html).
The GPM Ground Validation Micro Rain Radar (MRR) is a vertically pointing Doppler radar which provides measurements of vertical velocity, drop size distribution, rainfall rate, attenuation, liquid water content, and reflectivity factor obtained during the Midlatitude Continental Convective Clouds Experiment (MC3E), which took place in Oklahoma during Spring 2011.  The MRR is a frequency-modulated continuous wave (FMCW) vertically pointing Doppler radar, which operates at 24.24GHz, and it is the second generation of the instrument manufactured by METEK (URL: http://www.metek.de/product-details/mrr-2.html).
The GPM Ground Validation Micro Rain Radar (MRR) is a vertically pointing Doppler radar which provides measurements of vertical velocity, drop size distribution, rainfall rate, attenuation, liquid water content, and reflectivity factor obtained during the Midlatitude Continental Convective Clouds Experiment (MC3E), which took place in Oklahoma during Spring 2011.  The MRR is a frequency-modulated continuous wave (FMCW) vertically pointing Doppler radar, which operates at 24.24GHz, and it is the second generation of the instrument manufactured by METEK (URL: http://www.metek.de/product-details/mrr-2.html).
The GPM Ground Validation NASA S-Band Dual Polarimetric (NPOL) Doppler Radar IFloodS data set was collected from April 30, 2013 to June 16, 2013 near Traer, Iowa as a part of the Global Precipitation Measurement Mission (GPM) Iowa Flood Studies (IFloodS) campaign.  The NASA NPOL radar, developed by a research team from Wallops Flight Facility, is a fully transportable and self-contained S-band (10 cm), scanning dual-polarimetric, Doppler research radar that collected and operated nearly continuously during the IFloodS field campaign.  The GPM Ground Validation NASA S-Band Dual Polarimetric (NPOL) Doppler Radar IFloodS data is available in Universal [Radar] Format (UF).
The GPM Ground Validation NASA S-Band Dual Polarimetric (NPOL) Doppler Radar IFloodS data set was collected from April 30, 2013 to June 16, 2013 near Traer, Iowa as a part of the Global Precipitation Measurement Mission (GPM) Iowa Flood Studies (IFloodS) campaign.  The NASA NPOL radar, developed by a research team from Wallops Flight Facility, is a fully transportable and self-contained S-band (10 cm), scanning dual-polarimetric, Doppler research radar that collected and operated nearly continuously during the IFloodS field campaign.  The GPM Ground Validation NASA S-Band Dual Polarimetric (NPOL) Doppler Radar IFloodS data is available in Universal [Radar] Format (UF).
The GPM Ground Validation NASA S-Band Dual Polarimetric (NPOL) Doppler Radar IFloodS data set was collected from April 30, 2013 to June 16, 2013 near Traer, Iowa as a part of the Global Precipitation Measurement Mission (GPM) Iowa Flood Studies (IFloodS) campaign.  The NASA NPOL radar, developed by a research team from Wallops Flight Facility, is a fully transportable and self-contained S-band (10 cm), scanning dual-polarimetric, Doppler research radar that collected and operated nearly continuously during the IFloodS field campaign.  The GPM Ground Validation NASA S-Band Dual Polarimetric (NPOL) Doppler Radar IFloodS data is available in Universal [Radar] Format (UF).
The NASA NPOL radar, developed by a research team from Wallops Flight Facility, is a fully transportable and self-contained S-band (10 cm), scanning dual-polarimetric, doppler research radar that collected and operated nearly continuously during the MC3E field campaign.  NPOL scanned in high resolution RHI mode (every 40 sec) and provided measurements of precipitation in liquid, mixed and ice phase.  The scanning strategy emphasized vertical structure sampling via RHI and narrow sector-volume data collections.  Additional files were processed from the UF files using the Colorado State University (CSU) Hydrometeor Identification Algorithm (HID) providing classification of hydrometeors (e.g. rain, drizzle, hail, ice crystals, wet or dry snow, graupel density).  Data was collected from 11 April 2011 through 03 June 2011.
The NASA NPOL radar, developed by a research team from Wallops Flight Facility, is a fully transportable and self-contained S-band (10 cm), scanning dual-polarimetric, doppler research radar that collected and operated nearly continuously during the MC3E field campaign.  NPOL scanned in high resolution RHI mode (every 40 sec) and provided measurements of precipitation in liquid, mixed and ice phase.  The scanning strategy emphasized vertical structure sampling via RHI and narrow sector-volume data collections.  Additional files were processed from the UF files using the Colorado State University (CSU) Hydrometeor Identification Algorithm (HID) providing classification of hydrometeors (e.g. rain, drizzle, hail, ice crystals, wet or dry snow, graupel density).  Data was collected from 11 April 2011 through 03 June 2011.
The NASA NPOL radar, developed by a research team from Wallops Flight Facility, is a fully transportable and self-contained S-band (10 cm), scanning dual-polarimetric, doppler research radar that collected and operated nearly continuously during the MC3E field campaign.  NPOL scanned in high resolution RHI mode (every 40 sec) and provided measurements of precipitation in liquid, mixed and ice phase.  The scanning strategy emphasized vertical structure sampling via RHI and narrow sector-volume data collections.  Additional files were processed from the UF files using the Colorado State University (CSU) Hydrometeor Identification Algorithm (HID) providing classification of hydrometeors (e.g. rain, drizzle, hail, ice crystals, wet or dry snow, graupel density).  Data was collected from 11 April 2011 through 03 June 2011.
The GPM Ground Validation NCAR Cloud Microphysics Particle Probes GCPEx dataset was obtained from three instruments carried aboard the University of North Dakota (UND) Cessna Citation aircraft.  These probes, the 2D-C, Cloud Imaging Probe (CIP) and High Volume Precipitation Spectrometer (HVPS-3), collected particle size distributions and particle images which were processed by NCAR.  Data were collected January 16, 2012 through February 25, 2012.  A related cloud microphysics dataset, GPM Ground Validation UND Citation Cloud Microphysics GCPEx is also available.
The GPM Ground Validation NCAR Cloud Microphysics Particle Probes GCPEx dataset was obtained from three instruments carried aboard the University of North Dakota (UND) Cessna Citation aircraft.  These probes, the 2D-C, Cloud Imaging Probe (CIP) and High Volume Precipitation Spectrometer (HVPS-3), collected particle size distributions and particle images which were processed by NCAR.  Data were collected January 16, 2012 through February 25, 2012.  A related cloud microphysics dataset, GPM Ground Validation UND Citation Cloud Microphysics GCPEx is also available.
The GPM Ground Validation NCAR Cloud Microphysics Particle Probes GCPEx dataset was obtained from three instruments carried aboard the University of North Dakota (UND) Cessna Citation aircraft.  These probes, the 2D-C, Cloud Imaging Probe (CIP) and High Volume Precipitation Spectrometer (HVPS-3), collected particle size distributions and particle images which were processed by NCAR.  Data were collected January 16, 2012 through February 25, 2012.  A related cloud microphysics dataset, GPM Ground Validation UND Citation Cloud Microphysics GCPEx is also available.
The GPM Ground Validation NCAR Cloud Microphysics Particle Probes MC3E dataset was obtained from three instruments carried aboard the University of North Dakota (UND) Cessna Citation aircraft.  These probes, the 2D-C, Cloud Imaging Probe (CIP) and  High Volume Precipitation Spectrometer (HVPS-3), collected particle size distributions and particle images which were processed by NCAR.  Data were collected April 22, 2011 through June 2, 2011.  A related cloud microphysics dataset, GPM Ground Validation UND Citation Cloud Microphysics MC3E, is also available.
The GPM Ground Validation NCAR Cloud Microphysics Particle Probes MC3E dataset was obtained from three instruments carried aboard the University of North Dakota (UND) Cessna Citation aircraft.  These probes, the 2D-C, Cloud Imaging Probe (CIP) and  High Volume Precipitation Spectrometer (HVPS-3), collected particle size distributions and particle images which were processed by NCAR.  Data were collected April 22, 2011 through June 2, 2011.  A related cloud microphysics dataset, GPM Ground Validation UND Citation Cloud Microphysics MC3E, is also available.
The GPM Ground Validation NCAR Cloud Microphysics Particle Probes MC3E dataset was obtained from three instruments carried aboard the University of North Dakota (UND) Cessna Citation aircraft.  These probes, the 2D-C, Cloud Imaging Probe (CIP) and  High Volume Precipitation Spectrometer (HVPS-3), collected particle size distributions and particle images which were processed by NCAR.  Data were collected April 22, 2011 through June 2, 2011.  A related cloud microphysics dataset, GPM Ground Validation UND Citation Cloud Microphysics MC3E, is also available.
The NOAA Parsivel data collected during the Midlatitude Continental Convective Clouds Experiment (MC3E) experiment in central Oklahoma contains moment data (reflectivity and rain rate estimates) or raindrop number concentration estimates.  This data provided a reference reflectivity to calibrate the S-band profiler during the experiment.
The NOAA Parsivel data collected during the Midlatitude Continental Convective Clouds Experiment (MC3E) experiment in central Oklahoma contains moment data (reflectivity and rain rate estimates) or raindrop number concentration estimates.  This data provided a reference reflectivity to calibrate the S-band profiler during the experiment.
The NOAA Parsivel data collected during the Midlatitude Continental Convective Clouds Experiment (MC3E) experiment in central Oklahoma contains moment data (reflectivity and rain rate estimates) or raindrop number concentration estimates.  This data provided a reference reflectivity to calibrate the S-band profiler during the experiment.
The S-band Profiler Minute Dwell dataset in the netCDF format was gathered during the Midlatitude Continental Convective Clouds Experiment (MC3E) in Oklahoma April-June 2011.  The S-band 2.8 GHz profiler measures the backscattered power from raindrops and ice particles as precipitating cloud systems pass overhead.  After calibration, the instrument will provide an unattenuated reflectivity estimate through the precipitation.  Spectra and moment files are included.
The S-band Profiler Minute Dwell dataset in the netCDF format was gathered during the Midlatitude Continental Convective Clouds Experiment (MC3E) in Oklahoma April-June 2011.  The S-band 2.8 GHz profiler measures the backscattered power from raindrops and ice particles as precipitating cloud systems pass overhead.  After calibration, the instrument will provide an unattenuated reflectivity estimate through the precipitation.  Spectra and moment files are included.
The S-band Profiler Minute Dwell dataset in the netCDF format was gathered during the Midlatitude Continental Convective Clouds Experiment (MC3E) in Oklahoma April-June 2011.  The S-band 2.8 GHz profiler measures the backscattered power from raindrops and ice particles as precipitating cloud systems pass overhead.  After calibration, the instrument will provide an unattenuated reflectivity estimate through the precipitation.  Spectra and moment files are included.
The S-band Profiler Original Dwell dataset in the netCDF format was gathered during the Midlatitude Continental Convective Clouds Experiment (MC3E) in Oklahoma April-June 2011.  The S-band profiler operates at 2.8 GHz, points vertically, and measures the backscattered power from raindrops and ice particles as precipitating cloud systems pass overhead.  The S-band operated in two modes: precipitation mode and attenuated mode.  The precipitation mode was the normal or full-power mode, and the attenuated mode was the low-power mode.  The profiler alternated between modes collecting either 7 or 9 consecutive precipitation mode profiles separated by 1 attenuated mode profile.  Both modes processed radar pulses collected during a 7-second dwell before calculating the Doppler velocity spectra at each radar range gate that were separated by 60-meters in the vertical.  The attenuated and precipitation mode data are available in moment, pop spectra (uncalibrated raw spectra) and calibrated spectra hourly files.  The S-band spectra were calibrated against the surface disdrometer to determine a radar calibration constant.  Calibrated spectra were constructed for each profile and are expressed as reflectivity spectral density.  After calibration, the instrument provides a reflectivity estimate through the precipitation.  Data is in hourly files in the netCDF format.
The S-band Profiler Original Dwell dataset in the netCDF format was gathered during the Midlatitude Continental Convective Clouds Experiment (MC3E) in Oklahoma April-June 2011.  The S-band profiler operates at 2.8 GHz, points vertically, and measures the backscattered power from raindrops and ice particles as precipitating cloud systems pass overhead.  The S-band operated in two modes: precipitation mode and attenuated mode.  The precipitation mode was the normal or full-power mode, and the attenuated mode was the low-power mode.  The profiler alternated between modes collecting either 7 or 9 consecutive precipitation mode profiles separated by 1 attenuated mode profile.  Both modes processed radar pulses collected during a 7-second dwell before calculating the Doppler velocity spectra at each radar range gate that were separated by 60-meters in the vertical.  The attenuated and precipitation mode data are available in moment, pop spectra (uncalibrated raw spectra) and calibrated spectra hourly files.  The S-band spectra were calibrated against the surface disdrometer to determine a radar calibration constant.  Calibrated spectra were constructed for each profile and are expressed as reflectivity spectral density.  After calibration, the instrument provides a reflectivity estimate through the precipitation.  Data is in hourly files in the netCDF format.
The S-band Profiler Original Dwell dataset in the netCDF format was gathered during the Midlatitude Continental Convective Clouds Experiment (MC3E) in Oklahoma April-June 2011.  The S-band profiler operates at 2.8 GHz, points vertically, and measures the backscattered power from raindrops and ice particles as precipitating cloud systems pass overhead.  The S-band operated in two modes: precipitation mode and attenuated mode.  The precipitation mode was the normal or full-power mode, and the attenuated mode was the low-power mode.  The profiler alternated between modes collecting either 7 or 9 consecutive precipitation mode profiles separated by 1 attenuated mode profile.  Both modes processed radar pulses collected during a 7-second dwell before calculating the Doppler velocity spectra at each radar range gate that were separated by 60-meters in the vertical.  The attenuated and precipitation mode data are available in moment, pop spectra (uncalibrated raw spectra) and calibrated spectra hourly files.  The S-band spectra were calibrated against the surface disdrometer to determine a radar calibration constant.  Calibrated spectra were constructed for each profile and are expressed as reflectivity spectral density.  After calibration, the instrument provides a reflectivity estimate through the precipitation.  Data is in hourly files in the netCDF format.
The S-band Profiler Raw dataset was saved in two data formats: netCDF anda proprietary Vaisala SPC format. The numeric values in both formats are exactly the same.  The S-band Profiler Raw dataset in the netCDF format was gathered during the Midlatitude Continental Convective Clouds Experiment (MC3E) in Oklahoma April-June 2011 and consists of uncalibrated Doppler velocity spectra data in units of relative power return.  The S-band 2.8 GHz profiler points vertically and measures the backscattered power from raindrops and ice particles as precipitating cloud systems pass overhead.  The profiler processes radar pulses during a 7-second dwell before calculating and saving uncalibrated Doppler velocity spectra at each range gate that were separated by 60-meters in the vertical.  Data collected during each hour are saved in two files.  All precipitation mode profiles are saved in one hourly data file and all attenuated mode profiles are saved in another hourly data file.  After calibration, calibrated data can be obtained from the S-band Original Dwell and Minute datasets.
The S-band Profiler Raw dataset was saved in two data formats: netCDF anda proprietary Vaisala SPC format. The numeric values in both formats are exactly the same.  The S-band Profiler Raw dataset in the netCDF format was gathered during the Midlatitude Continental Convective Clouds Experiment (MC3E) in Oklahoma April-June 2011 and consists of uncalibrated Doppler velocity spectra data in units of relative power return.  The S-band 2.8 GHz profiler points vertically and measures the backscattered power from raindrops and ice particles as precipitating cloud systems pass overhead.  The profiler processes radar pulses during a 7-second dwell before calculating and saving uncalibrated Doppler velocity spectra at each range gate that were separated by 60-meters in the vertical.  Data collected during each hour are saved in two files.  All precipitation mode profiles are saved in one hourly data file and all attenuated mode profiles are saved in another hourly data file.  After calibration, calibrated data can be obtained from the S-band Original Dwell and Minute datasets.
The S-band Profiler Raw dataset was saved in two data formats: netCDF anda proprietary Vaisala SPC format. The numeric values in both formats are exactly the same.  The S-band Profiler Raw dataset in the netCDF format was gathered during the Midlatitude Continental Convective Clouds Experiment (MC3E) in Oklahoma April-June 2011 and consists of uncalibrated Doppler velocity spectra data in units of relative power return.  The S-band 2.8 GHz profiler points vertically and measures the backscattered power from raindrops and ice particles as precipitating cloud systems pass overhead.  The profiler processes radar pulses during a 7-second dwell before calculating and saving uncalibrated Doppler velocity spectra at each range gate that were separated by 60-meters in the vertical.  Data collected during each hour are saved in two files.  All precipitation mode profiles are saved in one hourly data file and all attenuated mode profiles are saved in another hourly data file.  After calibration, calibrated data can be obtained from the S-band Original Dwell and Minute datasets.
The S-band Profiler Raw dataset was saved in two data formats: netCDF and a proprietary Vaisala SPC format.  The numeric values in both formats are exactly the same.  The S-band Profiler Raw dataset in the proprietary Vaisala SPC format was gathered during the Midlatitude Continental Convective Clouds Experiment (MC3E) in Oklahoma April-June 2011 and consists of uncalibrated Doppler velocity spectra data in units of relative power return.  The S-band 2.8 GHz profiler points vertically and measures the backscattered power from raindrops and ice particles as precipitating cloud systems pass overhead.  The profiler processes radar pulses during a 7-second dwell before calculating and saving uncalibrated Doppler velocity spectra at each range gate that were separated by 60-meters in the vertical.  Data collected during each hour are saved in two files.  All precipitation mode profiles are saved in one hourly data file and all attenuated mode profiles are saved in another hourly data file.  After calibration, calibrated data can be obtained from the S-band Original Dwell and Minute datasets.  Specialized read software may be purchased from Vaisala.
The S-band Profiler Raw dataset was saved in two data formats: netCDF and a proprietary Vaisala SPC format.  The numeric values in both formats are exactly the same.  The S-band Profiler Raw dataset in the proprietary Vaisala SPC format was gathered during the Midlatitude Continental Convective Clouds Experiment (MC3E) in Oklahoma April-June 2011 and consists of uncalibrated Doppler velocity spectra data in units of relative power return.  The S-band 2.8 GHz profiler points vertically and measures the backscattered power from raindrops and ice particles as precipitating cloud systems pass overhead.  The profiler processes radar pulses during a 7-second dwell before calculating and saving uncalibrated Doppler velocity spectra at each range gate that were separated by 60-meters in the vertical.  Data collected during each hour are saved in two files.  All precipitation mode profiles are saved in one hourly data file and all attenuated mode profiles are saved in another hourly data file.  After calibration, calibrated data can be obtained from the S-band Original Dwell and Minute datasets.  Specialized read software may be purchased from Vaisala.
The S-band Profiler Raw dataset was saved in two data formats: netCDF and a proprietary Vaisala SPC format.  The numeric values in both formats are exactly the same.  The S-band Profiler Raw dataset in the proprietary Vaisala SPC format was gathered during the Midlatitude Continental Convective Clouds Experiment (MC3E) in Oklahoma April-June 2011 and consists of uncalibrated Doppler velocity spectra data in units of relative power return.  The S-band 2.8 GHz profiler points vertically and measures the backscattered power from raindrops and ice particles as precipitating cloud systems pass overhead.  The profiler processes radar pulses during a 7-second dwell before calculating and saving uncalibrated Doppler velocity spectra at each range gate that were separated by 60-meters in the vertical.  Data collected during each hour are saved in two files.  All precipitation mode profiles are saved in one hourly data file and all attenuated mode profiles are saved in another hourly data file.  After calibration, calibrated data can be obtained from the S-band Original Dwell and Minute datasets.  Specialized read software may be purchased from Vaisala.
The Surface Meteorological station collected at the NOAA Southern Great Plains Facility for the Midlatitude Continental Convective Clouds Experiment (MC3E) and includes wind speed and direction, temperature and humidity, and precipitation.  The instruments gathering this data were respectively a propeller wind monitor located 10 meters above the ground, a temperature and humidity sensor at the ground, and a tipping rain gauge at the ground.
The Surface Meteorological station collected at the NOAA Southern Great Plains Facility for the Midlatitude Continental Convective Clouds Experiment (MC3E) and includes wind speed and direction, temperature and humidity, and precipitation.  The instruments gathering this data were respectively a propeller wind monitor located 10 meters above the ground, a temperature and humidity sensor at the ground, and a tipping rain gauge at the ground.
The Surface Meteorological station collected at the NOAA Southern Great Plains Facility for the Midlatitude Continental Convective Clouds Experiment (MC3E) and includes wind speed and direction, temperature and humidity, and precipitation.  The instruments gathering this data were respectively a propeller wind monitor located 10 meters above the ground, a temperature and humidity sensor at the ground, and a tipping rain gauge at the ground.
The NOAA UHF 449 Profiler data was collected during the NASA supported Midlatitude Continental Convective Clouds Experiment (MC3E).  The Ultra High Frequency 449 MHz profiler was one of three NOAA deployed instruments which also included a Parsivel and a 2.8 GHz profiler (S-Band).  The 449 MHz profiler raw data files provide estimates of the vertical air motion during precipitation from near the surface to just below the freezing level.  Used together with the S-band profiler, vertical profiles of raindrop size distributions can be retrieved.  The raw 449MGx profiler data consists of uncalibrated Doppler velocity spectra data in units of relative power return.
The NOAA UHF 449 Profiler data was collected during the NASA supported Midlatitude Continental Convective Clouds Experiment (MC3E).  The Ultra High Frequency 449 MHz profiler was one of three NOAA deployed instruments which also included a Parsivel and a 2.8 GHz profiler (S-Band).  The 449 MHz profiler raw data files provide estimates of the vertical air motion during precipitation from near the surface to just below the freezing level.  Used together with the S-band profiler, vertical profiles of raindrop size distributions can be retrieved.  The raw 449MGx profiler data consists of uncalibrated Doppler velocity spectra data in units of relative power return.
The NOAA UHF 449 Profiler data was collected during the NASA supported Midlatitude Continental Convective Clouds Experiment (MC3E).  The Ultra High Frequency 449 MHz profiler was one of three NOAA deployed instruments which also included a Parsivel and a 2.8 GHz profiler (S-Band).  The 449 MHz profiler raw data files provide estimates of the vertical air motion during precipitation from near the surface to just below the freezing level.  Used together with the S-band profiler, vertical profiles of raindrop size distributions can be retrieved.  The raw 449MGx profiler data consists of uncalibrated Doppler velocity spectra data in units of relative power return.
The NOAA UHF 449 Profiler Raw SPC foramt data was collected during the NASA supported Midlatitude Continental Convective Clouds Experiment (MC3E).  The Ultra High Frequency 449 MHz profiler was one of three NOAA deployed instruments which also included a Parsivel and a 2.8 GHz profiler (S-Band).  The 449 MHz profiler raw data files provide estimates of the vertical air motion during precipitation from near the surface to just below the freezing level.  The raw 449MGx profiler data consists of uncalibrated Doppler velocity spectra data in units of relative power return.  The SPC format requires specialized read software which can be purchased from Vaisala.  The same data in netCDF format can be acquired by ordering the "GPM Ground Validation NOAA UHF 449 Profiler MC3E" dataset.
The GPM Ground Validation Oklahoma Climatological Survey Mesonet MC3E data were collected during the Midlatitude Continental Convective Clouds Experiment (MC3E) in central Oklahoma during the April-June 2011 period.  Collected by a network of weather stations, this dataset is composed of 15 minute and 5 minute files with one file per site per day in mts format.  Data can be read as ASCII text.  Multiple parameters found in this dataset include relative humidity, air temperature, wind speed and direction, precipitation and calibrated soil moisture.  More information on the contents and data format can be found at http://www.mesonet.org/index.php/site/about/mdf_mts_files.
The GPM Ground Validation Oklahoma Climatological Survey Mesonet MC3E data were collected during the Midlatitude Continental Convective Clouds Experiment (MC3E) in central Oklahoma during the April-June 2011 period.  Collected by a network of weather stations, this dataset is composed of 15 minute and 5 minute files with one file per site per day in mts format.  Data can be read as ASCII text.  Multiple parameters found in this dataset include relative humidity, air temperature, wind speed and direction, precipitation and calibrated soil moisture.  More information on the contents and data format can be found at http://www.mesonet.org/index.php/site/about/mdf_mts_files.
The GPM Ground Validation Oklahoma Climatological Survey Mesonet MC3E data were collected during the Midlatitude Continental Convective Clouds Experiment (MC3E) in central Oklahoma during the April-June 2011 period.  Collected by a network of weather stations, this dataset is composed of 15 minute and 5 minute files with one file per site per day in mts format.  Data can be read as ASCII text.  Multiple parameters found in this dataset include relative humidity, air temperature, wind speed and direction, precipitation and calibrated soil moisture.  More information on the contents and data format can be found at http://www.mesonet.org/index.php/site/about/mdf_mts_files.
The Pawnee radar data for the Midlatitude Continental Convective Clouds Experiment (MC3E) held in Oklahoma were collected on May 24, 2011 to support the CHILL radar and the NASA ER-2 instrumentation data.  The Pawnee is a single polarization (V polarization) Doppler radar which was located at approx. azimuth 352 deg / range 48 km with respect to CHILL.  The half-power antenna pattern main lobe beamwidth is ~1.8 degrees.  During the ER2 flight, the Pawnee conducted a wide azimuth opening PPI sector volume scan oriented towards the east designed to provide general 3D coverage of the ER2 flight area.  When the ER2 reported starting a course reversal; the CHILL and Pawnee radars attempted to start sector scans at the same time to support dual Doppler wind analyses.  In an effort to expand the MC3E sampling to a wider geographical area, the NASA ER2 aircraft was directed to Northeastern Colorado while widespread rain was in progress on May 24 2011.  The aircraft flew a series of pre-defined ground tracks that coincided with radials from the CSU-CHILL radar.  This aided in keeping the aircraft in the plane of a series of RHI scans done by CSU-CHILL.  The single polarization CSU-Pawnee radar maintained volume coverage of the echo system while the radial flight legs were in progress.  During aircraft course reversals at the ends of the radial legs, the CHILL and Pawnee radars started volume scans in synchronization to support dual Doppler wind syntheses.  CHILL and Pawnee radar data are available as separate datasets.
The Pawnee radar data for the Midlatitude Continental Convective Clouds Experiment (MC3E) held in Oklahoma were collected on May 24, 2011 to support the CHILL radar and the NASA ER-2 instrumentation data.  The Pawnee is a single polarization (V polarization) Doppler radar which was located at approx. azimuth 352 deg / range 48 km with respect to CHILL.  The half-power antenna pattern main lobe beamwidth is ~1.8 degrees.  During the ER2 flight, the Pawnee conducted a wide azimuth opening PPI sector volume scan oriented towards the east designed to provide general 3D coverage of the ER2 flight area.  When the ER2 reported starting a course reversal; the CHILL and Pawnee radars attempted to start sector scans at the same time to support dual Doppler wind analyses.  In an effort to expand the MC3E sampling to a wider geographical area, the NASA ER2 aircraft was directed to Northeastern Colorado while widespread rain was in progress on May 24 2011.  The aircraft flew a series of pre-defined ground tracks that coincided with radials from the CSU-CHILL radar.  This aided in keeping the aircraft in the plane of a series of RHI scans done by CSU-CHILL.  The single polarization CSU-Pawnee radar maintained volume coverage of the echo system while the radial flight legs were in progress.  During aircraft course reversals at the ends of the radial legs, the CHILL and Pawnee radars started volume scans in synchronization to support dual Doppler wind syntheses.  CHILL and Pawnee radar data are available as separate datasets.
The Pawnee radar data for the Midlatitude Continental Convective Clouds Experiment (MC3E) held in Oklahoma were collected on May 24, 2011 to support the CHILL radar and the NASA ER-2 instrumentation data.  The Pawnee is a single polarization (V polarization) Doppler radar which was located at approx. azimuth 352 deg / range 48 km with respect to CHILL.  The half-power antenna pattern main lobe beamwidth is ~1.8 degrees.  During the ER2 flight, the Pawnee conducted a wide azimuth opening PPI sector volume scan oriented towards the east designed to provide general 3D coverage of the ER2 flight area.  When the ER2 reported starting a course reversal; the CHILL and Pawnee radars attempted to start sector scans at the same time to support dual Doppler wind analyses.  In an effort to expand the MC3E sampling to a wider geographical area, the NASA ER2 aircraft was directed to Northeastern Colorado while widespread rain was in progress on May 24 2011.  The aircraft flew a series of pre-defined ground tracks that coincided with radials from the CSU-CHILL radar.  This aided in keeping the aircraft in the plane of a series of RHI scans done by CSU-CHILL.  The single polarization CSU-Pawnee radar maintained volume coverage of the echo system while the radial flight legs were in progress.  During aircraft course reversals at the ends of the radial legs, the CHILL and Pawnee radars started volume scans in synchronization to support dual Doppler wind syntheses.  CHILL and Pawnee radar data are available as separate datasets.
The Pluvio rain gauge dataset contains both one minute measurement and a cumulative record of the accumulation and intensity for liquid, solid, and mixed precipitation collected during the GPM Cold-season Precipitation Experiment (GCPEx).  GCPEx took place in Ontario, Canada during the Winter season December 2011 - February 2012 where data was collected at five sites: CARE, Huronia, Steamshow, Skydive and Morton.  The new generation Pluvio was designed by OTT Hydromet in Kempten, Germany.
The Pluvio rain gauge dataset contains both one minute measurement and a cumulative record of the accumulation and intensity for liquid, solid, and mixed precipitation collected during the GPM Cold-season Precipitation Experiment (GCPEx).  GCPEx took place in Ontario, Canada during the Winter season December 2011 - February 2012 where data was collected at five sites: CARE, Huronia, Steamshow, Skydive and Morton.  The new generation Pluvio was designed by OTT Hydromet in Kempten, Germany.
The Pluvio rain gauge dataset contains both one minute measurement and a cumulative record of the accumulation and intensity for liquid, solid, and mixed precipitation collected during the GPM Cold-season Precipitation Experiment (GCPEx).  GCPEx took place in Ontario, Canada during the Winter season December 2011 - February 2012 where data was collected at five sites: CARE, Huronia, Steamshow, Skydive and Morton.  The new generation Pluvio was designed by OTT Hydromet in Kempten, Germany.
The Pluvio rain gauge dataset contains both one minute measurement and a cumluative record of the accumulation and intensity for liquid, solid, and mixed precipitation collected during the Light Precipitation Experiment (LPVEx), part of Global Precipitation Measurement (GPM) Misson Ground Validation Experiment, LPVEx took place in Finland during September-October 2010 where data was collected at three sites: Harmaja, Emasalo, and Jarvenpaa.  The new generation Pluvio was designed by OTT Hydromet in Kempten, Germany.
The Pluvio rain gauge dataset contains both one minute measurement and a cumluative record of the accumulation and intensity for liquid, solid, and mixed precipitation collected during the Light Precipitation Experiment (LPVEx), part of Global Precipitation Measurement (GPM) Misson Ground Validation Experiment, LPVEx took place in Finland during September-October 2010 where data was collected at three sites: Harmaja, Emasalo, and Jarvenpaa.  The new generation Pluvio was designed by OTT Hydromet in Kempten, Germany.
The Pluvio rain gauge dataset contains both one minute measurement and a cumluative record of the accumulation and intensity for liquid, solid, and mixed precipitation collected during the Light Precipitation Experiment (LPVEx), part of Global Precipitation Measurement (GPM) Misson Ground Validation Experiment, LPVEx took place in Finland during September-October 2010 where data was collected at three sites: Harmaja, Emasalo, and Jarvenpaa.  The new generation Pluvio was designed by OTT Hydromet in Kempten, Germany.
The Precipitation Video Imager (PVI) collected precipitation particle images and drop size distribution data during November 2011 through March 2012 as part of the GPM Cold-season Precipitation Experiment (GCPEx) which occurred in Ontario, Canada.  Data files in an excel format contain the average, minimum and logarithmic DSD bin sizes and number of particles per unit time.  Browse images are available online.  The PVI instrument was designed by Dr. Larry Bliven at NASA Wallops Flight Facility.
The Precipitation Video Imager (PVI) collected precipitation particle images and drop size distribution data during November 2011 through March 2012 as part of the GPM Cold-season Precipitation Experiment (GCPEx) which occurred in Ontario, Canada.  Data files in an excel format contain the average, minimum and logarithmic DSD bin sizes and number of particles per unit time.  Browse images are available online.  The PVI instrument was designed by Dr. Larry Bliven at NASA Wallops Flight Facility.
The Precipitation Video Imager (PVI) collected precipitation particle images and drop size distribution data during November 2011 through March 2012 as part of the GPM Cold-season Precipitation Experiment (GCPEx) which occurred in Ontario, Canada.  Data files in an excel format contain the average, minimum and logarithmic DSD bin sizes and number of particles per unit time.  Browse images are available online.  The PVI instrument was designed by Dr. Larry Bliven at NASA Wallops Flight Facility.
The Satellite Simulator database is available for several campaigns: Light Precipitation Evaluation Experiment (LPVEX), Midlatitude Continental Convective Clouds Experiment (MC3E), Tropical Warm Pool - International Cloud Experiment (TWP-ICE) and Canadian Cloudsat/Calipso Validation Project (C3VP).  The Orbital database takes account for the atmospheric profiles, the cloud/rain profiles, and the detailed surface/terrain information from the Cloud-Resolving Model (CRM) database.  Unique geometry and antenna gain patters of each sensor (GMI imager, GMI sounder, DPR Ku, DPR Ka_MA, DPR Ka_HS) are considered.  The Orbital database consists of satellite orbit parameters, geolocation of IFOV/EFOV and satellite location, and simulated L1B/L2-like parameters in satellite orbital grid.  Orbital data covers a portion of sampling right over the Cloud-resolving model (CRM) domain. All orbital data format is NetCDF3, and it contains dimensions, parameter descriptions, and parameter units. Each project's data  is distributed as a separate dataset.   MC3E occurred in Oklahoma, USA in 2011;  LPVEX took place in Finland in  2010; C3VP experiment was held in Canada in 2007 and TWP-ICE took place in Australia in 2006.
The Satellite Simulator database is available for several campaigns: Light Precipitation Evaluation Experiment (LPVEX), Midlatitude Continental Convective Clouds Experiment (MC3E), Tropical Warm Pool - International Cloud Experiment (TWP-ICE) and Canadian Cloudsat/Calipso Validation Project (C3VP).  The Orbital database takes account for the atmospheric profiles, the cloud/rain profiles, and the detailed surface/terrain information from the Cloud-Resolving Model (CRM) database.  Unique geometry and antenna gain patters of each sensor (GMI imager, GMI sounder, DPR Ku, DPR Ka_MA, DPR Ka_HS) are considered.  The Orbital database consists of satellite orbit parameters, geolocation of IFOV/EFOV and satellite location, and simulated L1B/L2-like parameters in satellite orbital grid.  Orbital data covers a portion of sampling right over the Cloud-resolving model (CRM) domain. All orbital data format is NetCDF3, and it contains dimensions, parameter descriptions, and parameter units. Each project's data  is distributed as a separate dataset.   MC3E occurred in Oklahoma, USA in 2011;  LPVEX took place in Finland in  2010; C3VP experiment was held in Canada in 2007 and TWP-ICE took place in Australia in 2006.
The Satellite Simulator database is available for several campaigns: Light Precipitation Evaluation Experiment (LPVEX), Midlatitude Continental Convective Clouds Experiment (MC3E), Tropical Warm Pool - International Cloud Experiment (TWP-ICE) and Canadian Cloudsat/Calipso Validation Project (C3VP).  The Orbital database takes account for the atmospheric profiles, the cloud/rain profiles, and the detailed surface/terrain information from the Cloud-Resolving Model (CRM) database.  Unique geometry and antenna gain patters of each sensor (GMI imager, GMI sounder, DPR Ku, DPR Ka_MA, DPR Ka_HS) are considered.  The Orbital database consists of satellite orbit parameters, geolocation of IFOV/EFOV and satellite location, and simulated L1B/L2-like parameters in satellite orbital grid.  Orbital data covers a portion of sampling right over the Cloud-resolving model (CRM) domain. All orbital data format is NetCDF3, and it contains dimensions, parameter descriptions, and parameter units. Each project's data  is distributed as a separate dataset.   MC3E occurred in Oklahoma, USA in 2011;  LPVEX took place in Finland in  2010; C3VP experiment was held in Canada in 2007 and TWP-ICE took place in Australia in 2006.
The Satellite Simulator database is available for several campaigns: Light Precipitation Evaluation Experiment (LPVEX), Midlatitude Continental Convective Clouds Experiment (MC3E), Tropical Warm Pool - International Cloud Experiment (TWP-ICE) and Canadian Cloudsat/Calipso Validation Project (C3VP).  The Orbital database takes account for the atmospheric profiles, the cloud/rain profiles, and the detailed surface/terrain information from the Cloud-Resolving Model (CRM) database.  Unique geometry and antenna gain patters of each sensor (GMI imager, GMI sounder, DPR Ku, DPR Ka_MA, DPR Ka_HS) are considered.  The Orbital database consists of satellite orbit parameters, geolocation of IFOV/EFOV and satellite location, and simulated L1B/L2-like parameters in satellite orbital grid.  Orbital data covers a portion of sampling right over the Cloud-resolving model (CRM) domain. All orbital data format is NetCDF3, and it contains dimensions, parameter descriptions, and parameter units. Each project's data  is distributed as a separate dataset.   MC3E occurred in Oklahoma, USA in 2011;  LPVEX took place in Finland in  2010; C3VP experiment was held in Canada in 2007 and TWP-ICE took place in Australia in 2006.
The Satellite Simulator database is available for several campaigns: Light Precipitation Evaluation Experiment (LPVEX), Midlatitude Continental Convective Clouds Experiment (MC3E), Tropical Warm Pool - International Cloud Experiment (TWP-ICE) and Canadian Cloudsat/Calipso Validation Project (C3VP).  The Orbital database takes account for the atmospheric profiles, the cloud/rain profiles, and the detailed surface/terrain information from the Cloud-Resolving Model (CRM) database.  Unique geometry and antenna gain patters of each sensor (GMI imager, GMI sounder, DPR Ku, DPR Ka_MA, DPR Ka_HS) are considered.  The Orbital database consists of satellite orbit parameters, geolocation of IFOV/EFOV and satellite location, and simulated L1B/L2-like parameters in satellite orbital grid.  Orbital data covers a portion of sampling right over the Cloud-resolving model (CRM) domain. All orbital data format is NetCDF3, and it contains dimensions, parameter descriptions, and parameter units. Each project's data  is distributed as a separate dataset.   MC3E occurred in Oklahoma, USA in 2011;  LPVEX took place in Finland in  2010; C3VP experiment was held in Canada in 2007 and TWP-ICE took place in Australia in 2006.
The Satellite Simulator database is available for several campaigns: Light Precipitation Evaluation Experiment (LPVEX), Midlatitude Continental Convective Clouds Experiment (MC3E), Tropical Warm Pool - International Cloud Experiment (TWP-ICE) and Canadian Cloudsat/Calipso Validation Project (C3VP).  The Orbital database takes account for the atmospheric profiles, the cloud/rain profiles, and the detailed surface/terrain information from the Cloud-Resolving Model (CRM) database.  Unique geometry and antenna gain patters of each sensor (GMI imager, GMI sounder, DPR Ku, DPR Ka_MA, DPR Ka_HS) are considered.  The Orbital database consists of satellite orbit parameters, geolocation of IFOV/EFOV and satellite location, and simulated L1B/L2-like parameters in satellite orbital grid.  Orbital data covers a portion of sampling right over the Cloud-resolving model (CRM) domain. All orbital data format is NetCDF3, and it contains dimensions, parameter descriptions, and parameter units. Each project's data  is distributed as a separate dataset.   MC3E occurred in Oklahoma, USA in 2011;  LPVEX took place in Finland in  2010; C3VP experiment was held in Canada in 2007 and TWP-ICE took place in Australia in 2006.
The Satellite Simulator database is available for several campaigns: Light Precipitation Evaluation Experiment (LPVEX), Midlatitude Continental Convective Clouds Experiment (MC3E), Tropical Warm Pool - International Cloud Experiment (TWP-ICE) and Canadian Cloudsat/Calipso Validation Project (C3VP).  The Orbital database takes account for the atmospheric profiles, the cloud/rain profiles, and the detailed surface/terrain information from the Cloud-Resolving Model (CRM) database.  Unique geometry and antenna gain patters of each sensor (GMI imager, GMI sounder, DPR Ku, DPR Ka_MA, DPR Ka_HS) are considered.  The Orbital database consists of satellite orbit parameters, geolocation of IFOV/EFOV and satellite location, and simulated L1B/L2-like parameters in satellite orbital grid.  Orbital data covers a portion of sampling right over the Cloud-resolving model (CRM) domain. All orbital data format is NetCDF3, and it contains dimensions, parameter descriptions, and parameter units. Each project's data  is distributed as a separate dataset.   MC3E occurred in Oklahoma, USA in 2011;  LPVEX took place in Finland in  2010; C3VP experiment was held in Canada in 2007 and TWP-ICE took place in Australia in 2006.
The Satellite Simulator database is available for several campaigns: Light Precipitation Evaluation Experiment (LPVEX), Midlatitude Continental Convective Clouds Experiment (MC3E), Tropical Warm Pool - International Cloud Experiment (TWP-ICE) and Canadian Cloudsat/Calipso Validation Project (C3VP).  The Orbital database takes account for the atmospheric profiles, the cloud/rain profiles, and the detailed surface/terrain information from the Cloud-Resolving Model (CRM) database.  Unique geometry and antenna gain patters of each sensor (GMI imager, GMI sounder, DPR Ku, DPR Ka_MA, DPR Ka_HS) are considered.  The Orbital database consists of satellite orbit parameters, geolocation of IFOV/EFOV and satellite location, and simulated L1B/L2-like parameters in satellite orbital grid.  Orbital data covers a portion of sampling right over the Cloud-resolving model (CRM) domain. All orbital data format is NetCDF3, and it contains dimensions, parameter descriptions, and parameter units. Each project's data  is distributed as a separate dataset.   MC3E occurred in Oklahoma, USA in 2011;  LPVEX took place in Finland in  2010; C3VP experiment was held in Canada in 2007 and TWP-ICE took place in Australia in 2006.
The Satellite Simulator database is available for several campaigns: Light Precipitation Evaluation Experiment (LPVEX), Midlatitude Continental Convective Clouds Experiment (MC3E), Tropical Warm Pool - International Cloud Experiment (TWP-ICE) and Canadian Cloudsat/Calipso Validation Project (C3VP).  The Orbital database takes account for the atmospheric profiles, the cloud/rain profiles, and the detailed surface/terrain information from the Cloud-Resolving Model (CRM) database.  Unique geometry and antenna gain patters of each sensor (GMI imager, GMI sounder, DPR Ku, DPR Ka_MA, DPR Ka_HS) are considered.  The Orbital database consists of satellite orbit parameters, geolocation of IFOV/EFOV and satellite location, and simulated L1B/L2-like parameters in satellite orbital grid.  Orbital data covers a portion of sampling right over the Cloud-resolving model (CRM) domain. All orbital data format is NetCDF3, and it contains dimensions, parameter descriptions, and parameter units. Each project's data  is distributed as a separate dataset.   MC3E occurred in Oklahoma, USA in 2011;  LPVEX took place in Finland in  2010; C3VP experiment was held in Canada in 2007 and TWP-ICE took place in Australia in 2006.
The Satellite Simulator database is available for several campaigns: Light Precipitation Evaluation Experiment (LPVEX), Midlatitude Continental Convective Clouds Experiment (MC3E), Tropical Warm Pool - International Cloud Experiment (TWP-ICE) and Canadian Cloudsat/Calipso Validation Project (C3VP).  The Orbital database takes account for the atmospheric profiles, the cloud/rain profiles, and the detailed surface/terrain information from the Cloud-Resolving Model (CRM) database.  Unique geometry and antenna gain patters of each sensor (GMI imager, GMI sounder, DPR Ku, DPR Ka_MA, DPR Ka_HS) are considered.  The Orbital database consists of satellite orbit parameters, geolocation of IFOV/EFOV and satellite location, and simulated L1B/L2-like parameters in satellite orbital grid.  Orbital data covers a portion of sampling right over the Cloud-resolving model (CRM) domain. All orbital data format is NetCDF3, and it contains dimensions, parameter descriptions, and parameter units. Each project's data  is distributed as a separate dataset.   MC3E occurred in Oklahoma, USA in 2011;  LPVEX took place in Finland in  2010; C3VP experiment was held in Canada in 2007 and TWP-ICE took place in Australia in 2006.
The Satellite Simulator database is available for several campaigns: Light Precipitation Evaluation Experiment (LPVEX), Midlatitude Continental Convective Clouds Experiment (MC3E), Tropical Warm Pool - International Cloud Experiment (TWP-ICE) and Canadian Cloudsat/Calipso Validation Project (C3VP).  The Orbital database takes account for the atmospheric profiles, the cloud/rain profiles, and the detailed surface/terrain information from the Cloud-Resolving Model (CRM) database.  Unique geometry and antenna gain patters of each sensor (GMI imager, GMI sounder, DPR Ku, DPR Ka_MA, DPR Ka_HS) are considered.  The Orbital database consists of satellite orbit parameters, geolocation of IFOV/EFOV and satellite location, and simulated L1B/L2-like parameters in satellite orbital grid.  Orbital data covers a portion of sampling right over the Cloud-resolving model (CRM) domain. All orbital data format is NetCDF3, and it contains dimensions, parameter descriptions, and parameter units. Each project's data  is distributed as a separate dataset.   MC3E occurred in Oklahoma, USA in 2011;  LPVEX took place in Finland in  2010; C3VP experiment was held in Canada in 2007 and TWP-ICE took place in Australia in 2006.
The Satellite Simulator database is available for several campaigns: Light Precipitation Evaluation Experiment (LPVEX), Midlatitude Continental Convective Clouds Experiment (MC3E), Tropical Warm Pool - International Cloud Experiment (TWP-ICE) and Canadian Cloudsat/Calipso Validation Project (C3VP).  The Orbital database takes account for the atmospheric profiles, the cloud/rain profiles, and the detailed surface/terrain information from the Cloud-Resolving Model (CRM) database.  Unique geometry and antenna gain patters of each sensor (GMI imager, GMI sounder, DPR Ku, DPR Ka_MA, DPR Ka_HS) are considered.  The Orbital database consists of satellite orbit parameters, geolocation of IFOV/EFOV and satellite location, and simulated L1B/L2-like parameters in satellite orbital grid.  Orbital data covers a portion of sampling right over the Cloud-resolving model (CRM) domain. All orbital data format is NetCDF3, and it contains dimensions, parameter descriptions, and parameter units. Each project's data  is distributed as a separate dataset.   MC3E occurred in Oklahoma, USA in 2011;  LPVEX took place in Finland in  2010; C3VP experiment was held in Canada in 2007 and TWP-ICE took place in Australia in 2006.
The SSMI/S LPVEX dataset contains brightness temperature data processed from the NOAA CLASS QC temperature data records for the Light Precipitation Validation Experiment, part of the Global Precipitation Measurement project.  Only data with swaths within the area of interest are included.  The temporal range of the data includes the LPVEx campaign period (Sep/Oct 2010) and extends through the end of March 2011.
The SSMI/S LPVEX dataset contains brightness temperature data processed from the NOAA CLASS QC temperature data records for the Light Precipitation Validation Experiment, part of the Global Precipitation Measurement project.  Only data with swaths within the area of interest are included.  The temporal range of the data includes the LPVEx campaign period (Sep/Oct 2010) and extends through the end of March 2011.
The SSMI/S LPVEX dataset contains brightness temperature data processed from the NOAA CLASS QC temperature data records for the Light Precipitation Validation Experiment, part of the Global Precipitation Measurement project.  Only data with swaths within the area of interest are included.  The temporal range of the data includes the LPVEx campaign period (Sep/Oct 2010) and extends through the end of March 2011.
The GPM Ground Validation Total Precipitation Sensor (HotPlate) GCPEx dataset provides a measure of the liquid precipitation rate and accumulation for snow.  Additional data includes measurements of temperature, wind speed, relative humidity, pressure, solar and infrared radiation flux.  These were gathered during the GPM Cold-season Precipitation Experiment (GCPEx) at the CARE and SkyDive sites in Ontario, Canada during November 2011 - February 2012.
The GPM Ground Validation Total Precipitation Sensor (HotPlate) GCPEx dataset provides a measure of the liquid precipitation rate and accumulation for snow.  Additional data includes measurements of temperature, wind speed, relative humidity, pressure, solar and infrared radiation flux.  These were gathered during the GPM Cold-season Precipitation Experiment (GCPEx) at the CARE and SkyDive sites in Ontario, Canada during November 2011 - February 2012.
The GPM Ground Validation Total Precipitation Sensor (HotPlate) GCPEx dataset provides a measure of the liquid precipitation rate and accumulation for snow.  Additional data includes measurements of temperature, wind speed, relative humidity, pressure, solar and infrared radiation flux.  These were gathered during the GPM Cold-season Precipitation Experiment (GCPEx) at the CARE and SkyDive sites in Ontario, Canada during November 2011 - February 2012.
The Two-Dimensional Video Disdrometer (2DVD) data was collected during the GPM Cold-season Precipitation Experiment (GCPEx) held in Ontario, Canada.  Collected from six sites the data contains daily ascii files with information on individual snowflakes and hydrometeors, and binary files preprocessed from raw camera data.  Overall data dates range from 27 October 2011 through 27 February 2012 depending on the specific site.
The Two-Dimensional Video Disdrometer (2DVD) data was collected during the GPM Cold-season Precipitation Experiment (GCPEx) held in Ontario, Canada.  Collected from six sites the data contains daily ascii files with information on individual snowflakes and hydrometeors, and binary files preprocessed from raw camera data.  Overall data dates range from 27 October 2011 through 27 February 2012 depending on the specific site.
The Two-Dimensional Video Disdrometer (2DVD) data was collected during the GPM Cold-season Precipitation Experiment (GCPEx) held in Ontario, Canada.  Collected from six sites the data contains daily ascii files with information on individual snowflakes and hydrometeors, and binary files preprocessed from raw camera data.  Overall data dates range from 27 October 2011 through 27 February 2012 depending on the specific site.
The Light Precipitation Evaluation Experiment (LPVEx) took place in September and October 2010 in the Gulf of Finland to characterize the ability of CloudSat, the Global Precipitation Mission (GPM) Dual-frequency Precipitation Radar (DPR), and existing/planned passive microwave (PMW) sensors such as the GPM microwave imager (GMI) to detect light rain and evaluate their estimates of rainfall intensity in high latitude, shallow freezing level environments.  The experiment leveraged in situ microphysical property measurements, coordinated remote sensing observations, and cloud resolving model simulations of high latitude precipitation systems to conduct a comprehensive evaluation of precipitation algorithms for current and future satellite platforms.  The campaign will use these measurements to better understand the process of light rainfall formation at high latitudes and augment the currently limited database of light rainfall microphysical properties that form the critical assumptions at the root of satellite retrieval algorithm.
The Light Precipitation Evaluation Experiment (LPVEx) took place in September and October 2010 in the Gulf of Finland to characterize the ability of CloudSat, the Global Precipitation Mission (GPM) Dual-frequency Precipitation Radar (DPR), and existing/planned passive microwave (PMW) sensors such as the GPM microwave imager (GMI) to detect light rain and evaluate their estimates of rainfall intensity in high latitude, shallow freezing level environments.  The experiment leveraged in situ microphysical property measurements, coordinated remote sensing observations, and cloud resolving model simulations of high latitude precipitation systems to conduct a comprehensive evaluation of precipitation algorithms for current and future satellite platforms.  The campaign will use these measurements to better understand the process of light rainfall formation at high latitudes and augment the currently limited database of light rainfall microphysical properties that form the critical assumptions at the root of satellite retrieval algorithm.
The Light Precipitation Evaluation Experiment (LPVEx) took place in September and October 2010 in the Gulf of Finland to characterize the ability of CloudSat, the Global Precipitation Mission (GPM) Dual-frequency Precipitation Radar (DPR), and existing/planned passive microwave (PMW) sensors such as the GPM microwave imager (GMI) to detect light rain and evaluate their estimates of rainfall intensity in high latitude, shallow freezing level environments.  The experiment leveraged in situ microphysical property measurements, coordinated remote sensing observations, and cloud resolving model simulations of high latitude precipitation systems to conduct a comprehensive evaluation of precipitation algorithms for current and future satellite platforms.  The campaign will use these measurements to better understand the process of light rainfall formation at high latitudes and augment the currently limited database of light rainfall microphysical properties that form the critical assumptions at the root of satellite retrieval algorithm.
The 2DVD disdrometer dataset for the Midlatitude Continental Convective Clouds Experiment (MC3E) provides data on raindrop size and precipitation drop size distribution.  The Midlatitude Continental Convective Clouds Experiment (MC3E) took place in central Oklahoma during the April-June 2011 period.  The experiment was a collaborative effort between the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility and the National Aeronautics and Space Administration's (NASA) Global Precipitation Measurement (GPM) mission Ground Validation (GV) program.  The field campaign leveraged the unprecedented observing infrastructure currently available in the central United States, combined with an extensive sounding array, remote sensing and in situ aircraft observations, NASA GPM ground validation remote sensors, and new ARM instrumentation purchased with American Recovery and Reinvestment Act funding.  The overarching goal was to provide the most complete characterization of convective cloud systems, precipitation, and the environment that has ever been obtained, providing constraints for model cumulus parameterizations and space-based rainfall retrieval algorithms over land that had never before been available.
The 2DVD disdrometer dataset for the Midlatitude Continental Convective Clouds Experiment (MC3E) provides data on raindrop size and precipitation drop size distribution.  The Midlatitude Continental Convective Clouds Experiment (MC3E) took place in central Oklahoma during the April-June 2011 period.  The experiment was a collaborative effort between the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility and the National Aeronautics and Space Administration's (NASA) Global Precipitation Measurement (GPM) mission Ground Validation (GV) program.  The field campaign leveraged the unprecedented observing infrastructure currently available in the central United States, combined with an extensive sounding array, remote sensing and in situ aircraft observations, NASA GPM ground validation remote sensors, and new ARM instrumentation purchased with American Recovery and Reinvestment Act funding.  The overarching goal was to provide the most complete characterization of convective cloud systems, precipitation, and the environment that has ever been obtained, providing constraints for model cumulus parameterizations and space-based rainfall retrieval algorithms over land that had never before been available.
The 2DVD disdrometer dataset for the Midlatitude Continental Convective Clouds Experiment (MC3E) provides data on raindrop size and precipitation drop size distribution.  The Midlatitude Continental Convective Clouds Experiment (MC3E) took place in central Oklahoma during the April-June 2011 period.  The experiment was a collaborative effort between the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility and the National Aeronautics and Space Administration's (NASA) Global Precipitation Measurement (GPM) mission Ground Validation (GV) program.  The field campaign leveraged the unprecedented observing infrastructure currently available in the central United States, combined with an extensive sounding array, remote sensing and in situ aircraft observations, NASA GPM ground validation remote sensors, and new ARM instrumentation purchased with American Recovery and Reinvestment Act funding.  The overarching goal was to provide the most complete characterization of convective cloud systems, precipitation, and the environment that has ever been obtained, providing constraints for model cumulus parameterizations and space-based rainfall retrieval algorithms over land that had never before been available.
The Two-dimensional Video Disdrometer (2DVD) uses two high speed line scan cameras which provide continuous measurements of size distribution, shape and fall velocities of all precipitation particles and types.  This 2DVD is the third generation 2D video disdrometer designed by Joanneum Research of Graz, Austria.  This dataset provides rainfall data for the Global Precipitation Measurement (GPM) Mission Ground Validation Experiment collected at the National Space Science Technology Center (NSSTC), Hunstville, AL.  There may be occasional gaps in the data when the instrument is not resident at the NSSTC and is sent to participate in field campaigns.
The Two-dimensional Video Disdrometer (2DVD) uses two high speed line scan cameras which provide continuous measurements of size distribution, shape and fall velocities of all precipitation particles and types.  This 2DVD is the third generation 2D video disdrometer designed by Joanneum Research of Graz, Austria.  This dataset provides rainfall data for the Global Precipitation Measurement (GPM) Mission Ground Validation Experiment collected at the National Space Science Technology Center (NSSTC), Hunstville, AL.  There may be occasional gaps in the data when the instrument is not resident at the NSSTC and is sent to participate in field campaigns.
The Two-dimensional Video Disdrometer (2DVD) uses two high speed line scan cameras which provide continuous measurements of size distribution, shape and fall velocities of all precipitation particles and types.  This 2DVD is the third generation 2D video disdrometer designed by Joanneum Research of Graz, Austria.  This dataset provides rainfall data for the Global Precipitation Measurement (GPM) Mission Ground Validation Experiment collected at the National Space Science Technology Center (NSSTC), Hunstville, AL.  There may be occasional gaps in the data when the instrument is not resident at the NSSTC and is sent to participate in field campaigns.
The University of North Dakota (UND) Cessna Citation aircraft, an in-situ platform for the GCPEX campaign, carried a suite of instruments for measurements of cloud microphysics, state of the atmosphere parameters, aerosols, three-dimensional winds and turbulence.  The data are stored as a separate file for each flight, with a primary (*.gcpex) file containing both direct and derived parameters.  Raw data files for each cloud instrument are also archived for investigators who wish to use their own processing software.  Citation flight navigation data is also included in this dataset.
The University of North Dakota (UND) Cessna Citation aircraft, an in-situ platform for the GCPEX campaign, carried a suite of instruments for measurements of cloud microphysics, state of the atmosphere parameters, aerosols, three-dimensional winds and turbulence.  The data are stored as a separate file for each flight, with a primary (*.gcpex) file containing both direct and derived parameters.  Raw data files for each cloud instrument are also archived for investigators who wish to use their own processing software.  Citation flight navigation data is also included in this dataset.
The University of North Dakota (UND) Cessna Citation aircraft, an in-situ platform for the GCPEX campaign, carried a suite of instruments for measurements of cloud microphysics, state of the atmosphere parameters, aerosols, three-dimensional winds and turbulence.  The data are stored as a separate file for each flight, with a primary (*.gcpex) file containing both direct and derived parameters.  Raw data files for each cloud instrument are also archived for investigators who wish to use their own processing software.  Citation flight navigation data is also included in this dataset.
The University of North Dakota (UND) Cessna Citation aircraft, an in-situ platform for the MC3E campaign, carried a suite of instruments for measurements of cloud microphysics, state of the atmosphere parameters, aerosols, three-dimensional winds and turbulence.  The Citation flew 15 data missions, which totaled 42.6 flight hours.  The data are stored as a separate file for each flight, with a primary (*.mc3e) file containing both direct and derived parameters.  Raw data files for each cloud instrument are also archived to allow investigators who wish to use their own processing software.  Particle size spectra for the imaging probes were processed by NCAR and are archived and distributed as a separate dataset (Particle probes).
The University of North Dakota (UND) Cessna Citation aircraft, an in-situ platform for the MC3E campaign, carried a suite of instruments for measurements of cloud microphysics, state of the atmosphere parameters, aerosols, three-dimensional winds and turbulence.  The Citation flew 15 data missions, which totaled 42.6 flight hours.  The data are stored as a separate file for each flight, with a primary (*.mc3e) file containing both direct and derived parameters.  Raw data files for each cloud instrument are also archived to allow investigators who wish to use their own processing software.  Particle size spectra for the imaging probes were processed by NCAR and are archived and distributed as a separate dataset (Particle probes).
The University of North Dakota (UND) Cessna Citation aircraft, an in-situ platform for the MC3E campaign, carried a suite of instruments for measurements of cloud microphysics, state of the atmosphere parameters, aerosols, three-dimensional winds and turbulence.  The Citation flew 15 data missions, which totaled 42.6 flight hours.  The data are stored as a separate file for each flight, with a primary (*.mc3e) file containing both direct and derived parameters.  Raw data files for each cloud instrument are also archived to allow investigators who wish to use their own processing software.  Particle size spectra for the imaging probes were processed by NCAR and are archived and distributed as a separate dataset (Particle probes).
The Cessna Citation II Research aircraft owned and operated by the University of North Dakota (UND) participated in the GPM Cold-season Precipitation Experiment (GCPEx) supplying navigation data and also carrying cloud microphysics instruments.  This navigation dataset consists of final processed files containing records with flight time (UT seconds from midnight) and aircraft latitude, longitude and altitude.
The Cessna Citation II Research aircraft owned and operated by the University of North Dakota (UND) participated in the GPM Cold-season Precipitation Experiment (GCPEx) supplying navigation data and also carrying cloud microphysics instruments.  This navigation dataset consists of final processed files containing records with flight time (UT seconds from midnight) and aircraft latitude, longitude and altitude.
The Cessna Citation II Research aircraft owned and operated by the University of North Dakota (UND) participated in the GPM Cold-season Precipitation Experiment (GCPEx) supplying navigation data and also carrying cloud microphysics instruments.  This navigation dataset consists of final processed files containing records with flight time (UT seconds from midnight) and aircraft latitude, longitude and altitude.
The Cessna Citation II Research aircraft owned and operated by the University of North Dakota (UND) participated in the Midlatitude Continental Convective Clouds Experiment (MC3E) supplying navigation data and also carrying cloud microphysics instruments.  This navigation dataset consists of final processed files containing records with flight time (UT seconds from midnight) and aircraft latitude, longitude and altitude, and also contains the IWG1 data collected during the mission.  The Flight Summaries and Flight Track Imagery dataset which includes sonde maps, radar animation, 5-minute KICT track snapshots is distributed with this dataset.
The Cessna Citation II Research aircraft owned and operated by the University of North Dakota (UND) participated in the Midlatitude Continental Convective Clouds Experiment (MC3E) supplying navigation data and also carrying cloud microphysics instruments.  This navigation dataset consists of final processed files containing records with flight time (UT seconds from midnight) and aircraft latitude, longitude and altitude, and also contains the IWG1 data collected during the mission.  The Flight Summaries and Flight Track Imagery dataset which includes sonde maps, radar animation, 5-minute KICT track snapshots is distributed with this dataset.
The Cessna Citation II Research aircraft owned and operated by the University of North Dakota (UND) participated in the Midlatitude Continental Convective Clouds Experiment (MC3E) supplying navigation data and also carrying cloud microphysics instruments.  This navigation dataset consists of final processed files containing records with flight time (UT seconds from midnight) and aircraft latitude, longitude and altitude, and also contains the IWG1 data collected during the mission.  The Flight Summaries and Flight Track Imagery dataset which includes sonde maps, radar animation, 5-minute KICT track snapshots is distributed with this dataset.
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.  This dataset consists of a subset of data for the period of the Midlatitude Continental Convective Clouds Experiment (MC3E).
The GPM Ground Validation W-Band Cloud Radar (WCR) LPVEx dataset contains data collected during the Light Precipitation Evaluation Experiment (LPVEx) in September and October 2010 in the Gulf of Finland.  This dataset contains reflectivity observations and doppler velocity measurements along with aircraft navigation parameters gathered aboard the University of Wyoming King Air.
The GPM Ground Validation W-Band Cloud Radar (WCR) LPVEx dataset contains data collected during the Light Precipitation Evaluation Experiment (LPVEx) in September and October 2010 in the Gulf of Finland.  This dataset contains reflectivity observations and doppler velocity measurements along with aircraft navigation parameters gathered aboard the University of Wyoming King Air.
The GPM Ground Validation W-Band Cloud Radar (WCR) LPVEx dataset contains data collected during the Light Precipitation Evaluation Experiment (LPVEx) in September and October 2010 in the Gulf of Finland.  This dataset contains reflectivity observations and doppler velocity measurements along with aircraft navigation parameters gathered aboard the University of Wyoming King Air.
The GPM Ground Validation Cloud Microphysics dataset provides data from the Light Precipitation Evaluation Experiment (LPVEx) which was held in the Gulf of Finland during September and October of 2010.  Multiple instruments were carried aboard the UWKA, the University of Wyoming King Air.  In addition to aircraft parameters, the dataset contains many scientific parameters including static pressure, dew point temperature, relative humidity, mixing ratio, liquid water content and droplet concentration.
The GPM Ground Validation Cloud Microphysics dataset provides data from the Light Precipitation Evaluation Experiment (LPVEx) which was held in the Gulf of Finland during September and October of 2010.  Multiple instruments were carried aboard the UWKA, the University of Wyoming King Air.  In addition to aircraft parameters, the dataset contains many scientific parameters including static pressure, dew point temperature, relative humidity, mixing ratio, liquid water content and droplet concentration.
The GPM Ground Validation Cloud Microphysics dataset provides data from the Light Precipitation Evaluation Experiment (LPVEx) which was held in the Gulf of Finland during September and October of 2010.  Multiple instruments were carried aboard the UWKA, the University of Wyoming King Air.  In addition to aircraft parameters, the dataset contains many scientific parameters including static pressure, dew point temperature, relative humidity, mixing ratio, liquid water content and droplet concentration.
This data set provides incoming shortwave radiation measurements from fourteen stations of the Greenland Climate Network (GC-Net) distributed over the Greenland Ice Sheet. The original data were obtained from the GC-Net and subsequently quality controlled. The data span from 01 January 1995 through 09 May 2008. The data set is approximately 15 MB comprised of fourteen Network Common Data Form (netCDF) files. The data are available via FTP.
This data set provides incoming shortwave radiation measurements from fourteen stations of the Greenland Climate Network (GC-Net) distributed over the Greenland Ice Sheet. The original data were obtained from the GC-Net and subsequently quality controlled. The data span from 01 January 1995 through 09 May 2008. The data set is approximately 15 MB comprised of fourteen Network Common Data Form (netCDF) files. The data are available via FTP.
This data set provides incoming shortwave radiation measurements from fourteen stations of the Greenland Climate Network (GC-Net) distributed over the Greenland Ice Sheet. The original data were obtained from the GC-Net and subsequently quality controlled. The data span from 01 January 1995 through 09 May 2008. The data set is approximately 15 MB comprised of fourteen Network Common Data Form (netCDF) files. The data are available via FTP.
Gridded Population of the World, Version 2 (GPWv2) consists of estimates of human population for the years 1995 and 1990 by 2.5 arc-minute grid cells. The data products are population counts (raw counts), population densities (per square km), and land area (actual area net of ice and water), all of which are available in two GIS-compatible data formats at the global, continent (Antarctica not included), and country levels. A proportional allocation gridding algorithm, utilizing 127,105 national and sub-national administrative units, is used to assign population values to grid cells. Advantages to GPWv2 include higher quality data from the U.S., Africa, Australia, Canada, Europe, Russia, New Zealand, and India; 8 times the number of administrative units; national population estimates that have been adjusted to match the United Nations national estimated population for each country; a proportional allocation algorithm that reduces error with multiple input polygons; and higher spatial resolution. GPWv2 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI) and the World Resources Institute (WRI). (Suggested Usage: To serve a wide user community by providing the latest data on human population distribution that can be used in interdisciplinary studies of the environment.)
Gridded Population of the World, Version 2 (GPWv2) consists of estimates of human population for the years 1995 and 1990 by 2.5 arc-minute grid cells. The data products are population counts (raw counts), population densities (per square km), and land area (actual area net of ice and water), all of which are available in two GIS-compatible data formats at the global, continent (Antarctica not included), and country levels. A proportional allocation gridding algorithm, utilizing 127,105 national and sub-national administrative units, is used to assign population values to grid cells. Advantages to GPWv2 include higher quality data from the U.S., Africa, Australia, Canada, Europe, Russia, New Zealand, and India; 8 times the number of administrative units; national population estimates that have been adjusted to match the United Nations national estimated population for each country; a proportional allocation algorithm that reduces error with multiple input polygons; and higher spatial resolution. GPWv2 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI) and the World Resources Institute (WRI). (Suggested Usage: To serve a wide user community by providing the latest data on human population distribution that can be used in interdisciplinary studies of the environment.)
Gridded Population of the World, Version 2 (GPWv2) consists of estimates of human population for the years 1995 and 1990 by 2.5 arc-minute grid cells. The data products are population counts (raw counts), population densities (per square km), and land area (actual area net of ice and water), all of which are available in two GIS-compatible data formats at the global, continent (Antarctica not included), and country levels. A proportional allocation gridding algorithm, utilizing 127,105 national and sub-national administrative units, is used to assign population values to grid cells. Advantages to GPWv2 include higher quality data from the U.S., Africa, Australia, Canada, Europe, Russia, New Zealand, and India; 8 times the number of administrative units; national population estimates that have been adjusted to match the United Nations national estimated population for each country; a proportional allocation algorithm that reduces error with multiple input polygons; and higher spatial resolution. GPWv2 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI) and the World Resources Institute (WRI). (Suggested Usage: To serve a wide user community by providing the latest data on human population distribution that can be used in interdisciplinary studies of the environment.)
Gridded Population of the World, Version 2 (GPWv2) consists of estimates of human population for the years 1995 and 1990 by 2.5 arc-minute grid cells. The data products are population counts (raw counts), population densities (per square km), and land area (actual area net of ice and water), all of which are available in two GIS-compatible data formats at the global, continent (Antarctica not included), and country levels. A proportional allocation gridding algorithm, utilizing 127,105 national and sub-national administrative units, is used to assign population values to grid cells. Advantages to GPWv2 include higher quality data from the U.S., Africa, Australia, Canada, Europe, Russia, New Zealand, and India; 8 times the number of administrative units; national population estimates that have been adjusted to match the United Nations national estimated population for each country; a proportional allocation algorithm that reduces error with multiple input polygons; and higher spatial resolution. GPWv2 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI) and the World Resources Institute (WRI). (Suggested Usage: To serve a wide user community by providing the latest data on human population distribution that can be used in interdisciplinary studies of the environment.)
Gridded Population of the World, Version 2 (GPWv2) consists of estimates of human population for the years 1995 and 1990 by 2.5 arc-minute grid cells. The data products are population counts (raw counts), population densities (per square km), and land area (actual area net of ice and water), all of which are available in two GIS-compatible data formats at the global, continent (Antarctica not included), and country levels. A proportional allocation gridding algorithm, utilizing 127,105 national and sub-national administrative units, is used to assign population values to grid cells. Advantages to GPWv2 include higher quality data from the U.S., Africa, Australia, Canada, Europe, Russia, New Zealand, and India; 8 times the number of administrative units; national population estimates that have been adjusted to match the United Nations national estimated population for each country; a proportional allocation algorithm that reduces error with multiple input polygons; and higher spatial resolution. GPWv2 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI) and the World Resources Institute (WRI). (Suggested Usage: To serve a wide user community by providing the latest data on human population distribution that can be used in interdisciplinary studies of the environment.)
Gridded Population of the World, Version 2 (GPWv2) consists of estimates of human population for the years 1995 and 1990 by 2.5 arc-minute grid cells. The data products are population counts (raw counts), population densities (per square km), and land area (actual area net of ice and water), all of which are available in two GIS-compatible data formats at the global, continent (Antarctica not included), and country levels. A proportional allocation gridding algorithm, utilizing 127,105 national and sub-national administrative units, is used to assign population values to grid cells. Advantages to GPWv2 include higher quality data from the U.S., Africa, Australia, Canada, Europe, Russia, New Zealand, and India; 8 times the number of administrative units; national population estimates that have been adjusted to match the United Nations national estimated population for each country; a proportional allocation algorithm that reduces error with multiple input polygons; and higher spatial resolution. GPWv2 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI) and the World Resources Institute (WRI). (Suggested Usage: To serve a wide user community by providing the latest data on human population distribution that can be used in interdisciplinary studies of the environment.)
Gridded Population of the World, Version 3 (GPWv3) Centroids consists of estimates of human population counts and densities for the years 1990, 1995, 2000, 2005, 2010, and 2015 by administrative unit centroid location. The centroids are based on the 399,781 input administrative units used in GPWv3. In addition to population counts and variables, the centroids have associated administrative unit names and the land area of contained within the administrative unit. GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Gridded Population of the World, Version 3 (GPWv3) Centroids consists of estimates of human population counts and densities for the years 1990, 1995, 2000, 2005, 2010, and 2015 by administrative unit centroid location. The centroids are based on the 399,781 input administrative units used in GPWv3. In addition to population counts and variables, the centroids have associated administrative unit names and the land area of contained within the administrative unit. GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Gridded Population of the World, Version 3 (GPWv3) Centroids consists of estimates of human population counts and densities for the years 1990, 1995, 2000, 2005, 2010, and 2015 by administrative unit centroid location. The centroids are based on the 399,781 input administrative units used in GPWv3. In addition to population counts and variables, the centroids have associated administrative unit names and the land area of contained within the administrative unit. GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT). (Suggested Usage:  To provide a vector (point) version of the input administrative units used in GPWv3 for use in data integration.)
Gridded Population of the World, Version 3 (GPWv3) Coastlines are derived from the land area grid to show the outlines of pixels (cells) that contain administrative units in GPWv3. The coastlines are designed for cartographic use with the GPWv3 population raster datasets. GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Gridded Population of the World, Version 3 (GPWv3) Coastlines are derived from the land area grid to show the outlines of pixels (cells) that contain administrative units in GPWv3. The coastlines are designed for cartographic use with the GPWv3 population raster datasets. GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Gridded Population of the World, Version 3 (GPWv3) Coastlines are derived from the land area grid to show the outlines of pixels (cells) that contain administrative units in GPWv3. The coastlines are designed for cartographic use with the GPWv3 population raster datasets. GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT). (Suggested Usage: To provide a set of coastlines consistent with GPWv3 raster data for cartographic purposes.)
Gridded Population of the World, Version 3 (GPWv3) Land and Geographic Unit Area Grids measure land areas in square kilometers and the mean unit size (population-weighted) in square kilometers. The land area grid permits the summation of areas (net of permanent ice and water) at the same resolution as the population density, count, and urban-rural grids. The mean unit size grids provides a quantitative surface that indicates the size of the input unit(s) from which population count and density grids are derived..GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Gridded Population of the World, Version 3 (GPWv3) Land and Geographic Unit Area Grids measure land areas in square kilometers and the mean unit size (population-weighted) in square kilometers. The land area grid permits the summation of areas (net of permanent ice and water) at the same resolution as the population density, count, and urban-rural grids. The mean unit size grids provides a quantitative surface that indicates the size of the input unit(s) from which population count and density grids are derived..GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Gridded Population of the World, Version 3 (GPWv3) Land and Geographic Unit Area Grids measure land areas in square kilometers and the mean unit size (population-weighted) in square kilometers. The land area grid permits the summation of areas (net of permanent ice and water) at the same resolution as the population density, count, and urban-rural grids. The mean unit size grids provides a quantitative surface that indicates the size of the input unit(s) from which population count and density grids are derived..GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT). (Suggested Usage:  To provide a quantitative measure of the input resolution of administrative units used for GPWv3.)
Gridded Population of the World, Version 3 (GPWv3) National Boundaries are derived from the land area grid to show the outlines of pixels (cells) that contain administrative units in GPWv3 on a per-country/territory basis. The National Boundaries data are derived from the pixels as polygons and thus have rectilinear boundaries at large scale. Note that the polygons that outline the countries and territories are not official representations; rather, they represent the area covered by the statistical data as provided. The national/territorial boundaries are designed for cartographic use with the GPWv3 population raster datasets. GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Gridded Population of the World, Version 3 (GPWv3) National Boundaries are derived from the land area grid to show the outlines of pixels (cells) that contain administrative units in GPWv3 on a per-country/territory basis. The National Boundaries data are derived from the pixels as polygons and thus have rectilinear boundaries at large scale. Note that the polygons that outline the countries and territories are not official representations; rather, they represent the area covered by the statistical data as provided. The national/territorial boundaries are designed for cartographic use with the GPWv3 population raster datasets. GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Gridded Population of the World, Version 3 (GPWv3) National Boundaries are derived from the land area grid to show the outlines of pixels (cells) that contain administrative units in GPWv3 on a per-country/territory basis. The National Boundaries data are derived from the pixels as polygons and thus have rectilinear boundaries at large scale. Note that the polygons that outline the countries and territories are not official representations; rather, they represent the area covered by the statistical data as provided. The national/territorial boundaries are designed for cartographic use with the GPWv3 population raster datasets. GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT). (Suggested Usage:  To provide a quantitative measure of the input resolution of administrative units used for GPWv3.)
Gridded Population of the World, Version 3 (GPWv3) National Identifier Grid is derived from the land area grid to create a raster surface where pixels (cells) that cover the same country or territory have the same value. Note that the countries and territories are not official representations of countries boundaries; rather, they represent the area covered by the statistical data as provided. GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Gridded Population of the World, Version 3 (GPWv3) National Identifier Grid is derived from the land area grid to create a raster surface where pixels (cells) that cover the same country or territory have the same value. Note that the countries and territories are not official representations of countries boundaries; rather, they represent the area covered by the statistical data as provided. GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Gridded Population of the World, Version 3 (GPWv3) National Identifier Grid is derived from the land area grid to create a raster surface where pixels (cells) that cover the same country or territory have the same value. Note that the countries and territories are not official representations of countries boundaries; rather, they represent the area covered by the statistical data as provided. GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT). (Suggested Usage: To provide a raster representation of nation-states in GPWv3 for use in aggregating population data.)
Gridded Population of the World, Version 3 (GPWv3) consists of estimates of human population for the years 1990, 1995, and 2000 by 2.5 arc-minute grid cells and associated datasets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative units, is used to assign population values to grid cells. The population count grids contain estimates of the number of persons per grid cell. The grids are available in various GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Gridded Population of the World, Version 3 (GPWv3) consists of estimates of human population for the years 1990, 1995, and 2000 by 2.5 arc-minute grid cells and associated datasets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative units, is used to assign population values to grid cells. The population count grids contain estimates of the number of persons per grid cell. The grids are available in various GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Gridded Population of the World, Version 3 (GPWv3) consists of estimates of human population for the years 1990, 1995, and 2000 by 2.5 arc-minute grid cells and associated datasets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative units, is used to assign population values to grid cells. The population count grids contain estimates of the number of persons per grid cell. The grids are available in various GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT). (Suggested Usage:  To provide a time series of raster data on population to facilitate data integration.)
Gridded Population of the World, Version 3 (GPWv3) Future Estimates consists of estimates of human population for the years 2005, 2010, and 2015 by 2.5 arc-minute grid cells and associated datasets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative units, is used to assign population values to grid cells. The population counts that the grids are derived from are extrapolated based on a combination of subnational growth rates from census dates and national growth rates from United Nations statistics. All of the grids have been adjusted to match United Nations national level population estimates. The population count grids contain estimates of the number of persons per grid cell. The grids are available in various GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Gridded Population of the World, Version 3 (GPWv3) Future Estimates consists of estimates of human population for the years 2005, 2010, and 2015 by 2.5 arc-minute grid cells and associated datasets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative units, is used to assign population values to grid cells. The population counts that the grids are derived from are extrapolated based on a combination of subnational growth rates from census dates and national growth rates from United Nations statistics. All of the grids have been adjusted to match United Nations national level population estimates. The population count grids contain estimates of the number of persons per grid cell. The grids are available in various GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Gridded Population of the World, Version 3 (GPWv3) Future Estimates consists of estimates of human population for the years 2005, 2010, and 2015 by 2.5 arc-minute grid cells and associated datasets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative units, is used to assign population values to grid cells. The population counts that the grids are derived from are extrapolated based on a combination of subnational growth rates from census dates and national growth rates from United Nations statistics. All of the grids have been adjusted to match United Nations national level population estimates. The population count grids contain estimates of the number of persons per grid cell. The grids are available in various GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT). (Suggested Usage:  To provide a time series of raster data on population projected to the year 2015 to facilitate data integration.)
Gridded Population of the World, Version 3 (GPWv3) consists of estimates of human population for the years 1990, 1995, and 2000 by 2.5 arc-minute grid cells and associated 

datasets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative units, is used to assign population values to 

grid cells. The population density grids are derived by dividing the population count grids by the land area grid and represent persons per square kilometer. The grids are available in 

various GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). GPWv3 is produced by the Columbia University Center for 

International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Gridded Population of the World, Version 3 (GPWv3) consists of estimates of human population for the years 1990, 1995, and 2000 by 2.5 arc-minute grid cells and associated 

datasets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative units, is used to assign population values to 

grid cells. The population density grids are derived by dividing the population count grids by the land area grid and represent persons per square kilometer. The grids are available in 

various GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). GPWv3 is produced by the Columbia University Center for 

International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Gridded Population of the World, Version 3 (GPWv3) consists of estimates of human population for the years 1990, 1995, and 2000 by 2.5 arc-minute grid cells and associated 

datasets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative units, is used to assign population values to 

grid cells. The population density grids are derived by dividing the population count grids by the land area grid and represent persons per square kilometer. The grids are available in 

various GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). GPWv3 is produced by the Columbia University Center for 

International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Gridded Population of the World, Version 3 (GPWv3), Future Estimates consists of estimates of human population for the years 2005, 2010, and 2015 by 2.5 arc-minute grid cells. A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative units, is used to assign population values to grid cells. The future estimate population values are extrapolated based on a combination of subnational growth rates from census dates and national growth rates from United Nations statistics. All of the grids have been adjusted to match United Nations national level population estimates. The population density grids are derived by dividing the population count grids by the land area grid and represent persons per square kilometer. The grids are available in various GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Gridded Population of the World, Version 3 (GPWv3), Future Estimates consists of estimates of human population for the years 2005, 2010, and 2015 by 2.5 arc-minute grid cells. A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative units, is used to assign population values to grid cells. The future estimate population values are extrapolated based on a combination of subnational growth rates from census dates and national growth rates from United Nations statistics. All of the grids have been adjusted to match United Nations national level population estimates. The population density grids are derived by dividing the population count grids by the land area grid and represent persons per square kilometer. The grids are available in various GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
Gridded Population of the World, Version 3 (GPWv3), Future Estimates consists of estimates of human population for the years 2005, 2010, and 2015 by 2.5 arc-minute grid cells. A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative units, is used to assign population values to grid cells. The future estimate population values are extrapolated based on a combination of subnational growth rates from census dates and national growth rates from United Nations statistics. All of the grids have been adjusted to match United Nations national level population estimates. The population density grids are derived by dividing the population count grids by the land area grid and represent persons per square kilometer. The grids are available in various GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT). (Suggested Usage:  To provide a time series of raster data on population projected to the year 2015 to facilitate data integration..)
Gridded Population of the World, Version 3 (GPWv3) Subnational Administrative Boundaries are the basis of the population data products in GPWv3. Due to copyright 

restrictions, only maps of the subnational administrative boundaries are available, the underlying data cannot be released. GPWv3 is produced by the Columbia University Center for 

International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
The Birds of the Americas Family Richness Grids of the Gridded Species Distribution, Version 1 are the aggregations of the Presence Grids data at the family level. They are available in 30-arc second (1 kilometer) resolutions. The cell values represent the number of species in a particular family. The input vector layers were produced by a consortium led by NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Birds of the Americas Family Richness Grids of the Gridded Species Distribution, Version 1 are the aggregations of the Presence Grids data at the family level. They are available in 30-arc second (1 kilometer) resolutions. The cell values represent the number of species in a particular family. The input vector layers were produced by a consortium led by NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Birds of the Americas Family Richness Grids of the Gridded Species Distribution, Version 1 are the aggregations of the Presence Grids data at the family level. They are available in 30-arc second (1 kilometer) resolutions. The cell values represent the number of species in a particular family. The input vector layers were produced by a consortium led by NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Birds of the Americas Family Richness Grids of the Gridded Species Distribution, Version 1 are the aggregations of the Presence Grids data at the family level. They are available in 30-arc second (1 kilometer) resolutions. The cell values represent the number of species in a particular family. The input vector layers were produced by a consortium led by NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Birds of the Americas Original  Grids of the Gridded Species Distribution, Version 1are converted 1- kilometer grid cell data in the Geographic Coordinate System (GCS) that cover North America, South America and the Caribbean Islands. The input vector data were created by a consortium led by Natureserve.  The grids are produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Birds of the Americas Original  Grids of the Gridded Species Distribution, Version 1are converted 1- kilometer grid cell data in the Geographic Coordinate System (GCS) that cover North America, South America and the Caribbean Islands. The input vector data were created by a consortium led by Natureserve.  The grids are produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Birds of the Americas Original  Grids of the Gridded Species Distribution, Version 1are converted 1- kilometer grid cell data in the Geographic Coordinate System (GCS) that cover North America, South America and the Caribbean Islands. The input vector data were created by a consortium led by Natureserve.  The grids are produced by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide a gridded version of existing vector maps of bird species distribution at 1- kilometer spatial resolution, which in turn can be used in modeling efforts, wildlife conservation planning, natural resource management, policy-making, biodiversity studies and human-environment interactions.)
The Birds of the Americas Family Presence Grids of the Gridded Species Distribution, Version 1  is a reclassified version of the original  grids of the bird species distribution maps of  North America, South America and the Caribbean Islands. The data include 1- kilometer presence/absence grids for individual species available in Geographic Coordinate System (GCS). The input vector layers were produced by a consortium led by NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Birds of the Americas Family Presence Grids of the Gridded Species Distribution, Version 1  is a reclassified version of the original  grids of the bird species distribution maps of  North America, South America and the Caribbean Islands. The data include 1- kilometer presence/absence grids for individual species available in Geographic Coordinate System (GCS). The input vector layers were produced by a consortium led by NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Birds of the Americas Family Presence Grids of the Gridded Species Distribution, Version 1  is a reclassified version of the original  grids of the bird species distribution maps of  North America, South America and the Caribbean Islands. The data include 1- kilometer presence/absence grids for individual species available in Geographic Coordinate System (GCS). The input vector layers were produced by a consortium led by NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide a gridded version of existing vector maps of bird species presence at 1- kilometer spatial resolution, which in turn can be used in modeling efforts, wildlife conservation planning, natural resource management, policy-making, biodiversity studies and human-environment interactions.)
Global Amphibians Family Richness Grids of the Gridded Species Distribution, Version 1 are 

aggregations of the presence grids data at the family level. They are available in 30-arc second (1 kilometer) resolutions. The cell 

values represent the number of species in a particular family. The input vector layers were produced by a consortium led by 

NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information 

Network (CIESIN).
Global Amphibians Family Richness Grids of the Gridded Species Distribution, Version 1 are 

aggregations of the presence grids data at the family level. They are available in 30-arc second (1 kilometer) resolutions. The cell 

values represent the number of species in a particular family. The input vector layers were produced by a consortium led by 

NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information 

Network (CIESIN).
Global Amphibians Family Richness Grids of the Gridded Species Distribution, Version 1 are 

aggregations of the presence grids data at the family level. They are available in 30-arc second (1 kilometer) resolutions. The cell 

values represent the number of species in a particular family. The input vector layers were produced by a consortium led by 

NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information 

Network (CIESIN).
Global Amphibians Family Richness Grids of the Gridded Species Distribution, Version 1 are 

aggregations of the presence grids data at the family level. They are available in 30-arc second (1 kilometer) resolutions. The cell 

values represent the number of species in a particular family. The input vector layers were produced by a consortium led by 

NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information 

Network (CIESIN).
The Global Amphibians Original Grids of the Gridded Species Distribution, Version 1 are converted 1- kilometer grid cell data available in the Geographic Coordinate System (GCS). The input vector data were created by a consortium led by Natureserve. The grids are produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Global Amphibians Original Grids of the Gridded Species Distribution, Version 1 are converted 1- kilometer grid cell data available in the Geographic Coordinate System (GCS). The input vector data were created by a consortium led by Natureserve. The grids are produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Global Amphibians Original Grids of the Gridded Species Distribution, Version 1 are converted 1- kilometer grid cell data available in the Geographic Coordinate System (GCS). The input vector data were created by a consortium led by Natureserve. The grids are produced by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide a gridded version of existing vector maps of amphibian species distribution at 1- kilometer spatial resolution, which in turn can be used in modeling efforts, wildlife conservation planning, natural resource management, policy-making, biodiversity studies and human-environment interactions.)
The Global Amphibians Presence Grids of the Gridded Species Distribution, Version 1 is a reclassified version of the original  grids of amphibian species distribution maps. The data include 1- kilometer presence/absence grids for individual species available in Geographic Coordinate System (GCS). The input vector layers were produced by a consortium led by NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Global Amphibians Presence Grids of the Gridded Species Distribution, Version 1 is a reclassified version of the original  grids of amphibian species distribution maps. The data include 1- kilometer presence/absence grids for individual species available in Geographic Coordinate System (GCS). The input vector layers were produced by a consortium led by NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Global Amphibians Presence Grids of the Gridded Species Distribution, Version 1 is a reclassified version of the original  grids of amphibian species distribution maps. The data include 1- kilometer presence/absence grids for individual species available in Geographic Coordinate System (GCS). The input vector layers were produced by a consortium led by NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide a gridded version of existing vector maps of mammal species presence at 1- kilometer spatial resolution, which in turn can be used in modeling efforts, wildlife conservation planning, natural resource management, policy-making, biodiversity studies and human-environment interactions.)
The Mammals of the Americas Family Richness Grids of the Gridded Species Distribution, Version 1 

are aggregations of the presence grids data at the family level. They are available in 30-arc second (1 kilometer) resolutions. The 

cell values represent the number of species in a particular family. The input vector layers were produced by a consortium led by 

NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information 

Network (CIESIN).
The Mammals of the Americas Family Richness Grids of the Gridded Species Distribution, Version 1 

are aggregations of the presence grids data at the family level. They are available in 30-arc second (1 kilometer) resolutions. The 

cell values represent the number of species in a particular family. The input vector layers were produced by a consortium led by 

NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information 

Network (CIESIN).
The Mammals of the Americas Family Richness Grids of the Gridded Species Distribution, Version 1 

are aggregations of the presence grids data at the family level. They are available in 30-arc second (1 kilometer) resolutions. The 

cell values represent the number of species in a particular family. The input vector layers were produced by a consortium led by 

NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information 

Network (CIESIN).
The Mammals of the Americas Family Richness Grids of the Gridded Species Distribution, Version 1 

are aggregations of the presence grids data at the family level. They are available in 30-arc second (1 kilometer) resolutions. The 

cell values represent the number of species in a particular family. The input vector layers were produced by a consortium led by 

NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information 

Network (CIESIN).
The Mammals of the Americas Original Grids of the Gridded Species Distribution, Version 1 are converted 1- kilometer grid cell data in the Geographic Coordinate System (GCS) that cover North America, South America and the Caribbean Islands. The input vector data were created by a consortium led by Natureserve.  The grids are produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Mammals of the Americas Original Grids of the Gridded Species Distribution, Version 1 are converted 1- kilometer grid cell data in the Geographic Coordinate System (GCS) that cover North America, South America and the Caribbean Islands. The input vector data were created by a consortium led by Natureserve.  The grids are produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Mammals of the Americas Original Grids of the Gridded Species Distribution, Version 1 are converted 1- kilometer grid cell data in the Geographic Coordinate System (GCS) that cover North America, South America and the Caribbean Islands. The input vector data were created by a consortium led by Natureserve.  The grids are produced by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide a gridded version of existing vector maps of mammal species distribution at 1- kilometer spatial resolution, which in turn can be used in modeling efforts, wildlife conservation planning, natural resource management, policy-making, biodiversity studies and human-environment interactions.)
The Mammals of the Americas Presence Grids of the Gridded Species Distribution, Version 1 is a reclassified version of the original  grids of the mammal species distribution maps of  North America, South America and the Caribbean Islands. The data include 1- kilometer presence/absence grids for individual species available in Geographic Coordinate System (GCS). The input vector layers were produced by a consortium led by NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Mammals of the Americas Presence Grids of the Gridded Species Distribution, Version 1 is a reclassified version of the original  grids of the mammal species distribution maps of  North America, South America and the Caribbean Islands. The data include 1- kilometer presence/absence grids for individual species available in Geographic Coordinate System (GCS). The input vector layers were produced by a consortium led by NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Mammals of the Americas Presence Grids of the Gridded Species Distribution, Version 1 is a reclassified version of the original  grids of the mammal species distribution maps of  North America, South America and the Caribbean Islands. The data include 1- kilometer presence/absence grids for individual species available in Geographic Coordinate System (GCS). The input vector layers were produced by a consortium led by NatureServe. The gridding and grid processing are done by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide a gridded version of existing vector maps of mammal species presence at 1- kilometer spatial resolution, which in turn can be used in modeling efforts, wildlife conservation planning, natural resource management, policy-making, biodiversity studies and human-environment interactions.)
The Tropical Rainfall Measuring Mission (TRMM) is a joint U.S.-Japan  satellite mission to monitor tropical and subtropical precipitation. 
                  
The Visible/Infrared Scanner (VIRS) Radiance Gridded Orbital data are a special product derived from the TRMM standard product, VIRS Radiance (1B-01), and mapped to a 0.25 degree x 0.25 degree latitude/longitude grid. The spatial coverage is defined by a 720 km swath bounded by the latitudes 38 degree N and 38 degree S for a single satellite orbit. The parameters included in this data set are the scene radiance data for the five VIRS channels.
The Second Generation Airborne Precipitation Radar (APR-2) is a dual-frequency (13 GHz and 35 GHz), Doppler, dual-polarization radar system.  It has a downward looking antenna that performs cross track scans, covering a swath that is +/- 25 to each side of the aircraft path.  Additional features include: simultaneous dual-frequency, matched beam operation at 13.4 and 35.6 GHz (same as GPM Dual-Frequency Precipitation Radar), simultaneous measurement of both like- and cross-polarized signals at both frequencies, Doppler operation, and real-time pulse compression (calibrated reflectivity data can be produced for large areas in the field during flight, if necessary).  The APR-2 flew on the NASA DC-8 for the Genesis and Rapid Intensification Processes (GRIP) experiment and collected data between Aug 17, 2010 - Sep 22, 2010.
The Second Generation Airborne Precipitation Radar (APR-2) is a dual-frequency (13 GHz and 35 GHz), Doppler, dual-polarization radar system.  It has a downward looking antenna that performs cross track scans, covering a swath that is +/- 25 to each side of the aircraft path.  Additional features include: simultaneous dual-frequency, matched beam operation at 13.4 and 35.6 GHz (same as GPM Dual-Frequency Precipitation Radar), simultaneous measurement of both like- and cross-polarized signals at both frequencies, Doppler operation, and real-time pulse compression (calibrated reflectivity data can be produced for large areas in the field during flight, if necessary).  The APR-2 flew on the NASA DC-8 for the Genesis and Rapid Intensification Processes (GRIP) experiment and collected data between Aug 17, 2010 - Sep 22, 2010.
The Second Generation Airborne Precipitation Radar (APR-2) is a dual-frequency (13 GHz and 35 GHz), Doppler, dual-polarization radar system.  It has a downward looking antenna that performs cross track scans, covering a swath that is +/- 25 to each side of the aircraft path.  Additional features include: simultaneous dual-frequency, matched beam operation at 13.4 and 35.6 GHz (same as GPM Dual-Frequency Precipitation Radar), simultaneous measurement of both like- and cross-polarized signals at both frequencies, Doppler operation, and real-time pulse compression (calibrated reflectivity data can be produced for large areas in the field during flight, if necessary).  The APR-2 flew on the NASA DC-8 for the Genesis and Rapid Intensification Processes (GRIP) experiment and collected data between Aug 17, 2010 - Sep 22, 2010.
The GRIP Barbados/Cape Verde radiosonde data set consists of generally two soundings per day (06Z and 12Z) launched from Barbados, and one sounding per day (12Z) launched from Cape Verde.  These radiosondes measure the profile of atmospheric pressure, temperature, humidity, wind speed and direction, from the ground to an altitude of up to 40 km (in general, the sondes reached at least a pressure of 100 milibars).  The launch program began on 14 August, 2010 and ended 24 September, 2010.  The sondes used were type DFM-06, built by GRAW Radeosondes, Nurenberg Germany.  Most ascents were done with TOTEX 200-g latex balloons using the DMF-06 sondes.  A few launches were made using TOTEX 800-g Balloons with the DFM-97 package (connected with ECC ozonesonde).  On some days launch times were changed, and multiple launches were made from Barbados on September 9, 10 and 21.  The data were retrieved using a GRAWMET GS-E ground station.  The sample rate of the data was 4 seconds for the Barbados data and 2 seconds for the Cape Verde data.
The GRIP Barbados/Cape Verde radiosonde data set consists of generally two soundings per day (06Z and 12Z) launched from Barbados, and one sounding per day (12Z) launched from Cape Verde.  These radiosondes measure the profile of atmospheric pressure, temperature, humidity, wind speed and direction, from the ground to an altitude of up to 40 km (in general, the sondes reached at least a pressure of 100 milibars).  The launch program began on 14 August, 2010 and ended 24 September, 2010.  The sondes used were type DFM-06, built by GRAW Radeosondes, Nurenberg Germany.  Most ascents were done with TOTEX 200-g latex balloons using the DMF-06 sondes.  A few launches were made using TOTEX 800-g Balloons with the DFM-97 package (connected with ECC ozonesonde).  On some days launch times were changed, and multiple launches were made from Barbados on September 9, 10 and 21.  The data were retrieved using a GRAWMET GS-E ground station.  The sample rate of the data was 4 seconds for the Barbados data and 2 seconds for the Cape Verde data.
The GRIP Barbados/Cape Verde radiosonde data set consists of generally two soundings per day (06Z and 12Z) launched from Barbados, and one sounding per day (12Z) launched from Cape Verde.  These radiosondes measure the profile of atmospheric pressure, temperature, humidity, wind speed and direction, from the ground to an altitude of up to 40 km (in general, the sondes reached at least a pressure of 100 milibars).  The launch program began on 14 August, 2010 and ended 24 September, 2010.  The sondes used were type DFM-06, built by GRAW Radeosondes, Nurenberg Germany.  Most ascents were done with TOTEX 200-g latex balloons using the DMF-06 sondes.  A few launches were made using TOTEX 800-g Balloons with the DFM-97 package (connected with ECC ozonesonde).  On some days launch times were changed, and multiple launches were made from Barbados on September 9, 10 and 21.  The data were retrieved using a GRAWMET GS-E ground station.  The sample rate of the data was 4 seconds for the Barbados data and 2 seconds for the Cape Verde data.
The GRIP Campaign Reports dataset consists of various reports filed by the scientists during the GRIP campaign which took place 8/15/2010 - 9/30/2010; however several of the reports are from the planning and test flights.  Reports included in this datasets contain information for the Tri Agency Mission Scientists; DC-8, Global Hawk, and WB-57 Platform Scientists; DC-8, Global Hawk, and WB-57 Flight Reports and WB-57 Flight Summary; GRIP Telecons; and TropicalGRIP Forecasts.  The Tri Agency Mission Scientists reports, GRIP telecons and Forecast reports were primarily filed daily, while the Platform and Flight reports exist primarily for flight days.
The GRIP Campaign Reports dataset consists of various reports filed by the scientists during the GRIP campaign which took place 8/15/2010 - 9/30/2010; however several of the reports are from the planning and test flights.  Reports included in this datasets contain information for the Tri Agency Mission Scientists; DC-8, Global Hawk, and WB-57 Platform Scientists; DC-8, Global Hawk, and WB-57 Flight Reports and WB-57 Flight Summary; GRIP Telecons; and TropicalGRIP Forecasts.  The Tri Agency Mission Scientists reports, GRIP telecons and Forecast reports were primarily filed daily, while the Platform and Flight reports exist primarily for flight days.
The GRIP Campaign Reports dataset consists of various reports filed by the scientists during the GRIP campaign which took place 8/15/2010 - 9/30/2010; however several of the reports are from the planning and test flights.  Reports included in this datasets contain information for the Tri Agency Mission Scientists; DC-8, Global Hawk, and WB-57 Platform Scientists; DC-8, Global Hawk, and WB-57 Flight Reports and WB-57 Flight Summary; GRIP Telecons; and TropicalGRIP Forecasts.  The Tri Agency Mission Scientists reports, GRIP telecons and Forecast reports were primarily filed daily, while the Platform and Flight reports exist primarily for flight days.
This data set consists of data collected during the GRIP campaign from three probes: the Cloud, Aerosol, and Precipitation Spectrometer (CAPS), the Precipitation Imaging Probe (PIP), and the Cloud Droplet Probe (CDP).  All are manufactured by Droplet Measurement Technologies in Boulder, CO.  The CAPS is a combination of two probes, the Cloud Imaging Probe-Greyscale (CIP-G) and the Cloud and Aerosol Spectrometer (CAS).  Images of particles are recorded by the CIP-G and PIP while the CAS probe measures particle size distribution from 0.55 to 52.5 microns.  Some ice/liquid water content are derived from the particle size distribution.  Data was collected 13 Aug 2010 through 25 Sep 2010.
This data set consists of data collected during the GRIP campaign from three probes: the Cloud, Aerosol, and Precipitation Spectrometer (CAPS), the Precipitation Imaging Probe (PIP), and the Cloud Droplet Probe (CDP).  All are manufactured by Droplet Measurement Technologies in Boulder, CO.  The CAPS is a combination of two probes, the Cloud Imaging Probe-Greyscale (CIP-G) and the Cloud and Aerosol Spectrometer (CAS).  Images of particles are recorded by the CIP-G and PIP while the CAS probe measures particle size distribution from 0.55 to 52.5 microns.  Some ice/liquid water content are derived from the particle size distribution.  Data was collected 13 Aug 2010 through 25 Sep 2010.
This data set consists of data collected during the GRIP campaign from three probes: the Cloud, Aerosol, and Precipitation Spectrometer (CAPS), the Precipitation Imaging Probe (PIP), and the Cloud Droplet Probe (CDP).  All are manufactured by Droplet Measurement Technologies in Boulder, CO.  The CAPS is a combination of two probes, the Cloud Imaging Probe-Greyscale (CIP-G) and the Cloud and Aerosol Spectrometer (CAS).  Images of particles are recorded by the CIP-G and PIP while the CAS probe measures particle size distribution from 0.55 to 52.5 microns.  Some ice/liquid water content are derived from the particle size distribution.  Data was collected 13 Aug 2010 through 25 Sep 2010.
The DC-8 dropsonde system uses an integrated, highly accurate, GPS-located atmospheric profiling dropsonde, which measures and records current atmospheric conditions in a vertical column below the aircraft.  The dropsonde instrument is ejected from a tube in the underside of the DC8 aircraft.  As the dropsonde floats to the surface on a parachute, it continuously measures and transmits via a 400 MHz meteorological band telemetry link, pressure, temperature and relative humidity, as well as GPS-based wind formation data, to the receiving system onboard the aircraft.  Data was collected for the GRIP campaign from 17 Aug 2010 to 22 Sep 2010.
The DC-8 dropsonde system uses an integrated, highly accurate, GPS-located atmospheric profiling dropsonde, which measures and records current atmospheric conditions in a vertical column below the aircraft.  The dropsonde instrument is ejected from a tube in the underside of the DC8 aircraft.  As the dropsonde floats to the surface on a parachute, it continuously measures and transmits via a 400 MHz meteorological band telemetry link, pressure, temperature and relative humidity, as well as GPS-based wind formation data, to the receiving system onboard the aircraft.  Data was collected for the GRIP campaign from 17 Aug 2010 to 22 Sep 2010.
The DC-8 dropsonde system uses an integrated, highly accurate, GPS-located atmospheric profiling dropsonde, which measures and records current atmospheric conditions in a vertical column below the aircraft.  The dropsonde instrument is ejected from a tube in the underside of the DC8 aircraft.  As the dropsonde floats to the surface on a parachute, it continuously measures and transmits via a 400 MHz meteorological band telemetry link, pressure, temperature and relative humidity, as well as GPS-based wind formation data, to the receiving system onboard the aircraft.  Data was collected for the GRIP campaign from 17 Aug 2010 to 22 Sep 2010.
The MMS provides high-resolution and accurate meteorological parameters (pressure, temperature, turbulence index, and the 3-dimensional wind vector).  The MMS hardware consists of 3 major systems: an air-motion sensing system to measure air velocity with respect to the aircraft, an aircraft-motion sensing system to measure the aircraft velocity with respect to the earth, and a data acquisition system to sample, process, and record the measured quantities.  In addition to making the in flight measurements, a major and necessary step is the post mission systematic calibration and data processing.  The primary data set consists of 1 Hz meteorological data (P, T, 3D winds).  The secondary data set at 20 Hz includes the meteorological data and additional parameters such as Potential-Temperature; True-Air-Speed; aircraft GPS position, velocities, attitudes, acceleration and air flow data (angle-of-attack, sideslip).
The MMS provides high-resolution and accurate meteorological parameters (pressure, temperature, turbulence index, and the 3-dimensional wind vector).  The MMS hardware consists of 3 major systems: an air-motion sensing system to measure air velocity with respect to the aircraft, an aircraft-motion sensing system to measure the aircraft velocity with respect to the earth, and a data acquisition system to sample, process, and record the measured quantities.  In addition to making the in flight measurements, a major and necessary step is the post mission systematic calibration and data processing.  The primary data set consists of 1 Hz meteorological data (P, T, 3D winds).  The secondary data set at 20 Hz includes the meteorological data and additional parameters such as Potential-Temperature; True-Air-Speed; aircraft GPS position, velocities, attitudes, acceleration and air flow data (angle-of-attack, sideslip).
The MMS provides high-resolution and accurate meteorological parameters (pressure, temperature, turbulence index, and the 3-dimensional wind vector).  The MMS hardware consists of 3 major systems: an air-motion sensing system to measure air velocity with respect to the aircraft, an aircraft-motion sensing system to measure the aircraft velocity with respect to the earth, and a data acquisition system to sample, process, and record the measured quantities.  In addition to making the in flight measurements, a major and necessary step is the post mission systematic calibration and data processing.  The primary data set consists of 1 Hz meteorological data (P, T, 3D winds).  The secondary data set at 20 Hz includes the meteorological data and additional parameters such as Potential-Temperature; True-Air-Speed; aircraft GPS position, velocities, attitudes, acceleration and air flow data (angle-of-attack, sideslip).
This dataset contains aircraft navigational data obtained during the GRIP campaign (15 Aug 2010 - 30 Sep 2010).  The NASA DC-8 is outfitted with a navigational recording system which in combination with REVEAL provides detailed flight parameters such as airspeed, altitude, roll/pitch/yaw angles, ground speed, flight level wind speed, temperature and many others.  The Research Environment for Vehicle-Embedded Analysis on Linux (REVEAL) system is a configurable embedded system for facilitating integration of instrument payloads with vehicle systems and communication links.  REVEAL systems currently serve as onboard data acquisition, processing, and recording systems.  NASA has Altair-Class REVEAL systems operating on several airborne science platforms, including ER-2, DC-8, WB-57F, P-3B Orion and G-III.  This class of full-featured instrument is roughly the size of a loaf of bread and weights 10-20 lbs.
This dataset contains aircraft navigational data obtained during the GRIP campaign (15 Aug 2010 - 30 Sep 2010).  The NASA DC-8 is outfitted with a navigational recording system which in combination with REVEAL provides detailed flight parameters such as airspeed, altitude, roll/pitch/yaw angles, ground speed, flight level wind speed, temperature and many others.  The Research Environment for Vehicle-Embedded Analysis on Linux (REVEAL) system is a configurable embedded system for facilitating integration of instrument payloads with vehicle systems and communication links.  REVEAL systems currently serve as onboard data acquisition, processing, and recording systems.  NASA has Altair-Class REVEAL systems operating on several airborne science platforms, including ER-2, DC-8, WB-57F, P-3B Orion and G-III.  This class of full-featured instrument is roughly the size of a loaf of bread and weights 10-20 lbs.
This dataset contains aircraft navigational data obtained during the GRIP campaign (15 Aug 2010 - 30 Sep 2010).  The NASA DC-8 is outfitted with a navigational recording system which in combination with REVEAL provides detailed flight parameters such as airspeed, altitude, roll/pitch/yaw angles, ground speed, flight level wind speed, temperature and many others.  The Research Environment for Vehicle-Embedded Analysis on Linux (REVEAL) system is a configurable embedded system for facilitating integration of instrument payloads with vehicle systems and communication links.  REVEAL systems currently serve as onboard data acquisition, processing, and recording systems.  NASA has Altair-Class REVEAL systems operating on several airborne science platforms, including ER-2, DC-8, WB-57F, P-3B Orion and G-III.  This class of full-featured instrument is roughly the size of a loaf of bread and weights 10-20 lbs.
The Doppler Aerosol WiNd (DAWN), a pulsed lidar, operated aboard a NASA DC-8 aircraft during the Genesis and Rapid Intensification Processes (GRIP) field campaign.  Data values include LOS Winds, calculated vertical profiles of horizontal wind velocity, frequency-domain signal energy and time versus latitude and longitude.  Instrument details can be found in the dataset documentation.  Data was gathered during August -September 2010 over the Atlantic Ocean.
The Doppler Aerosol WiNd (DAWN), a pulsed lidar, operated aboard a NASA DC-8 aircraft during the Genesis and Rapid Intensification Processes (GRIP) field campaign.  Data values include LOS Winds, calculated vertical profiles of horizontal wind velocity, frequency-domain signal energy and time versus latitude and longitude.  Instrument details can be found in the dataset documentation.  Data was gathered during August -September 2010 over the Atlantic Ocean.
The Doppler Aerosol WiNd (DAWN), a pulsed lidar, operated aboard a NASA DC-8 aircraft during the Genesis and Rapid Intensification Processes (GRIP) field campaign.  Data values include LOS Winds, calculated vertical profiles of horizontal wind velocity, frequency-domain signal energy and time versus latitude and longitude.  Instrument details can be found in the dataset documentation.  Data was gathered during August -September 2010 over the Atlantic Ocean.
The GRIP Flight Tracks and Animations dataset includes both KML files and animation files.  The KML files use Google Earth to show the flight tracks on a map.  The animations vary by type.  Created by the Real-time Mission Monitor (RTMM) software, the .avi files show the flight track versus time superimposed over the GOES IR data.  The National SubOrbital Education and Research Center provided a file in two formats (.mov, .mp4) viewing hurricane Earl from the NASA DC-8 aircraft.  Also a NBC newscast informs the public of the GRIP's goals during the campaign.
The GRIP Flight Tracks and Animations dataset includes both KML files and animation files.  The KML files use Google Earth to show the flight tracks on a map.  The animations vary by type.  Created by the Real-time Mission Monitor (RTMM) software, the .avi files show the flight track versus time superimposed over the GOES IR data.  The National SubOrbital Education and Research Center provided a file in two formats (.mov, .mp4) viewing hurricane Earl from the NASA DC-8 aircraft.  Also a NBC newscast informs the public of the GRIP's goals during the campaign.
The GRIP Flight Tracks and Animations dataset includes both KML files and animation files.  The KML files use Google Earth to show the flight tracks on a map.  The animations vary by type.  Created by the Real-time Mission Monitor (RTMM) software, the .avi files show the flight track versus time superimposed over the GOES IR data.  The National SubOrbital Education and Research Center provided a file in two formats (.mov, .mp4) viewing hurricane Earl from the NASA DC-8 aircraft.  Also a NBC newscast informs the public of the GRIP's goals during the campaign.
The GRIP Global Hawk Navigation data was collected during the period Aug 15, 2010 to September 24, 2010 during the GRIP field campaign.  The Global Hawk is an unmanned Airborne System configured with in situ and remote sensing instruments, including the Lightning Imaging Package(LIP), High Altitude Wind and Rain Profiler (HIWRAP), and High Altitude MMIC Sounding Radiometer (HAMSR).  Data was collected for 7 dates and is in the IWGADTS IWG1 format.  The dataset also includes XML files containing metadata documenting the parameters and their format collected during each day's flight.
The GRIP Global Hawk Navigation data was collected during the period Aug 15, 2010 to September 24, 2010 during the GRIP field campaign.  The Global Hawk is an unmanned Airborne System configured with in situ and remote sensing instruments, including the Lightning Imaging Package(LIP), High Altitude Wind and Rain Profiler (HIWRAP), and High Altitude MMIC Sounding Radiometer (HAMSR).  Data was collected for 7 dates and is in the IWGADTS IWG1 format.  The dataset also includes XML files containing metadata documenting the parameters and their format collected during each day's flight.
The GRIP Global Hawk Navigation data was collected during the period Aug 15, 2010 to September 24, 2010 during the GRIP field campaign.  The Global Hawk is an unmanned Airborne System configured with in situ and remote sensing instruments, including the Lightning Imaging Package(LIP), High Altitude Wind and Rain Profiler (HIWRAP), and High Altitude MMIC Sounding Radiometer (HAMSR).  Data was collected for 7 dates and is in the IWGADTS IWG1 format.  The dataset also includes XML files containing metadata documenting the parameters and their format collected during each day's flight.
The GOES imagery files were produced and archived in near real time here at the Global Hydrology and Climate Center (http://ghcc.nsstc.nasa.gov) throughout the Genesis and Rapid Intensification Processes (GRIP) campaign. These image files were created for use with the Real Time Mission Monitor (RTMM). Generally, GOES-11 images are available for all dates between August 15 and September 30, 2010 at 15 minute intervals throughout this time period.
The GOES imagery files were produced and archived in near real time here at the Global Hydrology and Climate Center (http://ghcc.nsstc.nasa.gov) throughout the Genesis and Rapid Intensification Processes (GRIP) campaign. These image files were created for use with the Real Time Mission Monitor (RTMM). Generally, GOES-11 images are available for all dates between August 15 and September 30, 2010 at 15 minute intervals throughout this time period.
The GOES imagery files were produced and archived in near real time here at the Global Hydrology and Climate Center (http://ghcc.nsstc.nasa.gov) throughout the Genesis and Rapid Intensification Processes (GRIP) campaign. These image files were created for use with the Real Time Mission Monitor (RTMM). Generally, GOES-11 images are available for all dates between August 15 and September 30, 2010 at 15 minute intervals throughout this time period.
The GOES-13 "Overshooting Top" KML files were produced during the GRIP Field Experiment for use with the Real Time Mission Monitor (RTMM) tool.  The magnitude of each overshooting top is the difference between the "anvil" temperature and the "overshooting top" temperature.  These magnitudess are represented as a color coded display using Google Earth, a virtual globe, map and geographical information program.
The GOES-13 "Overshooting Top" KML files were produced during the GRIP Field Experiment for use with the Real Time Mission Monitor (RTMM) tool.  The magnitude of each overshooting top is the difference between the "anvil" temperature and the "overshooting top" temperature.  These magnitudess are represented as a color coded display using Google Earth, a virtual globe, map and geographical information program.
The GOES-13 "Overshooting Top" KML files were produced during the GRIP Field Experiment for use with the Real Time Mission Monitor (RTMM) tool.  The magnitude of each overshooting top is the difference between the "anvil" temperature and the "overshooting top" temperature.  These magnitudess are represented as a color coded display using Google Earth, a virtual globe, map and geographical information program.
The GOES imagery files were produced and archived in near real time here at the Global Hydrology and Climate Center (http://ghcc.nsstc.nasa.gov) throughout the Genesis and Rapid Intensification Processes (GRIP) campaign. These image files were created for use with the Real Time Mission Monitor (RTMM). Generally, GOES-13 images are available for all dates between August 15 and September 30, 2010 at 15 minute intervals throughout this time period.
The GOES imagery files were produced and archived in near real time here at the Global Hydrology and Climate Center (http://ghcc.nsstc.nasa.gov) throughout the Genesis and Rapid Intensification Processes (GRIP) campaign. These image files were created for use with the Real Time Mission Monitor (RTMM). Generally, GOES-13 images are available for all dates between August 15 and September 30, 2010 at 15 minute intervals throughout this time period.
The GOES imagery files were produced and archived in near real time here at the Global Hydrology and Climate Center (http://ghcc.nsstc.nasa.gov) throughout the Genesis and Rapid Intensification Processes (GRIP) campaign. These image files were created for use with the Real Time Mission Monitor (RTMM). Generally, GOES-13 images are available for all dates between August 15 and September 30, 2010 at 15 minute intervals throughout this time period.
The High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) is a dual-frequency (Ka- and Ku-band) conical scan system, configured with a nadir viewing antenna on the Global Hawk aircraft.  It provides calibrated reflectivity and unfolded Doppler velocity.  These dual-frequency radar measurements have similar frequencies to the GPM.  These data are from the Genesis and Rapid Intensification Processes (GRIP) experiment which took place in August and September 2010.  HIWRAP flew on the Global Hawk aircraft over the Pacific Ocean.
The High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) is a dual-frequency (Ka- and Ku-band) conical scan system, configured with a nadir viewing antenna on the Global Hawk aircraft.  It provides calibrated reflectivity and unfolded Doppler velocity.  These dual-frequency radar measurements have similar frequencies to the GPM.  These data are from the Genesis and Rapid Intensification Processes (GRIP) experiment which took place in August and September 2010.  HIWRAP flew on the Global Hawk aircraft over the Pacific Ocean.
The High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) is a dual-frequency (Ka- and Ku-band) conical scan system, configured with a nadir viewing antenna on the Global Hawk aircraft.  It provides calibrated reflectivity and unfolded Doppler velocity.  These dual-frequency radar measurements have similar frequencies to the GPM.  These data are from the Genesis and Rapid Intensification Processes (GRIP) experiment which took place in August and September 2010.  HIWRAP flew on the Global Hawk aircraft over the Pacific Ocean.
The High Altitude monolithic microwave integrated Circuit (MMIC) Sounding Radiometer (HAMSR) is a microwave atmospheric sounder developed by JPL under the NASA Instrument Incubator Program.  Operating with 25 spectral channels in 3 bands (50-60Ghz, 118 Ghz 183 HGz region), it provides measurements that can be used to infer the 3-D distribution of temperature, water vapor, and cloud liquid water in the atmosphere, even in the presence of clouds.  The new UAV-HAMSR with 183GHz LNA receiver reduces noise to less than a 0.1K level improving observations of small-scale water vapor.  HAMSR is mounted in payload zone 3 near the nose of the Global Hawk.
The High Altitude monolithic microwave integrated Circuit (MMIC) Sounding Radiometer (HAMSR) is a microwave atmospheric sounder developed by JPL under the NASA Instrument Incubator Program.  Operating with 25 spectral channels in 3 bands (50-60Ghz, 118 Ghz 183 HGz region), it provides measurements that can be used to infer the 3-D distribution of temperature, water vapor, and cloud liquid water in the atmosphere, even in the presence of clouds.  The new UAV-HAMSR with 183GHz LNA receiver reduces noise to less than a 0.1K level improving observations of small-scale water vapor.  HAMSR is mounted in payload zone 3 near the nose of the Global Hawk.
The High Altitude monolithic microwave integrated Circuit (MMIC) Sounding Radiometer (HAMSR) is a microwave atmospheric sounder developed by JPL under the NASA Instrument Incubator Program.  Operating with 25 spectral channels in 3 bands (50-60Ghz, 118 Ghz 183 HGz region), it provides measurements that can be used to infer the 3-D distribution of temperature, water vapor, and cloud liquid water in the atmosphere, even in the presence of clouds.  The new UAV-HAMSR with 183GHz LNA receiver reduces noise to less than a 0.1K level improving observations of small-scale water vapor.  HAMSR is mounted in payload zone 3 near the nose of the Global Hawk.
HIRAD is a hurricane imaging, single-pol passive C-band radiometer with both cross-track and along-track resolution that measures strong ocean surface winds through heavy rain from an aircraft or space-based platform.  Its swath width is approximately 60 degrees in either direction.  V0 data is available measuring brightness temperatures at 5 GHz.  Rain Rate and Wind speed files for EARL have been added to the collection.  HIRAD data was collected for storms EARL and KARL during the GRIP experiment during September 2010. The GRIP Hurricane Imaging Radiometer data set is a preliminary data set.  If you plan to use this data in a publication and/or a presentation, please contact GHRC User Services Office (ghrcdaac@itsc.uah.edu).
Langley Aerosol Research Group Experiment (LARGE) measures ultrafine aerosol number density, total and non-volatile aerosol number density, dry aerosol size distribution from 0.01 to 10 mm, total and submicron aerosol absorption coefficients at 470, 535, and 670 nm, total and submicron aerosol scattering coefficients at 550 nm, and total scattering and hemispheric backscattering coefficients at 400, 550 and 700 nm.  LARGE derives aerosol size statistics (mode, number and mass mean diameters, etc.), aerosol surface area and mass loading, aerosol extinction, single scattering albedo, and angstrom coefficients.  The GRIP LARGE dataset collected data over the Gulf of Mexico from 6 August 2010 to 22 Sep. 2010.
Langley Aerosol Research Group Experiment (LARGE) measures ultrafine aerosol number density, total and non-volatile aerosol number density, dry aerosol size distribution from 0.01 to 10 mm, total and submicron aerosol absorption coefficients at 470, 535, and 670 nm, total and submicron aerosol scattering coefficients at 550 nm, and total scattering and hemispheric backscattering coefficients at 400, 550 and 700 nm.  LARGE derives aerosol size statistics (mode, number and mass mean diameters, etc.), aerosol surface area and mass loading, aerosol extinction, single scattering albedo, and angstrom coefficients.  The GRIP LARGE dataset collected data over the Gulf of Mexico from 6 August 2010 to 22 Sep. 2010.
Langley Aerosol Research Group Experiment (LARGE) measures ultrafine aerosol number density, total and non-volatile aerosol number density, dry aerosol size distribution from 0.01 to 10 mm, total and submicron aerosol absorption coefficients at 470, 535, and 670 nm, total and submicron aerosol scattering coefficients at 550 nm, and total scattering and hemispheric backscattering coefficients at 400, 550 and 700 nm.  LARGE derives aerosol size statistics (mode, number and mass mean diameters, etc.), aerosol surface area and mass loading, aerosol extinction, single scattering albedo, and angstrom coefficients.  The GRIP LARGE dataset collected data over the Gulf of Mexico from 6 August 2010 to 22 Sep. 2010.
NASA's Lidar Atmospheric Sensing Experiment (LASE) system is an airborne DIAL (Differential Absorption Lidar) system used to measure water vapor, aerosols, and clouds throughout the troposphere.  LASE probes the atmosphere using lasers to transmit light in the 815-nm absorption band of water vapor.  Pulses of laser light are fired vertically below the aircraft.  A small fraction of the transmitted laser light is reflected from the atmosphere back to the aircraft and collected with a telescope receiver.  The received light indicates the amount of water vapor along the path of the laser beam.  LASE operated on the NASA DC-8 in the Geneesis and Rapid Intensification Processes (GRIP) experiment with data spanning between Aug. 13, 2010 - Sep.25, 2010.
NASA's Lidar Atmospheric Sensing Experiment (LASE) system is an airborne DIAL (Differential Absorption Lidar) system used to measure water vapor, aerosols, and clouds throughout the troposphere.  LASE probes the atmosphere using lasers to transmit light in the 815-nm absorption band of water vapor.  Pulses of laser light are fired vertically below the aircraft.  A small fraction of the transmitted laser light is reflected from the atmosphere back to the aircraft and collected with a telescope receiver.  The received light indicates the amount of water vapor along the path of the laser beam.  LASE operated on the NASA DC-8 in the Geneesis and Rapid Intensification Processes (GRIP) experiment with data spanning between Aug. 13, 2010 - Sep.25, 2010.
NASA's Lidar Atmospheric Sensing Experiment (LASE) system is an airborne DIAL (Differential Absorption Lidar) system used to measure water vapor, aerosols, and clouds throughout the troposphere.  LASE probes the atmosphere using lasers to transmit light in the 815-nm absorption band of water vapor.  Pulses of laser light are fired vertically below the aircraft.  A small fraction of the transmitted laser light is reflected from the atmosphere back to the aircraft and collected with a telescope receiver.  The received light indicates the amount of water vapor along the path of the laser beam.  LASE operated on the NASA DC-8 in the Geneesis and Rapid Intensification Processes (GRIP) experiment with data spanning between Aug. 13, 2010 - Sep.25, 2010.
The Lightning Instrument Package (LIP) consists of 6 rotating vane type electric field sensors 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).  During the GRIP campaign the LIP instrument package flew aboard the Global Hawk aircraft.
The Lightning Instrument Package (LIP) consists of 6 rotating vane type electric field sensors 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).  During the GRIP campaign the LIP instrument package flew aboard the Global Hawk aircraft.
The Lightning Instrument Package (LIP) consists of 6 rotating vane type electric field sensors 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).  During the GRIP campaign the LIP instrument package flew aboard the Global Hawk aircraft.
The GRIP Meteosat Second Generation (MSG) data and browse was collected during the Genesis and Rapid Intensification Processes (GRIP) experiment from 15 Aug 2010 to 30 Sep 2010.  Infrared and visible radiances, and water vapor were collected.  Meteosat Second Generation (MSG) consists of a series of four geostationary meteorological satellites, along with ground-based infrastructure, that will operate consecutively until 2020.  The MSG system is established under cooperation between The European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and the European Space Agency (ESA) to ensure the continuity of meteorological observations from geostationary orbit.  The MSG satellites carry an impressive pair of instruments, the Spinning Enhanced Visible and InfraRed Imager (SEVIRI), which has the capacity to observe the Earth in 12 spectral channels and provide image data which is core to operational forecasting needs, and the Geostationary Earth Radiation Budget (GERB) instrument supporting climate studies.
The GRIP Meteosat Second Generation (MSG) data and browse was collected during the Genesis and Rapid Intensification Processes (GRIP) experiment from 15 Aug 2010 to 30 Sep 2010.  Infrared and visible radiances, and water vapor were collected.  Meteosat Second Generation (MSG) consists of a series of four geostationary meteorological satellites, along with ground-based infrastructure, that will operate consecutively until 2020.  The MSG system is established under cooperation between The European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and the European Space Agency (ESA) to ensure the continuity of meteorological observations from geostationary orbit.  The MSG satellites carry an impressive pair of instruments, the Spinning Enhanced Visible and InfraRed Imager (SEVIRI), which has the capacity to observe the Earth in 12 spectral channels and provide image data which is core to operational forecasting needs, and the Geostationary Earth Radiation Budget (GERB) instrument supporting climate studies.
The GRIP Meteosat Second Generation (MSG) data and browse was collected during the Genesis and Rapid Intensification Processes (GRIP) experiment from 15 Aug 2010 to 30 Sep 2010.  Infrared and visible radiances, and water vapor were collected.  Meteosat Second Generation (MSG) consists of a series of four geostationary meteorological satellites, along with ground-based infrastructure, that will operate consecutively until 2020.  The MSG system is established under cooperation between The European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and the European Space Agency (ESA) to ensure the continuity of meteorological observations from geostationary orbit.  The MSG satellites carry an impressive pair of instruments, the Spinning Enhanced Visible and InfraRed Imager (SEVIRI), which has the capacity to observe the Earth in 12 spectral channels and provide image data which is core to operational forecasting needs, and the Geostationary Earth Radiation Budget (GERB) instrument supporting climate studies.
The NOAA Global Hawk In-flight Turbulence Sensor (GHIS) instrument measures acceleration at the location of the instrument.  Two accelerometers (2g and 5g full scale) are used on each of two measurement axes.  The GHIS accelerometers are from the Model 1221 family manufactured by Silicon Designs, Inc. with a frequency response of 400-600Hz.  The data system samples each sensor output at 1000 Hz and processes these data to produce mean, maximum, and root-mean square (RMS) values at 10 Hz.  The processed data are then broadcast on the GH internet and brought to the ground via Status and User UDP packets.  GHIS operated on the Global Hawk for the Genesis and Rapid Intensification Processes (GRIP) experiment and collected data between Aug 15, 2010 - Sep 23, 2010.
The NOAA Global Hawk In-flight Turbulence Sensor (GHIS) instrument measures acceleration at the location of the instrument.  Two accelerometers (2g and 5g full scale) are used on each of two measurement axes.  The GHIS accelerometers are from the Model 1221 family manufactured by Silicon Designs, Inc. with a frequency response of 400-600Hz.  The data system samples each sensor output at 1000 Hz and processes these data to produce mean, maximum, and root-mean square (RMS) values at 10 Hz.  The processed data are then broadcast on the GH internet and brought to the ground via Status and User UDP packets.  GHIS operated on the Global Hawk for the Genesis and Rapid Intensification Processes (GRIP) experiment and collected data between Aug 15, 2010 - Sep 23, 2010.
The NOAA Global Hawk In-flight Turbulence Sensor (GHIS) instrument measures acceleration at the location of the instrument.  Two accelerometers (2g and 5g full scale) are used on each of two measurement axes.  The GHIS accelerometers are from the Model 1221 family manufactured by Silicon Designs, Inc. with a frequency response of 400-600Hz.  The data system samples each sensor output at 1000 Hz and processes these data to produce mean, maximum, and root-mean square (RMS) values at 10 Hz.  The processed data are then broadcast on the GH internet and brought to the ground via Status and User UDP packets.  GHIS operated on the Global Hawk for the Genesis and Rapid Intensification Processes (GRIP) experiment and collected data between Aug 15, 2010 - Sep 23, 2010.
The GRIP WB-57 Navigation data was collected on flight days occuring between July 13 , 2010 to September 17, 2010 during the GRIP field campaign.  The NASA WB-57 is a weather research aircraft capable of operating for extended periods of time(~6.5 hours) from sea level to altitudes well over 60,000 feet (12 miles high).  During the GRIP campaign the High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) instrument was flown aboard the WB-57.  Both data in IWG1 format and error logs are part of this dataset.
The GRIP WB-57 Navigation data was collected on flight days occuring between July 13 , 2010 to September 17, 2010 during the GRIP field campaign.  The NASA WB-57 is a weather research aircraft capable of operating for extended periods of time(~6.5 hours) from sea level to altitudes well over 60,000 feet (12 miles high).  During the GRIP campaign the High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) instrument was flown aboard the WB-57.  Both data in IWG1 format and error logs are part of this dataset.
The GRIP WB-57 Navigation data was collected on flight days occuring between July 13 , 2010 to September 17, 2010 during the GRIP field campaign.  The NASA WB-57 is a weather research aircraft capable of operating for extended periods of time(~6.5 hours) from sea level to altitudes well over 60,000 feet (12 miles high).  During the GRIP campaign the High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) instrument was flown aboard the WB-57.  Both data in IWG1 format and error logs are part of this dataset.
The Global Patterns in Human Appropriation of Net Primary Productivity (HANPP) portion of the HANPP Collection represents a digital map of human 

appropriation of net primary productivity measured in units of elemental carbon on a one-quarter degree global grid. Net primary productivity (NPP), the net amount of solar energy converted 

to plant organic matter through photosynthesis, can be measured in units of elemental carbon and represents the primary food energy source for the world's ecosystems. Humans appropriate net 

primary productivity through the consumption of food, paper, wood and fiber, which alters the composition of the atmosphere, levels of biodiversity, energy flows within food webs and the 

provision of important ecosystem services. The dataset is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Global Patterns in Human Appropriation of Net Primary Productivity (HANPP) portion of the HANPP Collection represents a digital map of human 

appropriation of net primary productivity measured in units of elemental carbon on a one-quarter degree global grid. Net primary productivity (NPP), the net amount of solar energy converted 

to plant organic matter through photosynthesis, can be measured in units of elemental carbon and represents the primary food energy source for the world's ecosystems. Humans appropriate net 

primary productivity through the consumption of food, paper, wood and fiber, which alters the composition of the atmosphere, levels of biodiversity, energy flows within food webs and the 

provision of important ecosystem services. The dataset is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Global Patterns in Human Appropriation of Net Primary Productivity (HANPP) portion of the HANPP Collection represents a digital map of human 

appropriation of net primary productivity measured in units of elemental carbon on a one-quarter degree global grid. Net primary productivity (NPP), the net amount of solar energy converted 

to plant organic matter through photosynthesis, can be measured in units of elemental carbon and represents the primary food energy source for the world's ecosystems. Humans appropriate net 

primary productivity through the consumption of food, paper, wood and fiber, which alters the composition of the atmosphere, levels of biodiversity, energy flows within food webs and the 

provision of important ecosystem services. The dataset is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Global Patterns in Net Primary Productivity (NPP) portion of the HANPP Collection maps the net amount of solar energy converted to plant organic 

matter through photosynthesis. NPP is measured in units of elemental carbon and represents the primary food energy source for the world's ecosystems. This dataset is distributed by the 

Columbia University Center for International Earth Science Information Network (CIESIN).
The Global Patterns in Net Primary Productivity (NPP) portion of the HANPP Collection maps the net amount of solar energy converted to plant organic 

matter through photosynthesis. NPP is measured in units of elemental carbon and represents the primary food energy source for the world's ecosystems. This dataset is distributed by the 

Columbia University Center for International Earth Science Information Network (CIESIN).
The Global Patterns in Net Primary Productivity (NPP) portion of the HANPP Collection maps the net amount of solar energy converted to plant organic 

matter through photosynthesis. NPP is measured in units of elemental carbon and represents the primary food energy source for the world's ecosystems. This dataset is distributed by the 

Columbia University Center for International Earth Science Information Network (CIESIN).
The Human Appropriation of Net Primary Productivity (HANPP) by Country and Product portion of the HANPP Collection contains tabular data on carbon-equivalents of consumption by country and by type of product. The data were compiled from national-level FAO statistics on consumption of products such as vegetables, meat, paper, and wood. HANPP represents the amount of carbon required to derive food and fibre products consumed by humans including organic matter that is lost during harvesting and processing. Net primary productivity (NPP), the net amount of solar energy converted to plant organic matter through photosynthesis, can be measured in units of elemental carbon and represents the primary food energy source for the world's ecosystems. These tabular data were used to allocate country level NPP consumption to a spatial surface of NPP consumption (Global Patterns in Human Appropriation of Net Primary Productivity), which is part of this collection. This dataset is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Human Appropriation of Net Primary Productivity (HANPP) by Country and Product portion of the HANPP Collection contains tabular data on carbon-equivalents of consumption by country and by type of product. The data were compiled from national-level FAO statistics on consumption of products such as vegetables, meat, paper, and wood. HANPP represents the amount of carbon required to derive food and fibre products consumed by humans including organic matter that is lost during harvesting and processing. Net primary productivity (NPP), the net amount of solar energy converted to plant organic matter through photosynthesis, can be measured in units of elemental carbon and represents the primary food energy source for the world's ecosystems. These tabular data were used to allocate country level NPP consumption to a spatial surface of NPP consumption (Global Patterns in Human Appropriation of Net Primary Productivity), which is part of this collection. This dataset is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Human Appropriation of Net Primary Productivity (HANPP) by Country and Product portion of the HANPP Collection contains tabular data on carbon-equivalents of consumption by country and by type of product. The data were compiled from national-level FAO statistics on consumption of products such as vegetables, meat, paper, and wood. HANPP represents the amount of carbon required to derive food and fibre products consumed by humans including organic matter that is lost during harvesting and processing. Net primary productivity (NPP), the net amount of solar energy converted to plant organic matter through photosynthesis, can be measured in units of elemental carbon and represents the primary food energy source for the world's ecosystems. These tabular data were used to allocate country level NPP consumption to a spatial surface of NPP consumption (Global Patterns in Human Appropriation of Net Primary Productivity), which is part of this collection. This dataset is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide tabular data on human appropriation of net primary productivity by country.)
The Human Appropriation of Net Primary Productivity (HANPP) as a Percentage of Net Primary Product (NPP) portion of the HANPP Collection represents a 

map identifying regions in which human consumption of NPP is greatly in excess of production by local ecosystems. Humans appropriate net primary productivity through the consumption of 

food, paper, wood and fiber, which alters the composition of the atmosphere, levels of biodiversity, energy flows within food webs and the provision of important ecosystem services. Net 

primary productivity (NPP), the net amount of solar energy converted to plant organic matter through photosynthesis, can be measured in units of elemental carbon and represents the primary 

food energy source for the world's ecosystems. This dataset is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Human Appropriation of Net Primary Productivity (HANPP) as a Percentage of Net Primary Product (NPP) portion of the HANPP Collection represents a 

map identifying regions in which human consumption of NPP is greatly in excess of production by local ecosystems. Humans appropriate net primary productivity through the consumption of 

food, paper, wood and fiber, which alters the composition of the atmosphere, levels of biodiversity, energy flows within food webs and the provision of important ecosystem services. Net 

primary productivity (NPP), the net amount of solar energy converted to plant organic matter through photosynthesis, can be measured in units of elemental carbon and represents the primary 

food energy source for the world's ecosystems. This dataset is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Human Appropriation of Net Primary Productivity (HANPP) as a Percentage of Net Primary Product (NPP) portion of the HANPP Collection represents a 

map identifying regions in which human consumption of NPP is greatly in excess of production by local ecosystems. Humans appropriate net primary productivity through the consumption of 

food, paper, wood and fiber, which alters the composition of the atmosphere, levels of biodiversity, energy flows within food webs and the provision of important ecosystem services. Net 

primary productivity (NPP), the net amount of solar energy converted to plant organic matter through photosynthesis, can be measured in units of elemental carbon and represents the primary 

food energy source for the world's ecosystems. This dataset is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
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 consists of a sampling of each type of Hierarchical Data Format version 4 (HDF4) data that are archived at the eight National Aeronautic and Space Administration (NASA) Earth Science Data Centers (ESDCs). The data were sampled for a collaborative study between The HDF Group, the Goddard Earth Sciences Data and Information Services Center (GES-DISC), and the National Snow and Ice Data Center (NSIDC) in order to assess the complex internal byte layout of HDF files. Based on the results of this assessment, methods for producing a map of the layout of the HDF4 files held by NASA were prototyped using a markup-language-based HDF tool. The resulting maps allow a separate program to read the file without recourse to the HDF application programming interface (API) (Duerr et al. 2009). Data products selected for the study, and a table summarizing the results, 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 consists of a sampling of each type of Hierarchical Data Format version 4 (HDF4) data that are archived at the eight National Aeronautic and Space Administration (NASA) Earth Science Data Centers (ESDCs). The data were sampled for a collaborative study between The HDF Group, the Goddard Earth Sciences Data and Information Services Center (GES-DISC), and the National Snow and Ice Data Center (NSIDC) in order to assess the complex internal byte layout of HDF files. Based on the results of this assessment, methods for producing a map of the layout of the HDF4 files held by NASA were prototyped using a markup-language-based HDF tool. The resulting maps allow a separate program to read the file without recourse to the HDF application programming interface (API) (Duerr et al. 2009). Data products selected for the study, and a table summarizing the results, 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 consists of a sampling of each type of Hierarchical Data Format version 4 (HDF4) data that are archived at the eight National Aeronautic and Space Administration (NASA) Earth Science Data Centers (ESDCs). The data were sampled for a collaborative study between The HDF Group, the Goddard Earth Sciences Data and Information Services Center (GES-DISC), and the National Snow and Ice Data Center (NSIDC) in order to assess the complex internal byte layout of HDF files. Based on the results of this assessment, methods for producing a map of the layout of the HDF4 files held by NASA were prototyped using a markup-language-based HDF tool. The resulting maps allow a separate program to read the file without recourse to the HDF application programming interface (API) (Duerr et al. 2009). Data products selected for the study, and a table summarizing the results, are available via FTP.
Canopy spectral reflectance data collected from the helicopter-mounted MMR in the Superior National Forest, Minnesota, 1983-84
Canopy spectral reflectance data collected from the helicopter-mounted MMR in the Superior National Forest, Minnesota, 1983-84
ABSTRACT: Canopy spectral reflectance data collected from the helicopter-mounted MMR in the Superior National Forest, Minnesota, 1983-84
HIRMLS3IWC is the Joint EOS High Resolution Dynamics Limb Sounder (HIRDLS) and Microwave Limb Sounder (MLS) monthly 10 deg lat x 20 deg lon gridded product for ice water content (IWC) data. This is version 2 released to the public, with the original input coming from v3.3 MLS and v7 HIRDLS. The grid spatial coverage is near-global (-80 deg to +90 deg latitude). The product contains HIRDLS and MLS IWC data for the time of the HIRDLS mission from February 1, 2005 through December 31, 2007. The vertical range of the data is from 215 to 82 hPa for both HIRDLS and MLS, and the vertical resolution is about 1.5 km for HIRDLS and 3 km for MLS. Users of the HIRMLS3IWC data product should read the Version 2 HIRDLS-MLS Level 3 IWC Data Description and Quality document for more information

The data are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5), which is based on the version 5 Hierarchical Data Format, or HDF5. The data file contains two grid objects (one with HIRDLS data, the other with MLS data), each with a set of data fields, attributes, and metadata. Each grid contains data fields with IWC values, and the HIRDLS grid includes data fields with volume density, cloud top pressure and frequency of clouds. Time, latitude and vertical pressure information are also included in each grid.

Parameters contained in the data files include the following:
Variable Name|Description|Units
IWC|Ice Water Content|g/m3
End of parameter information
The "HIRDLS/Aura Level 3 Chlorine Nitrate (ClONO2) Zonal Fourier Coefficients" version 7 data product (H3ZFCCLONO2) contains the entire mission (~3 years) of HIRDLS data expressed as zonal Fourier coefficients in 1 degree latitude bands and 121 pressure levels. The coefficients are computed from the HIRDLS Level 2 profiles with a Kalman filter approach using both forward and backward passes in time. Expressed as the mean and up to 7 sine and cosine coefficients (4 waves for ascending and descending, 7 waves for combined), these coefficients may be used to compute values at any longitude. The data are provided on a pressure grid with 24 levels per decade, corresponding to about 1 km vertical resolution. The vertical range of the data is 100 to 1.0 hPa. The precision values are given by the root-mean square of the differences between the estimated fields and the input data.

The data are stored in the version 5 Hierarchical Data Format for the Earth Observing System (HDF-EOS5), which is an extension of the HDF5 format. Each file contains a zonal object with data for the entire mission with separate data
fields for ascending (daytime), descending (nighttime), and combined orbit node. The data arrays have 145 latitude steps (-64 to 80 degrees), 121 pressure steps, 15 Fourier coefficients (mean plus first 7 cosine and 7 sign waves),
and 1151 daily time steps from January 22, 2005 through March 17, 2008. The coefficients are computed at a daily synoptic time of 12:00 UTC.  That time is expressed in TAI-93 seconds (seconds since January 1, 1993) and the date is also stored in separate year, month and day fields. The ascending and descending datasets include LocalSolarTime and SolarZenithAngle values.

Parameters contained in the data files include the following:
Variable Name|Description|Units
ClONO2|Chlorine Nitrate (ClONO2) Volume Mixing Ratio|mol/mol
End of parameter information
The "HIRDLS/Aura Level 3 Chlorofluorocarbon-11 (CFC-11) Zonal Fourier Coefficients" version 7 data product (H3ZFCCFC11) contains the entire mission (~3 years) of HIRDLS data expressed as zonal Fourier coefficients in 1 degree latitude bands and 121 pressure levels. The coefficients are computed from the HIRDLS Level 2 profiles with a Kalman filter approach using both forward and backward passes in time. Expressed as the mean and up to 7 sine and cosine coefficients (4 waves for ascending and descending, 7 waves for combined), these coefficients may be used to compute values at any longitude. The data are provided on a pressure grid with 24 levels per decade, corresponding to about 1 km vertical resolution. The vertical range of the CFC-11 data is 316 to 17.8 hPa. The precision values are given by the root-mean square of the differences between the estimated fields and the input data.

The data are stored in the version 5 Hierarchical Data Format for the Earth Observing System (HDF-EOS5), which is an extension of the HDF5 format. Each file contains a zonal object with data for the entire mission with separate data
fields for ascending (daytime), descending (nighttime), and combined orbit node. The data arrays have 145 latitude steps (-64 to 80 degrees), 121 pressure steps, 15 Fourier coefficients (mean plus first 7 cosine and 7 sign waves),
and 1151 daily time steps from January 22, 2005 through March 17, 2008. The coefficients are computed at a daily synoptic time of 12:00 UTC.  That time is expressed in TAI-93 seconds (seconds since January 1, 1993) and the date is also stored in separate year, month and day fields. The ascending and descending datasets include LocalSolarTime and SolarZenithAngle values.

Parameters contained in the data files include the following:
Variable Name|Description|Units
CFC11|CFC-11 (CFCl<sub>3</sub>) Volume Mixing Ratio|mol/mol
End of parameter information
The "HIRDLS/Aura Level 3 Chlorofluorocarbon-12 (CFC-12) Zonal Fourier Coefficients" version 7 data product (H3ZFCCFC12) contains the entire mission (~3 years) of HIRDLS data expressed as zonal Fourier coefficients in 1 degree latitude bands and 121 pressure levels. The coefficients are computed from the HIRDLS Level 2 profiles with a Kalman filter approach using both forward and backward passes in time. Expressed as the mean and up to 7 sine and cosine coefficients (4 waves for ascending and descending, 7 waves for combined), these coefficients may be used to compute values at any longitude. The data are provided on a pressure grid with 24 levels per decade, corresponding to about 1 km vertical resolution. The vertical range of the CFC-12 data is 316 to 8.3 hPa. The precision values are given by the root-mean square of the differences between the estimated fields and the input data.

The data are stored in the version 5 Hierarchical Data Format for the Earth Observing System (HDF-EOS5), which is an extension of the HDF5 format. Each file contains a zonal object with data for the entire mission with separate data
fields for ascending (daytime), descending (nighttime), and combined orbit node. The data arrays have 145 latitude steps (-64 to 80 degrees), 121 pressure steps, 15 Fourier coefficients (mean plus first 7 cosine and 7 sign waves),
and 1151 daily time steps from January 22, 2005 through March 17, 2008. The coefficients are computed at a daily synoptic time of 12:00 UTC.  That time is expressed in TAI-93 seconds (seconds since January 1, 1993) and the date is also stored in separate year, month and day fields. The ascending and descending datasets include LocalSolarTime and SolarZenithAngle values.

Parameters contained in the data files include the following:
Variable Name|Description|Units
CFC12|CFC-12 (CF<sub>2</sub>Cl<sub>2</sub>) Volume Mixing Ratio|mol/mol
End of parameter information
HIR3SCOL is the EOS High Resolution Dynamics Limb Sounder (HIRDLS/Aura) level 3 daily gridded 1 x 1 deg. stratospheric columns of NO2 (nitrogen dioxide) data product. The current version is 7. The product contains 1 x 1 degree gridded data between +80 to -64 degrees latitude. The stratospheric column is computed from data at 57 to 1.0 hPa. The product consists of one file spanning the entire HIRDLS mission from January 22, 2005 through March 17, 2008. Users of the HIR3SCOL data product should read the Version 7 HIRDLS Data Description and Quality document for more information

The data are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5), which is based on the version 5 Hierarchical Data Format, or HDF5. The data file contains one grid object with data fields, attributes, and metadata. The data fields include the stratospheric column amount, precision (standard deviation), and data counts per grid cell. Time, latitude and longitude information are also included in the file.

Parameters contained in the data files include the following:
Variable Name|Description|Units
NO2|Nitrogen Dioxide (NO2) Volume Mixing Ratio|mol/mol
End of parameter information
The "HIRDLS/Aura Level 3 Dinitrogen Pentoxide (N2O5) Zonal Fourier Coefficients" version 7 data product (H3ZFCN2O) contains the entire mission (~3 years) of HIRDLS data expressed as zonal Fourier coefficients in 1 degree latitude bands and 121 pressure levels. The coefficients are computed from the HIRDLS Level 2 profiles with a Kalman filter approach using both forward and backward passes in time. Expressed as the mean and up to 7 sine and cosine coefficients (4 waves for ascending and descending, 7 waves for combined), these coefficients may be used to compute values at any longitude. The data are provided on a pressure grid with 24 levels per decade, corresponding to about 1 km vertical resolution. The vertical range of the data is 82.5 to 1.0 hPa. The precision values are given by the root-mean square of the differences between the estimated fields and the input data.

The data are stored in the version 5 Hierarchical Data Format for the Earth Observing System (HDF-EOS5), which is an extension of the HDF5 format. Each file contains a zonal object with data for the entire mission with separate data
fields for ascending (daytime), descending (nighttime), and combined orbit node. The data arrays have 145 latitude steps (-64 to 80 degrees), 121 pressure steps, 15 Fourier coefficients (mean plus first 7 cosine and 7 sign waves),
and 1151 daily time steps from January 22, 2005 through March 17, 2008. The coefficients are computed at a daily synoptic time of 12:00 UTC.  That time is expressed in TAI-93 seconds (seconds since January 1, 1993) and the date is also stored in separate year, month and day fields. The ascending and descending datasets include LocalSolarTime and SolarZenithAngle values.

Parameters contained in the data files include the following:
Variable Name|Description|Units
N2O5|Dinitrogen Pentoxide (N2O5) Volume Mixing Ratio|mol/mol
End of parameter information
The "HIRDLS/Aura Level 3 Extinction at 12.1 Microns Zonal Fourier Coefficients" version 7 data product (H3ZFC12MEXT) contains the entire mission (~3 years) of HIRDLS data expressed as zonal Fourier coefficients in 1 degree latitude bands and 121 pressure levels. The coefficients are computed from the HIRDLS Level 2 profiles with a Kalman filter approach using both forward and backward passes in time. Expressed as the mean and up to 7 sine and cosine coefficients (4 waves for ascending and descending, 7 waves for combined), these coefficients may be used to compute values at any longitude. The data are provided on a pressure grid with 24 levels per decade, corresponding to about 1 km vertical resolution. The vertical range of the data is 215 to 20 hPa. The precision values are given by the root-mean square of the differences between the estimated fields and the input data.

The data are stored in the version 5 Hierarchical Data Format for the Earth Observing System (HDF-EOS5), which is an extension of the HDF5 format. Each file contains a zonal object with data for the entire mission with separate data
fields for ascending (daytime), descending (nighttime), and combined orbit node. The data arrays have 145 latitude steps (-64 to 80 degrees), 121 pressure steps, 15 Fourier coefficients (mean plus first 7 cosine and 7 sign waves),
and 1151 daily time steps from January 22, 2005 through March 17, 2008. The coefficients are computed at a daily synoptic time of 12:00 UTC.  That time is expressed in TAI-93 seconds (seconds since January 1, 1993) and the date is also stored in separate year, month and day fields. The ascending and descending datasets include LocalSolarTime and SolarZenithAngle values.

Parameters contained in the data files include the following:
Variable Name|Description|Units
12.1MicronExtinction|Aerosol Extinction at 12.1 Microns|1/km
End of parameter information
The "HIRDLS/Aura Level 3 Extinction at 8.3 Microns Zonal Fourier Coefficients" version 7 data product (H3ZFC8MEXT) contains the entire mission (~3 years) of HIRDLS data expressed as zonal Fourier coefficients in 1 degree latitude bands and 121 pressure levels. The coefficients are computed from the HIRDLS Level 2 profiles with a Kalman filter approach using both forward and backward passes in time. Expressed as the mean and up to 7 sine and cosine coefficients (4 waves for ascending and descending, 7 waves for combined), these coefficients may be used to compute values at any longitude. The data are provided on a pressure grid with 24 levels per decade, corresponding to about 1 km vertical resolution. The vertical range of the data is 215 to 20 hPa. The precision values are given by the root-mean square of the differences between the estimated fields and the input data.

The data are stored in the version 5 Hierarchical Data Format for the Earth Observing System (HDF-EOS5), which is an extension of the HDF5 format. Each file contains a zonal object with data for the entire mission with separate data
fields for ascending (daytime), descending (nighttime), and combined orbit node. The data arrays have 145 latitude steps (-64 to 80 degrees), 121 pressure steps, 15 Fourier coefficients (mean plus first 7 cosine and 7 sign waves),
and 1151 daily time steps from January 22, 2005 through March 17, 2008. The coefficients are computed at a daily synoptic time of 12:00 UTC.  That time is expressed in TAI-93 seconds (seconds since January 1, 1993) and the date is also stored in separate year, month and day fields. The ascending and descending datasets include LocalSolarTime and SolarZenithAngle values.

Parameters contained in the data files include the following:
Variable Name|Description|Units
8.3MicronExtinction|Aerosol Extinction at 8.3 Microns|1/km
End of parameter information
The "HIRDLS/Aura Level 3 Geopotential Height Zonal Fourier Coefficients" version 7 data product (H3ZFCGPH) contains the entire mission (~3 years) of HIRDLS data expressed as zonal Fourier coefficients in 1 degree latitude bands and 121 pressure levels. The coefficients are computed from the HIRDLS Level 2 profiles with a Kalman filter approach using both forward and backward passes in time. Expressed as the mean and up to 7 sine and cosine coefficients (4 waves for ascending and descending, 7 waves for combined), these coefficients may be used to compute values at any longitude. The data are provided on a pressure grid with 24 levels per decade, corresponding to about 1 km vertical resolution. The vertical range of the data is 1000 to 0.01 hPa. The precision values are given by the root-mean square of the differences between the estimated fields and the input data.

The data are stored in the version 5 Hierarchical Data Format for the Earth Observing System (HDF-EOS5), which is an extension of the HDF5 format. Each file contains a zonal object with data for the entire mission with separate data
fields for ascending (daytime), descending (nighttime), and combined orbit node. The data arrays have 145 latitude steps (-64 to 80 degrees), 121 pressure steps, 15 Fourier coefficients (mean plus first 7 cosine and 7 sign waves),
and 1151 daily time steps from January 22, 2005 through March 17, 2008. The coefficients are computed at a daily synoptic time of 12:00 UTC.  That time is expressed in TAI-93 seconds (seconds since January 1, 1993) and the date is also stored in separate year, month and day fields. The ascending and descending datasets include LocalSolarTime and SolarZenithAngle values.

Parameters contained in the data files include the following:
Variable Name|Description|Units
GPH|Geopotential Height|m
End of parameter information
The "HIRDLS/Aura Level 3 Nitric Acid (HNO3) Zonal Fourier Coefficients" version 7 data product (H3ZFCHNO3) contains the entire mission (~3 years) of HIRDLS data expressed as zonal Fourier coefficients in 1 degree latitude bands and 121 pressure levels. The coefficients are computed from the HIRDLS Level 2 profiles with a Kalman filter approach using both forward and backward passes in time. Expressed as the mean and up to 7 sine and cosine coefficients (4 waves for ascending and descending, 7 waves for combined), these coefficients may be used to compute values at any longitude. The data are provided on a pressure grid with 24 levels per decade, corresponding to about 1 km vertical resolution. The vertical range of the data is 215 to 5.1 hPa. The precision values are given by the root-mean square of the differences between the estimated fields and the input data.

The data are stored in the version 5 Hierarchical Data Format for the Earth Observing System (HDF-EOS5), which is an extension of the HDF5 format. Each file contains a zonal object with data for the entire mission with separate data
fields for ascending (daytime), descending (nighttime), and combined orbit node. The data arrays have 145 latitude steps (-64 to 80 degrees), 121 pressure steps, 15 Fourier coefficients (mean plus first 7 cosine and 7 sign waves),
and 1151 daily time steps from January 22, 2005 through March 17, 2008. The coefficients are computed at a daily synoptic time of 12:00 UTC.  That time is expressed in TAI-93 seconds (seconds since January 1, 1993) and the date is also stored in separate year, month and day fields. The ascending and descending datasets include LocalSolarTime and SolarZenithAngle values.

Parameters contained in the data files include the following:
Variable Name|Description|Units
HNO3|Nitric Acid (HNO3) Volume Mixing Ratio|mol/mol
End of parameter information
The "HIRDLS/Aura Level 3 Nitrogen Dioxide (NO2) Zonal Fourier Coefficients" version 7 data product (H3ZFCNO2) contains the entire mission (~3 years) of HIRDLS data expressed as zonal Fourier coefficients in 1 degree latitude bands and 121 pressure levels. The coefficients are computed from the HIRDLS Level 2 profiles with a Kalman filter approach using both forward and backward passes in time. Expressed as the mean and up to 7 sine and cosine coefficients (4 waves for ascending and descending, 7 waves for combined), these coefficients may be used to compute values at any longitude. The data are provided on a pressure grid with 24 levels per decade, corresponding to about 1 km vertical resolution. The vertical range of the data is 287 to 0.1 hPa. The precision values are given by the root-mean square of the differences between the estimated fields and the input data.

The data are stored in the version 5 Hierarchical Data Format for the Earth Observing System (HDF-EOS5), which is an extension of the HDF5 format. Each file contains a zonal object with data for the entire mission with separate data
fields for ascending (daytime), descending (nighttime), and combined orbit node. The data arrays have 145 latitude steps (-64 to 80 degrees), 121 pressure steps, 15 Fourier coefficients (mean plus first 7 cosine and 7 sign waves),
and 1151 daily time steps from January 22, 2005 through March 17, 2008. The coefficients are computed at a daily synoptic time of 12:00 UTC.  That time is expressed in TAI-93 seconds (seconds since January 1, 1993) and the date is also stored in separate year, month and day fields. The ascending and descending datasets include LocalSolarTime and SolarZenithAngle values.

Parameters contained in the data files include the following:
Variable Name|Description|Units
NO2|Nitrogen Dioxide (NO2) Volume Mixing Ratio|mol/mol
End of parameter information
The "HIRDLS/Aura Level 3 Nitrous Oxide (N2O) Zonal Fourier Coefficients" version 7 data product (H3ZFCN2O) contains the entire mission (~3 years) of HIRDLS data expressed as zonal Fourier coefficients in 1 degree latitude bands and 121 pressure levels. The coefficients are computed from the HIRDLS Level 2 profiles with a Kalman filter approach using both forward and backward passes in time. Expressed as the mean and up to 7 sine and cosine coefficients (4 waves for ascending and descending, 7 waves for combined), these coefficients may be used to compute values at any longitude. The data are provided on a pressure grid with 24 levels per decade, corresponding to about 1 km vertical resolution. The vertical range of the data is 100 to 5.1 hPa. The precision values are given by the root-mean square of the differences between the estimated fields and the input data.

The data are stored in the version 5 Hierarchical Data Format for the Earth Observing System (HDF-EOS5), which is an extension of the HDF5 format. Each file contains a zonal object with data for the entire mission with separate data
fields for ascending (daytime), descending (nighttime), and combined orbit node. The data arrays have 145 latitude steps (-64 to 80 degrees), 121 pressure steps, 15 Fourier coefficients (mean plus first 7 cosine and 7 sign waves),
and 1151 daily time steps from January 22, 2005 through March 17, 2008. The coefficients are computed at a daily synoptic time of 12:00 UTC.  That time is expressed in TAI-93 seconds (seconds since January 1, 1993) and the date is also stored in separate year, month and day fields. The ascending and descending datasets include LocalSolarTime and SolarZenithAngle values.

Parameters contained in the data files include the following:
Variable Name|Description|Units
N2O|Nitrous Oxide (N2O) Volume Mixing Ratio|mol/mol
End of parameter information
The "HIRDLS/Aura Level 3 Ozone (O3) Zonal Fourier Coefficients" version 7 data product (H3ZFCO3) contains the entire mission (~3 years) of HIRDLS data expressed as zonal Fourier coefficients in 1 degree latitude bands and 121 pressure levels. The coefficients are computed from the HIRDLS Level 2 profiles with a Kalman filter approach using both forward and backward passes in time. Expressed as the mean and up to 7 sine and cosine coefficients (4 waves for ascending and descending, 7 waves for combined), these coefficients may be used to compute values at any longitude. The data are provided on a pressure grid with 24 levels per decade, corresponding to about 1 km vertical resolution. The vertical range of the data is 422 to 0.1 hPa. The precision values are given by the root-mean square of the differences between the estimated fields and the input data.

The data are stored in the version 5 Hierarchical Data Format for the Earth Observing System (HDF-EOS5), which is an extension of the HDF5 format. Each file contains a zonal object with data for the entire mission with separate data
fields for ascending (daytime), descending (nighttime), and combined orbit node. The data arrays have 145 latitude steps (-64 to 80 degrees), 121 pressure steps, 15 Fourier coefficients (mean plus first 7 cosine and 7 sign waves),
and 1151 daily time steps from January 22, 2005 through March 17, 2008. The coefficients are computed at a daily synoptic time of 12:00 UTC.  That time is expressed in TAI-93 seconds (seconds since January 1, 1993) and the date is also stored in separate year, month and day fields. The ascending and descending datasets include LocalSolarTime and SolarZenithAngle values.

Parameters contained in the data files include the following:
Variable Name|Description|Units
O3|Ozone (O3) Volume Mixing Ratio|mol/mol
End of parameter information
The "HIRDLS/Aura Level 3 Temperature Zonal Fourier Coefficients" version 7 data product (H3ZFCT) contains the entire mission (~3 years) of HIRDLS data expressed as zonal Fourier coefficients in 1 degree latitude bands and 121 pressure levels. The coefficients are computed from the HIRDLS Level 2 profiles with a Kalman filter approach using both forward and backward passes in time. Expressed as the mean and up to 7 sine and cosine coefficients (4 waves for ascending and descending, 7 waves for combined), these coefficients may be used to compute values at any longitude. The data are provided on a pressure grid with 24 levels per decade, corresponding to about 1 km vertical resolution. The vertical range of the data is 1000 to 0.0042 hPa. The precision values are given by the root-mean square of the differences between the estimated fields and the input data.

The data are stored in the version 5 Hierarchical Data Format for the Earth Observing System (HDF-EOS5), which is an extension of the HDF5 format. Each file contains a zonal object with data for the entire mission with separate data
fields for ascending (daytime), descending (nighttime), and combined orbit node. The data arrays have 145 latitude steps (-64 to 80 degrees), 121 pressure steps, 15 Fourier coefficients (mean plus first 7 cosine and 7 sign waves),
and 1151 daily time steps from January 22, 2005 through March 17, 2008. The coefficients are computed at a daily synoptic time of 12:00 UTC.  That time is expressed in TAI-93 seconds (seconds since January 1, 1993) and the date is also stored in separate year, month and day fields. The ascending and descending datasets include LocalSolarTime and SolarZenithAngle values.

Parameters contained in the data files include the following:
Variable Name|Description|Units
Temperature|Temperature Profile|K
End of parameter information
The "HIRDLS/Aura Level 3 Water Vapor (H2O) Zonal Fourier Coefficients" version 7 data product (H3ZFCH2O) contains the entire mission (~3 years) of HIRDLS data expressed as zonal Fourier coefficients in 1 degree latitude bands and 121 pressure levels. The coefficients are computed from the HIRDLS Level 2 profiles with a Kalman filter approach using both forward and backward passes in time. Expressed as the mean and up to 7 sine and cosine coefficients (4 waves for ascending and descending, 7 waves for combined), these coefficients may be used to compute values at any longitude. The data are provided on a pressure grid with 24 levels per decade, corresponding to about 1 km vertical resolution. The vertical range of the data is 200 to 10 hPa. The precision values are given by the root-mean square of the differences between the estimated fields and the input data.

The data are stored in the version 5 Hierarchical Data Format for the Earth Observing System (HDF-EOS5), which is an extension of the HDF5 format. Each file contains a zonal object with data for the entire mission with separate data
fields for ascending (daytime), descending (nighttime), and combined orbit node. The data arrays have 145 latitude steps (-64 to 80 degrees), 121 pressure steps, 15 Fourier coefficients (mean plus first 7 cosine and 7 sign waves),
and 1151 daily time steps from January 22, 2005 through March 17, 2008. The coefficients are computed at a daily synoptic time of 12:00 UTC.  That time is expressed in TAI-93 seconds (seconds since January 1, 1993) and the date is also stored in separate year, month and day fields. The ascending and descending datasets include LocalSolarTime and SolarZenithAngle values.

Parameters contained in the data files include the following:
Variable Name|Description|Units
H2O|Water Vapor (H2O) Volume Mixing Ratio|mol/mol
End of parameter information
Daily temperature & rainfall measured on the KSU campus
Daily temperature & rainfall measured on the KSU campus
ABSTRACT: Daily temperature & rainfall measured on the KSU campus
Manhattan, KS. average rainfall measurements for every month since January 1858
Manhattan, KS. average rainfall measurements for every month since January 1858
ABSTRACT: Manhattan, KS. average rainfall measurements for every month since January 1858
<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 Historical Arctic Rawinsonde Archive is on FTP, and it contains millions of vertical soundings of temperature, pressure, humidity, and wind, representing all available rawinsonde ascents from Arctic land stations poleward of 65 degrees North. HARA includes soundings from the beginning of record through mid-1996. Most stations began recording soundings in the late 1950s, but a few began in 1947 or 1948. Coverage is relatively uniform, except for the interior of Greenland. Typically, 20 to 40 levels are available in each sounding. HARA documentation is provided in the FTP directory and in hard copy (NSIDC Special Report 2, 1992). The FTP directory contain software (Fortran and C) for retrieval of sounding data subsets. The original soundings were obtained from the National Center for Atmospheric Research (NCAR), Boulder, Colorado and the National Climatic Data Center (NCDC) of NOAA in Asheville, North Carolina.
<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 Historical Arctic Rawinsonde Archive is on FTP, and it contains millions of vertical soundings of temperature, pressure, humidity, and wind, representing all available rawinsonde ascents from Arctic land stations poleward of 65 degrees North. HARA includes soundings from the beginning of record through mid-1996. Most stations began recording soundings in the late 1950s, but a few began in 1947 or 1948. Coverage is relatively uniform, except for the interior of Greenland. Typically, 20 to 40 levels are available in each sounding. HARA documentation is provided in the FTP directory and in hard copy (NSIDC Special Report 2, 1992). The FTP directory contain software (Fortran and C) for retrieval of sounding data subsets. The original soundings were obtained from the National Center for Atmospheric Research (NCAR), Boulder, Colorado and the National Climatic Data Center (NCDC) of NOAA in Asheville, North Carolina.
<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 Historical Arctic Rawinsonde Archive is on FTP, and it contains millions of vertical soundings of temperature, pressure, humidity, and wind, representing all available rawinsonde ascents from Arctic land stations poleward of 65 degrees North. HARA includes soundings from the beginning of record through mid-1996. Most stations began recording soundings in the late 1950s, but a few began in 1947 or 1948. Coverage is relatively uniform, except for the interior of Greenland. Typically, 20 to 40 levels are available in each sounding. HARA documentation is provided in the FTP directory and in hard copy (NSIDC Special Report 2, 1992). The FTP directory contain software (Fortran and C) for retrieval of sounding data subsets. The original soundings were obtained from the National Center for Atmospheric Research (NCAR), Boulder, Colorado and the National Climatic Data Center (NCDC) of NOAA in Asheville, North Carolina.
IceBridge ATM L1B Elevation and Return Strength
IceBridge ATM L1B Qfit Elevation and Return Strength
IceBridge ATM L2 Elevation, Slope, and Roughness
IceBridge ATM L2 Icessn Elevation, Slope, and Roughness
IceBridge ATM L4 Surface Elevation Rate of Change
IceBridge BGM-3 Gravimeter L1B Time-Tagged Accelerations
IceBridge CMG 1A Dynamic Gravity Meter Timer-Tagged L1B Vertical Accelerations
IceBridge CMG GT-1A Gravimeter L2 Geolocated Free Air Gravity Disturbances
IceBridge DMS L1B Geolocated and Orthorectified Images
IceBridge KT19 IR Surface Temperature
IceBridge MCoRDS L2 Ice Thickness
IceBridge Merged Photon Counting Lidar/Profiler L4 Surface Slope and Elevations
The IceBridge Mission Flight Reports data set contains flight reports from NASA Operation IceBridge Greenland, Arctic, Antarctic, and Alaska missions.  Flight reports contain information on region, mission, aircraft model, flight data, purpose of flight, and on-board sensors. The flight reports were collected as part of Operation IceBridge funded aircraft survey campaigns.  The reports are stored in ASCII text and PDF formats and are available for periodic, ongoing campaigns from 27 March 2009 to the present via FTP.
The IceBridge Mission Flight Reports data set contains flight reports from NASA Operation IceBridge Greenland, Arctic, Antarctic, and Alaska missions.  Flight reports contain information on region, mission, aircraft model, flight data, purpose of flight, and on-board sensors. The flight reports were collected as part of Operation IceBridge funded aircraft survey campaigns.  The reports are stored in ASCII text and PDF formats and are available for periodic, ongoing campaigns from 27 March 2009 to the present via FTP.
The IceBridge Mission Flight Reports data set contains flight reports from NASA Operation IceBridge Greenland, Arctic, Antarctic, and Alaska missions.  Flight reports contain information on region, mission, aircraft model, flight data, purpose of flight, and on-board sensors. The flight reports were collected as part of Operation IceBridge funded aircraft survey campaigns.  The reports are stored in ASCII text and PDF formats and are available for periodic, ongoing campaigns from 27 March 2009 to the present via FTP.
IceBridge Narrow Swath ATM L1B Elevation and Return Strength
IceBridge Narrow Swath ATM L1B Qfit Elevation and Return Strength
IceBridge PARIS L2 Ice Thickness
IceBridge Sander AIRGrav L1B Geolocated Free Air Gravity Anomalies
IceBridge Sea Ice Freeboard, Snow Depth, and Thickness
The NASA IceBridge UAF Lidar Profiler L1B Geolocated Surface Elevation Triplets data set contains surface profiles of Alaska Glaciers acquired using the airborne University of Alaska Fairbanks (UAF) Glacier Lidar system.  The data were collected as part of Operation IceBridge funded aircraft survey campaigns, and are stored in binary las 1.2 format and are available from 22 May 2009 to 02 June 2009 via FTP.
The NASA IceBridge UAF Lidar Profiler L1B Geolocated Surface Elevation Triplets data set contains surface profiles of Alaska Glaciers acquired using the airborne University of Alaska Fairbanks (UAF) Glacier Lidar system.  The data were collected as part of Operation IceBridge funded aircraft survey campaigns, and are stored in binary las 1.2 format and are available from 22 May 2009 to 02 June 2009 via FTP.
The NASA IceBridge UAF Lidar Profiler L1B Geolocated Surface Elevation Triplets data set contains surface profiles of Alaska Glaciers acquired using the airborne University of Alaska Fairbanks (UAF) Glacier Lidar system.  The data were collected as part of Operation IceBridge funded aircraft survey campaigns, and are stored in binary las 1.2 format and are available from 22 May 2009 to 02 June 2009 via FTP.
IceBridge WISE L2 Ice Thickness and Surface Elevation
The Ancillary Data component of the Indicators of Coastal Water Quality Collection includes a 5 arc-minute (approximately 9 x 9 km at the equator) sequence grid, grid cell centroids that relate to the grid cells in the tabular "Indicators of Coastal Water Quality: Change in Chlorophyll-a Concentration 1998-2007" dataset, and a country buffer dataset that is divided by exclusive economic zones (EEZ). The data are produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Ancillary Data component of the Indicators of Coastal Water Quality Collection includes a 5 arc-minute (approximately 9 x 9 km at the equator) sequence grid, grid cell centroids that relate to the grid cells in the tabular "Indicators of Coastal Water Quality: Change in Chlorophyll-a Concentration 1998-2007" dataset, and a country buffer dataset that is divided by exclusive economic zones (EEZ). The data are produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Ancillary Data component of the Indicators of Coastal Water Quality Collection includes a 5 arc-minute (approximately 9 x 9 km at the equator) sequence grid, grid cell centroids that relate to the grid cells in the tabular "Indicators of Coastal Water Quality: Change in Chlorophyll-a Concentration 1998-2007" dataset, and a country buffer dataset that is divided by exclusive economic zones (EEZ). The data are produced by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide data that can assist in the extraction and analysis of chlorophyll-a concentration and trends from global grids.)
The Annual Chlorophyll-a Concentrations component of the Indicators of Coastal Water Quality Collection consists of gridded satellite measurements of chlorophyll-a concentrations (in nanogram/cubic meter) in a band extending between 10 and 100 km from the shoreline. Chlorophyll-a concentrations are derived from NASA's Sea-viewing Wide Field-of-view Sensor (SeaWiFS). The grids are based on annual composites of SeaWiFS satellite data provided by the SeaWiFS Project, NASA/Goddard Space Flight Center and GeoEye in the form of HDF files at a resolution of 5 arc-minutes (approximately 9 x 9 km at the equator). The source files are true-color images generated from sub-sampled, calibrated, Rayleigh-corrected level-2 data, which are derived from raw radiance counts by applying sensor calibration, atmospheric corrections, and bio-optical algorithms. To arrive at chlorophyll-a concentrations, radiance counts were converted using the conversion formula provided as part of the original data files. The gridding is done by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Annual Chlorophyll-a Concentrations component of the Indicators of Coastal Water Quality Collection consists of gridded satellite measurements of chlorophyll-a concentrations (in nanogram/cubic meter) in a band extending between 10 and 100 km from the shoreline. Chlorophyll-a concentrations are derived from NASA's Sea-viewing Wide Field-of-view Sensor (SeaWiFS). The grids are based on annual composites of SeaWiFS satellite data provided by the SeaWiFS Project, NASA/Goddard Space Flight Center and GeoEye in the form of HDF files at a resolution of 5 arc-minutes (approximately 9 x 9 km at the equator). The source files are true-color images generated from sub-sampled, calibrated, Rayleigh-corrected level-2 data, which are derived from raw radiance counts by applying sensor calibration, atmospheric corrections, and bio-optical algorithms. To arrive at chlorophyll-a concentrations, radiance counts were converted using the conversion formula provided as part of the original data files. The gridding is done by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Annual Chlorophyll-a Concentrations component of the Indicators of Coastal Water Quality Collection consists of gridded satellite measurements of chlorophyll-a concentrations (in nanogram/cubic meter) in a band extending between 10 and 100 km from the shoreline. Chlorophyll-a concentrations are derived from NASA's Sea-viewing Wide Field-of-view Sensor (SeaWiFS). The grids are based on annual composites of SeaWiFS satellite data provided by the SeaWiFS Project, NASA/Goddard Space Flight Center and GeoEye in the form of HDF files at a resolution of 5 arc-minutes (approximately 9 x 9 km at the equator). The source files are true-color images generated from sub-sampled, calibrated, Rayleigh-corrected level-2 data, which are derived from raw radiance counts by applying sensor calibration, atmospheric corrections, and bio-optical algorithms. To arrive at chlorophyll-a concentrations, radiance counts were converted using the conversion formula provided as part of the original data files. The gridding is done by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide a gridded version of existing SeaWiFS data in GIS-compatible formats in order to determine concentrations of chlorophyll-a in the coastal water column and to facilitate the integration with other data.)
The Change in Chlorophyll-a Concentrations 1998-2007 component of the Indicators of Coastal Water Quality Collection represents a tabular time series of 

the chlorophyll-a concentrations for each grid cell, derived from the "Indicators of Coastal Water Quality: Annual Chlorophyll-a Concentration 1998-2007" dataset. Chlorophyll-a 

concentrations are derived from NASA's Sea-viewing Wide Field-of-view Sensor (SeaWiFS). The grid cells are organized by country, and the percentage of change from 1998-2007 is calculated 

for each cell. Each time series was assessed with a linear regression, and cells with statistically significant trends in chlorophyll-a concentrations are identified. The rows of the table 

are linked to a sequence grid from the "Indicators of Coastal Water Quality: Ancillary Data" collection to facilitate the mapping of the trend values for selected countries and areas of 

interest. The data are processed and compiled by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Change in Chlorophyll-a Concentrations 1998-2007 component of the Indicators of Coastal Water Quality Collection represents a tabular time series of 

the chlorophyll-a concentrations for each grid cell, derived from the "Indicators of Coastal Water Quality: Annual Chlorophyll-a Concentration 1998-2007" dataset. Chlorophyll-a 

concentrations are derived from NASA's Sea-viewing Wide Field-of-view Sensor (SeaWiFS). The grid cells are organized by country, and the percentage of change from 1998-2007 is calculated 

for each cell. Each time series was assessed with a linear regression, and cells with statistically significant trends in chlorophyll-a concentrations are identified. The rows of the table 

are linked to a sequence grid from the "Indicators of Coastal Water Quality: Ancillary Data" collection to facilitate the mapping of the trend values for selected countries and areas of 

interest. The data are processed and compiled by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Change in Chlorophyll-a Concentrations 1998-2007 component of the Indicators of Coastal Water Quality Collection represents a tabular time series of 

the chlorophyll-a concentrations for each grid cell, derived from the "Indicators of Coastal Water Quality: Annual Chlorophyll-a Concentration 1998-2007" dataset. Chlorophyll-a 

concentrations are derived from NASA's Sea-viewing Wide Field-of-view Sensor (SeaWiFS). The grid cells are organized by country, and the percentage of change from 1998-2007 is calculated 

for each cell. Each time series was assessed with a linear regression, and cells with statistically significant trends in chlorophyll-a concentrations are identified. The rows of the table 

are linked to a sequence grid from the "Indicators of Coastal Water Quality: Ancillary Data" collection to facilitate the mapping of the trend values for selected countries and areas of 

interest. The data are processed and compiled by the Columbia University Center for International Earth Science Information Network (CIESIN).
The National Center for Environmental Prediction/Aviation Weather Center Infrared Global Geostationary Composite data set contains global composite images from the infrared channels of multiple weather satellites in geosynchronous orbit. These satellites include the GMS (Japan), GOES (USA), and Meteosat (Europe).  These imagers span nearly the entire globe with a small gap over India. The data resolution is 14 km spatial with the data remapped into a Mercator projection. The data have not necessarily been cross calibrated between sensors.
The National Center for Environmental Prediction/Aviation Weather Center Infrared Global Geostationary Composite data set contains global composite images from the infrared channels of multiple weather satellites in geosynchronous orbit. These satellites include the GMS (Japan), GOES (USA), and Meteosat (Europe).  These imagers span nearly the entire globe with a small gap over India. The data resolution is 14 km spatial with the data remapped into a Mercator projection. The data have not necessarily been cross calibrated between sensors.
The National Center for Environmental Prediction/Aviation Weather Center Infrared Global Geostationary Composite data set contains global composite images from the infrared channels of multiple weather satellites in geosynchronous orbit. These satellites include the GMS (Japan), GOES (USA), and Meteosat (Europe).  These imagers span nearly the entire globe with a small gap over India. The data resolution is 14 km spatial with the data remapped into a Mercator projection. The data have not necessarily been cross calibrated between sensors.
The World Climate Research Programme (WCRP) International Programme
for Antarctic Buoys (IPAB), through participating research
organizations in various countries, maintains a network of drifting
buoys in the Antarctic sea ice zone to support a better understanding
of sea ice motion, meteorology, and oceanography.  The IPAB Antarctic
Drifting Buoy Data archive, presently spanning the years 1995 to 1998,
includes measurements of buoy position, atmospheric pressure, air
temperature, and sea surface temperature.  Data are organized by daily
and three-hour averages and the raw, instantaneous, non-interpolated
data values.  Data were collected from buoys initially deployed in
three study regions: East Antarctica; the Weddell Sea; and the
Bellingshausen, Amundsen, and Ross Seas.  Data are in ASCII text
format and are available by ftp.  Data updates will become available
as data are processed and new buoys are deployed.
The World Climate Research Programme (WCRP) International Programme
for Antarctic Buoys (IPAB), through participating research
organizations in various countries, maintains a network of drifting
buoys in the Antarctic sea ice zone to support a better understanding
of sea ice motion, meteorology, and oceanography.  The IPAB Antarctic
Drifting Buoy Data archive, presently spanning the years 1995 to 1998,
includes measurements of buoy position, atmospheric pressure, air
temperature, and sea surface temperature.  Data are organized by daily
and three-hour averages and the raw, instantaneous, non-interpolated
data values.  Data were collected from buoys initially deployed in
three study regions: East Antarctica; the Weddell Sea; and the
Bellingshausen, Amundsen, and Ross Seas.  Data are in ASCII text
format and are available by ftp.  Data updates will become available
as data are processed and new buoys are deployed.
The World Climate Research Programme (WCRP) International Programme
for Antarctic Buoys (IPAB), through participating research
organizations in various countries, maintains a network of drifting
buoys in the Antarctic sea ice zone to support a better understanding
of sea ice motion, meteorology, and oceanography.  The IPAB Antarctic
Drifting Buoy Data archive, presently spanning the years 1995 to 1998,
includes measurements of buoy position, atmospheric pressure, air
temperature, and sea surface temperature.  Data are organized by daily
and three-hour averages and the raw, instantaneous, non-interpolated
data values.  Data were collected from buoys initially deployed in
three study regions: East Antarctica; the Weddell Sea; and the
Bellingshausen, Amundsen, and Ross Seas.  Data are in ASCII text
format and are available by ftp.  Data updates will become available
as data are processed and new buoys are deployed.
The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessement Report (AR4) Observed Climate Change Impacts Database contains observed responses to climate change across a wide range of systems as well as regions. These data were taken from the Intergovernmental Panel on Climate Change Fourth Assessment Report and Rosenzweig et al. (2008). It consists of responses in the the physical, terrestrial biological systems and marine-ecosystems. The observations that were selected include data that demonstrate a statistically significant trend in change in either direction in systems related to temperature or other climate change variable, and the is for at least 20 years between 1970 and 2004, although study periods may extend earlier or later. For each observation, the data series is described in terms of system, region, longitude and latitude, dates and duration, statistical significance, type of impact, and whether or not land use was identified as a driving factor. System changes are taken from  about 80 studies (of which about 75 are new since the IPCC Third Assessment Report) containing more than 29,500 data series. Observations in the database are characterized as a change consistent with warming or a change not consistent with warming based on information from the underlying studies. The data is distributed by the Columbia University Center for Earth Science Information Network (CIESIN).
The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessement Report (AR4) Observed Climate Change Impacts Database contains observed responses to climate change across a wide range of systems as well as regions. These data were taken from the Intergovernmental Panel on Climate Change Fourth Assessment Report and Rosenzweig et al. (2008). It consists of responses in the the physical, terrestrial biological systems and marine-ecosystems. The observations that were selected include data that demonstrate a statistically significant trend in change in either direction in systems related to temperature or other climate change variable, and the is for at least 20 years between 1970 and 2004, although study periods may extend earlier or later. For each observation, the data series is described in terms of system, region, longitude and latitude, dates and duration, statistical significance, type of impact, and whether or not land use was identified as a driving factor. System changes are taken from  about 80 studies (of which about 75 are new since the IPCC Third Assessment Report) containing more than 29,500 data series. Observations in the database are characterized as a change consistent with warming or a change not consistent with warming based on information from the underlying studies. The data is distributed by the Columbia University Center for Earth Science Information Network (CIESIN).
The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessement Report (AR4) Observed Climate Change Impacts Database contains observed responses to climate change across a wide range of systems as well as regions. These data were taken from the Intergovernmental Panel on Climate Change Fourth Assessment Report and Rosenzweig et al. (2008). It consists of responses in the the physical, terrestrial biological systems and marine-ecosystems. The observations that were selected include data that demonstrate a statistically significant trend in change in either direction in systems related to temperature or other climate change variable, and the is for at least 20 years between 1970 and 2004, although study periods may extend earlier or later. For each observation, the data series is described in terms of system, region, longitude and latitude, dates and duration, statistical significance, type of impact, and whether or not land use was identified as a driving factor. System changes are taken from  about 80 studies (of which about 75 are new since the IPCC Third Assessment Report) containing more than 29,500 data series. Observations in the database are characterized as a change consistent with warming or a change not consistent with warming based on information from the underlying studies. The data is distributed by the Columbia University Center for Earth Science Information Network (CIESIN).
The Intergovernmental Panel on Climate Change (IPCC) IS92 Emissions Scenarios (A, B, C, D, E, F) Dataset Version 1.1 consists of six global and regional greenhouse gases (GHGs) emissions scenarios projected from 1990 through 2100. The six alternative IPCC scenarios (IS92 A to F) were published in the 1992 Supplementary Report to the IPCC Assessment. These scenarios embodied a wide array of assumptions affecting how future greenhouse gas emissions might evolve in the absence of climate policies beyond those already adopted. The dataset was originally produced by IPCC in 1992, and the digital version was re-edited in 2005 to resolve the discrepancies among versions of the data over years. The definitive version of this dataset is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Intergovernmental Panel on Climate Change (IPCC) IS92 Emissions Scenarios (A, B, C, D, E, F) Dataset Version 1.1 consists of six global and regional greenhouse gases (GHGs) emissions scenarios projected from 1990 through 2100. The six alternative IPCC scenarios (IS92 A to F) were published in the 1992 Supplementary Report to the IPCC Assessment. These scenarios embodied a wide array of assumptions affecting how future greenhouse gas emissions might evolve in the absence of climate policies beyond those already adopted. The dataset was originally produced by IPCC in 1992, and the digital version was re-edited in 2005 to resolve the discrepancies among versions of the data over years. The definitive version of this dataset is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Intergovernmental Panel on Climate Change (IPCC) IS92 Emissions Scenarios (A, B, C, D, E, F) Dataset Version 1.1 consists of six global and regional greenhouse gases (GHGs) emissions scenarios projected from 1990 through 2100. The six alternative IPCC scenarios (IS92 A to F) were published in the 1992 Supplementary Report to the IPCC Assessment. These scenarios embodied a wide array of assumptions affecting how future greenhouse gas emissions might evolve in the absence of climate policies beyond those already adopted. The dataset was originally produced by IPCC in 1992, and the digital version was re-edited in 2005 to resolve the discrepancies among versions of the data over years. The definitive version of this dataset is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide the projections of anthropogenic emissions of gases that have the potential to affect climate change.)
The Intergovernmental Panel on Climate Change (IPCC) Socio-Economic Baseline Dataset consists of population, human development, economic, water resources, land cover, land use, agriculture, food, energy and biodiversity data . This dataset was collated by IPCC from a variety of sources such as The World Bank, United Nations Environment Programme (UNEP), and Food and Agriculture Organization of the United Nations (FAO), and is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Intergovernmental Panel on Climate Change (IPCC) Socio-Economic Baseline Dataset consists of population, human development, economic, water resources, land cover, land use, agriculture, food, energy and biodiversity data . This dataset was collated by IPCC from a variety of sources such as The World Bank, United Nations Environment Programme (UNEP), and Food and Agriculture Organization of the United Nations (FAO), and is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Intergovernmental Panel on Climate Change (IPCC) Socio-Economic Baseline Dataset consists of population, human development, economic, water resources, land cover, land use, agriculture, food, energy and biodiversity data . This dataset was collated by IPCC from a variety of sources such as The World Bank, United Nations Environment Programme (UNEP), and Food and Agriculture Organization of the United Nations (FAO), and is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide a baseline dataset for the evaluation of climate change impact.)
The Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) 1x1 Degree Gridded Emissions Dataset consists of global gridded emissions for greenhouse gases (GHGs) projected every 10 years beginning in 1990 through 2100. The grids are produced for reactive gases Methane (CH4), Carbon Monoxide (CO), Nitrogen Oxides (NOx), and Non-Methane Volatile Organic Compounds (NMVOC), along with Sulfur Dioxide (SO2), based on the IPCC SRES Emissions Scenarios Data Set Version 1.1. This dataset is produced by the IPCC and is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) 1x1 Degree Gridded Emissions Dataset consists of global gridded emissions for greenhouse gases (GHGs) projected every 10 years beginning in 1990 through 2100. The grids are produced for reactive gases Methane (CH4), Carbon Monoxide (CO), Nitrogen Oxides (NOx), and Non-Methane Volatile Organic Compounds (NMVOC), along with Sulfur Dioxide (SO2), based on the IPCC SRES Emissions Scenarios Data Set Version 1.1. This dataset is produced by the IPCC and is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) 1x1 Degree Gridded Emissions Dataset consists of global gridded emissions for greenhouse gases (GHGs) projected every 10 years beginning in 1990 through 2100. The grids are produced for reactive gases Methane (CH4), Carbon Monoxide (CO), Nitrogen Oxides (NOx), and Non-Methane Volatile Organic Compounds (NMVOC), along with Sulfur Dioxide (SO2), based on the IPCC SRES Emissions Scenarios Data Set Version 1.1. This dataset is produced by the IPCC and is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide gridded emissions data that can be used in interdisciplinary studies of the environment.)
The Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) Emissions Scenarios Dataset Version 1.1 consists of 40 global and regional greenhouse gases (GHGs) and sulfur emissions scenarios projected every 10 years beginning in 1990 through 2100. The scenarios are based on extensive assessment of driving forces and emissions in the scenario literature, alternative modeling approaches, and an open process that solicited wide participation and feedback. The scenarios provide the basis for future assessments of climate change and possible response strategies. This dataset is produced by the IPCC and is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) Emissions Scenarios Dataset Version 1.1 consists of 40 global and regional greenhouse gases (GHGs) and sulfur emissions scenarios projected every 10 years beginning in 1990 through 2100. The scenarios are based on extensive assessment of driving forces and emissions in the scenario literature, alternative modeling approaches, and an open process that solicited wide participation and feedback. The scenarios provide the basis for future assessments of climate change and possible response strategies. This dataset is produced by the IPCC and is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) Emissions Scenarios Dataset Version 1.1 consists of 40 global and regional greenhouse gases (GHGs) and sulfur emissions scenarios projected every 10 years beginning in 1990 through 2100. The scenarios are based on extensive assessment of driving forces and emissions in the scenario literature, alternative modeling approaches, and an open process that solicited wide participation and feedback. The scenarios provide the basis for future assessments of climate change and possible response strategies. This dataset is produced by the IPCC and is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide new emissions scenarios for the IPCC Assessment Reports.)
The Intergovernmental Panel on Climate Change (IPCC) Special Report Emissions Scenarios (SRES) Fluor-Gases Emissions Dataset consists of global and regional emissions of Hydrofluorocarbons (HFCs), Perfluorocarbons (PFCs), Sulfur Hexafluoride (SF6), Cholorfluorocarbons (CFCs) and Hydrochlorofluorocarbons (HCFCs) projected every 10 years beginning in 1990 through 2100. This dataset is produced by the IPCC and is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Intergovernmental Panel on Climate Change (IPCC) Special Report Emissions Scenarios (SRES) Fluor-Gases Emissions Dataset consists of global and regional emissions of Hydrofluorocarbons (HFCs), Perfluorocarbons (PFCs), Sulfur Hexafluoride (SF6), Cholorfluorocarbons (CFCs) and Hydrochlorofluorocarbons (HCFCs) projected every 10 years beginning in 1990 through 2100. This dataset is produced by the IPCC and is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
The Intergovernmental Panel on Climate Change (IPCC) Special Report Emissions Scenarios (SRES) Fluor-Gases Emissions Dataset consists of global and regional emissions of Hydrofluorocarbons (HFCs), Perfluorocarbons (PFCs), Sulfur Hexafluoride (SF6), Cholorfluorocarbons (CFCs) and Hydrochlorofluorocarbons (HCFCs) projected every 10 years beginning in 1990 through 2100. This dataset is produced by the IPCC and is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN). (Suggested Usage: To provide fluor-gases emissions data that can be used in interdisciplinary studies of the environment.)
International Satellite Cloud Climatology Project (ISCCP) Ice Snow Product in Native (NAT) Format
International Satellite Cloud Climatology Project (ISCCP) TIROS Operational Vertical Sounder (TOVS) Product in Native (NAT) Format
The Continental Atmospheric CO2 Consumption data set represents gridded estimates for the riverine export of carbon and of sediments based on empirical models. All data exist for the overall continental area in a spatial resolution of 0.5 x 0.5 degree longitude/ latitude. The units are tC/km2/yr for all carbon species, and t/km2/yr for sediment fluxes. There are two data files (*.zip) with this data set which describe the following: dissolved organic carbon (DOC) export, particulate organic carbon (POC) export, bicarbonate export, export of bicarbonate being of atmospheric origin (also called atmospheric CO2 consumption by rock weathering), and sediment export.
The Continental Atmospheric CO2 Consumption data set represents gridded estimates for the riverine export of carbon and of sediments based on empirical models. All data exist for the overall continental area in a spatial resolution of 0.5 x 0.5 degree longitude/ latitude. The units are tC/km2/yr for all carbon species, and t/km2/yr for sediment fluxes. There are two data files (*.zip) with this data set which describe the following: dissolved organic carbon (DOC) export, particulate organic carbon (POC) export, bicarbonate export, export of bicarbonate being of atmospheric origin (also called atmospheric CO2 consumption by rock weathering), and sediment export.
ABSTRACT: The Continental Atmospheric CO2 Consumption data set represents gridded estimates for the riverine export of carbon and of sediments based on empirical models. All data exist for the overall continental area in a spatial resolution of 0.5 x 0.5 degree longitude/ latitude. The units are tC/km2/yr for all carbon species, and t/km2/yr for sediment fluxes. There are two data files (*.zip) with this data set which describe the following: dissolved organic carbon (DOC) export, particulate organic carbon (POC) export, bicarbonate export, export of bicarbonate being of atmospheric origin (also called atmospheric CO2 consumption by rock weathering), and sediment export.
This Albedo and BRDF (Bidirectional Reflectance Distribution Function) data set contains three files containing BRDF parameters, white- sky albedo and black-sky albedo at solar noon for three bands ((350-680nm, 680-3000nm, and 350-30000nm)derived from AVHRR (Advanced Very High Resolution Radiometer). These data are available at spatial resolutions of quarter, half, and one degree. Black-sky albedo (direct beam contribution) and white-sky (Completely diffuse contribution) can be linearly combined as a function of the fraction of diffuse skylight (itself a function of optical depth) to provide an actual or instantaneous albedo at local solar noon.
This Albedo and BRDF (Bidirectional Reflectance Distribution Function) data set contains three files containing BRDF parameters, white- sky albedo and black-sky albedo at solar noon for three bands ((350-680nm, 680-3000nm, and 350-30000nm)derived from AVHRR (Advanced Very High Resolution Radiometer). These data are available at spatial resolutions of quarter, half, and one degree. Black-sky albedo (direct beam contribution) and white-sky (Completely diffuse contribution) can be linearly combined as a function of the fraction of diffuse skylight (itself a function of optical depth) to provide an actual or instantaneous albedo at local solar noon.
ABSTRACT: This Albedo and BRDF (Bidirectional Reflectance Distribution Function) data set contains three files containing BRDF parameters, white- sky albedo and black-sky albedo at solar noon for three bands ((350-680nm, 680-3000nm, and 350-30000nm)derived from AVHRR (Advanced Very High Resolution Radiometer). These data are available at spatial resolutions of quarter, half, and one degree. Black-sky albedo (direct beam contribution) and white-sky (Completely diffuse contribution) can be linearly combined as a function of the fraction of diffuse skylight (itself a function of optical depth) to provide an actual or instantaneous albedo at local solar noon.
This data set contains decadal (1950, 1960, 1970, 1980, 1990 and 1995) estimates of gridded fossil-fuel emissions, expressed in 1,000 metric tons C per year per one degree latitude by one degree longitude. The CO2 emissions are the summed emissions from fossil-fuel burning, hydraulic cement production and gas flaring. The years 1950 to 1990 were developed and compiled using somewhat different procedures and information than the 1995 data. The national annual estimates (Boden et al., 1996) from 1950 to 1990 were allocated to one degree grid cells based on gridded information on national boundaries and political units, and a 1984 gridded human population map (Andres et al., 1996). For the 1995 data, the population data base developed by Li (1996a) and documented by CDIAC (DB1016: Li, 1996b) was used as proxy to grid the 1995 emission estimates. There is one *.zip data file with this data set at 1.0 degree spatial resolution.
This data set contains decadal (1950, 1960, 1970, 1980, 1990 and 1995) estimates of gridded fossil-fuel emissions, expressed in 1,000 metric tons C per year per one degree latitude by one degree longitude. The CO2 emissions are the summed emissions from fossil-fuel burning, hydraulic cement production and gas flaring. The years 1950 to 1990 were developed and compiled using somewhat different procedures and information than the 1995 data. The national annual estimates (Boden et al., 1996) from 1950 to 1990 were allocated to one degree grid cells based on gridded information on national boundaries and political units, and a 1984 gridded human population map (Andres et al., 1996). For the 1995 data, the population data base developed by Li (1996a) and documented by CDIAC (DB1016: Li, 1996b) was used as proxy to grid the 1995 emission estimates. There is one *.zip data file with this data set at 1.0 degree spatial resolution.
ABSTRACT: This data set contains decadal (1950, 1960, 1970, 1980, 1990 and 1995) estimates of gridded fossil-fuel emissions, expressed in 1,000 metric tons C per year per one degree latitude by one degree longitude. The CO2 emissions are the summed emissions from fossil-fuel burning, hydraulic cement production and gas flaring. The years 1950 to 1990 were developed and compiled using somewhat different procedures and information than the 1995 data. The national annual estimates (Boden et al., 1996) from 1950 to 1990 were allocated to one degree grid cells based on gridded information on national boundaries and political units, and a 1984 gridded human population map (Andres et al., 1996). For the 1995 data, the population data base developed by Li (1996a) and documented by CDIAC (DB1016: Li, 1996b) was used as proxy to grid the 1995 emission estimates. There is one *.zip data file with this data set at 1.0 degree spatial resolution.
Carbon dioxide flux and meteorological data for the Harvard Forest, MA (1992-95) and BOREAS Northern Study Area, Old Black Spruce (Alberta, Canada; 1994-95) FLUXNET sites are provided as examples of the larger FLUXNET data archive available at the ORNL Distributed Active Archive Center [ http://daac.ornl.gov/FLUXNET/fluxnet.html]. FLUXNET is a global network of micrometeorological tower sites that use eddy covariance methods to measure the exchanges of carbon dioxide (CO2), water vapor, and energy between terrestrial ecosystem and atmosphere. Gap-filled flux data and meteorological data for half-hourly, daily, weekly, monthly, and annual time intervals are presented for each site and year. There are 6 *.zip files with this data set.
Carbon dioxide flux and meteorological data for the Harvard Forest, MA (1992-95) and BOREAS Northern Study Area, Old Black Spruce (Alberta, Canada; 1994-95) FLUXNET sites are provided as examples of the larger FLUXNET data archive available at the ORNL Distributed Active Archive Center [ http://daac.ornl.gov/FLUXNET/fluxnet.html]. FLUXNET is a global network of micrometeorological tower sites that use eddy covariance methods to measure the exchanges of carbon dioxide (CO2), water vapor, and energy between terrestrial ecosystem and atmosphere. Gap-filled flux data and meteorological data for half-hourly, daily, weekly, monthly, and annual time intervals are presented for each site and year. There are 6 *.zip files with this data set.
ABSTRACT: Carbon dioxide flux and meteorological data for the Harvard Forest, MA (1992-95) and BOREAS Northern Study Area, Old Black Spruce (Alberta, Canada; 1994-95) FLUXNET sites are provided as examples of the larger FLUXNET data archive available at the ORNL Distributed Active Archive Center [ http://daac.ornl.gov/FLUXNET/fluxnet.html]. FLUXNET is a global network of micrometeorological tower sites that use eddy covariance methods to measure the exchanges of carbon dioxide (CO2), water vapor, and energy between terrestrial ecosystem and atmosphere. Gap-filled flux data and meteorological data for half-hourly, daily, weekly, monthly, and annual time intervals are presented for each site and year. There are 6 *.zip files with this data set.
This data set contains a mean monthly climatology for several climate variables averaged over the period from 1961 to 1990,  and constructed from a data set of station 1961-1990 climatological normals, numbering between 19,800 (precipitation) and 3,615 (windspeed; see New et al, 1999 for details). The station data were interpolated as a function of latitude, longitude and elevation using thin-plate splines. The data comprise a suite of climate elements: precipitation, mean, maximum, and minimum  temperature, frost frequency, diurnal temperature range, radiation, wet-day frequency, vapor pressure, wind, and cloud cover. There are 23 files in this data set provided at 0.5 and 1.0 degree spatial resolutions.
This data set contains a mean monthly climatology for several climate variables averaged over the period from 1961 to 1990,  and constructed from a data set of station 1961-1990 climatological normals, numbering between 19,800 (precipitation) and 3,615 (windspeed; see New et al, 1999 for details). The station data were interpolated as a function of latitude, longitude and elevation using thin-plate splines. The data comprise a suite of climate elements: precipitation, mean, maximum, and minimum  temperature, frost frequency, diurnal temperature range, radiation, wet-day frequency, vapor pressure, wind, and cloud cover. There are 23 files in this data set provided at 0.5 and 1.0 degree spatial resolutions.
ABSTRACT: This data set contains a mean monthly climatology for several climate variables averaged over the period from 1961 to 1990,  and constructed from a data set of station 1961-1990 climatological normals, numbering between 19,800 (precipitation) and 3,615 (windspeed; see New et al, 1999 for details). The station data were interpolated as a function of latitude, longitude and elevation using thin-plate splines. The data comprise a suite of climate elements: precipitation, mean, maximum, and minimum  temperature, frost frequency, diurnal temperature range, radiation, wet-day frequency, vapor pressure, wind, and cloud cover. There are 23 files in this data set provided at 0.5 and 1.0 degree spatial resolutions.
This data set contains cloud and meteorology data on a 1.0 degree x 1.0 degree spatial resolution. There are eight data files (*.zip) with this data set for several cloud parameters (monthly only) and meteorological parameters including monthly surface skin temperature, monthly total column ozone, and water vapor burdens for the period 1986-1995. All monthly parameters include files with a monthly mean value, a monthly standard deviation, and monthly minimum and maximum values.
This data set contains cloud and meteorology data on a 1.0 degree x 1.0 degree spatial resolution. There are eight data files (*.zip) with this data set for several cloud parameters (monthly only) and meteorological parameters including monthly surface skin temperature, monthly total column ozone, and water vapor burdens for the period 1986-1995. All monthly parameters include files with a monthly mean value, a monthly standard deviation, and monthly minimum and maximum values.
ABSTRACT: This data set contains cloud and meteorology data on a 1.0 degree x 1.0 degree spatial resolution. There are eight data files (*.zip) with this data set for several cloud parameters (monthly only) and meteorological parameters including monthly surface skin temperature, monthly total column ozone, and water vapor burdens for the period 1986-1995. All monthly parameters include files with a monthly mean value, a monthly standard deviation, and monthly minimum and maximum values.
This data set contains monthly climate time series data created by the Climatic Research Unit (CRU) at the University of East Anglia, U.K.,for every year covering the period 1986 to 1995. This time series is a subset of a larger CRU monthly data set that covers the period of 1901 to 1996.  The data comprise a suite of six climate elements: precipitation, mean temperature, diurnal temperature range, wet-day frequency, vapor pressure, and cloud cover. There are 13 files in this data set provided at 0.5 and 1.0 degree spatial resolutions.
This data set contains monthly climate time series data created by the Climatic Research Unit (CRU) at the University of East Anglia, U.K.,for every year covering the period 1986 to 1995. This time series is a subset of a larger CRU monthly data set that covers the period of 1901 to 1996.  The data comprise a suite of six climate elements: precipitation, mean temperature, diurnal temperature range, wet-day frequency, vapor pressure, and cloud cover. There are 13 files in this data set provided at 0.5 and 1.0 degree spatial resolutions.
ABSTRACT: This data set contains monthly climate time series data created by the Climatic Research Unit (CRU) at the University of East Anglia, U.K.,for every year covering the period 1986 to 1995. This time series is a subset of a larger CRU monthly data set that covers the period of 1901 to 1996.  The data comprise a suite of six climate elements: precipitation, mean temperature, diurnal temperature range, wet-day frequency, vapor pressure, and cloud cover. There are 13 files in this data set provided at 0.5 and 1.0 degree spatial resolutions.
The goals of the Earth Radiation Budget Experiment (ERBE) are (1) to understand the radiation balance between the Sun, Earth, atmosphere, and space and (2) to establish an accurate, long-term baseline data set for detection of climate changes. Earth Radiation Budget (ERB) data are fundamental to the development of realistic climate models and to the understanding of natural and anthropogenic perturbations of the climate system. As part of ERBE, measurements of broadband shortwave radiation reflected from the Earth-atmosphere system were obtained, from which top of atmosphere albedo values were calculated. In addition, values from scenes determined to be free of clouds were analyzed separately and clear-sky albedos were derived.For this study, only the clear-sky albedos are included. The ERBE data sets for the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II contain global, top of atmosphere, clear sky albedo data from January 1986 to February 1990. The original ERBE albedo data at 2.5 degree spatial resolution were re-gridded to a 1 degree spatial resolution by the ISLSCP II staff. Both the original data at 2.5 degree resolution and the 1 degree data set are provided.
The goals of the Earth Radiation Budget Experiment (ERBE) are (1) to understand the radiation balance between the Sun, Earth, atmosphere, and space and (2) to establish an accurate, long-term baseline data set for detection of climate changes. Earth Radiation Budget (ERB) data are fundamental to the development of realistic climate models and to the understanding of natural and anthropogenic perturbations of the climate system. As part of ERBE, measurements of broadband shortwave radiation reflected from the Earth-atmosphere system were obtained, from which top of atmosphere albedo values were calculated. In addition, values from scenes determined to be free of clouds were analyzed separately and clear-sky albedos were derived.For this study, only the clear-sky albedos are included. The ERBE data sets for the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II contain global, top of atmosphere, clear sky albedo data from January 1986 to February 1990. The original ERBE albedo data at 2.5 degree spatial resolution were re-gridded to a 1 degree spatial resolution by the ISLSCP II staff. Both the original data at 2.5 degree resolution and the 1 degree data set are provided.
ABSTRACT: The goals of the Earth Radiation Budget Experiment (ERBE) are (1) to understand the radiation balance between the Sun, Earth, atmosphere, and space and (2) to establish an accurate, long-term baseline data set for detection of climate changes. Earth Radiation Budget (ERB) data are fundamental to the development of realistic climate models and to the understanding of natural and anthropogenic perturbations of the climate system. As part of ERBE, measurements of broadband shortwave radiation reflected from the Earth-atmosphere system were obtained, from which top of atmosphere albedo values were calculated. In addition, values from scenes determined to be free of clouds were analyzed separately and clear-sky albedos were derived.For this study, only the clear-sky albedos are included. The ERBE data sets for the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II contain global, top of atmosphere, clear sky albedo data from January 1986 to February 1990. The original ERBE albedo data at 2.5 degree spatial resolution were re-gridded to a 1 degree spatial resolution by the ISLSCP II staff. Both the original data at 2.5 degree resolution and the 1 degree data set are provided.
This data set for the ISLSCP Initiative II data collection provides meteorology data with fixed, monthly, monthly-6-hourly, 6-hourly, and 3-hourly temporal resolutions. The data were derived from the European Centre for Medium-range Weather Forecasts (ECMWF) near-surface meteorology data set, 40-year re-analysis, or ERA-40 (Simmons and Gibson, 2000), which covers the years 1957 to 2001. The data were processed onto the ISLSCP II Earth grid with a spatial resolution of 1-degree in both latitude and longitude, and span the common ISLSCP II period from 1986 to 1995.The ECMWF forecast system is called the Integrated Forecasting System (IFS) and was developed in co-operation with Meteo-France. For ERA40 it is used with 60 levels from the top of the model at 10 Pa to the lowest level at about 10 m above the surface. There are 46 compressed (.tar.gz) data files with this data set. Each uncompressed file contains space-delimited text (.asc) data files.
This data set for the ISLSCP Initiative II data collection provides meteorology data with fixed, monthly, monthly-6-hourly, 6-hourly, and 3-hourly temporal resolutions. The data were derived from the European Centre for Medium-range Weather Forecasts (ECMWF) near-surface meteorology data set, 40-year re-analysis, or ERA-40 (Simmons and Gibson, 2000), which covers the years 1957 to 2001. The data were processed onto the ISLSCP II Earth grid with a spatial resolution of 1-degree in both latitude and longitude, and span the common ISLSCP II period from 1986 to 1995.The ECMWF forecast system is called the Integrated Forecasting System (IFS) and was developed in co-operation with Meteo-France. For ERA40 it is used with 60 levels from the top of the model at 10 Pa to the lowest level at about 10 m above the surface. There are 46 compressed (.tar.gz) data files with this data set. Each uncompressed file contains space-delimited text (.asc) data files.
ABSTRACT: This data set for the ISLSCP Initiative II data collection provides meteorology data with fixed, monthly, monthly-6-hourly, 6-hourly, and 3-hourly temporal resolutions. The data were derived from the European Centre for Medium-range Weather Forecasts (ECMWF) near-surface meteorology data set, 40-year re-analysis, or ERA-40 (Simmons and Gibson, 2000), which covers the years 1957 to 2001. The data were processed onto the ISLSCP II Earth grid with a spatial resolution of 1-degree in both latitude and longitude, and span the common ISLSCP II period from 1986 to 1995.The ECMWF forecast system is called the Integrated Forecasting System (IFS) and was developed in co-operation with Meteo-France. For ERA40 it is used with 60 levels from the top of the model at 10 Pa to the lowest level at about 10 m above the surface. There are 46 compressed (.tar.gz) data files with this data set. Each uncompressed file contains space-delimited text (.asc) data files.
The EDGAR (Emission Database for Global Atmospheric Research) database project is a comprehensive task carried out jointly by the National Institute for Public Health (RIVM) and the Netherlands Organization for Applied Scientific Research (TNO) and stores global emission inventories of direct and indirect greenhouse gases from anthropogenic sources including halocarbons and aerosols both on a per country and region basis as well as on a grid (see http://www.rivm.nl/edgar/). For the ISLSCP Initiative II data collection, gridded global annual anthropogenic emissions for the greenhouse gases CO2, CH4, N2O are provided on a 1.0 degree by 1.0 degree grid for the years 1970, 1980, 1990, and 1995 and for the tropospheric ozone precursor gases CO, NOx, NMVOC (Non-Methane Volatile Organic Compounds) and SO2 for the years 1990 and 1995. There are 2 *.zip data files with this data set.
The EDGAR (Emission Database for Global Atmospheric Research) database project is a comprehensive task carried out jointly by the National Institute for Public Health (RIVM) and the Netherlands Organization for Applied Scientific Research (TNO) and stores global emission inventories of direct and indirect greenhouse gases from anthropogenic sources including halocarbons and aerosols both on a per country and region basis as well as on a grid (see http://www.rivm.nl/edgar/). For the ISLSCP Initiative II data collection, gridded global annual anthropogenic emissions for the greenhouse gases CO2, CH4, N2O are provided on a 1.0 degree by 1.0 degree grid for the years 1970, 1980, 1990, and 1995 and for the tropospheric ozone precursor gases CO, NOx, NMVOC (Non-Methane Volatile Organic Compounds) and SO2 for the years 1990 and 1995. There are 2 *.zip data files with this data set.
ABSTRACT: The EDGAR (Emission Database for Global Atmospheric Research) database project is a comprehensive task carried out jointly by the National Institute for Public Health (RIVM) and the Netherlands Organization for Applied Scientific Research (TNO) and stores global emission inventories of direct and indirect greenhouse gases from anthropogenic sources including halocarbons and aerosols both on a per country and region basis as well as on a grid (see http://www.rivm.nl/edgar/). For the ISLSCP Initiative II data collection, gridded global annual anthropogenic emissions for the greenhouse gases CO2, CH4, N2O are provided on a 1.0 degree by 1.0 degree grid for the years 1970, 1980, 1990, and 1995 and for the tropospheric ozone precursor gases CO, NOx, NMVOC (Non-Methane Volatile Organic Compounds) and SO2 for the years 1990 and 1995. There are 2 *.zip data files with this data set.
The Fourier-Adjusted, Sensor and Solar zenith angle corrected, Interpolated, Reconstructed (FASIR) adjusted Normalized Difference Vegetation Index (NDVI) data set and derived biophysical parameter fields were generated to provide a 17-year, satellite record of monthly changes in the photosynthetic activity of terrestrial vegetation. This multiple resolution (1/4, 1/2 and 1 degree in latitude and longitude) biophysical parameter data set contains essential variables for the calculation of photosynthesis, and the energy and water exchange between the Earth's surface (in particular of vegetation) and the lower boundary layer of the atmosphere. The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is related to the light absorption and the photosynthetic capacity of vegetation. It also serves as an intermediate variable to calculate vegetation cover fraction (Vcover), total Leaf Area Index (LAI_T), green leaf area index (LAI_G), roughness length (z0), zero plane displacement (d), and snow-free albedo. The biophysical parameters were derived assuming one canopy layer. The production of the FASIR NDVI data set and its associated biophysical parameters was funded by NASA's Land Surface Hydrology program and the Higher Education Funding Council for Wales (HEFCW) as a core component of the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II Data Collection.
The Fourier-Adjusted, Sensor and Solar zenith angle corrected, Interpolated, Reconstructed (FASIR) adjusted Normalized Difference Vegetation Index (NDVI) data set and derived biophysical parameter fields were generated to provide a 17-year, satellite record of monthly changes in the photosynthetic activity of terrestrial vegetation. This multiple resolution (1/4, 1/2 and 1 degree in latitude and longitude) biophysical parameter data set contains essential variables for the calculation of photosynthesis, and the energy and water exchange between the Earth's surface (in particular of vegetation) and the lower boundary layer of the atmosphere. The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is related to the light absorption and the photosynthetic capacity of vegetation. It also serves as an intermediate variable to calculate vegetation cover fraction (Vcover), total Leaf Area Index (LAI_T), green leaf area index (LAI_G), roughness length (z0), zero plane displacement (d), and snow-free albedo. The biophysical parameters were derived assuming one canopy layer. The production of the FASIR NDVI data set and its associated biophysical parameters was funded by NASA's Land Surface Hydrology program and the Higher Education Funding Council for Wales (HEFCW) as a core component of the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II Data Collection.
ABSTRACT: The Fourier-Adjusted, Sensor and Solar zenith angle corrected, Interpolated, Reconstructed (FASIR) adjusted Normalized Difference Vegetation Index (NDVI) data set and derived biophysical parameter fields were generated to provide a 17-year, satellite record of monthly changes in the photosynthetic activity of terrestrial vegetation. This multiple resolution (1/4, 1/2 and 1 degree in latitude and longitude) biophysical parameter data set contains essential variables for the calculation of photosynthesis, and the energy and water exchange between the Earth's surface (in particular of vegetation) and the lower boundary layer of the atmosphere. The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is related to the light absorption and the photosynthetic capacity of vegetation. It also serves as an intermediate variable to calculate vegetation cover fraction (Vcover), total Leaf Area Index (LAI_T), green leaf area index (LAI_G), roughness length (z0), zero plane displacement (d), and snow-free albedo. The biophysical parameters were derived assuming one canopy layer. The production of the FASIR NDVI data set and its associated biophysical parameters was funded by NASA's Land Surface Hydrology program and the Higher Education Funding Council for Wales (HEFCW) as a core component of the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II Data Collection.
The Fourier-Adjusted, Sensor and Solar zenith angle corrected, Interpolated, Reconstructed (FASIR) adjusted Normalized Difference Vegetation Index (NDVI) data sets were generated to provide a 17-year, satellite record of monthly changes in the photosynthetic activity of terrestrial vegetation. FASIR-NDVI data are also used in climate models and biogeochemical models to calculate photosynthesis, the exchange of CO2 between the atmosphere and the land surface, land-surface evapotranspiration and the absorption and release of energy by the land surface. There are three data files provided at spatial resolutions of 0.25, 0.5 and 1.0 degree in latitude and longitude. FASIR adjustments concentrated on reducing NDVI variations arising from atmospheric, calibration, view and illumination geometries and other effects not related to actual vegetation change.FASIR NDVI was also generated to provide inputs for computing a 17-year time series of associated biophysical parameters, provided as a separate data set in this data collection. The production of the FASIR NDVI data set and its associated biophysical parameters was funded by NASA's Land Surface Hydrology program and the Higher Education Funding Council for Wales (HEFCW) as a core component of the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II Data Collection.
The Fourier-Adjusted, Sensor and Solar zenith angle corrected, Interpolated, Reconstructed (FASIR) adjusted Normalized Difference Vegetation Index (NDVI) data sets were generated to provide a 17-year, satellite record of monthly changes in the photosynthetic activity of terrestrial vegetation. FASIR-NDVI data are also used in climate models and biogeochemical models to calculate photosynthesis, the exchange of CO2 between the atmosphere and the land surface, land-surface evapotranspiration and the absorption and release of energy by the land surface. There are three data files provided at spatial resolutions of 0.25, 0.5 and 1.0 degree in latitude and longitude. FASIR adjustments concentrated on reducing NDVI variations arising from atmospheric, calibration, view and illumination geometries and other effects not related to actual vegetation change.FASIR NDVI was also generated to provide inputs for computing a 17-year time series of associated biophysical parameters, provided as a separate data set in this data collection. The production of the FASIR NDVI data set and its associated biophysical parameters was funded by NASA's Land Surface Hydrology program and the Higher Education Funding Council for Wales (HEFCW) as a core component of the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II Data Collection.
ABSTRACT: The Fourier-Adjusted, Sensor and Solar zenith angle corrected, Interpolated, Reconstructed (FASIR) adjusted Normalized Difference Vegetation Index (NDVI) data sets were generated to provide a 17-year, satellite record of monthly changes in the photosynthetic activity of terrestrial vegetation. FASIR-NDVI data are also used in climate models and biogeochemical models to calculate photosynthesis, the exchange of CO2 between the atmosphere and the land surface, land-surface evapotranspiration and the absorption and release of energy by the land surface. There are three data files provided at spatial resolutions of 0.25, 0.5 and 1.0 degree in latitude and longitude. FASIR adjustments concentrated on reducing NDVI variations arising from atmospheric, calibration, view and illumination geometries and other effects not related to actual vegetation change.FASIR NDVI was also generated to provide inputs for computing a 17-year time series of associated biophysical parameters, provided as a separate data set in this data collection. The production of the FASIR NDVI data set and its associated biophysical parameters was funded by NASA's Land Surface Hydrology program and the Higher Education Funding Council for Wales (HEFCW) as a core component of the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II Data Collection.
The objective of this work was to construct a long-term data set of daily precipitation on half degree and one degree latitude/longitude grids over the global land areas. The analyses are defined by interpolating station observations from GTS (Global Telecommunications System) gauges using the algorithm of Shepard (1968). The algorithm of Shepard (1968) has been widely used to interpolate gauge observations of monthly, pentad, and daily precipitation (Rudolf 1993, Xie et al. 1996). This algorithm is used to interpolate the irregularly distributed station observations onto grid points. The weighting coefficients are inversely proportional to the gauge-grid point distance and are adjusted by a cosine function taking into account the directional isolation of each gauge relative to all other nearby gauges. There are 6 data files with this data set.
The objective of this work was to construct a long-term data set of daily precipitation on half degree and one degree latitude/longitude grids over the global land areas. The analyses are defined by interpolating station observations from GTS (Global Telecommunications System) gauges using the algorithm of Shepard (1968). The algorithm of Shepard (1968) has been widely used to interpolate gauge observations of monthly, pentad, and daily precipitation (Rudolf 1993, Xie et al. 1996). This algorithm is used to interpolate the irregularly distributed station observations onto grid points. The weighting coefficients are inversely proportional to the gauge-grid point distance and are adjusted by a cosine function taking into account the directional isolation of each gauge relative to all other nearby gauges. There are 6 data files with this data set.
ABSTRACT: The objective of this work was to construct a long-term data set of daily precipitation on half degree and one degree latitude/longitude grids over the global land areas. The analyses are defined by interpolating station observations from GTS (Global Telecommunications System) gauges using the algorithm of Shepard (1968). The algorithm of Shepard (1968) has been widely used to interpolate gauge observations of monthly, pentad, and daily precipitation (Rudolf 1993, Xie et al. 1996). This algorithm is used to interpolate the irregularly distributed station observations onto grid points. The weighting coefficients are inversely proportional to the gauge-grid point distance and are adjusted by a cosine function taking into account the directional isolation of each gauge relative to all other nearby gauges. There are 6 data files with this data set.
The Global Inventory Modelling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) data sets were generated to provide a 22-year satellite record of monthly changes in terrestrial vegetation. This data set contains three data files provided at spatial resolutions of 0.25, 0.5 and 1.0 degree in latitude and longitude with data from July 1981 through December 2002. New features include reduced NDVI variations arising from calibration, view geometry, volcanic aerosols, and other effects not related to actual vegetation change. In particular, NOAA-9 descending node data from September 1994 to January 1995, volcanic stratospheric aerosol correction for 1982-1984 and 1991-1994, and improved NDVI using empirical mode decomposition/reconstruction (EMD) to minimize effects of orbital drift. Global NDVI was generated to provide inputs for computing the time series of biophysical parameters contained in the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II collection. NDVI is used in climate models and biogeochemical models to calculate photosynthesis, the exchange of CO2 between the atmosphere and the land surface, land-surface evapotranspiration and the absorption and release of energy by the land surface.
The Global Inventory Modelling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) data sets were generated to provide a 22-year satellite record of monthly changes in terrestrial vegetation. This data set contains three data files provided at spatial resolutions of 0.25, 0.5 and 1.0 degree in latitude and longitude with data from July 1981 through December 2002. New features include reduced NDVI variations arising from calibration, view geometry, volcanic aerosols, and other effects not related to actual vegetation change. In particular, NOAA-9 descending node data from September 1994 to January 1995, volcanic stratospheric aerosol correction for 1982-1984 and 1991-1994, and improved NDVI using empirical mode decomposition/reconstruction (EMD) to minimize effects of orbital drift. Global NDVI was generated to provide inputs for computing the time series of biophysical parameters contained in the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II collection. NDVI is used in climate models and biogeochemical models to calculate photosynthesis, the exchange of CO2 between the atmosphere and the land surface, land-surface evapotranspiration and the absorption and release of energy by the land surface.
ABSTRACT: The Global Inventory Modelling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) data sets were generated to provide a 22-year satellite record of monthly changes in terrestrial vegetation. This data set contains three data files provided at spatial resolutions of 0.25, 0.5 and 1.0 degree in latitude and longitude with data from July 1981 through December 2002. New features include reduced NDVI variations arising from calibration, view geometry, volcanic aerosols, and other effects not related to actual vegetation change. In particular, NOAA-9 descending node data from September 1994 to January 1995, volcanic stratospheric aerosol correction for 1982-1984 and 1991-1994, and improved NDVI using empirical mode decomposition/reconstruction (EMD) to minimize effects of orbital drift. Global NDVI was generated to provide inputs for computing the time series of biophysical parameters contained in the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II collection. NDVI is used in climate models and biogeochemical models to calculate photosynthesis, the exchange of CO2 between the atmosphere and the land surface, land-surface evapotranspiration and the absorption and release of energy by the land surface.
The data sets in this directory were provided by Mr. Gregory Yetman and Drs. Stuart Gaffin and Deborah Balk from the Center for International Earth Science Information Network (CIESIN) at Columbia University. There are three data files at three spatial resolutions of 0.25, 0.5 and 1.0 degree in both latitude and longitude and for the reference year of 1990.Estimates of Gross Domestic Product (GDP) are commonly given for nations as a single aggregated number. This data set generates estimates of GDP density distributed subnationally to facilitate the integration of GDP with other data at a sub-national level and to promote interdisciplinary studies that include socioeconomic aspects.  This is one of two coarse resolution Socioeconomic data sets included in the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II data collection, the other being the Gridded Population of the World (GPW), also produced by CIESIN.
The data sets in this directory were provided by Mr. Gregory Yetman and Drs. Stuart Gaffin and Deborah Balk from the Center for International Earth Science Information Network (CIESIN) at Columbia University. There are three data files at three spatial resolutions of 0.25, 0.5 and 1.0 degree in both latitude and longitude and for the reference year of 1990.Estimates of Gross Domestic Product (GDP) are commonly given for nations as a single aggregated number. This data set generates estimates of GDP density distributed subnationally to facilitate the integration of GDP with other data at a sub-national level and to promote interdisciplinary studies that include socioeconomic aspects.  This is one of two coarse resolution Socioeconomic data sets included in the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II data collection, the other being the Gridded Population of the World (GPW), also produced by CIESIN.
ABSTRACT: The data sets in this directory were provided by Mr. Gregory Yetman and Drs. Stuart Gaffin and Deborah Balk from the Center for International Earth Science Information Network (CIESIN) at Columbia University. There are three data files at three spatial resolutions of 0.25, 0.5 and 1.0 degree in both latitude and longitude and for the reference year of 1990.Estimates of Gross Domestic Product (GDP) are commonly given for nations as a single aggregated number. This data set generates estimates of GDP density distributed subnationally to facilitate the integration of GDP with other data at a sub-national level and to promote interdisciplinary studies that include socioeconomic aspects.  This is one of two coarse resolution Socioeconomic data sets included in the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II data collection, the other being the Gridded Population of the World (GPW), also produced by CIESIN.
This data set provides gridded data for selected soil parameters derived from data and methods developed by the Global Soil Data Task, an international collaborative project with the objective of making accurate and appropriate data relating to soil properties accessible to the global change research community. The task was coordinated by the International Geosphere-Biosphere Programme (IGBP-DIS). The data in this data set were produced by the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) staff from data obtained from the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC, http://daac.ornl.gov/). See the related data sets section below. Two-dimensional gridded maps of selected soil parameters, including soil texture, at a 1.0 by 1.0 degree spatial resolution and for two soil depths are provided. All data layers have been adjusted to match the ISLSCP II land/water mask. There are 36 data files with this data set.
This data set provides gridded data for selected soil parameters derived from data and methods developed by the Global Soil Data Task, an international collaborative project with the objective of making accurate and appropriate data relating to soil properties accessible to the global change research community. The task was coordinated by the International Geosphere-Biosphere Programme (IGBP-DIS). The data in this data set were produced by the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) staff from data obtained from the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC, http://daac.ornl.gov/). See the related data sets section below. Two-dimensional gridded maps of selected soil parameters, including soil texture, at a 1.0 by 1.0 degree spatial resolution and for two soil depths are provided. All data layers have been adjusted to match the ISLSCP II land/water mask. There are 36 data files with this data set.
ABSTRACT: This data set provides gridded data for selected soil parameters derived from data and methods developed by the Global Soil Data Task, an international collaborative project with the objective of making accurate and appropriate data relating to soil properties accessible to the global change research community. The task was coordinated by the International Geosphere-Biosphere Programme (IGBP-DIS). The data in this data set were produced by the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) staff from data obtained from the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC, http://daac.ornl.gov/). See the related data sets section below. Two-dimensional gridded maps of selected soil parameters, including soil texture, at a 1.0 by 1.0 degree spatial resolution and for two soil depths are provided. All data layers have been adjusted to match the ISLSCP II land/water mask. There are 36 data files with this data set.
Global Population of the World (GPW) translates census population data to a latitude-longitude grid so that population data may be used in cross-disciplinary studies. There are three data files with this data set for the reference years 1990 and 1995. Over 127,000 administrative units and population counts were collected and integrated from various sources to create the gridded data. In brief, GPW was created using the following steps:    * Population data were estimated for the product reference years, 1990 and 1995, either by the data source or by interpolating or extrapolating the given estimates for other years.    * Additional population estimates were created by adjusting the source population data to match UN national population estimates for the reference years.    * Borders and coastlines of the spatial data were matched to the Digital Chart of the World where appropriate and lakes from the Digital Chart of the World were added.    * The resulting data were then transformed into grids of UN-adjusted and unadjusted population counts for the reference years.    * Grids containing the area of administrative boundary data in each cell (net of lakes) were created and used with the count grids to produce population densities.As with any global data set based on multiple data sources, the spatial and attribute precision of GPW is variable. The level of detail and accuracy, both in time and space, vary among the countries for which data were obtained.
Global Population of the World (GPW) translates census population data to a latitude-longitude grid so that population data may be used in cross-disciplinary studies. There are three data files with this data set for the reference years 1990 and 1995. Over 127,000 administrative units and population counts were collected and integrated from various sources to create the gridded data. In brief, GPW was created using the following steps:    * Population data were estimated for the product reference years, 1990 and 1995, either by the data source or by interpolating or extrapolating the given estimates for other years.    * Additional population estimates were created by adjusting the source population data to match UN national population estimates for the reference years.    * Borders and coastlines of the spatial data were matched to the Digital Chart of the World where appropriate and lakes from the Digital Chart of the World were added.    * The resulting data were then transformed into grids of UN-adjusted and unadjusted population counts for the reference years.    * Grids containing the area of administrative boundary data in each cell (net of lakes) were created and used with the count grids to produce population densities.As with any global data set based on multiple data sources, the spatial and attribute precision of GPW is variable. The level of detail and accuracy, both in time and space, vary among the countries for which data were obtained.
ABSTRACT: Global Population of the World (GPW) translates census population data to a latitude-longitude grid so that population data may be used in cross-disciplinary studies. There are three data files with this data set for the reference years 1990 and 1995. Over 127,000 administrative units and population counts were collected and integrated from various sources to create the gridded data. In brief, GPW was created using the following steps:    * Population data were estimated for the product reference years, 1990 and 1995, either by the data source or by interpolating or extrapolating the given estimates for other years.    * Additional population estimates were created by adjusting the source population data to match UN national population estimates for the reference years.    * Borders and coastlines of the spatial data were matched to the Digital Chart of the World where appropriate and lakes from the Digital Chart of the World were added.    * The resulting data were then transformed into grids of UN-adjusted and unadjusted population counts for the reference years.    * Grids containing the area of administrative boundary data in each cell (net of lakes) were created and used with the count grids to produce population densities.As with any global data set based on multiple data sources, the spatial and attribute precision of GPW is variable. The level of detail and accuracy, both in time and space, vary among the countries for which data were obtained.
The Global Precipitation Climatology Centre (GPCC), which is operated by the Deutscher Wetterdienst (National Meteorological Service of Germany), is a component of the Global Precipitation Climatology Project (GPCP) with the main emphasis on the treatment of the global in-situ observations. The GPCC simultaneously contributes to the Global Climate Observing System (GCOS) and other international research and climate monitoring projects. This rain gauge-only data set was acquired from GPCC and resampled to 0.5 degree grid boxes for use in the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II. The GPCC collects precipitation data which are locally observed at rain gauge stations and distributed as CLIMAT and SYNOP reports via the Global Telecommunication System of the World Weather Watch (GTS) of the World Meteorological Organization (WMO). The Centre acquires additional monthly precipitation data from meteorological and hydrological networks which are operated by national services.
The Global Precipitation Climatology Centre (GPCC), which is operated by the Deutscher Wetterdienst (National Meteorological Service of Germany), is a component of the Global Precipitation Climatology Project (GPCP) with the main emphasis on the treatment of the global in-situ observations. The GPCC simultaneously contributes to the Global Climate Observing System (GCOS) and other international research and climate monitoring projects. This rain gauge-only data set was acquired from GPCC and resampled to 0.5 degree grid boxes for use in the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II. The GPCC collects precipitation data which are locally observed at rain gauge stations and distributed as CLIMAT and SYNOP reports via the Global Telecommunication System of the World Weather Watch (GTS) of the World Meteorological Organization (WMO). The Centre acquires additional monthly precipitation data from meteorological and hydrological networks which are operated by national services.
ABSTRACT: The Global Precipitation Climatology Centre (GPCC), which is operated by the Deutscher Wetterdienst (National Meteorological Service of Germany), is a component of the Global Precipitation Climatology Project (GPCP) with the main emphasis on the treatment of the global in-situ observations. The GPCC simultaneously contributes to the Global Climate Observing System (GCOS) and other international research and climate monitoring projects. This rain gauge-only data set was acquired from GPCC and resampled to 0.5 degree grid boxes for use in the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II. The GPCC collects precipitation data which are locally observed at rain gauge stations and distributed as CLIMAT and SYNOP reports via the Global Telecommunication System of the World Weather Watch (GTS) of the World Meteorological Organization (WMO). The Centre acquires additional monthly precipitation data from meteorological and hydrological networks which are operated by national services.
The Global Precipitation Climatology Project (GPCP) pentad version 1 precipitation data set includes global precipitation rates for 5-day, or pentad, periods. The data sets are derived from measured rain gauge data and merged with satellite estimates of rainfall. This is a portion of the version 1 GPCP pentad data set and covers the ISLSCP II period from 1986 to 1995. The original precipitation rates at 2.5 degrees were re-gridded to a 1 degree spatial resolution by the ISLSCP II staff.
The Global Precipitation Climatology Project (GPCP) pentad version 1 precipitation data set includes global precipitation rates for 5-day, or pentad, periods. The data sets are derived from measured rain gauge data and merged with satellite estimates of rainfall. This is a portion of the version 1 GPCP pentad data set and covers the ISLSCP II period from 1986 to 1995. The original precipitation rates at 2.5 degrees were re-gridded to a 1 degree spatial resolution by the ISLSCP II staff.
ABSTRACT: The Global Precipitation Climatology Project (GPCP) pentad version 1 precipitation data set includes global precipitation rates for 5-day, or pentad, periods. The data sets are derived from measured rain gauge data and merged with satellite estimates of rainfall. This is a portion of the version 1 GPCP pentad data set and covers the ISLSCP II period from 1986 to 1995. The original precipitation rates at 2.5 degrees were re-gridded to a 1 degree spatial resolution by the ISLSCP II staff.
The Global Precipitation Climatology Project (GPCP) Version 2 data set includes global, monthly precipitation rates and associated random errors (RMSE), and a monthly precipitation climatology derived as an average from all GPCP data sets from January 1979 to December 1999. The data are derived from measured gauge data and merged with satellite estimates of rainfall. This is a portion of the version 2 GPCP data and covers the ISLSCP II period from 1986 to 1995. There are six data files included with this data set:  the original precipitation rates, errors and climatology at 2.5 degrees spatial resolution, and the same data  re-gridded to a 1 degree spatial resolution by the ISLSCP II staff.and merged with satellite estimates of rainfall. This is a portion of the version 2 GPCP data sets and covers the ISLSCP II period from 1986 to 1995. There are six data files included with this data set:  the original precipitation rates, errors and climatology at 2.5 degrees spatial resolution, and the same data  re-gridded to a 1 degree spatial resolution by the ISLSCP II staff.
The Global Precipitation Climatology Project (GPCP) Version 2 data set includes global, monthly precipitation rates and associated random errors (RMSE), and a monthly precipitation climatology derived as an average from all GPCP data sets from January 1979 to December 1999. The data are derived from measured gauge data and merged with satellite estimates of rainfall. This is a portion of the version 2 GPCP data and covers the ISLSCP II period from 1986 to 1995. There are six data files included with this data set:  the original precipitation rates, errors and climatology at 2.5 degrees spatial resolution, and the same data  re-gridded to a 1 degree spatial resolution by the ISLSCP II staff.and merged with satellite estimates of rainfall. This is a portion of the version 2 GPCP data sets and covers the ISLSCP II period from 1986 to 1995. There are six data files included with this data set:  the original precipitation rates, errors and climatology at 2.5 degrees spatial resolution, and the same data  re-gridded to a 1 degree spatial resolution by the ISLSCP II staff.
ABSTRACT: The Global Precipitation Climatology Project (GPCP) Version 2 data set includes global, monthly precipitation rates and associated random errors (RMSE), and a monthly precipitation climatology derived as an average from all GPCP data sets from January 1979 to December 1999. The data are derived from measured gauge data and merged with satellite estimates of rainfall. This is a portion of the version 2 GPCP data and covers the ISLSCP II period from 1986 to 1995. There are six data files included with this data set:  the original precipitation rates, errors and climatology at 2.5 degrees spatial resolution, and the same data  re-gridded to a 1 degree spatial resolution by the ISLSCP II staff.and merged with satellite estimates of rainfall. This is a portion of the version 2 GPCP data sets and covers the ISLSCP II period from 1986 to 1995. There are six data files included with this data set:  the original precipitation rates, errors and climatology at 2.5 degrees spatial resolution, and the same data  re-gridded to a 1 degree spatial resolution by the ISLSCP II staff.
Net Primary Production (NPP) is an important component of the carbon cycle and, among the pools and fluxes that make up the cycle, it is one of the steps that are most accessible to field measurement. Direct measurement of NPP is not practical for large areas and so models are generally used to study the carbon cycle at a global scale.  This data set contains 2 *.zip files for above ground and total NPP data.
Net Primary Production (NPP) is an important component of the carbon cycle and, among the pools and fluxes that make up the cycle, it is one of the steps that are most accessible to field measurement. Direct measurement of NPP is not practical for large areas and so models are generally used to study the carbon cycle at a global scale.  This data set contains 2 *.zip files for above ground and total NPP data.
ABSTRACT: Net Primary Production (NPP) is an important component of the carbon cycle and, among the pools and fluxes that make up the cycle, it is one of the steps that are most accessible to field measurement. Direct measurement of NPP is not practical for large areas and so models are generally used to study the carbon cycle at a global scale.  This data set contains 2 *.zip files for above ground and total NPP data.
The River Carbon Flux data set represents estimates for the riverine export of carbon and of sediments. This data set includes the amounts of carbon and of sediments that are discharged to the oceans by rivers for each coastal grid point which receives river inputs. This data set contains three compressed (*.zip) files: the original data at 2.5 x 2.0 degrees, and global maps at spatial resolutions of 0.5 and 1.0 degree which the ISLSCP II staff has created from the original data.
The River Carbon Flux data set represents estimates for the riverine export of carbon and of sediments. This data set includes the amounts of carbon and of sediments that are discharged to the oceans by rivers for each coastal grid point which receives river inputs. This data set contains three compressed (*.zip) files: the original data at 2.5 x 2.0 degrees, and global maps at spatial resolutions of 0.5 and 1.0 degree which the ISLSCP II staff has created from the original data.
ABSTRACT: The River Carbon Flux data set represents estimates for the riverine export of carbon and of sediments. This data set includes the amounts of carbon and of sediments that are discharged to the oceans by rivers for each coastal grid point which receives river inputs. This data set contains three compressed (*.zip) files: the original data at 2.5 x 2.0 degrees, and global maps at spatial resolutions of 0.5 and 1.0 degree which the ISLSCP II staff has created from the original data.
This International Satellite Land Surface Climatology Project (ISLSCP) Initiative II data set is based on the Goddard Space Flight Center (GSFC) Sea Ice Concentrations from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) and the Defense Meteorological Satellites Program (DMSP) Special Sensor Microwave/Imager (SSM/I) Passive Microwave Data. This data set contains four zip files which includes sea ice concentration (in percentage of ocean area covered by sea ice), table data and map data.  These original data were re-gridded by the National Snow and Ice Data Center (NSIDC) from their original 25-km spatial resolution and EASE-Grid into equal angle Earth grids with quarter, half and one degree spatial resolutions in latitude/longitude. The ISLSCP II staff have taken the one degree resolution original data provided by the Principal Investigator and created global maps of monthly sea ice concentration on a global one degree grid using the latitude and longitude coordinates that were provided. Individual monthly files were created and written to the ASCII format. The re-gridded one degree original data were also adjusted to match the one degree ISLSCP II land/water mask.
This International Satellite Land Surface Climatology Project (ISLSCP) Initiative II data set is based on the Goddard Space Flight Center (GSFC) Sea Ice Concentrations from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) and the Defense Meteorological Satellites Program (DMSP) Special Sensor Microwave/Imager (SSM/I) Passive Microwave Data. This data set contains four zip files which includes sea ice concentration (in percentage of ocean area covered by sea ice), table data and map data.  These original data were re-gridded by the National Snow and Ice Data Center (NSIDC) from their original 25-km spatial resolution and EASE-Grid into equal angle Earth grids with quarter, half and one degree spatial resolutions in latitude/longitude. The ISLSCP II staff have taken the one degree resolution original data provided by the Principal Investigator and created global maps of monthly sea ice concentration on a global one degree grid using the latitude and longitude coordinates that were provided. Individual monthly files were created and written to the ASCII format. The re-gridded one degree original data were also adjusted to match the one degree ISLSCP II land/water mask.
ABSTRACT: This International Satellite Land Surface Climatology Project (ISLSCP) Initiative II data set is based on the Goddard Space Flight Center (GSFC) Sea Ice Concentrations from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) and the Defense Meteorological Satellites Program (DMSP) Special Sensor Microwave/Imager (SSM/I) Passive Microwave Data. This data set contains four zip files which includes sea ice concentration (in percentage of ocean area covered by sea ice), table data and map data.  These original data were re-gridded by the National Snow and Ice Data Center (NSIDC) from their original 25-km spatial resolution and EASE-Grid into equal angle Earth grids with quarter, half and one degree spatial resolutions in latitude/longitude. The ISLSCP II staff have taken the one degree resolution original data provided by the Principal Investigator and created global maps of monthly sea ice concentration on a global one degree grid using the latitude and longitude coordinates that were provided. Individual monthly files were created and written to the ASCII format. The re-gridded one degree original data were also adjusted to match the one degree ISLSCP II land/water mask.
The GlobalView Carbon Dioxide (CO2) data product contains synchronized and smoothed time series of atmospheric CO2 concentrations at selected sites that were created using the data extension and integration techniques described by Masarie and Tans, (1995). The information needed to derive this time series is also in this data set, along with extensive documentation. The longest period of coverage is from 1979 to 2001 with some sites having longer or shorter temporal coverage. Note that the GlobalView CO2 data products are derived from measurements but contain no actual data. To facilitate heterogeneous CO2 data use in carbon cycle modeling studies, the measurements have been processed (smoothed, interpolated, and extrapolated) resulting in extended records that are evenly incremented in time. There are 92 files with this data set which includes 89 *.zip data files. The other three files include 2  files with site information, one comma-delimited ASCII file (.csv), and one .dat file, and one .dat file which is a single reference marine boundary layer matrix file which contains CO2 mixing ratios as a function of time and sine of latitude and is a by-product of the data extension procedure.
The GlobalView Carbon Dioxide (CO2) data product contains synchronized and smoothed time series of atmospheric CO2 concentrations at selected sites that were created using the data extension and integration techniques described by Masarie and Tans, (1995). The information needed to derive this time series is also in this data set, along with extensive documentation. The longest period of coverage is from 1979 to 2001 with some sites having longer or shorter temporal coverage. Note that the GlobalView CO2 data products are derived from measurements but contain no actual data. To facilitate heterogeneous CO2 data use in carbon cycle modeling studies, the measurements have been processed (smoothed, interpolated, and extrapolated) resulting in extended records that are evenly incremented in time. There are 92 files with this data set which includes 89 *.zip data files. The other three files include 2  files with site information, one comma-delimited ASCII file (.csv), and one .dat file, and one .dat file which is a single reference marine boundary layer matrix file which contains CO2 mixing ratios as a function of time and sine of latitude and is a by-product of the data extension procedure.
ABSTRACT: The GlobalView Carbon Dioxide (CO2) data product contains synchronized and smoothed time series of atmospheric CO2 concentrations at selected sites that were created using the data extension and integration techniques described by Masarie and Tans, (1995). The information needed to derive this time series is also in this data set, along with extensive documentation. The longest period of coverage is from 1979 to 2001 with some sites having longer or shorter temporal coverage. Note that the GlobalView CO2 data products are derived from measurements but contain no actual data. To facilitate heterogeneous CO2 data use in carbon cycle modeling studies, the measurements have been processed (smoothed, interpolated, and extrapolated) resulting in extended records that are evenly incremented in time. There are 92 files with this data set which includes 89 *.zip data files. The other three files include 2  files with site information, one comma-delimited ASCII file (.csv), and one .dat file, and one .dat file which is a single reference marine boundary layer matrix file which contains CO2 mixing ratios as a function of time and sine of latitude and is a by-product of the data extension procedure.
The GlobalView Methane (CH4) data product contains synchronized and smoothed time series of atmospheric CH4 concentrations at selected sites that were created using the data extension and integration techniques described by Masarie and Tans (1995). The information needed to derive this time series is also in this data set, along with extensive documentation. The longest period of coverage is from 1984 to 1998 with some sites having shorter or longer temporal coverage. Note that the GlobalView-CH4 data products are derived from measurements but contain no actual data. To facilitate heterogeneous CH4 data use in carbon cycle modeling studies, the measurements have been processed (smoothed, interpolated, and extrapolated) resulting in extended records that are evenly incremented in time. There are 74 files with this data set which includes 71 *.zip data files. The other three files include 2 files with site information, one comma-delimited ASCII file (.csv), and one .dat file, and one .dat file which is a single reference marine boundary layer matrix file containing CH4 mixing ratios as a function of time and sine of latitude and is a by-product of the data extension procedure.
The GlobalView Methane (CH4) data product contains synchronized and smoothed time series of atmospheric CH4 concentrations at selected sites that were created using the data extension and integration techniques described by Masarie and Tans (1995). The information needed to derive this time series is also in this data set, along with extensive documentation. The longest period of coverage is from 1984 to 1998 with some sites having shorter or longer temporal coverage. Note that the GlobalView-CH4 data products are derived from measurements but contain no actual data. To facilitate heterogeneous CH4 data use in carbon cycle modeling studies, the measurements have been processed (smoothed, interpolated, and extrapolated) resulting in extended records that are evenly incremented in time. There are 74 files with this data set which includes 71 *.zip data files. The other three files include 2 files with site information, one comma-delimited ASCII file (.csv), and one .dat file, and one .dat file which is a single reference marine boundary layer matrix file containing CH4 mixing ratios as a function of time and sine of latitude and is a by-product of the data extension procedure.
ABSTRACT: The GlobalView Methane (CH4) data product contains synchronized and smoothed time series of atmospheric CH4 concentrations at selected sites that were created using the data extension and integration techniques described by Masarie and Tans (1995). The information needed to derive this time series is also in this data set, along with extensive documentation. The longest period of coverage is from 1984 to 1998 with some sites having shorter or longer temporal coverage. Note that the GlobalView-CH4 data products are derived from measurements but contain no actual data. To facilitate heterogeneous CH4 data use in carbon cycle modeling studies, the measurements have been processed (smoothed, interpolated, and extrapolated) resulting in extended records that are evenly incremented in time. There are 74 files with this data set which includes 71 *.zip data files. The other three files include 2 files with site information, one comma-delimited ASCII file (.csv), and one .dat file, and one .dat file which is a single reference marine boundary layer matrix file containing CH4 mixing ratios as a function of time and sine of latitude and is a by-product of the data extension procedure.
The Global Primary Production Data Initiative (GPPDI) was set up as a Focus 1 activity of the IGBP Data and Information System, a coordinated international program to improve worldwide estimates of terrestrial net primary productivity (NPP) for parameterization, calibration, and validation of NPP models at various scales.The GPPDI data collection contains documented field measurements of NPP for global terrestrial sites compiled from published literature and other extant data sources. The point measurements of NPP were categorized as either Class A, representing intensively studied or well-documented study sites (e.g., with site-specific climate, soils information, etc.), Class B, representing more numerous extensive sites with less documentation and site-specific information available, or Class C, representing regional collections of half-degree latitude-longitude grid cells. This data set in the ISLSCP II collection represents the GPPDI Class B NPP data. The Class B NPP data file contains biomass dynamics, climate, and site-characteristics data georeferenced to each site. There is one ASCII data file with this data set.
The Global Primary Production Data Initiative (GPPDI) was set up as a Focus 1 activity of the IGBP Data and Information System, a coordinated international program to improve worldwide estimates of terrestrial net primary productivity (NPP) for parameterization, calibration, and validation of NPP models at various scales.The GPPDI data collection contains documented field measurements of NPP for global terrestrial sites compiled from published literature and other extant data sources. The point measurements of NPP were categorized as either Class A, representing intensively studied or well-documented study sites (e.g., with site-specific climate, soils information, etc.), Class B, representing more numerous extensive sites with less documentation and site-specific information available, or Class C, representing regional collections of half-degree latitude-longitude grid cells. This data set in the ISLSCP II collection represents the GPPDI Class B NPP data. The Class B NPP data file contains biomass dynamics, climate, and site-characteristics data georeferenced to each site. There is one ASCII data file with this data set.
ABSTRACT: The Global Primary Production Data Initiative (GPPDI) was set up as a Focus 1 activity of the IGBP Data and Information System, a coordinated international program to improve worldwide estimates of terrestrial net primary productivity (NPP) for parameterization, calibration, and validation of NPP models at various scales.The GPPDI data collection contains documented field measurements of NPP for global terrestrial sites compiled from published literature and other extant data sources. The point measurements of NPP were categorized as either Class A, representing intensively studied or well-documented study sites (e.g., with site-specific climate, soils information, etc.), Class B, representing more numerous extensive sites with less documentation and site-specific information available, or Class C, representing regional collections of half-degree latitude-longitude grid cells. This data set in the ISLSCP II collection represents the GPPDI Class B NPP data. The Class B NPP data file contains biomass dynamics, climate, and site-characteristics data georeferenced to each site. There is one ASCII data file with this data set.
The Historical Croplands Cover data set was developed to understand the consequences of historical changes in land use and land cover for ecosystem goods and services. In particular, this data set can be used to study how global changes in cultivated area has influenced climate, biogeochemical cycles, biodiversity, etc. This data set can be used directly within spatially-explicit climate and biogeochemical models.This is a gridded data set describing the fraction of each grid cell in the globe that is occupied by cultivated land from 1700 to 1992. Data layers are provided for every 50 years from 1700 to 1850, every 10 years from 1850 to 1980, and every year from 1986 to 1992.There are two sources of global land cover/land use data. The most recent estimates are derived from satellite measurements, and are available in a spatially-explicit fashion for roughly the last 30 years. The other estimate is based on ground-based sources such as census statistics, land surveys, estimates by historical geographers, etc. These land inventory data are only available at the scale of political units, but have the advantage of being historical. Ramankutty and Foley (1998) derived a spatially-explicit data set of croplands in 1992 by synthesizing remotely-sensed land cover data with contemporary land inventory data. Furthermore, Ramankutty and Foley (1999) extended this data set into the past (back to 1700) using historical land inventory data.The data set should only be used for continental-to-global scale analysis and modeling. The data set captures the broad patterns of cropland change over history, but not necessarily the fine details at local to regional scales - please check the data quality before using it at fine spatial scales. The quality of historical data for the Russian Federation is poor. The quality of data prior to 1850 is poor -- only continental-scale historical data were used for that period.
The Historical Croplands Cover data set was developed to understand the consequences of historical changes in land use and land cover for ecosystem goods and services. In particular, this data set can be used to study how global changes in cultivated area has influenced climate, biogeochemical cycles, biodiversity, etc. This data set can be used directly within spatially-explicit climate and biogeochemical models.This is a gridded data set describing the fraction of each grid cell in the globe that is occupied by cultivated land from 1700 to 1992. Data layers are provided for every 50 years from 1700 to 1850, every 10 years from 1850 to 1980, and every year from 1986 to 1992.There are two sources of global land cover/land use data. The most recent estimates are derived from satellite measurements, and are available in a spatially-explicit fashion for roughly the last 30 years. The other estimate is based on ground-based sources such as census statistics, land surveys, estimates by historical geographers, etc. These land inventory data are only available at the scale of political units, but have the advantage of being historical. Ramankutty and Foley (1998) derived a spatially-explicit data set of croplands in 1992 by synthesizing remotely-sensed land cover data with contemporary land inventory data. Furthermore, Ramankutty and Foley (1999) extended this data set into the past (back to 1700) using historical land inventory data.The data set should only be used for continental-to-global scale analysis and modeling. The data set captures the broad patterns of cropland change over history, but not necessarily the fine details at local to regional scales - please check the data quality before using it at fine spatial scales. The quality of historical data for the Russian Federation is poor. The quality of data prior to 1850 is poor -- only continental-scale historical data were used for that period.
ABSTRACT: The Historical Croplands Cover data set was developed to understand the consequences of historical changes in land use and land cover for ecosystem goods and services. In particular, this data set can be used to study how global changes in cultivated area has influenced climate, biogeochemical cycles, biodiversity, etc. This data set can be used directly within spatially-explicit climate and biogeochemical models.This is a gridded data set describing the fraction of each grid cell in the globe that is occupied by cultivated land from 1700 to 1992. Data layers are provided for every 50 years from 1700 to 1850, every 10 years from 1850 to 1980, and every year from 1986 to 1992.There are two sources of global land cover/land use data. The most recent estimates are derived from satellite measurements, and are available in a spatially-explicit fashion for roughly the last 30 years. The other estimate is based on ground-based sources such as census statistics, land surveys, estimates by historical geographers, etc. These land inventory data are only available at the scale of political units, but have the advantage of being historical. Ramankutty and Foley (1998) derived a spatially-explicit data set of croplands in 1992 by synthesizing remotely-sensed land cover data with contemporary land inventory data. Furthermore, Ramankutty and Foley (1999) extended this data set into the past (back to 1700) using historical land inventory data.The data set should only be used for continental-to-global scale analysis and modeling. The data set captures the broad patterns of cropland change over history, but not necessarily the fine details at local to regional scales - please check the data quality before using it at fine spatial scales. The quality of historical data for the Russian Federation is poor. The quality of data prior to 1850 is poor -- only continental-scale historical data were used for that period.
The Historical Land Cover and Land Use data set was developed to provide the global change community with historical land use estimates. The data set describes historical land use changes over a 300-year historical period (1700-1990).Testing against historical data is an important step for validating integrated models of global environmental change. Owing to long time lags in the climate and biogeochemical systems, these models should aim to simulate the land use dynamics for long periods, i.e., spanning decades to centuries. Developing such models requires an understanding of past and current trends and is therefore strongly data dependent. For this purpose, a historical database of the global environment has been developed: HYDE. Historical statistical inventories on agricultural land (census data, tax records, land surveys, etc) and different spatial analysis techniques were used to create a geographically-explicit data set of land use change, with a regular time interval. The data set can be used to test integrated models of global change. Continental-scale historical data were used for that period.
The Historical Land Cover and Land Use data set was developed to provide the global change community with historical land use estimates. The data set describes historical land use changes over a 300-year historical period (1700-1990).Testing against historical data is an important step for validating integrated models of global environmental change. Owing to long time lags in the climate and biogeochemical systems, these models should aim to simulate the land use dynamics for long periods, i.e., spanning decades to centuries. Developing such models requires an understanding of past and current trends and is therefore strongly data dependent. For this purpose, a historical database of the global environment has been developed: HYDE. Historical statistical inventories on agricultural land (census data, tax records, land surveys, etc) and different spatial analysis techniques were used to create a geographically-explicit data set of land use change, with a regular time interval. The data set can be used to test integrated models of global change. Continental-scale historical data were used for that period.
ABSTRACT: The Historical Land Cover and Land Use data set was developed to provide the global change community with historical land use estimates. The data set describes historical land use changes over a 300-year historical period (1700-1990).Testing against historical data is an important step for validating integrated models of global environmental change. Owing to long time lags in the climate and biogeochemical systems, these models should aim to simulate the land use dynamics for long periods, i.e., spanning decades to centuries. Developing such models requires an understanding of past and current trends and is therefore strongly data dependent. For this purpose, a historical database of the global environment has been developed: HYDE. Historical statistical inventories on agricultural land (census data, tax records, land surveys, etc) and different spatial analysis techniques were used to create a geographically-explicit data set of land use change, with a regular time interval. The data set can be used to test integrated models of global change. Continental-scale historical data were used for that period.
This data set contains coarse scale elevation and elevation-based parameters at 1.0 and 0.5-degree spatial resolutions that were developed to support a wide variety of global modeling activities through the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II data collection. These coarse scale data have sufficient statistical information (up to fourth moment) to allow a good statistical description of the sub-cell distribution of any particular elevation parameter (i.e. elevation, slope and aspect). The database used in the development effort was the HYDRO1k product (http://eros.usgs.gov/#/Find_Data/Products_and_Data_Available/HYDRO1K) with a native spatial resolution of 1 km, the highest resolution database of global coverage of standard elevation-based derivatives (slope, aspect, elevation, compound topographic index, etc.).
This data set contains coarse scale elevation and elevation-based parameters at 1.0 and 0.5-degree spatial resolutions that were developed to support a wide variety of global modeling activities through the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II data collection. These coarse scale data have sufficient statistical information (up to fourth moment) to allow a good statistical description of the sub-cell distribution of any particular elevation parameter (i.e. elevation, slope and aspect). The database used in the development effort was the HYDRO1k product (http://eros.usgs.gov/#/Find_Data/Products_and_Data_Available/HYDRO1K) with a native spatial resolution of 1 km, the highest resolution database of global coverage of standard elevation-based derivatives (slope, aspect, elevation, compound topographic index, etc.).
ABSTRACT: This data set contains coarse scale elevation and elevation-based parameters at 1.0 and 0.5-degree spatial resolutions that were developed to support a wide variety of global modeling activities through the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II data collection. These coarse scale data have sufficient statistical information (up to fourth moment) to allow a good statistical description of the sub-cell distribution of any particular elevation parameter (i.e. elevation, slope and aspect). The database used in the development effort was the HYDRO1k product (http://eros.usgs.gov/#/Find_Data/Products_and_Data_Available/HYDRO1K) with a native spatial resolution of 1 km, the highest resolution database of global coverage of standard elevation-based derivatives (slope, aspect, elevation, compound topographic index, etc.).
This data set contains modeled annual net primary production (NPP) for the land biosphere from seventeen different global models. Annual NPP is defined as the net difference of annual carbon uptake (grams CO2/m2/yr) from the atmosphere through photosynthesis by the land vegetation and that lost back to the atmosphere through autotrophic and maintenance respiration. NPP is also related to the Net Ecosystem Exchange (NEE) of carbon accumulated by or lost from the surface by its vegetation and soils. NPP is NEE plus heterotrophic (decomposition) respiration of the vegetation and soils. Only NPP values are included in this data set as some models did not estimate NEE. Data for the mean, standard deviation and coefficient of variation of NPP for the 17 models are provided at spatial resolutions of 1.0 degree and 0.5 degrees. There are two compressed (*.zip) data files with this data set.
This data set contains modeled annual net primary production (NPP) for the land biosphere from seventeen different global models. Annual NPP is defined as the net difference of annual carbon uptake (grams CO2/m2/yr) from the atmosphere through photosynthesis by the land vegetation and that lost back to the atmosphere through autotrophic and maintenance respiration. NPP is also related to the Net Ecosystem Exchange (NEE) of carbon accumulated by or lost from the surface by its vegetation and soils. NPP is NEE plus heterotrophic (decomposition) respiration of the vegetation and soils. Only NPP values are included in this data set as some models did not estimate NEE. Data for the mean, standard deviation and coefficient of variation of NPP for the 17 models are provided at spatial resolutions of 1.0 degree and 0.5 degrees. There are two compressed (*.zip) data files with this data set.
ABSTRACT: This data set contains modeled annual net primary production (NPP) for the land biosphere from seventeen different global models. Annual NPP is defined as the net difference of annual carbon uptake (grams CO2/m2/yr) from the atmosphere through photosynthesis by the land vegetation and that lost back to the atmosphere through autotrophic and maintenance respiration. NPP is also related to the Net Ecosystem Exchange (NEE) of carbon accumulated by or lost from the surface by its vegetation and soils. NPP is NEE plus heterotrophic (decomposition) respiration of the vegetation and soils. Only NPP values are included in this data set as some models did not estimate NEE. Data for the mean, standard deviation and coefficient of variation of NPP for the 17 models are provided at spatial resolutions of 1.0 degree and 0.5 degrees. There are two compressed (*.zip) data files with this data set.
This data set contains the ISLSCP II fixed land/water masks and percentages of land or water in each cell. There are seven zip data files: four produced from a 1-km land/water mask compiled at the Jet Propulsion Laboratory (JPL) in support of NASA's Earth Observing System;  two files of a land outline overlay created from the land/water mask files created at NASA's Goddard Space Flight Center; and one file which is a latitude grid coordinate file and longitude grid coordinate file produced by the ISLSCP II staff. All of these data are provided at three spatial resolutions of .25, 0.5 and 1-degree in latitude and longitude and on a common Earth grid.
This data set contains the ISLSCP II fixed land/water masks and percentages of land or water in each cell. There are seven zip data files: four produced from a 1-km land/water mask compiled at the Jet Propulsion Laboratory (JPL) in support of NASA's Earth Observing System;  two files of a land outline overlay created from the land/water mask files created at NASA's Goddard Space Flight Center; and one file which is a latitude grid coordinate file and longitude grid coordinate file produced by the ISLSCP II staff. All of these data are provided at three spatial resolutions of .25, 0.5 and 1-degree in latitude and longitude and on a common Earth grid.
ABSTRACT: This data set contains the ISLSCP II fixed land/water masks and percentages of land or water in each cell. There are seven zip data files: four produced from a 1-km land/water mask compiled at the Jet Propulsion Laboratory (JPL) in support of NASA's Earth Observing System;  two files of a land outline overlay created from the land/water mask files created at NASA's Goddard Space Flight Center; and one file which is a latitude grid coordinate file and longitude grid coordinate file produced by the ISLSCP II staff. All of these data are provided at three spatial resolutions of .25, 0.5 and 1-degree in latitude and longitude and on a common Earth grid.
Leaf Area Index (LAI) data from the scientific literature, covering the period from 1932-2000, have been compiled at the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC) to support model development and validation for products from the MODerate Resolution Imaging Spectroradiometer (MODIS) instrument. There is one data file which consists of a spreadsheet table, together with a bibliography of more than 300 original-source references. Although the majority of measurements are from natural or semi-natural ecosystems, some LAI values have been included from crops (limited to a sub-set representing different crops at different stages of development under a range of treatments). Like Net Primary Productivity (NPP), Leaf Area Index (LAI) is a key parameter for global and regional models of biosphere/atmosphere exchange. Modeling and validation of coarse scale satellite measurements both require field measurements to constrain LAI values for different biomes (typical minimum, maximum values, phenology, etc.). Maximum values for point measurements are unlikely to be approached or exceeded by area-weighted LAI, which is what satellites and true spatial models are estimating.
Leaf Area Index (LAI) data from the scientific literature, covering the period from 1932-2000, have been compiled at the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC) to support model development and validation for products from the MODerate Resolution Imaging Spectroradiometer (MODIS) instrument. There is one data file which consists of a spreadsheet table, together with a bibliography of more than 300 original-source references. Although the majority of measurements are from natural or semi-natural ecosystems, some LAI values have been included from crops (limited to a sub-set representing different crops at different stages of development under a range of treatments). Like Net Primary Productivity (NPP), Leaf Area Index (LAI) is a key parameter for global and regional models of biosphere/atmosphere exchange. Modeling and validation of coarse scale satellite measurements both require field measurements to constrain LAI values for different biomes (typical minimum, maximum values, phenology, etc.). Maximum values for point measurements are unlikely to be approached or exceeded by area-weighted LAI, which is what satellites and true spatial models are estimating.
ABSTRACT: Leaf Area Index (LAI) data from the scientific literature, covering the period from 1932-2000, have been compiled at the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC) to support model development and validation for products from the MODerate Resolution Imaging Spectroradiometer (MODIS) instrument. There is one data file which consists of a spreadsheet table, together with a bibliography of more than 300 original-source references. Although the majority of measurements are from natural or semi-natural ecosystems, some LAI values have been included from crops (limited to a sub-set representing different crops at different stages of development under a range of treatments). Like Net Primary Productivity (NPP), Leaf Area Index (LAI) is a key parameter for global and regional models of biosphere/atmosphere exchange. Modeling and validation of coarse scale satellite measurements both require field measurements to constrain LAI values for different biomes (typical minimum, maximum values, phenology, etc.). Maximum values for point measurements are unlikely to be approached or exceeded by area-weighted LAI, which is what satellites and true spatial models are estimating.
The MODIS BRDF/Albedo Product (MOD43B) provides measures of clear sky surface albedo every 16 days. Both white-sky albedo (bihemispherical reflectance) and black-sky albedo (directional hemispherical reflectance) at local solar noon are provided for 7 spectral bands and 3 broadbands. Since black-sky albedo represents the direct beam contribution while white-sky represents the completely diffuse contribution, these measures can be linearly combined as a function of the fraction of diffuse skylight (itself a function of optical depth) to provide an actual or instantaneous albedo at local solar noon.  This data set provides albedo data for the period January 2002 through December 2002.
The MODIS BRDF/Albedo Product (MOD43B) provides measures of clear sky surface albedo every 16 days. Both white-sky albedo (bihemispherical reflectance) and black-sky albedo (directional hemispherical reflectance) at local solar noon are provided for 7 spectral bands and 3 broadbands. Since black-sky albedo represents the direct beam contribution while white-sky represents the completely diffuse contribution, these measures can be linearly combined as a function of the fraction of diffuse skylight (itself a function of optical depth) to provide an actual or instantaneous albedo at local solar noon.  This data set provides albedo data for the period January 2002 through December 2002.
ABSTRACT: The MODIS BRDF/Albedo Product (MOD43B) provides measures of clear sky surface albedo every 16 days. Both white-sky albedo (bihemispherical reflectance) and black-sky albedo (directional hemispherical reflectance) at local solar noon are provided for 7 spectral bands and 3 broadbands. Since black-sky albedo represents the direct beam contribution while white-sky represents the completely diffuse contribution, these measures can be linearly combined as a function of the fraction of diffuse skylight (itself a function of optical depth) to provide an actual or instantaneous albedo at local solar noon.  This data set provides albedo data for the period January 2002 through December 2002.
The objective of the MODIS Land Cover Product is to provide a suite of land cover types useful to global system science modelers by exploiting the information content of MODIS data in the spectral, temporal, spatial, and directional domains.These are global land cover classifications (dominant type, classification confidence and fractional cover) generated using a full year of MODerate Resolution Imaging Spectroradiometer (MODIS) data covering the period from October 2000 to October 2001. These products describe the geographic distribution of the 17 land cover classification scheme proposed by the International Geosphere-Biosphere Programme (IGBP).
The objective of the MODIS Land Cover Product is to provide a suite of land cover types useful to global system science modelers by exploiting the information content of MODIS data in the spectral, temporal, spatial, and directional domains.These are global land cover classifications (dominant type, classification confidence and fractional cover) generated using a full year of MODerate Resolution Imaging Spectroradiometer (MODIS) data covering the period from October 2000 to October 2001. These products describe the geographic distribution of the 17 land cover classification scheme proposed by the International Geosphere-Biosphere Programme (IGBP).
ABSTRACT: The objective of the MODIS Land Cover Product is to provide a suite of land cover types useful to global system science modelers by exploiting the information content of MODIS data in the spectral, temporal, spatial, and directional domains.These are global land cover classifications (dominant type, classification confidence and fractional cover) generated using a full year of MODerate Resolution Imaging Spectroradiometer (MODIS) data covering the period from October 2000 to October 2001. These products describe the geographic distribution of the 17 land cover classification scheme proposed by the International Geosphere-Biosphere Programme (IGBP).
This data set contains monthly average snow-free surface shortwave albedo calculated for the period 1982-1998 and estimates of background soil/litter reflectances in the visible (0.4-0.7 mm) and near-infrared (NIR) (0.7-1.0 mm) wavelengths. Biophysical Parameters derived from the FASIR-NDVI (Fourier Adjusted, Solar zenith angle correction, Interpolation, and Reconstruction of Normalized Difference Vegetation Index) data set developed for the ISLSCP Initiative II data collection for the months of January 1982 through December 1998 were used to calculate monthly mean surface albedos at 1 X 1 degree spatial resolution for vegetated land surfaces (Sellers et al, 1996b) for the wavelength interval from 0.4 to 3.0 mm. The instantaneous albedo is a function of the properties of the land surface and the solar zenith angle. The monthly mean albedo is an average weighted over time weighted by the incident radiation. NDVI data are used to generate the biophysical parameters leaf area index (LAI) and green fraction of vegetation (Greenness) used by the canopy radiative transfer model of the Simple Biosphere (SiB2) model (Sellers et al, 1996a), which computes the instantaneous albedo. This is coupled to the Colorado State University (CSU) General Circulation Model (GCM) (Randall et al, 1989) which integrates the SiB2 radiative transfer through time. The incident radiation for weighting the time-averaged albedo was provided by a previous run of the GCM using the atmospheric radiation parameterization of Harshvardhan et al (1987). The Harshvardhan parameterization models radiative transfer through the atmosphere in both the longwave and shortwave bands, including the effects of cloudiness and water vapor, carbon dioxide and ozone. The shortwave radiation distinguishes between the direct and diffuse components of the solar beam.
This data set contains monthly average snow-free surface shortwave albedo calculated for the period 1982-1998 and estimates of background soil/litter reflectances in the visible (0.4-0.7 mm) and near-infrared (NIR) (0.7-1.0 mm) wavelengths. Biophysical Parameters derived from the FASIR-NDVI (Fourier Adjusted, Solar zenith angle correction, Interpolation, and Reconstruction of Normalized Difference Vegetation Index) data set developed for the ISLSCP Initiative II data collection for the months of January 1982 through December 1998 were used to calculate monthly mean surface albedos at 1 X 1 degree spatial resolution for vegetated land surfaces (Sellers et al, 1996b) for the wavelength interval from 0.4 to 3.0 mm. The instantaneous albedo is a function of the properties of the land surface and the solar zenith angle. The monthly mean albedo is an average weighted over time weighted by the incident radiation. NDVI data are used to generate the biophysical parameters leaf area index (LAI) and green fraction of vegetation (Greenness) used by the canopy radiative transfer model of the Simple Biosphere (SiB2) model (Sellers et al, 1996a), which computes the instantaneous albedo. This is coupled to the Colorado State University (CSU) General Circulation Model (GCM) (Randall et al, 1989) which integrates the SiB2 radiative transfer through time. The incident radiation for weighting the time-averaged albedo was provided by a previous run of the GCM using the atmospheric radiation parameterization of Harshvardhan et al (1987). The Harshvardhan parameterization models radiative transfer through the atmosphere in both the longwave and shortwave bands, including the effects of cloudiness and water vapor, carbon dioxide and ozone. The shortwave radiation distinguishes between the direct and diffuse components of the solar beam.
ABSTRACT: This data set contains monthly average snow-free surface shortwave albedo calculated for the period 1982-1998 and estimates of background soil/litter reflectances in the visible (0.4-0.7 mm) and near-infrared (NIR) (0.7-1.0 mm) wavelengths. Biophysical Parameters derived from the FASIR-NDVI (Fourier Adjusted, Solar zenith angle correction, Interpolation, and Reconstruction of Normalized Difference Vegetation Index) data set developed for the ISLSCP Initiative II data collection for the months of January 1982 through December 1998 were used to calculate monthly mean surface albedos at 1 X 1 degree spatial resolution for vegetated land surfaces (Sellers et al, 1996b) for the wavelength interval from 0.4 to 3.0 mm. The instantaneous albedo is a function of the properties of the land surface and the solar zenith angle. The monthly mean albedo is an average weighted over time weighted by the incident radiation. NDVI data are used to generate the biophysical parameters leaf area index (LAI) and green fraction of vegetation (Greenness) used by the canopy radiative transfer model of the Simple Biosphere (SiB2) model (Sellers et al, 1996a), which computes the instantaneous albedo. This is coupled to the Colorado State University (CSU) General Circulation Model (GCM) (Randall et al, 1989) which integrates the SiB2 radiative transfer through time. The incident radiation for weighting the time-averaged albedo was provided by a previous run of the GCM using the atmospheric radiation parameterization of Harshvardhan et al (1987). The Harshvardhan parameterization models radiative transfer through the atmosphere in both the longwave and shortwave bands, including the effects of cloudiness and water vapor, carbon dioxide and ozone. The shortwave radiation distinguishes between the direct and diffuse components of the solar beam.
The objective of this work was to produce a monthly climatology of broadband surface albedos for use in global numerical weather prediction models at the National Centers for Environmental Prediction (NCEP). Monthly means of clear-sky, surface, broadband, snow-free albedos for overhead sun illumination angle were determined using data from a five-year period from April 1985-December 1987 and January 1989-March 1991. The data set is compatible in temporal coverage and spatial resolution with a monthly climatology of green vegetation fraction (Gutman and Ignatov, 1998) delivered earlier and currently in use at NCEP. Three zip files are provided at three spatial resolutions of quarter, half and on degree, each containing 12 data files in standard ESRI ArcGIS ArcInfo Grid format, and 12 data files in ASCII format denoting defifferences between the original data set and the ISLSCP II Land Sea Mask.
The objective of this work was to produce a monthly climatology of broadband surface albedos for use in global numerical weather prediction models at the National Centers for Environmental Prediction (NCEP). Monthly means of clear-sky, surface, broadband, snow-free albedos for overhead sun illumination angle were determined using data from a five-year period from April 1985-December 1987 and January 1989-March 1991. The data set is compatible in temporal coverage and spatial resolution with a monthly climatology of green vegetation fraction (Gutman and Ignatov, 1998) delivered earlier and currently in use at NCEP. Three zip files are provided at three spatial resolutions of quarter, half and on degree, each containing 12 data files in standard ESRI ArcGIS ArcInfo Grid format, and 12 data files in ASCII format denoting defifferences between the original data set and the ISLSCP II Land Sea Mask.
ABSTRACT: The objective of this work was to produce a monthly climatology of broadband surface albedos for use in global numerical weather prediction models at the National Centers for Environmental Prediction (NCEP). Monthly means of clear-sky, surface, broadband, snow-free albedos for overhead sun illumination angle were determined using data from a five-year period from April 1985-December 1987 and January 1989-March 1991. The data set is compatible in temporal coverage and spatial resolution with a monthly climatology of green vegetation fraction (Gutman and Ignatov, 1998) delivered earlier and currently in use at NCEP. Three zip files are provided at three spatial resolutions of quarter, half and on degree, each containing 12 data files in standard ESRI ArcGIS ArcInfo Grid format, and 12 data files in ASCII format denoting defifferences between the original data set and the ISLSCP II Land Sea Mask.
This ISLSCP data set is derived from the National Snow and Ice Data Center (NSIDC) Northern Hemisphere EASE-Grid Weekly Snow Cover and Sea Ice Extent product which combines snow cover and sea ice extent at weekly intervals for October 1978 through June 2001, and snow cover alone from 1966 through June 2001. The original data set was the first representation of combined snow and sea ice measurements derived from satellite observations for the period of record. Designed to facilitate study of Northern Hemisphere seasonal fluctuations of snow cover and sea ice extent, the original NSIDC data set also includes monthly climatologies describing average extent, probability of occurrence, and variance.This data set shows the extent of snow on the land at a variety of scales (1.0 degree, 0.5 degree, 0.25 degree). The values represent the percentage of days in each month where snow was present -- 100 means 100% of the month, 80 means 80% of the month, etc. There are 4 .zip files provided. Missing data is represented by -99 for water and -88 for land. The data were originally in a yearly tabular format. The file was converted to multi-scale maps by plotting each point in the tabular data onto a map of -99 (water) and -88 (land) created from the standard ISLSCP II Land/Sea Mask.
This ISLSCP data set is derived from the National Snow and Ice Data Center (NSIDC) Northern Hemisphere EASE-Grid Weekly Snow Cover and Sea Ice Extent product which combines snow cover and sea ice extent at weekly intervals for October 1978 through June 2001, and snow cover alone from 1966 through June 2001. The original data set was the first representation of combined snow and sea ice measurements derived from satellite observations for the period of record. Designed to facilitate study of Northern Hemisphere seasonal fluctuations of snow cover and sea ice extent, the original NSIDC data set also includes monthly climatologies describing average extent, probability of occurrence, and variance.This data set shows the extent of snow on the land at a variety of scales (1.0 degree, 0.5 degree, 0.25 degree). The values represent the percentage of days in each month where snow was present -- 100 means 100% of the month, 80 means 80% of the month, etc. There are 4 .zip files provided. Missing data is represented by -99 for water and -88 for land. The data were originally in a yearly tabular format. The file was converted to multi-scale maps by plotting each point in the tabular data onto a map of -99 (water) and -88 (land) created from the standard ISLSCP II Land/Sea Mask.
ABSTRACT: This ISLSCP data set is derived from the National Snow and Ice Data Center (NSIDC) Northern Hemisphere EASE-Grid Weekly Snow Cover and Sea Ice Extent product which combines snow cover and sea ice extent at weekly intervals for October 1978 through June 2001, and snow cover alone from 1966 through June 2001. The original data set was the first representation of combined snow and sea ice measurements derived from satellite observations for the period of record. Designed to facilitate study of Northern Hemisphere seasonal fluctuations of snow cover and sea ice extent, the original NSIDC data set also includes monthly climatologies describing average extent, probability of occurrence, and variance.This data set shows the extent of snow on the land at a variety of scales (1.0 degree, 0.5 degree, 0.25 degree). The values represent the percentage of days in each month where snow was present -- 100 means 100% of the month, 80 means 80% of the month, etc. There are 4 .zip files provided. Missing data is represented by -99 for water and -88 for land. The data were originally in a yearly tabular format. The file was converted to multi-scale maps by plotting each point in the tabular data onto a map of -99 (water) and -88 (land) created from the standard ISLSCP II Land/Sea Mask.
This data set was developed to describe the state of the global land cover in terms of 15 major vegetation types, plus water, before alteration by humans. It forms a complement to the historical croplands data set developed by Ramankutty and Foley (1999). By overlaying the two, one can determine the extent to which natural vegetation has been cleared for cultivation. This data set can be used directly within spatially-explicit climate and biogeochemical models. There are four total files in this data set. Two files contain the land cover types representing potential natural vegetation before human alteration, and two other files contain those points in the original data set submitted by the Principal Investigator that have been modified in order to match the land/water mask of the ISLSCP Initiative II.The geographic distribution of contemporary land cover types can be derived from remotely-sensed data. However, humans now dominate much of the world and there is little evidence of the pre-human-settlement natural vegetation or Potential Natural Vegetation (PNV). PNV, as defined here, does not necessarily represent the world's natural pre-human-disturbance vegetation. Rather, our definition of PNV represents the world's vegetation cover that would most likely exist now in equilibrium with present-day climate and natural disturbance, in the absence of human activities.
This data set was developed to describe the state of the global land cover in terms of 15 major vegetation types, plus water, before alteration by humans. It forms a complement to the historical croplands data set developed by Ramankutty and Foley (1999). By overlaying the two, one can determine the extent to which natural vegetation has been cleared for cultivation. This data set can be used directly within spatially-explicit climate and biogeochemical models. There are four total files in this data set. Two files contain the land cover types representing potential natural vegetation before human alteration, and two other files contain those points in the original data set submitted by the Principal Investigator that have been modified in order to match the land/water mask of the ISLSCP Initiative II.The geographic distribution of contemporary land cover types can be derived from remotely-sensed data. However, humans now dominate much of the world and there is little evidence of the pre-human-settlement natural vegetation or Potential Natural Vegetation (PNV). PNV, as defined here, does not necessarily represent the world's natural pre-human-disturbance vegetation. Rather, our definition of PNV represents the world's vegetation cover that would most likely exist now in equilibrium with present-day climate and natural disturbance, in the absence of human activities.
ABSTRACT: This data set was developed to describe the state of the global land cover in terms of 15 major vegetation types, plus water, before alteration by humans. It forms a complement to the historical croplands data set developed by Ramankutty and Foley (1999). By overlaying the two, one can determine the extent to which natural vegetation has been cleared for cultivation. This data set can be used directly within spatially-explicit climate and biogeochemical models. There are four total files in this data set. Two files contain the land cover types representing potential natural vegetation before human alteration, and two other files contain those points in the original data set submitted by the Principal Investigator that have been modified in order to match the land/water mask of the ISLSCP Initiative II.The geographic distribution of contemporary land cover types can be derived from remotely-sensed data. However, humans now dominate much of the world and there is little evidence of the pre-human-settlement natural vegetation or Potential Natural Vegetation (PNV). PNV, as defined here, does not necessarily represent the world's natural pre-human-disturbance vegetation. Rather, our definition of PNV represents the world's vegetation cover that would most likely exist now in equilibrium with present-day climate and natural disturbance, in the absence of human activities.
The Simulated Topological Network (STN-30p) data set provides the large-scale hydrological modeling community an accurate representation of the global river system at 0.5 degree and 1.0 degree spatial resolutions. STN-30p represents the potential connectivity of the continental land mass by assigning one of eight (E, SE, S, SW, W, NW, N, NE) possible flow directions to each continental grid cell (Jenson 1988, Band 1993). The potentiality of STN-30p reflects the fact that flow direction is assigned to every land cell regardless of the existence of actively flowing rivers. STN-30p can be viewed as a river network which would exist if sufficient surface runoff was available to form river channels everywhere. There are two data files with this data set.
The Simulated Topological Network (STN-30p) data set provides the large-scale hydrological modeling community an accurate representation of the global river system at 0.5 degree and 1.0 degree spatial resolutions. STN-30p represents the potential connectivity of the continental land mass by assigning one of eight (E, SE, S, SW, W, NW, N, NE) possible flow directions to each continental grid cell (Jenson 1988, Band 1993). The potentiality of STN-30p reflects the fact that flow direction is assigned to every land cell regardless of the existence of actively flowing rivers. STN-30p can be viewed as a river network which would exist if sufficient surface runoff was available to form river channels everywhere. There are two data files with this data set.
ABSTRACT: The Simulated Topological Network (STN-30p) data set provides the large-scale hydrological modeling community an accurate representation of the global river system at 0.5 degree and 1.0 degree spatial resolutions. STN-30p represents the potential connectivity of the continental land mass by assigning one of eight (E, SE, S, SW, W, NW, N, NE) possible flow directions to each continental grid cell (Jenson 1988, Band 1993). The potentiality of STN-30p reflects the fact that flow direction is assigned to every land cell regardless of the existence of actively flowing rivers. STN-30p can be viewed as a river network which would exist if sufficient surface runoff was available to form river channels everywhere. There are two data files with this data set.
Sea surface temperature (SST) is an important indicator of the state of the earth climate system as well as a key variable in the coupling between the atmosphere and the ocean. Accurate knowledge of SST is essential for climate monitoring, prediction and research. It is also a key surface boundary condition for numerical weather prediction and for other atmospheric simulations using atmospheric general circulation models and regional models. SST also is important in gas exchange between the ocean and atmosphere, including the air-sea flux of carbon. Gridded SST products have been developed to satisfy these needs. There are 3 .zip files provided with this data set.Gridded monthly and weekly sea surface temperature (SST) and long term SST monthly climatology for the period 1971-2000 are provided here. Weekly normalized error variance fields are also provided with the weekly data. The data are derived using the National Oceanic and Atmospheric Administration (NOAA) Optimum Interpolation (OI) global sea surface temperature analyses that use seven days of in situ (ship and buoy) and satellite SST observations and SST values derived from sea ice concentration. These analyses are produced weekly using optimum interpolation (OI) on a 1-degree grid. The data sets included in the ISLSCP II data collection are produced using version 2 of the OI analyses, called OIv2. In this data set, the ISLSCP II staff have masked land areas based on the ISLSCP II land/water mask. A file describing the differences between the ISLSCP II mask and the original mask used is provided.
Sea surface temperature (SST) is an important indicator of the state of the earth climate system as well as a key variable in the coupling between the atmosphere and the ocean. Accurate knowledge of SST is essential for climate monitoring, prediction and research. It is also a key surface boundary condition for numerical weather prediction and for other atmospheric simulations using atmospheric general circulation models and regional models. SST also is important in gas exchange between the ocean and atmosphere, including the air-sea flux of carbon. Gridded SST products have been developed to satisfy these needs. There are 3 .zip files provided with this data set.Gridded monthly and weekly sea surface temperature (SST) and long term SST monthly climatology for the period 1971-2000 are provided here. Weekly normalized error variance fields are also provided with the weekly data. The data are derived using the National Oceanic and Atmospheric Administration (NOAA) Optimum Interpolation (OI) global sea surface temperature analyses that use seven days of in situ (ship and buoy) and satellite SST observations and SST values derived from sea ice concentration. These analyses are produced weekly using optimum interpolation (OI) on a 1-degree grid. The data sets included in the ISLSCP II data collection are produced using version 2 of the OI analyses, called OIv2. In this data set, the ISLSCP II staff have masked land areas based on the ISLSCP II land/water mask. A file describing the differences between the ISLSCP II mask and the original mask used is provided.
ABSTRACT: Sea surface temperature (SST) is an important indicator of the state of the earth climate system as well as a key variable in the coupling between the atmosphere and the ocean. Accurate knowledge of SST is essential for climate monitoring, prediction and research. It is also a key surface boundary condition for numerical weather prediction and for other atmospheric simulations using atmospheric general circulation models and regional models. SST also is important in gas exchange between the ocean and atmosphere, including the air-sea flux of carbon. Gridded SST products have been developed to satisfy these needs. There are 3 .zip files provided with this data set.Gridded monthly and weekly sea surface temperature (SST) and long term SST monthly climatology for the period 1971-2000 are provided here. Weekly normalized error variance fields are also provided with the weekly data. The data are derived using the National Oceanic and Atmospheric Administration (NOAA) Optimum Interpolation (OI) global sea surface temperature analyses that use seven days of in situ (ship and buoy) and satellite SST observations and SST values derived from sea ice concentration. These analyses are produced weekly using optimum interpolation (OI) on a 1-degree grid. The data sets included in the ISLSCP II data collection are produced using version 2 of the OI analyses, called OIv2. In this data set, the ISLSCP II staff have masked land areas based on the ISLSCP II land/water mask. A file describing the differences between the ISLSCP II mask and the original mask used is provided.
This data set contains 9 files for snow-free, spatially complete 16-day global black-sky albedos at local solar noon, white-sky albedos and quality information based on MODerate Resolution Imaging Spectroradiometer (MODIS) Collection 4 Albedo Products (MOD43B3). Data  are provided for 7 spectral bands and 3 broad bands for a full year of MODIS data (2002). An ecosystem-dependent temporal interpolation technique was developed to fill any missing or seasonally snow-covered data in the official MOD43B3 albedo product. The resulting data set maintains the original resolution and data of the MOD43B3 product while replacing fill values to provide snow-free spatially complete maps.
This data set contains 9 files for snow-free, spatially complete 16-day global black-sky albedos at local solar noon, white-sky albedos and quality information based on MODerate Resolution Imaging Spectroradiometer (MODIS) Collection 4 Albedo Products (MOD43B3). Data  are provided for 7 spectral bands and 3 broad bands for a full year of MODIS data (2002). An ecosystem-dependent temporal interpolation technique was developed to fill any missing or seasonally snow-covered data in the official MOD43B3 albedo product. The resulting data set maintains the original resolution and data of the MOD43B3 product while replacing fill values to provide snow-free spatially complete maps.
ABSTRACT: This data set contains 9 files for snow-free, spatially complete 16-day global black-sky albedos at local solar noon, white-sky albedos and quality information based on MODerate Resolution Imaging Spectroradiometer (MODIS) Collection 4 Albedo Products (MOD43B3). Data  are provided for 7 spectral bands and 3 broad bands for a full year of MODIS data (2002). An ecosystem-dependent temporal interpolation technique was developed to fill any missing or seasonally snow-covered data in the official MOD43B3 albedo product. The resulting data set maintains the original resolution and data of the MOD43B3 product while replacing fill values to provide snow-free spatially complete maps.
This data set contains global Surface Radiation Budget (SRB) and a few top-of-atmosphere (TOA) radiation budget parameters on a 1-degree x 1-degree spatial resolution. These parameters are provided as monthly, monthly-3 hourly (i.e. monthly average for a particular 3 hourly period) and 3-hourly averages. All monthly parameters include files with a monthly mean value, a monthly standard deviation, and monthly minimum and maximum values. The surface and TOA Shortwave (SW) radiative parameters were computed with the Pinker and Laszlo (1992) radiation model. The Longwave (LW) SRB parameters were derived with the Gupta et al. (1992) model. Meteorological inputs for all processing were taken from the Goddard Earth Observing System version 1 (GEOS-1) reanalysis data sets (Schubert et al., 1993) from the Data Assimilation Office (DAO), at NASA Goddard Space Flight Center (GSFC). Required cloud parameters were derived at NASA Langley Research Center (LaRC) from International Satellite Cloud Climatology Project (ISCCP) DX data using the algorithms developed at the NASA Goddard Institute for Space Studies (GISS) (Rossow et al., 1996). Surface albedos are derived internally in the Pinker and Laszlo SW model. There are 30 compressed data files (*.zip) with this data set. When the *.zip files are expanded, there are 114,912 3-hourly files, 42,064 diurnal files, and 6,254 monthly files.
This data set contains global Surface Radiation Budget (SRB) and a few top-of-atmosphere (TOA) radiation budget parameters on a 1-degree x 1-degree spatial resolution. These parameters are provided as monthly, monthly-3 hourly (i.e. monthly average for a particular 3 hourly period) and 3-hourly averages. All monthly parameters include files with a monthly mean value, a monthly standard deviation, and monthly minimum and maximum values. The surface and TOA Shortwave (SW) radiative parameters were computed with the Pinker and Laszlo (1992) radiation model. The Longwave (LW) SRB parameters were derived with the Gupta et al. (1992) model. Meteorological inputs for all processing were taken from the Goddard Earth Observing System version 1 (GEOS-1) reanalysis data sets (Schubert et al., 1993) from the Data Assimilation Office (DAO), at NASA Goddard Space Flight Center (GSFC). Required cloud parameters were derived at NASA Langley Research Center (LaRC) from International Satellite Cloud Climatology Project (ISCCP) DX data using the algorithms developed at the NASA Goddard Institute for Space Studies (GISS) (Rossow et al., 1996). Surface albedos are derived internally in the Pinker and Laszlo SW model. There are 30 compressed data files (*.zip) with this data set. When the *.zip files are expanded, there are 114,912 3-hourly files, 42,064 diurnal files, and 6,254 monthly files.
ABSTRACT: This data set contains global Surface Radiation Budget (SRB) and a few top-of-atmosphere (TOA) radiation budget parameters on a 1-degree x 1-degree spatial resolution. These parameters are provided as monthly, monthly-3 hourly (i.e. monthly average for a particular 3 hourly period) and 3-hourly averages. All monthly parameters include files with a monthly mean value, a monthly standard deviation, and monthly minimum and maximum values. The surface and TOA Shortwave (SW) radiative parameters were computed with the Pinker and Laszlo (1992) radiation model. The Longwave (LW) SRB parameters were derived with the Gupta et al. (1992) model. Meteorological inputs for all processing were taken from the Goddard Earth Observing System version 1 (GEOS-1) reanalysis data sets (Schubert et al., 1993) from the Data Assimilation Office (DAO), at NASA Goddard Space Flight Center (GSFC). Required cloud parameters were derived at NASA Langley Research Center (LaRC) from International Satellite Cloud Climatology Project (ISCCP) DX data using the algorithms developed at the NASA Goddard Institute for Space Studies (GISS) (Rossow et al., 1996). Surface albedos are derived internally in the Pinker and Laszlo SW model. There are 30 compressed data files (*.zip) with this data set. When the *.zip files are expanded, there are 114,912 3-hourly files, 42,064 diurnal files, and 6,254 monthly files.
This data set provides two estimates of the geographic distribution of the total plant-available soil water storage capacity of the rooting zone ("rooting zone water storage size") on a 1.0 degree global grid. Two inverse modeling methods were used. The first modeling approach (optimization) was based on the assumption that vegetation has adapted to the environment such that it makes optimum use of water (Kleidon and Heimann 1998). The second method (assimilation) was based on the assumption that green vegetation indicates sufficient available water for transpiration (Knorr 1997). The data set was developed to provide alternative means to describe rooting characteristics of the global vegetation cover for land surface and climate models in support of the ISLSCP Initiative II data collection. There are three files in this data set.
This data set provides two estimates of the geographic distribution of the total plant-available soil water storage capacity of the rooting zone ("rooting zone water storage size") on a 1.0 degree global grid. Two inverse modeling methods were used. The first modeling approach (optimization) was based on the assumption that vegetation has adapted to the environment such that it makes optimum use of water (Kleidon and Heimann 1998). The second method (assimilation) was based on the assumption that green vegetation indicates sufficient available water for transpiration (Knorr 1997). The data set was developed to provide alternative means to describe rooting characteristics of the global vegetation cover for land surface and climate models in support of the ISLSCP Initiative II data collection. There are three files in this data set.
ABSTRACT: This data set provides two estimates of the geographic distribution of the total plant-available soil water storage capacity of the rooting zone ("rooting zone water storage size") on a 1.0 degree global grid. Two inverse modeling methods were used. The first modeling approach (optimization) was based on the assumption that vegetation has adapted to the environment such that it makes optimum use of water (Kleidon and Heimann 1998). The second method (assimilation) was based on the assumption that green vegetation indicates sufficient available water for transpiration (Knorr 1997). The data set was developed to provide alternative means to describe rooting characteristics of the global vegetation cover for land surface and climate models in support of the ISLSCP Initiative II data collection. There are three files in this data set.
The University of New Hampshire (UNH)/Global Runoff Data Centre (GRDC) composite runoff data combines simulated water balance model runoff estimates derived from climate forcing with monitored river discharge. It can be viewed as a data assimilation applied in a water balance model context (conceptually similar to the commonly used 4DDA techniques used in meteorological modeling). Such a data assimilation scheme preserves the spatial specificity of the water balance calculations while constrained by the more accurate discharge measurement. There are 11 data files in this data set and 1 changemap file which shows the differences between the ISLSCP II land/water mask and the original data set.
The University of New Hampshire (UNH)/Global Runoff Data Centre (GRDC) composite runoff data combines simulated water balance model runoff estimates derived from climate forcing with monitored river discharge. It can be viewed as a data assimilation applied in a water balance model context (conceptually similar to the commonly used 4DDA techniques used in meteorological modeling). Such a data assimilation scheme preserves the spatial specificity of the water balance calculations while constrained by the more accurate discharge measurement. There are 11 data files in this data set and 1 changemap file which shows the differences between the ISLSCP II land/water mask and the original data set.
ABSTRACT: The University of New Hampshire (UNH)/Global Runoff Data Centre (GRDC) composite runoff data combines simulated water balance model runoff estimates derived from climate forcing with monitored river discharge. It can be viewed as a data assimilation applied in a water balance model context (conceptually similar to the commonly used 4DDA techniques used in meteorological modeling). Such a data assimilation scheme preserves the spatial specificity of the water balance calculations while constrained by the more accurate discharge measurement. There are 11 data files in this data set and 1 changemap file which shows the differences between the ISLSCP II land/water mask and the original data set.
The objective of this study was to create a land cover map derived from 1 kilometer AVHRR data using all available bands and derived Normalized Difference Vegetation Index (NDVI) and a full year of data (April 1992-March 1993). This thematic map was resampled to 0.25, 0.5 and 1.0 degree grids for ISLSCP II. During this re-processing, the original University of Maryland (UMD) land cover type and fraction maps were adjusted to match the water/land fraction of the ISLSCP II land/water mask. These maps were generated for use by modelers of global biogeochemical cycles and others in need of an internally consistent, global depiction of land cover. This 1km map was also one of the MODIS (Moderate Resolution Imaging Spectroradiometer) at-launch land cover maps.The data set describes the geographic distributions of 13 classes of vegetation cover (plus water and unclassified classes) based on a modified International Geosphere-Biosphere Programme (IGBP) legend. The data set also provides the fraction of each of the 15 classes within the coarser resolution cells. The data set is provided at three spatial resolutions of 0.25, 0.5 and 1.0 degrees in latitude and longitude. We refer the reader to the reference below for more information on data processing of the original 1km data set.
The objective of this study was to create a land cover map derived from 1 kilometer AVHRR data using all available bands and derived Normalized Difference Vegetation Index (NDVI) and a full year of data (April 1992-March 1993). This thematic map was resampled to 0.25, 0.5 and 1.0 degree grids for ISLSCP II. During this re-processing, the original University of Maryland (UMD) land cover type and fraction maps were adjusted to match the water/land fraction of the ISLSCP II land/water mask. These maps were generated for use by modelers of global biogeochemical cycles and others in need of an internally consistent, global depiction of land cover. This 1km map was also one of the MODIS (Moderate Resolution Imaging Spectroradiometer) at-launch land cover maps.The data set describes the geographic distributions of 13 classes of vegetation cover (plus water and unclassified classes) based on a modified International Geosphere-Biosphere Programme (IGBP) legend. The data set also provides the fraction of each of the 15 classes within the coarser resolution cells. The data set is provided at three spatial resolutions of 0.25, 0.5 and 1.0 degrees in latitude and longitude. We refer the reader to the reference below for more information on data processing of the original 1km data set.
ABSTRACT: The objective of this study was to create a land cover map derived from 1 kilometer AVHRR data using all available bands and derived Normalized Difference Vegetation Index (NDVI) and a full year of data (April 1992-March 1993). This thematic map was resampled to 0.25, 0.5 and 1.0 degree grids for ISLSCP II. During this re-processing, the original University of Maryland (UMD) land cover type and fraction maps were adjusted to match the water/land fraction of the ISLSCP II land/water mask. These maps were generated for use by modelers of global biogeochemical cycles and others in need of an internally consistent, global depiction of land cover. This 1km map was also one of the MODIS (Moderate Resolution Imaging Spectroradiometer) at-launch land cover maps.The data set describes the geographic distributions of 13 classes of vegetation cover (plus water and unclassified classes) based on a modified International Geosphere-Biosphere Programme (IGBP) legend. The data set also provides the fraction of each of the 15 classes within the coarser resolution cells. The data set is provided at three spatial resolutions of 0.25, 0.5 and 1.0 degrees in latitude and longitude. We refer the reader to the reference below for more information on data processing of the original 1km data set.
JERS-1 Standard Beam Data in ASF Frame Size
JERS-1 Standard Beam Data in ASF Frame Size
JERS-1 Standard Beam Data in ASF Frame Size
JERS-1 Standard Beam Data in ASF Frame Size Processed to Level 0
JERS-1 Standard Beam Data in ASF Frame Size Processed to Level 0
JERS-1 Standard Beam Data in ASF Frame Size Processed to Level 0
JERS-1 Standard Beam Data in ASF Frame Size Processed to Level 1
JERS-1 Standard Beam Data in ASF Frame Size Processed to Level 1
JERS-1 Standard Beam Data in ASF Frame Size Processed to Level 1
JERS-1 Standard Beam Data in Full Swath Format
JERS-1 Standard Beam Data in Full Swath Format
JERS-1 Standard Beam Data in Full Swath Format
This data set contains four ISO images of a CD-ROM set from the Japanese Earth Resources Satellite 1 (JERS-1)Synthetic Aperture Radar (SAR) of the National Space Development Agency of Japan (NASDA); in particular, radar images of South America. The data have been "mosaicked" into mosaic tiles; each of which consists of about 50 JERS-1 scenes. The data were acquired between September and December 1995 (low flood season for the reiver) and between May and July of 1996. This data set consitutdes the first-ever high resolution and single season coverage of the entire Amazon river basin and is made possible by the cloud penetrating properties of the radar sensor.In addition, gif imagery of topography and slope from the GTOPO30 Global 30 Arc Second Elevation data set are also included.The CD-ROM contains four volumes, each distributed as a single iso image. Once extrapolated, each CD-ROM has the same documentation, but links to a different set of mosaic tiles.
This data set contains four ISO images of a CD-ROM set from the Japanese Earth Resources Satellite 1 (JERS-1)Synthetic Aperture Radar (SAR) of the National Space Development Agency of Japan (NASDA); in particular, radar images of South America. The data have been "mosaicked" into mosaic tiles; each of which consists of about 50 JERS-1 scenes. The data were acquired between September and December 1995 (low flood season for the reiver) and between May and July of 1996. This data set consitutdes the first-ever high resolution and single season coverage of the entire Amazon river basin and is made possible by the cloud penetrating properties of the radar sensor.In addition, gif imagery of topography and slope from the GTOPO30 Global 30 Arc Second Elevation data set are also included.The CD-ROM contains four volumes, each distributed as a single iso image. Once extrapolated, each CD-ROM has the same documentation, but links to a different set of mosaic tiles.
ABSTRACT: This data set contains four ISO images of a CD-ROM set from the Japanese Earth Resources Satellite 1 (JERS-1)Synthetic Aperture Radar (SAR) of the National Space Development Agency of Japan (NASDA); in particular, radar images of South America. The data have been "mosaicked" into mosaic tiles; each of which consists of about 50 JERS-1 scenes. The data were acquired between September and December 1995 (low flood season for the reiver) and between May and July of 1996. This data set consitutdes the first-ever high resolution and single season coverage of the entire Amazon river basin and is made possible by the cloud penetrating properties of the radar sensor.In addition, gif imagery of topography and slope from the GTOPO30 Global 30 Arc Second Elevation data set are also included.The CD-ROM contains four volumes, each distributed as a single iso image. Once extrapolated, each CD-ROM has the same documentation, but links to a different set of mosaic tiles.
ABSTRACT: This data set contains two image mosaics of L-band radar backscatter and two image mosaics of first order texture. The two backscatter images are mosaics of L-band Radar Backscatter at Horizontal-Horizontal (HH) Polarization created from 1,500 images collected by the Japanese Earth Resources Satellite-1 (JERS-1) Synthetic Aperture Radar (SAR) over the Amazon River Basin as part of the Global Rainforest Mapping Project (GRMP). These backscatter image mosaics were developed using data collected over 62 days from August to November of 1995 for the peak of the dry season and for 62 days from May to June of 1996 during the peak of the wet season. The two image mosaics are at 3 arc-sec resolution. Data provided under this project are resampled images at 30 arc-sec resolution (or about 1 km resolution). For each radar backscatter image, first order texture statistical information was derived and is distributed along with the image mosaic.This data set contains four images each in both geotiff and ENVI formats, provided in eight zip files.  The four files in ENVI file format contain envi in their file name and when extrapolated contain an envi image (*_envi.dat) and an envi image header file (_envi.hdr). The four files in geotiff format contain geotiff  in their file name and when extrapolated contain *.tif and *.tfw file pairs. See Section 2 for more information about the characteristics of these data files.
ABSTRACT: This data set contains two image mosaics of L-band radar backscatter and two image mosaics of first order texture. The two backscatter images are mosaics of L-band Radar Backscatter at Horizontal-Horizontal (HH) Polarization created from 1,500 images collected by the Japanese Earth Resources Satellite-1 (JERS-1) Synthetic Aperture Radar (SAR) over the Amazon River Basin as part of the Global Rainforest Mapping Project (GRMP). These backscatter image mosaics were developed using data collected over 62 days from August to November of 1995 for the peak of the dry season and for 62 days from May to June of 1996 during the peak of the wet season. The two image mosaics are at 3 arc-sec resolution. Data provided under this project are resampled images at 30 arc-sec resolution (or about 1 km resolution). For each radar backscatter image, first order texture statistical information was derived and is distributed along with the image mosaic.This data set contains four images each in both geotiff and ENVI formats, provided in eight zip files.  The four files in ENVI file format contain envi in their file name and when extrapolated contain an envi image (*_envi.dat) and an envi image header file (_envi.hdr). The four files in geotiff format contain geotiff  in their file name and when extrapolated contain *.tif and *.tfw file pairs. See Section 2 for more information about the characteristics of these data files.
ABSTRACT: This data set contains two image mosaics of L-band radar backscatter and two image mosaics of first order texture. The two backscatter images are mosaics of L-band Radar Backscatter at Horizontal-Horizontal (HH) Polarization created from 1,500 images collected by the Japanese Earth Resources Satellite-1 (JERS-1) Synthetic Aperture Radar (SAR) over the Amazon River Basin as part of the Global Rainforest Mapping Project (GRMP). These backscatter image mosaics were developed using data collected over 62 days from August to November of 1995 for the peak of the dry season and for 62 days from May to June of 1996 during the peak of the wet season. The two image mosaics are at 3 arc-sec resolution. Data provided under this project are resampled images at 30 arc-sec resolution (or about 1 km resolution). For each radar backscatter image, first order texture statistical information was derived and is distributed along with the image mosaic.This data set contains four images each in both geotiff and ENVI formats, provided in eight zip files.  The four files in ENVI file format contain envi in their file name and when extrapolated contain an envi image (*_envi.dat) and an envi image header file (_envi.hdr). The four files in geotiff format contain geotiff  in their file name and when extrapolated contain *.tif and *.tfw file pairs. See Section 2 for more information about the characteristics of these data files.
The L4 analysis is based upon nighttime GHRSST L2P subskin SST observations from several satellites and instruments such as: AMSRE, MODIS-Aqua, and MODIS-Terra.
The L4 analysis is based upon nighttime GHRSST L2P subskin SST observations from several satellites and instruments such as: AMSRE, MODIS-Aqua, and MODIS-Terra.
The L4 analysis is based upon nighttime GHRSST L2P subskin SST observations from several satellites and instruments such as: AMSRE, MODIS-Aqua, and MODIS-Terra.
The L4 analysis is based upon nighttime GHRSST L2P subskin SST observations from several satellites and instruments such as: AMSRE, MODIS-Aqua, and MODIS-Terra.
L4 sea surface temperature analysis produced daily on an operational basis by the OurOcean Team, Jet Propulsion Laboratory from MODIS, GOES, AVHRR, AATSR, METOP, MTSAT, SEVIRI, AMSRE, TMI and in situ
L4 sea surface temperature analysis produced daily on an operational basis by the OurOcean Team, Jet Propulsion Laboratory from MODIS, GOES, AVHRR, AATSR, METOP, MTSAT, SEVIRI, AMSRE, TMI and in situ
L4 sea surface temperature analysis produced daily on an operational basis by the OurOcean Team, Jet Propulsion Laboratory from MODIS, GOES, AVHRR, AATSR, METOP, MTSAT, SEVIRI, AMSRE, TMI and in situ
L4 sea surface temperature analysis produced daily on an operational basis by the OurOcean Team, Jet Propulsion Laboratory from MODIS, GOES, AVHRR, AATSR, METOP, MTSAT, SEVIRI, AMSRE, TMI and in situ
The Advanced Ground Based Field Mill (AGBFM) network consists of 34
(31 operational) field mills located at Kennedy Space Center (KSC),
Florida.  The field mills measure the electrostatic vertical field.
This system can measure electrostatic fields in the range of 4 V/m
to 32 kV/m at 10 Hz resolution (digitized at 50 Hz).  Individual
lightning events can be detected within approximately 50 nautical
miles of KSC proper.
The Advanced Ground Based Field Mill (AGBFM) network consists of 34
(31 operational) field mills located at Kennedy Space Center (KSC),
Florida.  The field mills measure the electrostatic vertical field.
This system can measure electrostatic fields in the range of 4 V/m
to 32 kV/m at 10 Hz resolution (digitized at 50 Hz).  Individual
lightning events can be detected within approximately 50 nautical
miles of KSC proper.
The Advanced Ground Based Field Mill (AGBFM) network consists of 34
(31 operational) field mills located at Kennedy Space Center (KSC),
Florida.  The field mills measure the electrostatic vertical field.
This system can measure electrostatic fields in the range of 4 V/m
to 32 kV/m at 10 Hz resolution (digitized at 50 Hz).  Individual
lightning events can be detected within approximately 50 nautical
miles of KSC proper.
LAI and PAR above & below canopy measured with light bar by KSU staff science
LAI and PAR above & below canopy measured with light bar by KSU staff science
ABSTRACT: LAI and PAR above & below canopy measured with light bar by KSU staff science
Light bar data recorded using LICOR LI-191SA Line Quantum Sensor
Light bar data recorded using LICOR LI-191SA Line Quantum Sensor
ABSTRACT: Light bar data recorded using LICOR LI-191SA Line Quantum Sensor
LAI and mean tip angle from LI-COR LAI-2000 Plant Canopy Analyzer
LAI and mean tip angle from LI-COR LAI-2000 Plant Canopy Analyzer
ABSTRACT: LAI and mean tip angle from LI-COR LAI-2000 Plant Canopy Analyzer
The NCAR LSM 1.0 is a land surface model developed to examine biogeophysical and biogeochemical land-atmosphere interactions, especially the effects of land surfaces on climate and atmospheric chemistry. It can be run coupled to an atmospheric model or uncoupled, in a stand-alone mode, if an atmospheric forcing is provided. The model runs on a spatial grid that can range from one point to global. The model was designed for coupling to atmospheric numerical models. Consequently, there is a compromise between computational efficiency and the complexity with which the necessary atmospheric, ecological, and hydrologic processes are parameterized. The model is not meant to be a detailed micrometeorological model, but rather a simplified treatment of surface fluxes that reproduces at minimal computational cost the essential characteristics of land-atmosphere interactions important for climate simulations. The model is a complete executable code with its own time-stepping driver, initialization (subroutine lsmini), and main calling routine (subroutine lsmdrv). When coupled to an atmospheric model, the atmospheric model is the time-stepping driver. There is one call to subroutine lsmini during initialization to initialize all land points in the domain; there is one call per time step to subroutine lsmdrv to calculate surface fluxes and update the ecological, hydrological, and thermal state for all land points in the domain. The model writes its own restart and history files. These can be turned off if appropriate. Available for downloading from the ORNL DAAC are the LMS Model Documentation and User's Guide, the model source code, input data set, and scripts for running the model.  Applications of the model are described in two additional companion files.
The NCAR LSM 1.0 is a land surface model developed to examine biogeophysical and biogeochemical land-atmosphere interactions, especially the effects of land surfaces on climate and atmospheric chemistry. It can be run coupled to an atmospheric model or uncoupled, in a stand-alone mode, if an atmospheric forcing is provided. The model runs on a spatial grid that can range from one point to global. The model was designed for coupling to atmospheric numerical models. Consequently, there is a compromise between computational efficiency and the complexity with which the necessary atmospheric, ecological, and hydrologic processes are parameterized. The model is not meant to be a detailed micrometeorological model, but rather a simplified treatment of surface fluxes that reproduces at minimal computational cost the essential characteristics of land-atmosphere interactions important for climate simulations. The model is a complete executable code with its own time-stepping driver, initialization (subroutine lsmini), and main calling routine (subroutine lsmdrv). When coupled to an atmospheric model, the atmospheric model is the time-stepping driver. There is one call to subroutine lsmini during initialization to initialize all land points in the domain; there is one call per time step to subroutine lsmdrv to calculate surface fluxes and update the ecological, hydrological, and thermal state for all land points in the domain. The model writes its own restart and history files. These can be turned off if appropriate. Available for downloading from the ORNL DAAC are the LMS Model Documentation and User's Guide, the model source code, input data set, and scripts for running the model.  Applications of the model are described in two additional companion files.
ABSTRACT: The NCAR LSM 1.0 is a land surface model developed to examine biogeophysical and biogeochemical land-atmosphere interactions, especially the effects of land surfaces on climate and atmospheric chemistry. It can be run coupled to an atmospheric model or uncoupled, in a stand-alone mode, if an atmospheric forcing is provided. The model runs on a spatial grid that can range from one point to global. The model was designed for coupling to atmospheric numerical models. Consequently, there is a compromise between computational efficiency and the complexity with which the necessary atmospheric, ecological, and hydrologic processes are parameterized. The model is not meant to be a detailed micrometeorological model, but rather a simplified treatment of surface fluxes that reproduces at minimal computational cost the essential characteristics of land-atmosphere interactions important for climate simulations. The model is a complete executable code with its own time-stepping driver, initialization (subroutine lsmini), and main calling routine (subroutine lsmdrv). When coupled to an atmospheric model, the atmospheric model is the time-stepping driver. There is one call to subroutine lsmini during initialization to initialize all land points in the domain; there is one call per time step to subroutine lsmdrv to calculate surface fluxes and update the ecological, hydrological, and thermal state for all land points in the domain. The model writes its own restart and history files. These can be turned off if appropriate. Available for downloading from the ORNL DAAC are the LMS Model Documentation and User's Guide, the model source code, input data set, and scripts for running the model.  Applications of the model are described in two additional companion files.
Abstract: The Landsat Multispectral Scanner (MSS) was a sensor 
                onboard Landsats 1 through 5 and acquired images of the Earth nearly continuously 
                from July 1972 to October 1992, with an 18-day repeat cycle for Landsats 1 through 3 
                and a 16-day repeat cycle for Landsats 4 and 5.                  
                Landsat MSS image data consist of four spectral bands (band designations), although 
                the specific band designations changed between Landsats 1-3 and Landsats 4-5. The 
                resolution for all bands of 79 m, and approximate scene size is 170 km north-south by 
                185 km east-west (106 mi by 115 miles).
                Systematic Correction (Level 1G) includes both radiometric and geometric correction. 
                The scene will be rotated aligned, and georeferenced to a user-specified map projection. 
                Precision Correction (Level 1P) includes radiometric and geometric correction, as well as 
                the use of ground control points (GCPs) to improve accuracy. For locations outside the 
                United States, accuracy of the precision corrected product will depend on the availability 
                of local GCPs. 
                Terrain Correction (Level 1T) includes radiometric, geometric, and precision correction, 
                as well as the use of a digital elevation model (DEM) to improve the satellite model and 
                to correct for relief displacement caused by local terrain. For locations outside the United 
                States, the accuracy of a terrain-corrected product will depend on the availability of local 
                ground control points (GCPs), as well as the quality of the best available DEM.
Abstract: The Landsat Enhanced Thematic Mapper Plus (ETM+) is a sensor
                carried onboard the Landsat 7 satellite and has acquired images of the Earth nearly
                continuously since July 1999, with a 16-day repeat cycle. Landsat ETM+ image data
                consist of eight spectral bands (band designations), with a spatial resolution of 30
                meters for bands 1 to 5 and band 7. Resolution for band 6 (thermal infrared) is 60
                meters and resolution for band 8 (panchromatic) is 15 meters. Approximate scene size
                is 170 km north-south by 183 km east-west (106 mi by 114 mi). The Level 0R data
                product is reformatted raw data. Reformatting involves shifting pixels by integer
                amounts to correct for three effects: 1) the alternating forward-reverse scanning
                pattern of the Landsat ETM+ sensor; 2) the odd-even detector arrangement within each
                band; and 3) the detector offsets inherent in engineering design of the focal plane
                array. Pixels in L0R images are not resampled, nor are they geometrically corrected
                or registered, which means that the pixels are NOT aligned per scan line. The Level 1T (L1T)
                data product provides systematic radiometric accuracy, geometric accuracy by
                incorporating ground control points, while also employing a Digital Elevation Model
                (DEM) for topographic accuracy. Geodetic accuracy of the product depends on the
                accuracy of the ground control points and the resolution of the DEM used.
Abstract:The Landsat 8 OLI/TIRS Pre-WRS-2 data set contains nearly 10,000
                scenes acquired by the Operational Land Imager (OLI) and/or Thermal Infrared Sensor
                (TIRS) sensors after launch (February 11, 2013) through April 10, 2013, when the
                satellite achieved operational orbit (WRS-2). The earliest images are TIRS data
                only. While these data meet the quality standards and have the same geometric
                precision as data acquired on April 11, 2013 and beyond, the geographic extents of
                each scene will differ. Most data will be processed to an L1T (as other standard
                products), and the pixel size will be 30 meters. There may be some differences in
                the early TIRS images due to telescope temperature changes, although they should be
                within +/- 1 percent. The data acquired during the Landsat 7/Landsat 8 underfly on
                March 29 - 30, 2013 are also available.
Abstract:The Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) are instruments onboard the Landsat 8 satellite, which was launched in February of 2013. The satellite collects images of the Earth with a 16-day repeat cycle, referenced to the Worldwide Reference System-2 (WRS-2), and has an 8-day offset to Landsat 7.  The satellite achieved operational WRS-2 orbit on April 11, 2013. 
Landsat OLI image data consists of nine spectral bands (band designations) with a spatial resolution of 30 meters for Bands 1 through 7 and Band 9. The resolution of Band 8 (panchromatic) is 15 meters.

Landsat TIRS image data consists of two thermal bands with a spatial resolution of 100 meters (resampled to 30) for Bands 10 and 11. The TIRS data are packaged with the OLI for data distribution the majority of the time; however there are a small number of only-OLI or only-TIRS scenes that may be available.

The approximate scene size will be 170 km north-south by 183 km east-west (106 mi by 114 mi).
The Global Human Footprint Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density, population settlements), human land use and infrastructure (built up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). This dataset is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN), and is available in the Geographic Coordinate system.
The Global Human Footprint Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density, population settlements), human land use and infrastructure (built up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). This dataset is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN), and is available in the Geographic Coordinate system.
The Global Human Footprint Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density, population settlements), human land use and infrastructure (built up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). This dataset is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN), and is available in the Geographic Coordinate system. (Suggested Usage: To provide an upgrade to existing maps of wild areas, which in turn can be used in modeling efforts, wildlife conservation planning, natural resource management, policy-making, biodiversity studies and human-environment interactions.)
The Global Human Footprint Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density, population settlements), human land use and infrastructure (built up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). This dataset is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN), and is available in the Interrupted Goode Homolosine Projection (IGHP) system.
The Global Human Footprint Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density, population settlements), human land use and infrastructure (built up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). This dataset is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN), and is available in the Interrupted Goode Homolosine Projection (IGHP) system.
The Global Human Footprint Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density, population settlements), human land use and infrastructure (built up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). This dataset is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN), and is available in the Interrupted Goode Homolosine Projection (IGHP) system. (Suggested Usage: To provide an upgrade to existing maps of wild areas, which in turn can be used in modeling efforts, wildlife conservation planning, natural resource management, policy-making, biodiversity studies and human-environment interactions.)
The Last of the Wild Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is derived from the LWP-1 Human Footprint Dataset. The gridded data are classified according to their raster value (wild = 0-10; not wild >10). The ten largest polygons of more than 5 square kilometers within each biome by realm are selected and identified. This dataset is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN), and is available in the Geographic Coordinate system.
The Last of the Wild Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is derived from the LWP-1 Human Footprint Dataset. The gridded data are classified according to their raster value (wild = 0-10; not wild >10). The ten largest polygons of more than 5 square kilometers within each biome by realm are selected and identified. This dataset is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN), and is available in the Geographic Coordinate system.
The Last of the Wild Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is derived from the LWP-1 Human Footprint Dataset. The gridded data are classified according to their raster value (wild = 0-10; not wild >10). The ten largest polygons of more than 5 square kilometers within each biome by realm are selected and identified. This dataset is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN), and is available in the Geographic Coordinate system. (Suggested Usage: To provide a map of wild areas in geographic projection which can be used in wildlife conservation planning, natural resource management, and research on human-environment interactions.)
The Last of the Wild Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is derived from the LWP-1 Human Footprint Dataset. The gridded data are classified according to their raster value (wild = 0-10; not wild >10). The ten largest polygons of more than 5 square kilometers within each biome by realm are selected and identified. This dataset is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN), and is available in the Interrupted Goode Homolosine Projection (IGHP) system.
The Last of the Wild Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is derived from the LWP-1 Human Footprint Dataset. The gridded data are classified according to their raster value (wild = 0-10; not wild >10). The ten largest polygons of more than 5 square kilometers within each biome by realm are selected and identified. This dataset is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN), and is available in the Interrupted Goode Homolosine Projection (IGHP) system.
The Last of the Wild Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is derived from the LWP-1 Human Footprint Dataset. The gridded data are classified according to their raster value (wild = 0-10; not wild >10). The ten largest polygons of more than 5 square kilometers within each biome by realm are selected and identified. This dataset is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN), and is available in the Interrupted Goode Homolosine Projection (IGHP) system. (Suggested Usage: To provide a map of wild areas in the Interrupted Goode Homosoline Projection which can be used in wildlife conservation planning, natural resource management, and research on human-environment interactions.)
The Top One Percent Wild Areas Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is derived from the LWP-1 Human Footprint Dataset. The gridded data are classified according to their raster value (wild = 0-1; not wild >1). The top 1% of the wild areas within each biome by realm are selected and identified. This dataset is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN), and is available in the Geographic Coordinate system.
The Top One Percent Wild Areas Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is derived from the LWP-1 Human Footprint Dataset. The gridded data are classified according to their raster value (wild = 0-1; not wild >1). The top 1% of the wild areas within each biome by realm are selected and identified. This dataset is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN), and is available in the Geographic Coordinate system.
The Top One Percent Wild Areas Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is derived from the LWP-1 Human Footprint Dataset. The gridded data are classified according to their raster value (wild = 0-1; not wild >1). The top 1% of the wild areas within each biome by realm are selected and identified. This dataset is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN), and is available in the Geographic Coordinate system. (Suggested Usage: To provide a map of the wildest areas in geographic projection which can be used in wildlife conservation planning, natural resource management, and research on human-environment interactions.)
The Top One Percent Wild Areas Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is derived from the LWP-1 Human Footprint Dataset. The gridded data are classified according to their raster value (wild = 0-1; not wild >1). The top 1% of the wild areas within each biome by realm are selected and identified. This dataset is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN), and is available in the Interrupted Goode Homolosine Projection (IGHP) system.
The Top One Percent Wild Areas Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is derived from the LWP-1 Human Footprint Dataset. The gridded data are classified according to their raster value (wild = 0-1; not wild >1). The top 1% of the wild areas within each biome by realm are selected and identified. This dataset is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN), and is available in the Interrupted Goode Homolosine Projection (IGHP) system.
The Top One Percent Wild Areas Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is derived from the LWP-1 Human Footprint Dataset. The gridded data are classified according to their raster value (wild = 0-1; not wild >1). The top 1% of the wild areas within each biome by realm are selected and identified. This dataset is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN), and is available in the Interrupted Goode Homolosine Projection (IGHP) system. (Suggested Usage: To provide a map of the wildest areas in Interrupted Goode Homosoline Projection which can be used in wildlife conservation planning, natural resource management, and research on human-environment interactions.)
The Global Human Footprint Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is the Human Influence 

Index (HII) normalized by biome and realm. The HII is a global dataset of 1-kilometer grid cells, created from nine global data 

layers covering human population pressure (population density), human land use and infrastructure (built-up areas, nighttime lights, 

land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). The dataset is produced by the Wildlife 

Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN) and is 

available in the Geographic Coordinate system.
The Global Human Footprint Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is the Human Influence 

Index (HII) normalized by biome and realm. The HII is a global dataset of 1-kilometer grid cells, created from nine global data 

layers covering human population pressure (population density), human land use and infrastructure (built-up areas, nighttime lights, 

land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). The dataset is produced by the Wildlife 

Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN) and is 

available in the Geographic Coordinate system.
The Global Human Footprint Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is the Human Influence 

Index (HII) normalized by biome and realm. The HII is a global dataset of 1-kilometer grid cells, created from nine global data 

layers covering human population pressure (population density), human land use and infrastructure (built-up areas, nighttime lights, 

land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). The dataset is produced by the Wildlife 

Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN) and is 

available in the Geographic Coordinate system.
The Global Human Footprint Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is the Human Influence Index (HII) normalized by biome. The HII is a global dataset of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density), human land use and infrastructure (built-up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). The dataset is produced by the Wildlife Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN) and is available in the Interrupted Goode Homolosine Projection (IGHP) system.
The Global Human Footprint Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is the Human Influence Index (HII) normalized by biome. The HII is a global dataset of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density), human land use and infrastructure (built-up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). The dataset is produced by the Wildlife Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN) and is available in the Interrupted Goode Homolosine Projection (IGHP) system.
The Global Human Footprint Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is the Human Influence Index (HII) normalized by biome. The HII is a global dataset of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density), human land use and infrastructure (built-up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). The dataset is produced by the Wildlife Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN) and is available in the Interrupted Goode Homolosine Projection (IGHP) system. (Suggested Usage:  To provide an updated map of anthropogenic impacts on the environment in Interrupted Goode Homosoline Projection which can be used in wildlife conservation planning, natural resource management, and research on human-environment interactions.)
The Global Human Influence Index Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is a global dataset 

of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density), human land 

use and infrastructure (built-up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, 

navigable rivers). The dataset is produced by the Wildlife Conservation Society (WCS) and the Columbia University Center for 

International Earth Science Information Network (CIESIN) and is available in Geographic Coordinate system.
The Global Human Influence Index Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is a global dataset 

of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density), human land 

use and infrastructure (built-up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, 

navigable rivers). The dataset is produced by the Wildlife Conservation Society (WCS) and the Columbia University Center for 

International Earth Science Information Network (CIESIN) and is available in Geographic Coordinate system.
The Global Human Influence Index Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is a global dataset 

of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density), human land 

use and infrastructure (built-up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, 

navigable rivers). The dataset is produced by the Wildlife Conservation Society (WCS) and the Columbia University Center for 

International Earth Science Information Network (CIESIN) and is available in Geographic Coordinate system.
The Global Human Influence Index Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is a global dataset of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density), human land use and infrastructure (built-up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). The dataset is produced by the Wildlife Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN) and is and is available in the Interrupted Goode Homolosine Projection (IGHP) system.
The Global Human Influence Index Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is a global dataset of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density), human land use and infrastructure (built-up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). The dataset is produced by the Wildlife Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN) and is and is available in the Interrupted Goode Homolosine Projection (IGHP) system.
The Global Human Influence Index Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is a global dataset of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density), human land use and infrastructure (built-up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). The dataset is produced by the Wildlife Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN) and is and is available in the Interrupted Goode Homolosine Projection (IGHP) system. (Suggested Usage: The dataset is to be used in mapping wild areas, modeling and wildlife conservation planning. Other uses of the data include natural resource management, policy making, biodiversity studies and human-environment interactions. )
The Last of the Wild Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is derived from the LWP-2 Human 

Footprint Dataset. The gridded data are classified according to their raster value (wild = 0-10; not wild >10). The ten largest 

polygons of more than 5 square kilometers within each biome by realm are selected and identified. The dataset is produced by the 

Wildlife Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN) 

and is available in the Geographic Coordinate system.
The Last of the Wild Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is derived from the LWP-2 Human 

Footprint Dataset. The gridded data are classified according to their raster value (wild = 0-10; not wild >10). The ten largest 

polygons of more than 5 square kilometers within each biome by realm are selected and identified. The dataset is produced by the 

Wildlife Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN) 

and is available in the Geographic Coordinate system.
The Last of the Wild Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is derived from the LWP-2 Human 

Footprint Dataset. The gridded data are classified according to their raster value (wild = 0-10; not wild >10). The ten largest 

polygons of more than 5 square kilometers within each biome by realm are selected and identified. The dataset is produced by the 

Wildlife Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN) 

and is available in the Geographic Coordinate system.
The Last of the Wild Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is derived from the LWP-2 Human Footprint Dataset. The gridded data are classified according to their raster value (wild = 0-10; not wild >10). The ten largest polygons of more than 5 square kilometers within each biome by realm are selected and identified. The dataset is produced by the Wildlife Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN) and is available in the Interrupted Goode Homolosine Projection (IGHP) system.
The Last of the Wild Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is derived from the LWP-2 Human Footprint Dataset. The gridded data are classified according to their raster value (wild = 0-10; not wild >10). The ten largest polygons of more than 5 square kilometers within each biome by realm are selected and identified. The dataset is produced by the Wildlife Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN) and is available in the Interrupted Goode Homolosine Projection (IGHP) system.
The Last of the Wild Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is derived from the LWP-2 Human Footprint Dataset. The gridded data are classified according to their raster value (wild = 0-10; not wild >10). The ten largest polygons of more than 5 square kilometers within each biome by realm are selected and identified. The dataset is produced by the Wildlife Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN) and is available in the Interrupted Goode Homolosine Projection (IGHP) system. (Suggested Usage: To provide an updated map of wild areas in Interrupted Goode Homosoline Projection which can be used for wildlife conservation planning, natural resource management, and research on human-environment interactions.)
This data set is an expanded version of the Costa et al. (2000) data set and consists of a single grid with values of 1 for cells within the basins and 0 for cells outside. The resolution of the data set is 5 x 5 min (approximately 9 x 9 km). The area of this data set is consistent with the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America. The data file is in ASCII GRID format.
This data set is an expanded version of the Costa et al. (2000) data set and consists of a single grid with values of 1 for cells within the basins and 0 for cells outside. The resolution of the data set is 5 x 5 min (approximately 9 x 9 km). The area of this data set is consistent with the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America. The data file is in ASCII GRID format.
ABSTRACT: This data set is an expanded version of the Costa et al. (2000) data set and consists of a single grid with values of 1 for cells within the basins and 0 for cells outside. The resolution of the data set is 5 x 5 min (approximately 9 x 9 km). The area of this data set is consistent with the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America. The data file is in ASCII GRID format.
The Legal Amazon of Brazil is defined by law to include the states of Acre, Amapa, Amazonas, Para, Rondonia, Roraima, Mato Grosso, Maranhao, and Tocantins [Fundacao Instituto Brasileiro de Geografia e Estatistica (IBGE) 1991]. This is the definition used in generating the Legal Amazon mask. The 8-km Legal Amazon mask was generated by Christopher Potter at the Ecosystem Science and Technology Branch of the Earth Science Division at NASA Ames Research Center (Potter and Brooks-Genovese 1999). The mask was generated from the Digital Chart of the World available from Environmental Systems Research Institute, Inc. (ESRI). The mask is available in ASCII GRID format. The README file accompanying the mask has more information regarding data format. More information can be found at ftp://daac.ornl.gov/data/lba/human_dimensions/legal_amazon_mask/comp/legamazon_readme.pdf.
The Legal Amazon of Brazil is defined by law to include the states of Acre, Amapa, Amazonas, Para, Rondonia, Roraima, Mato Grosso, Maranhao, and Tocantins [Fundacao Instituto Brasileiro de Geografia e Estatistica (IBGE) 1991]. This is the definition used in generating the Legal Amazon mask. The 8-km Legal Amazon mask was generated by Christopher Potter at the Ecosystem Science and Technology Branch of the Earth Science Division at NASA Ames Research Center (Potter and Brooks-Genovese 1999). The mask was generated from the Digital Chart of the World available from Environmental Systems Research Institute, Inc. (ESRI). The mask is available in ASCII GRID format. The README file accompanying the mask has more information regarding data format. More information can be found at ftp://daac.ornl.gov/data/lba/human_dimensions/legal_amazon_mask/comp/legamazon_readme.pdf.
ABSTRACT:  The Legal Amazon of Brazil is defined by law to include the states of Acre, Amapa, Amazonas, Para, Rondonia, Roraima, Mato Grosso, Maranhao, and Tocantins [Fundacao Instituto Brasileiro de Geografia e Estatistica (IBGE) 1991]. This is the definition used in generating the Legal Amazon mask. The 8-km Legal Amazon mask was generated by Christopher Potter at the Ecosystem Science and Technology Branch of the Earth Science Division at NASA Ames Research Center (Potter and Brooks-Genovese 1999). The mask was generated from the Digital Chart of the World available from Environmental Systems Research Institute, Inc. (ESRI). The mask is available in ASCII GRID format. The README file accompanying the mask has more information regarding data format. More information can be found at ftp://daac.ornl.gov/data/lba/human_dimensions/legal_amazon_mask/comp/legamazon_readme.pdf.
The data set consists of a subset of the ISRIC-WISE global data set of derived soil properties for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., longitude 85 to 30 degrees W, latitude 25 degrees S to 10 degrees N). More information about LBA and links to other LBA project sites can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.
The data set consists of a subset of the ISRIC-WISE global data set of derived soil properties for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., longitude 85 to 30 degrees W, latitude 25 degrees S to 10 degrees N). More information about LBA and links to other LBA project sites can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.
ABSTRACT: The data set consists of a subset of the ISRIC-WISE global data set of derived soil properties for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., longitude 85 to 30 degrees W, latitude 25 degrees S to 10 degrees N). More information about LBA and links to other LBA project sites can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.
This data set consists of a subset of a 1-degree gridded global freshwater wetlands database (Stillwell-Soller et al. 1995). This subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., 10 N to 25 S, 30 to 85 W). The data are in ASCII GRID format.The global freshwater wetlands database was assembled from two data sets: Aselman and Crutzen's (1989) wetlands data set and Klinger's political Alaska data set (pers. comm. to L. M. Stillwell-Soller, 1995). The aim of Stillwell-Soller's global data set was to provide an accurate, comprehensive and uniform set of files for convenient specification of wetlands in global climate models. The main source of data was Aselman and Crutzen's global maps of percent cover for a variety of wetlands categories at 2.5-degree latitude by 5-degree longitude resolution. There was some reorganization for seasonally varying categories. Aselman and Crutzen's data were interpolated to a standard 1-degree by 1-degree grid through bilinear interpolation. Their data were geographically complete except for the Alaskan region, for which Klinger's data set provided values.More information can be found at ftp://daac.ornl.gov/data/lba/land_use_land_cover_change/soller_wetlands/comp/soller_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.
This data set consists of a subset of a 1-degree gridded global freshwater wetlands database (Stillwell-Soller et al. 1995). This subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., 10 N to 25 S, 30 to 85 W). The data are in ASCII GRID format.The global freshwater wetlands database was assembled from two data sets: Aselman and Crutzen's (1989) wetlands data set and Klinger's political Alaska data set (pers. comm. to L. M. Stillwell-Soller, 1995). The aim of Stillwell-Soller's global data set was to provide an accurate, comprehensive and uniform set of files for convenient specification of wetlands in global climate models. The main source of data was Aselman and Crutzen's global maps of percent cover for a variety of wetlands categories at 2.5-degree latitude by 5-degree longitude resolution. There was some reorganization for seasonally varying categories. Aselman and Crutzen's data were interpolated to a standard 1-degree by 1-degree grid through bilinear interpolation. Their data were geographically complete except for the Alaskan region, for which Klinger's data set provided values.More information can be found at ftp://daac.ornl.gov/data/lba/land_use_land_cover_change/soller_wetlands/comp/soller_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.
ABSTRACT: This data set consists of a subset of a 1-degree gridded global freshwater wetlands database (Stillwell-Soller et al. 1995). This subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., 10 N to 25 S, 30 to 85 W). The data are in ASCII GRID format.The global freshwater wetlands database was assembled from two data sets: Aselman and Crutzen's (1989) wetlands data set and Klinger's political Alaska data set (pers. comm. to L. M. Stillwell-Soller, 1995). The aim of Stillwell-Soller's global data set was to provide an accurate, comprehensive and uniform set of files for convenient specification of wetlands in global climate models. The main source of data was Aselman and Crutzen's global maps of percent cover for a variety of wetlands categories at 2.5-degree latitude by 5-degree longitude resolution. There was some reorganization for seasonally varying categories. Aselman and Crutzen's data were interpolated to a standard 1-degree by 1-degree grid through bilinear interpolation. Their data were geographically complete except for the Alaskan region, for which Klinger's data set provided values.More information can be found at ftp://daac.ornl.gov/data/lba/land_use_land_cover_change/soller_wetlands/comp/soller_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.
This data set consists of a subset of the Global Historical Climatology Network (GHCN) Version 1 database for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., longitude 85 to 30 degrees W, latitude 25 degrees S to 10 degrees N). There are three files available, one each for precipitation, temperature, and pressure data.  Within this subset the oldest data date from 1832 and the most recent from 1990. More information about LBA and links to other LBA project sites can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.
This data set consists of a subset of the Global Historical Climatology Network (GHCN) Version 1 database for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., longitude 85 to 30 degrees W, latitude 25 degrees S to 10 degrees N). There are three files available, one each for precipitation, temperature, and pressure data.  Within this subset the oldest data date from 1832 and the most recent from 1990. More information about LBA and links to other LBA project sites can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.
ABSTRACT: This data set consists of a subset of the Global Historical Climatology Network (GHCN) Version 1 database for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., longitude 85 to 30 degrees W, latitude 25 degrees S to 10 degrees N). There are three files available, one each for precipitation, temperature, and pressure data.  Within this subset the oldest data date from 1832 and the most recent from 1990. More information about LBA and links to other LBA project sites can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.
This data set is a subset of Cogley's 1998 global hydrographic data set (GGHYDRO, Release 2.2). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America. The subset is organized into 19 files containing terrain type, stream frequency counts, major drainage basins, and annual water runoff for the LBA study area. The data are presented at a spatial resolution of 1-degree latitude by 1-degree longitude in ASCII GRID file format.
This data set is a subset of Cogley's 1998 global hydrographic data set (GGHYDRO, Release 2.2). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America. The subset is organized into 19 files containing terrain type, stream frequency counts, major drainage basins, and annual water runoff for the LBA study area. The data are presented at a spatial resolution of 1-degree latitude by 1-degree longitude in ASCII GRID file format.
ABSTRACT: This data set is a subset of Cogley's 1998 global hydrographic data set (GGHYDRO, Release 2.2). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America. The subset is organized into 19 files containing terrain type, stream frequency counts, major drainage basins, and annual water runoff for the LBA study area. The data are presented at a spatial resolution of 1-degree latitude by 1-degree longitude in ASCII GRID file format.
This data set consists of a subset of a 1-degree global land cover product (DeFries and Townshend 1994). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America. The data are in ASCII GRID format.
This data set consists of a subset of a 1-degree global land cover product (DeFries and Townshend 1994). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America. The data are in ASCII GRID format.
ABSTRACT: This data set consists of a subset of a 1-degree global land cover product (DeFries and Townshend 1994). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America. The data are in ASCII GRID format.
This data set is a subset of the IGBP DISCover data set, which was derived from the Global Land Cover Characteristics database. The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., latitude 10 deg N to 25 deg S, longitude 30 to 85 W). The data are at 1-km resolution in ASCII GRID format.
This data set is a subset of the IGBP DISCover data set, which was derived from the Global Land Cover Characteristics database. The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., latitude 10 deg N to 25 deg S, longitude 30 to 85 W). The data are at 1-km resolution in ASCII GRID format.
ABSTRACT: This data set is a subset of the IGBP DISCover data set, which was derived from the Global Land Cover Characteristics database. The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., latitude 10 deg N to 25 deg S, longitude 30 to 85 W). The data are at 1-km resolution in ASCII GRID format.
This data set is a subset of Cramer and Leemans' (2001) global database of mean monthly climatology, which contains monthly averages of mean temperature, temperature range, precipitation, rain days, and sunshine hours for terrestrial areas during 1931-1960. This subset was created for the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., latitude 10 N to 25 S, longitude 30 to 85 W). The data are presented at 0.5-degree latitude/longitude resolution in ASCII GRID file format. Cramer and Leemans (2001, Version 2.1) constituted a major update of an earlier database, Leemans and Cramer (1991). The new version was generated from a larger database by means of the partial thin-plate splining algorithm developed by Michael F. Hutchinson, Canberra (Hutchinson and Bischof 1983). Version 2.1 has been used widely, notably by all groups participating in the International Geosphere-Biosphere Programme's Net Primary Productivity (NPP) model intercomparison (Olsen et al. 2001).More information about the data can be found at ftp://daac.ornl.gov/data/lba/physical_climate/leemans_cramer/comp/cramer_lmns_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.
This data set is a subset of Cramer and Leemans' (2001) global database of mean monthly climatology, which contains monthly averages of mean temperature, temperature range, precipitation, rain days, and sunshine hours for terrestrial areas during 1931-1960. This subset was created for the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., latitude 10 N to 25 S, longitude 30 to 85 W). The data are presented at 0.5-degree latitude/longitude resolution in ASCII GRID file format. Cramer and Leemans (2001, Version 2.1) constituted a major update of an earlier database, Leemans and Cramer (1991). The new version was generated from a larger database by means of the partial thin-plate splining algorithm developed by Michael F. Hutchinson, Canberra (Hutchinson and Bischof 1983). Version 2.1 has been used widely, notably by all groups participating in the International Geosphere-Biosphere Programme's Net Primary Productivity (NPP) model intercomparison (Olsen et al. 2001).More information about the data can be found at ftp://daac.ornl.gov/data/lba/physical_climate/leemans_cramer/comp/cramer_lmns_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.
ABSTRACT: This data set is a subset of Cramer and Leemans' (2001) global database of mean monthly climatology, which contains monthly averages of mean temperature, temperature range, precipitation, rain days, and sunshine hours for terrestrial areas during 1931-1960. This subset was created for the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., latitude 10 N to 25 S, longitude 30 to 85 W). The data are presented at 0.5-degree latitude/longitude resolution in ASCII GRID file format. Cramer and Leemans (2001, Version 2.1) constituted a major update of an earlier database, Leemans and Cramer (1991). The new version was generated from a larger database by means of the partial thin-plate splining algorithm developed by Michael F. Hutchinson, Canberra (Hutchinson and Bischof 1983). Version 2.1 has been used widely, notably by all groups participating in the International Geosphere-Biosphere Programme's Net Primary Productivity (NPP) model intercomparison (Olsen et al. 2001).More information about the data can be found at ftp://daac.ornl.gov/data/lba/physical_climate/leemans_cramer/comp/cramer_lmns_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.
The data set contains a subset of a global organic soil carbon and nitrogen data set (Zinke et al. 1986). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., 10 N to 25 S, 30 to 85 W). The point data are available in three formats: a comma-delimited ASCII file (*.csv), an ESRI shapefile, and an ESRI export file (*.e00).The data for the global data set (Zinke et al. 1986) were obtained from soil surveys conducted by Zinke in 1965-1984 and from soil survey literature. The main samples for laboratory analyses were collected at uniform soil increments and included bulk density determinations. Many samples reported in the literature did not have uniform soil increments or bulk density determinations. Only soil profiles that had been sampled either to a meter in depth or to actual depth were included in this database from soil survey literature. When carbon content was known but bulk densities were absent from soil samples reported in the literature, densities were estimated by regression analysis on the basis of the relationship between organic carbon content and measured bulk density in 1800 soil profiles for which bulk densities were known.Further information can be found at ftp://daac.ornl.gov/data/lba/carbon_dynamics/Zinke_soil/comp/zinke_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.
The data set contains a subset of a global organic soil carbon and nitrogen data set (Zinke et al. 1986). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., 10 N to 25 S, 30 to 85 W). The point data are available in three formats: a comma-delimited ASCII file (*.csv), an ESRI shapefile, and an ESRI export file (*.e00).The data for the global data set (Zinke et al. 1986) were obtained from soil surveys conducted by Zinke in 1965-1984 and from soil survey literature. The main samples for laboratory analyses were collected at uniform soil increments and included bulk density determinations. Many samples reported in the literature did not have uniform soil increments or bulk density determinations. Only soil profiles that had been sampled either to a meter in depth or to actual depth were included in this database from soil survey literature. When carbon content was known but bulk densities were absent from soil samples reported in the literature, densities were estimated by regression analysis on the basis of the relationship between organic carbon content and measured bulk density in 1800 soil profiles for which bulk densities were known.Further information can be found at ftp://daac.ornl.gov/data/lba/carbon_dynamics/Zinke_soil/comp/zinke_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.
ABSTRACT: The data set contains a subset of a global organic soil carbon and nitrogen data set (Zinke et al. 1986). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., 10 N to 25 S, 30 to 85 W). The point data are available in three formats: a comma-delimited ASCII file (*.csv), an ESRI shapefile, and an ESRI export file (*.e00).The data for the global data set (Zinke et al. 1986) were obtained from soil surveys conducted by Zinke in 1965-1984 and from soil survey literature. The main samples for laboratory analyses were collected at uniform soil increments and included bulk density determinations. Many samples reported in the literature did not have uniform soil increments or bulk density determinations. Only soil profiles that had been sampled either to a meter in depth or to actual depth were included in this database from soil survey literature. When carbon content was known but bulk densities were absent from soil samples reported in the literature, densities were estimated by regression analysis on the basis of the relationship between organic carbon content and measured bulk density in 1800 soil profiles for which bulk densities were known.Further information can be found at ftp://daac.ornl.gov/data/lba/carbon_dynamics/Zinke_soil/comp/zinke_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.
The data set consists of a subset for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., longitude 85 deg to 30 deg W, latitude 25 deg S to 10 deg N) 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 original map was derived at a 5-min resolution and contains natural vegetation classified into 15 types.
The data set consists of a subset for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., longitude 85 deg to 30 deg W, latitude 25 deg S to 10 deg N) 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 original map was derived at a 5-min resolution and contains natural vegetation classified into 15 types.
ABSTRACT: The data set consists of a subset for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., longitude 85 deg to 30 deg W, latitude 25 deg S to 10 deg N) 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 original map was derived at a 5-min resolution and contains natural vegetation classified into 15 types.
This data set is a subset of a global river discharge data set by Coe and Olejniczak (1999). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., 10 N to 25 S, 30 to 85 W).The global river discharge data set (Coe and Olejniczak 1999), formerly known as the "Climate, People, and Environment Program (CPEP) Global River Discharge Database," is a compilation of monthly mean discharge data for more than 2600 sites worldwide. The data were compiled from RivDIS Version 1.1 (Vorosmarty et al. 1998), the U.S. Geological Survey, and the Brazilian National Department of Water and Electrical Energy. The period of record for the sites varies from 3 years to greater than 100.The purpose of the global compilation is to provide detailed hydrographic information for the climate research community in as general a format as possible. Data are given in units of meters cubed per second (m**3/sec) and are in ASCII format. Data from stations that had less than 3 years of information or that had a basin area less than 5000 square kilometers were excluded from the global data set. Thus, the data sources may include more sites than the data set by Coe and Olejniczak (1999). Users should refer to the data originators for further documentation on the source data.More information, a map of discharge sites, and a clickable site data table can be found at ftp://daac.ornl.gov/data/lba/surf_hydro_and_water_chem/sage/comp/sagedischarge_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. Further information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.
This data set is a subset of a global river discharge data set by Coe and Olejniczak (1999). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., 10 N to 25 S, 30 to 85 W).The global river discharge data set (Coe and Olejniczak 1999), formerly known as the "Climate, People, and Environment Program (CPEP) Global River Discharge Database," is a compilation of monthly mean discharge data for more than 2600 sites worldwide. The data were compiled from RivDIS Version 1.1 (Vorosmarty et al. 1998), the U.S. Geological Survey, and the Brazilian National Department of Water and Electrical Energy. The period of record for the sites varies from 3 years to greater than 100.The purpose of the global compilation is to provide detailed hydrographic information for the climate research community in as general a format as possible. Data are given in units of meters cubed per second (m**3/sec) and are in ASCII format. Data from stations that had less than 3 years of information or that had a basin area less than 5000 square kilometers were excluded from the global data set. Thus, the data sources may include more sites than the data set by Coe and Olejniczak (1999). Users should refer to the data originators for further documentation on the source data.More information, a map of discharge sites, and a clickable site data table can be found at ftp://daac.ornl.gov/data/lba/surf_hydro_and_water_chem/sage/comp/sagedischarge_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. Further information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.
This data set is a subset of the 1-km global tree cover data set (DeFries et al. 1999) developed at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland. The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America. The data are in ASCII GRID format.
This data set is a subset of the 1-km global tree cover data set (DeFries et al. 1999) developed at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland. The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America. The data are in ASCII GRID format.
ABSTRACT: This data set is a subset of the 1-km global tree cover data set (DeFries et al. 1999) developed at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland. The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America. The data are in ASCII GRID format.
This data set is a subset of a global database compiled by Matthews and Fung (1987) on the distribution and environmental characteristics of natural wetlands. The global database was developed to evaluate the role of wetlands in the annual emission of methane from terrestrial sources. This subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America.
This data set is a subset of a global database compiled by Matthews and Fung (1987) on the distribution and environmental characteristics of natural wetlands. The global database was developed to evaluate the role of wetlands in the annual emission of methane from terrestrial sources. This subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America.
ABSTRACT: This data set is a subset of a global database compiled by Matthews and Fung (1987) on the distribution and environmental characteristics of natural wetlands. The global database was developed to evaluate the role of wetlands in the annual emission of methane from terrestrial sources. This subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America.
This data set contains meteorological data collected around the confluence of the Tapajos River with the Amazon River in the Amazon Basin near Santarem, Brazil, in July and August 2001. Boundary layer and upper air measurements were collected with an acoustic sounder-sodar instrument, pilot balloons with optical theodolites, and radiosondes. Radiosondes also measured pressure, temperature, and relative humidity in addition to wind speed and direction. Measurements were made from five local stations at varying frequencies. There are 41 comma-delimited data files with this data set. Supporting information provided with the data set as companion files include: Weather forecasts: Weather forecasts were used to determine the presence of favorable conditions for the balloon flights during the CIRSAN experiment, as well as to help decide the radiosonde launch frequency. The daily observed and forecast weather descriptions for the study period (Weather_forecasts_Santarem.txt) are included. Satellite images: All the satellite images during the CIRSAN period are provided. This is a compilation of images from various instruments and satellite platforms. (See readme_sat.txt). There are 42 images in .gif format. CPTEC Analysis files: The CIRSAN measurement data were used in the CPTEC Global Analysis modeling activity. Model output results for the Pacific and South American region are provided in GRIB format. (See readme_GPSA.txt)
This data set contains meteorological data collected around the confluence of the Tapajos River with the Amazon River in the Amazon Basin near Santarem, Brazil, in July and August 2001. Boundary layer and upper air measurements were collected with an acoustic sounder-sodar instrument, pilot balloons with optical theodolites, and radiosondes. Radiosondes also measured pressure, temperature, and relative humidity in addition to wind speed and direction. Measurements were made from five local stations at varying frequencies. There are 41 comma-delimited data files with this data set. Supporting information provided with the data set as companion files include: Weather forecasts: Weather forecasts were used to determine the presence of favorable conditions for the balloon flights during the CIRSAN experiment, as well as to help decide the radiosonde launch frequency. The daily observed and forecast weather descriptions for the study period (Weather_forecasts_Santarem.txt) are included. Satellite images: All the satellite images during the CIRSAN period are provided. This is a compilation of images from various instruments and satellite platforms. (See readme_sat.txt). There are 42 images in .gif format. CPTEC Analysis files: The CIRSAN measurement data were used in the CPTEC Global Analysis modeling activity. Model output results for the Pacific and South American region are provided in GRIB format. (See readme_GPSA.txt)
ABSTRACT: This data set contains meteorological data collected around the confluence of the Tapajos River with the Amazon River in the Amazon Basin near Santarem, Brazil, in July and August 2001. Boundary layer and upper air measurements were collected with an acoustic sounder-sodar instrument, pilot balloons with optical theodolites, and radiosondes. Radiosondes also measured pressure, temperature, and relative humidity in addition to wind speed and direction. Measurements were made from five local stations at varying frequencies. There are 41 comma-delimited data files with this data set. Supporting information provided with the data set as companion files include: Weather forecasts: Weather forecasts were used to determine the presence of favorable conditions for the balloon flights during the CIRSAN experiment, as well as to help decide the radiosonde launch frequency. The daily observed and forecast weather descriptions for the study period (Weather_forecasts_Santarem.txt) are included. Satellite images: All the satellite images during the CIRSAN period are provided. This is a compilation of images from various instruments and satellite platforms. (See readme_sat.txt). There are 42 images in .gif format. CPTEC Analysis files: The CIRSAN measurement data were used in the CPTEC Global Analysis modeling activity. Model output results for the Pacific and South American region are provided in GRIB format. (See readme_GPSA.txt)
This data set reports delta 13C/12C results for leaf tissues and atmospheric carbon dioxide (CO2), delta 15N/14N ratios for leaf tissue, and leaf carbon and nitrogen concentrations along a topographical gradient in old-growth forests in the ZF2 Reserve (km 34), Instituto Nacional de Pesquisas da Amazonia (INPA), near Manaus, Amazonas, Brazil. During the dry seasons of 2004 and 2006, leaves were sampled at various heights within the canopy and atmospheric air flask samples were also collected at various heights at three locations along this gradient. Also included are coincident meteorological, atmospheric CO2, and CO2 flux measurements from the plateau KM34 tower. There are 3 comma-delimited data files with this data set.
This data set reports delta 13C/12C results for leaf tissues and atmospheric carbon dioxide (CO2), delta 15N/14N ratios for leaf tissue, and leaf carbon and nitrogen concentrations along a topographical gradient in old-growth forests in the ZF2 Reserve (km 34), Instituto Nacional de Pesquisas da Amazonia (INPA), near Manaus, Amazonas, Brazil. During the dry seasons of 2004 and 2006, leaves were sampled at various heights within the canopy and atmospheric air flask samples were also collected at various heights at three locations along this gradient. Also included are coincident meteorological, atmospheric CO2, and CO2 flux measurements from the plateau KM34 tower. There are 3 comma-delimited data files with this data set.
ABSTRACT: This data set reports delta 13C/12C results for leaf tissues and atmospheric carbon dioxide (CO2), delta 15N/14N ratios for leaf tissue, and leaf carbon and nitrogen concentrations along a topographical gradient in old-growth forests in the ZF2 Reserve (km 34), Instituto Nacional de Pesquisas da Amazonia (INPA), near Manaus, Amazonas, Brazil. During the dry seasons of 2004 and 2006, leaves were sampled at various heights within the canopy and atmospheric air flask samples were also collected at various heights at three locations along this gradient. Also included are coincident meteorological, atmospheric CO2, and CO2 flux measurements from the plateau KM34 tower. There are 3 comma-delimited data files with this data set.
This data set reports carbon and oxygen stable isotope ratios of atmospheric carbon dioxide (CO2) collected at several forest and pasture sites and in the free troposphere over Amazonia. There are three comma-delimited ASCII files with this data set.Atmospheric CO2 concentrations and isotope signatures were measured at ten different forest and pasture canopy sites across the states of Amazonas, Para, and Rondonia within the Brazilian Amazon between March 1999 and March 2004. Both daytime and nighttime profile samples were collected.Samples of CO2 in the troposphere were collected during aircraft flights over the Amazon/Tapajos Rivers, FLONA Tapajos, and pasture/agriculture areas during five days in May 2003 (wet season). Samples were analyzed for carbon and oxygen isotopes of atmospheric CO2. Flights ranged from low altitudes to above the diurnal tropospheric boundary layer.Measurements of carbon and oxygen stable isotope ratios of atmospheric carbon dioxide (CO2) are a powerful indicator of large-scale CO2 exchange on land across multiple spatial scales. Stable carbon isotope composition of leaf tissue and CO2 released by respiration (delta r) can be used as an estimate of changes in ecosystem isotopic discrimination that occur in response to seasonal and interannual changes in environmental conditions, and land-use change (forest-pasture conversion). Understanding of carbon dioxide stable isotope composition can play a central role in influencing our understanding of the extent to which terrestrial ecosystems are carbon sinks.
This data set reports carbon and oxygen stable isotope ratios of atmospheric carbon dioxide (CO2) collected at several forest and pasture sites and in the free troposphere over Amazonia. There are three comma-delimited ASCII files with this data set.Atmospheric CO2 concentrations and isotope signatures were measured at ten different forest and pasture canopy sites across the states of Amazonas, Para, and Rondonia within the Brazilian Amazon between March 1999 and March 2004. Both daytime and nighttime profile samples were collected.Samples of CO2 in the troposphere were collected during aircraft flights over the Amazon/Tapajos Rivers, FLONA Tapajos, and pasture/agriculture areas during five days in May 2003 (wet season). Samples were analyzed for carbon and oxygen isotopes of atmospheric CO2. Flights ranged from low altitudes to above the diurnal tropospheric boundary layer.Measurements of carbon and oxygen stable isotope ratios of atmospheric carbon dioxide (CO2) are a powerful indicator of large-scale CO2 exchange on land across multiple spatial scales. Stable carbon isotope composition of leaf tissue and CO2 released by respiration (delta r) can be used as an estimate of changes in ecosystem isotopic discrimination that occur in response to seasonal and interannual changes in environmental conditions, and land-use change (forest-pasture conversion). Understanding of carbon dioxide stable isotope composition can play a central role in influencing our understanding of the extent to which terrestrial ecosystems are carbon sinks.
ABSTRACT: This data set reports carbon and oxygen stable isotope ratios of atmospheric carbon dioxide (CO2) collected at several forest and pasture sites and in the free troposphere over Amazonia. There are three comma-delimited ASCII files with this data set.Atmospheric CO2 concentrations and isotope signatures were measured at ten different forest and pasture canopy sites across the states of Amazonas, Para, and Rondonia within the Brazilian Amazon between March 1999 and March 2004. Both daytime and nighttime profile samples were collected.Samples of CO2 in the troposphere were collected during aircraft flights over the Amazon/Tapajos Rivers, FLONA Tapajos, and pasture/agriculture areas during five days in May 2003 (wet season). Samples were analyzed for carbon and oxygen isotopes of atmospheric CO2. Flights ranged from low altitudes to above the diurnal tropospheric boundary layer.Measurements of carbon and oxygen stable isotope ratios of atmospheric carbon dioxide (CO2) are a powerful indicator of large-scale CO2 exchange on land across multiple spatial scales. Stable carbon isotope composition of leaf tissue and CO2 released by respiration (delta r) can be used as an estimate of changes in ecosystem isotopic discrimination that occur in response to seasonal and interannual changes in environmental conditions, and land-use change (forest-pasture conversion). Understanding of carbon dioxide stable isotope composition can play a central role in influencing our understanding of the extent to which terrestrial ecosystems are carbon sinks.
This data set reports the measurement of stable carbon, nitrogen, and oxygen isotope ratios in organic material (plant, litter and soil samples) in forest canopy profiles and pasture (grasses and shrubs) as well as corresponding carbon and nitrogen tissue concentrations in a number of different sites across Brazil. The sampling design captured the temporal variation in rainfall over the course of several years. Carbon and nitrogen isotope ratios can act as a proxy for interpreting aspects of the carbon and nitrogen cycles in Amazonian rainforests. Data are in three comma-delimited ASCII files.
This data set reports the measurement of stable carbon, nitrogen, and oxygen isotope ratios in organic material (plant, litter and soil samples) in forest canopy profiles and pasture (grasses and shrubs) as well as corresponding carbon and nitrogen tissue concentrations in a number of different sites across Brazil. The sampling design captured the temporal variation in rainfall over the course of several years. Carbon and nitrogen isotope ratios can act as a proxy for interpreting aspects of the carbon and nitrogen cycles in Amazonian rainforests. Data are in three comma-delimited ASCII files.
ABSTRACT: This data set reports the measurement of stable carbon, nitrogen, and oxygen isotope ratios in organic material (plant, litter and soil samples) in forest canopy profiles and pasture (grasses and shrubs) as well as corresponding carbon and nitrogen tissue concentrations in a number of different sites across Brazil. The sampling design captured the temporal variation in rainfall over the course of several years. Carbon and nitrogen isotope ratios can act as a proxy for interpreting aspects of the carbon and nitrogen cycles in Amazonian rainforests. Data are in three comma-delimited ASCII files.
This data set reports on Leaf Area Index (LAI) and Specific Leaf Area (SLA) measurements collected from forest and pasture sites in or near the Tapajos National Forest (TNF), 80 km south of the city of Santarem, Para, Brazil. The collections were between October 1999 and June 2003 from tower sites accessed via the km 67 forest entrance. There are 2 comma-delimited ASCII data files with this data set, and 1 companion data file which provides site descriptions.
This data set reports on Leaf Area Index (LAI) and Specific Leaf Area (SLA) measurements collected from forest and pasture sites in or near the Tapajos National Forest (TNF), 80 km south of the city of Santarem, Para, Brazil. The collections were between October 1999 and June 2003 from tower sites accessed via the km 67 forest entrance. There are 2 comma-delimited ASCII data files with this data set, and 1 companion data file which provides site descriptions.
ABSTRACT: This data set reports on Leaf Area Index (LAI) and Specific Leaf Area (SLA) measurements collected from forest and pasture sites in or near the Tapajos National Forest (TNF), 80 km south of the city of Santarem, Para, Brazil. The collections were between October 1999 and June 2003 from tower sites accessed via the km 67 forest entrance. There are 2 comma-delimited ASCII data files with this data set, and 1 companion data file which provides site descriptions.
This data set reports leaf gas flux and leaf properties from samples collected from trees, liana, pasture saplings, and pasture grass located at eight different sampling locations in the states of Para (south of Santarem) and Amazonas (near Manaus) from November 1999 through December 2003. Data are reported on photosynthesis measurements, CO2 response curves, light response curves, humidity response curves, and stomatal responses to variations of the leaf-to-air water vapor mole fraction deficit. Leaf weight, carbon and nitrogen concentrations as well as stable isotope signatures for 13C and 15N are reported for a subset of the samples. There is one comma-delimited ASCII data file with this data set.
This data set reports leaf gas flux and leaf properties from samples collected from trees, liana, pasture saplings, and pasture grass located at eight different sampling locations in the states of Para (south of Santarem) and Amazonas (near Manaus) from November 1999 through December 2003. Data are reported on photosynthesis measurements, CO2 response curves, light response curves, humidity response curves, and stomatal responses to variations of the leaf-to-air water vapor mole fraction deficit. Leaf weight, carbon and nitrogen concentrations as well as stable isotope signatures for 13C and 15N are reported for a subset of the samples. There is one comma-delimited ASCII data file with this data set.
ABSTRACT: This data set reports leaf gas flux and leaf properties from samples collected from trees, liana, pasture saplings, and pasture grass located at eight different sampling locations in the states of Para (south of Santarem) and Amazonas (near Manaus) from November 1999 through December 2003. Data are reported on photosynthesis measurements, CO2 response curves, light response curves, humidity response curves, and stomatal responses to variations of the leaf-to-air water vapor mole fraction deficit. Leaf weight, carbon and nitrogen concentrations as well as stable isotope signatures for 13C and 15N are reported for a subset of the samples. There is one comma-delimited ASCII data file with this data set.
Data are reported for leaf water potential of leaves of seven species of trees and lianas from the primary forest at the km 67 Tower Site, Tapajos National Forest, and measurements of five sapling tree species and the grass Brachiaria brizantha from a pasture site located near the km 77 Pasture Tower Site, approximately 10 km from the primary forest site. The research area is situated within the Tapajos National Forest reserve, south of the city of Santarem, Para, Brazil. Measurements were made quarterly between March 2000 and March 2001. There is one comma-delimited data file with this data set.
Data are reported for leaf water potential of leaves of seven species of trees and lianas from the primary forest at the km 67 Tower Site, Tapajos National Forest, and measurements of five sapling tree species and the grass Brachiaria brizantha from a pasture site located near the km 77 Pasture Tower Site, approximately 10 km from the primary forest site. The research area is situated within the Tapajos National Forest reserve, south of the city of Santarem, Para, Brazil. Measurements were made quarterly between March 2000 and March 2001. There is one comma-delimited data file with this data set.
ABSTRACT: Data are reported for leaf water potential of leaves of seven species of trees and lianas from the primary forest at the km 67 Tower Site, Tapajos National Forest, and measurements of five sapling tree species and the grass Brachiaria brizantha from a pasture site located near the km 77 Pasture Tower Site, approximately 10 km from the primary forest site. The research area is situated within the Tapajos National Forest reserve, south of the city of Santarem, Para, Brazil. Measurements were made quarterly between March 2000 and March 2001. There is one comma-delimited data file with this data set.
This data set reports the oxygen isotope signatures of water extracted from plant tissue (xylem from the stems and leaf tissue) and of atmospheric water vapor from twelve different sites (including both pasture and forest) throughout the Amazon region of Brazil. Samples were collected approximately every 4 months between 1999 and 2003 with additional samples collected monthly between January and May of 2003. In 2004 the collection of water samples from plant tissue continued at two sites, though water vapor collections were discontinued, and measurements of deuterium signatures were added to the analyses. In addition, water vapor from the troposphere was collected during a series of aircraft flights over the Tapajos National Forest in May of 2003 and analyzed for oxygen isotopes using the same methodology. There is one comma-delimited ASCII data file with this data set.
This data set reports the oxygen isotope signatures of water extracted from plant tissue (xylem from the stems and leaf tissue) and of atmospheric water vapor from twelve different sites (including both pasture and forest) throughout the Amazon region of Brazil. Samples were collected approximately every 4 months between 1999 and 2003 with additional samples collected monthly between January and May of 2003. In 2004 the collection of water samples from plant tissue continued at two sites, though water vapor collections were discontinued, and measurements of deuterium signatures were added to the analyses. In addition, water vapor from the troposphere was collected during a series of aircraft flights over the Tapajos National Forest in May of 2003 and analyzed for oxygen isotopes using the same methodology. There is one comma-delimited ASCII data file with this data set.
ABSTRACT: This data set reports the oxygen isotope signatures of water extracted from plant tissue (xylem from the stems and leaf tissue) and of atmospheric water vapor from twelve different sites (including both pasture and forest) throughout the Amazon region of Brazil. Samples were collected approximately every 4 months between 1999 and 2003 with additional samples collected monthly between January and May of 2003. In 2004 the collection of water samples from plant tissue continued at two sites, though water vapor collections were discontinued, and measurements of deuterium signatures were added to the analyses. In addition, water vapor from the troposphere was collected during a series of aircraft flights over the Tapajos National Forest in May of 2003 and analyzed for oxygen isotopes using the same methodology. There is one comma-delimited ASCII data file with this data set.
A Vaisala CT-25K ceilometer was installed at an old-growth forest site located at the km 67 Eddy Flux Tower site in the Tapajos National Forest, Para, Brazil, off Kilometer 67 of BR-163 south of Santarem in April 2001 and remained operational through December 2003, with reliable data being collected between May 2001 and June 2003.Annual, 2001 to 2003, 30-minute average cloud base and backscatter profile data and measurement statistics (sample count, variance, skewness, and kurtosis) are presented in 15 ASCII comma-delineated files. In addition, the cloud base values (m) and measurement statistics for the three reported cloud base levels have been consolidated in 3 annual comma-separated files.The ceilometer provides 15-second measurements of cloud base (three levels up to 7500 m), echo intensity, and a 30-m resolution backscatter profile. The ceilometer reports vertical visibility during periods when the sky is obscured but a cloud base is not detectable. The ceilometer was operational for a sufficient amount of time to examine wet-to-dry season variations in cloud cover fraction and cloud base height.
A Vaisala CT-25K ceilometer was installed at an old-growth forest site located at the km 67 Eddy Flux Tower site in the Tapajos National Forest, Para, Brazil, off Kilometer 67 of BR-163 south of Santarem in April 2001 and remained operational through December 2003, with reliable data being collected between May 2001 and June 2003.Annual, 2001 to 2003, 30-minute average cloud base and backscatter profile data and measurement statistics (sample count, variance, skewness, and kurtosis) are presented in 15 ASCII comma-delineated files. In addition, the cloud base values (m) and measurement statistics for the three reported cloud base levels have been consolidated in 3 annual comma-separated files.The ceilometer provides 15-second measurements of cloud base (three levels up to 7500 m), echo intensity, and a 30-m resolution backscatter profile. The ceilometer reports vertical visibility during periods when the sky is obscured but a cloud base is not detectable. The ceilometer was operational for a sufficient amount of time to examine wet-to-dry season variations in cloud cover fraction and cloud base height.
ABSTRACT: A Vaisala CT-25K ceilometer was installed at an old-growth forest site located at the km 67 Eddy Flux Tower site in the Tapajos National Forest, Para, Brazil, off Kilometer 67 of BR-163 south of Santarem in April 2001 and remained operational through December 2003, with reliable data being collected between May 2001 and June 2003.Annual, 2001 to 2003, 30-minute average cloud base and backscatter profile data and measurement statistics (sample count, variance, skewness, and kurtosis) are presented in 15 ASCII comma-delineated files. In addition, the cloud base values (m) and measurement statistics for the three reported cloud base levels have been consolidated in 3 annual comma-separated files.The ceilometer provides 15-second measurements of cloud base (three levels up to 7500 m), echo intensity, and a 30-m resolution backscatter profile. The ceilometer reports vertical visibility during periods when the sky is obscured but a cloud base is not detectable. The ceilometer was operational for a sufficient amount of time to examine wet-to-dry season variations in cloud cover fraction and cloud base height.
Eddy correlation and micrometeorological measurements began in 2001 and continued through 2005 at the pasture site at km 77 on BR-163 just south of the city of Santarem, Para, Brazil. Measurements included turbulent fluxes (momentum, heat, water vapor, and CO2) using the eddy covariance (EC) approach. Other measurements included the CO2 profile, air temperature, humidity, wind speed profile, downward and upward solar and terrestrial radiation, downward and upward photosynthetically active radiation (PAR), atmospheric pressure, rainfall, soil temperature, soil moisture, and soil heat flux. Data are presented in 5 comma-separated ASCII value (csv) files each corresponding roughly to one calendar year. At the beginning of the measurements, in September 2000, the field was a pasture. In November 2001, the pasture was burned, plowed, and planted in upland (non-irrigated) rice. Land use practices during the study period were recorded and are included in a table in Section 5 of this guide.The EC system was composed of a 3D sonic anemometer (ATI 3D) and an infrared analyzer (LICOR 6262) installed on a 20m tower in the agricultural field. The methodology to calculate the flux is described in detail in Sakai et al. (2004) and a companion file is included that describes in detail the formulae used to calculate the eddy flux variables  (CD03_Pasture_Flux_Calculations.pdf).
Eddy correlation and micrometeorological measurements began in 2001 and continued through 2005 at the pasture site at km 77 on BR-163 just south of the city of Santarem, Para, Brazil. Measurements included turbulent fluxes (momentum, heat, water vapor, and CO2) using the eddy covariance (EC) approach. Other measurements included the CO2 profile, air temperature, humidity, wind speed profile, downward and upward solar and terrestrial radiation, downward and upward photosynthetically active radiation (PAR), atmospheric pressure, rainfall, soil temperature, soil moisture, and soil heat flux. Data are presented in 5 comma-separated ASCII value (csv) files each corresponding roughly to one calendar year. At the beginning of the measurements, in September 2000, the field was a pasture. In November 2001, the pasture was burned, plowed, and planted in upland (non-irrigated) rice. Land use practices during the study period were recorded and are included in a table in Section 5 of this guide.The EC system was composed of a 3D sonic anemometer (ATI 3D) and an infrared analyzer (LICOR 6262) installed on a 20m tower in the agricultural field. The methodology to calculate the flux is described in detail in Sakai et al. (2004) and a companion file is included that describes in detail the formulae used to calculate the eddy flux variables  (CD03_Pasture_Flux_Calculations.pdf).
ABSTRACT: Eddy correlation and micrometeorological measurements began in 2001 and continued through 2005 at the pasture site at km 77 on BR-163 just south of the city of Santarem, Para, Brazil. Measurements included turbulent fluxes (momentum, heat, water vapor, and CO2) using the eddy covariance (EC) approach. Other measurements included the CO2 profile, air temperature, humidity, wind speed profile, downward and upward solar and terrestrial radiation, downward and upward photosynthetically active radiation (PAR), atmospheric pressure, rainfall, soil temperature, soil moisture, and soil heat flux. Data are presented in 5 comma-separated ASCII value (csv) files each corresponding roughly to one calendar year. At the beginning of the measurements, in September 2000, the field was a pasture. In November 2001, the pasture was burned, plowed, and planted in upland (non-irrigated) rice. Land use practices during the study period were recorded and are included in a table in Section 5 of this guide.The EC system was composed of a 3D sonic anemometer (ATI 3D) and an infrared analyzer (LICOR 6262) installed on a 20m tower in the agricultural field. The methodology to calculate the flux is described in detail in Sakai et al. (2004) and a companion file is included that describes in detail the formulae used to calculate the eddy flux variables  (CD03_Pasture_Flux_Calculations.pdf).
A mesoscale network has been set up in the Santarem region of Para, Brazil. This network consists of eight meteorological stations named Belterra, Km 117 (Fazenda Sr. Davi), Mojui, Jamaraqua, Guarana, Embrapa (Cacoal Grande), Vila Franca and Sudam (Curua Una). Belterra and Km117 stations have been almost continuously collecting data since August, 1998, respectively. Mojui, Jamaraqua, and Guarana have been collecting data since July, 2000. Embrapa, Vila Franca and Sudam stations have been collecting data since 2002. Data are presented in 52 individual comma-separated ASCII files. Each file contains data from one calendar year for one site; both site and year are identified clearly in the data file name and all files follow the same header information and organizational structure. Measurements include air temperature and pressure, wind speed and direction, relative humidity, downward solar radiation, and at some stations soil temperature and moisture.
A mesoscale network has been set up in the Santarem region of Para, Brazil. This network consists of eight meteorological stations named Belterra, Km 117 (Fazenda Sr. Davi), Mojui, Jamaraqua, Guarana, Embrapa (Cacoal Grande), Vila Franca and Sudam (Curua Una). Belterra and Km117 stations have been almost continuously collecting data since August, 1998, respectively. Mojui, Jamaraqua, and Guarana have been collecting data since July, 2000. Embrapa, Vila Franca and Sudam stations have been collecting data since 2002. Data are presented in 52 individual comma-separated ASCII files. Each file contains data from one calendar year for one site; both site and year are identified clearly in the data file name and all files follow the same header information and organizational structure. Measurements include air temperature and pressure, wind speed and direction, relative humidity, downward solar radiation, and at some stations soil temperature and moisture.
ABSTRACT: A mesoscale network has been set up in the Santarem region of Para, Brazil. This network consists of eight meteorological stations named Belterra, Km 117 (Fazenda Sr. Davi), Mojui, Jamaraqua, Guarana, Embrapa (Cacoal Grande), Vila Franca and Sudam (Curua Una). Belterra and Km117 stations have been almost continuously collecting data since August, 1998, respectively. Mojui, Jamaraqua, and Guarana have been collecting data since July, 2000. Embrapa, Vila Franca and Sudam stations have been collecting data since 2002. Data are presented in 52 individual comma-separated ASCII files. Each file contains data from one calendar year for one site; both site and year are identified clearly in the data file name and all files follow the same header information and organizational structure. Measurements include air temperature and pressure, wind speed and direction, relative humidity, downward solar radiation, and at some stations soil temperature and moisture.
This data set contains measurements of nocturnal meteorological profiles collected from tethered balloon platforms during July 2001, October 2001, and November 2003. Measurements were made near the pasture/agricultural tower site at km 77 on BR-163 just south of the city of Santarem, and the near the Tapajos National Forest, km 83 tower site, Santarem, Para, Brazil.  Measurements collected include air temperature, wind speed and direction, and specific humidity. The 2003 measurements also included CO2 concentrations. Sites were near enough to allow comparison between sounding profiles and tower data. There are three comma-delimited ASCII files with this data set. Profiles were obtained from sunset until the first hours after sunrise. Each sounding provided information on temperature, humidity, horizontal wind magnitude and direction as the balloon went up and down. Typical soundings went up to 300 to 400 m. During most of the night, soundings were performed hourly. The balloon rose at a rate of 0.5 m per second in the first 100 m, and 2 m per second above it. The time between successive samplings was 10 s. Intensive periods of shallow, successive soundings were performed starting at dawn, to catch the early development of the convective boundary layer (CBL). These early morning soundings went up only to the capping inversion.
This data set contains measurements of nocturnal meteorological profiles collected from tethered balloon platforms during July 2001, October 2001, and November 2003. Measurements were made near the pasture/agricultural tower site at km 77 on BR-163 just south of the city of Santarem, and the near the Tapajos National Forest, km 83 tower site, Santarem, Para, Brazil.  Measurements collected include air temperature, wind speed and direction, and specific humidity. The 2003 measurements also included CO2 concentrations. Sites were near enough to allow comparison between sounding profiles and tower data. There are three comma-delimited ASCII files with this data set. Profiles were obtained from sunset until the first hours after sunrise. Each sounding provided information on temperature, humidity, horizontal wind magnitude and direction as the balloon went up and down. Typical soundings went up to 300 to 400 m. During most of the night, soundings were performed hourly. The balloon rose at a rate of 0.5 m per second in the first 100 m, and 2 m per second above it. The time between successive samplings was 10 s. Intensive periods of shallow, successive soundings were performed starting at dawn, to catch the early development of the convective boundary layer (CBL). These early morning soundings went up only to the capping inversion.
ABSTRACT: This data set contains measurements of nocturnal meteorological profiles collected from tethered balloon platforms during July 2001, October 2001, and November 2003. Measurements were made near the pasture/agricultural tower site at km 77 on BR-163 just south of the city of Santarem, and the near the Tapajos National Forest, km 83 tower site, Santarem, Para, Brazil.  Measurements collected include air temperature, wind speed and direction, and specific humidity. The 2003 measurements also included CO2 concentrations. Sites were near enough to allow comparison between sounding profiles and tower data. There are three comma-delimited ASCII files with this data set. Profiles were obtained from sunset until the first hours after sunrise. Each sounding provided information on temperature, humidity, horizontal wind magnitude and direction as the balloon went up and down. Typical soundings went up to 300 to 400 m. During most of the night, soundings were performed hourly. The balloon rose at a rate of 0.5 m per second in the first 100 m, and 2 m per second above it. The time between successive samplings was 10 s. Intensive periods of shallow, successive soundings were performed starting at dawn, to catch the early development of the convective boundary layer (CBL). These early morning soundings went up only to the capping inversion.
This data set contains the results of a biometric tree survey of a 19.25 ha area adjacent to the eddy flux tower at the km 83 logged forest tower site in Tapajos National Forest, Para, Brazil. The survey was done in March 2000. All measurements reported here were taken before the logging began. Diameters of all trees > 35 cm DBH within the 19.25 ha survey area were recorded and trees with DBH between 10 and 35 cm DBH were recorded along three transects with a total area of 2.3 ha (Miller et al., 2004). These data were used to calculate net ecosystem productivity (NEP) and the role of this forest as a carbon source or sink. Biometric data are reported in one comma-delimited ASCII file.
This data set contains the results of a biometric tree survey of a 19.25 ha area adjacent to the eddy flux tower at the km 83 logged forest tower site in Tapajos National Forest, Para, Brazil. The survey was done in March 2000. All measurements reported here were taken before the logging began. Diameters of all trees > 35 cm DBH within the 19.25 ha survey area were recorded and trees with DBH between 10 and 35 cm DBH were recorded along three transects with a total area of 2.3 ha (Miller et al., 2004). These data were used to calculate net ecosystem productivity (NEP) and the role of this forest as a carbon source or sink. Biometric data are reported in one comma-delimited ASCII file.
ABSTRACT: This data set contains the results of a biometric tree survey of a 19.25 ha area adjacent to the eddy flux tower at the km 83 logged forest tower site in Tapajos National Forest, Para, Brazil. The survey was done in March 2000. All measurements reported here were taken before the logging began. Diameters of all trees > 35 cm DBH within the 19.25 ha survey area were recorded and trees with DBH between 10 and 35 cm DBH were recorded along three transects with a total area of 2.3 ha (Miller et al., 2004). These data were used to calculate net ecosystem productivity (NEP) and the role of this forest as a carbon source or sink. Biometric data are reported in one comma-delimited ASCII file.
This data set reports 30-minute values for above-canopy meteorology and fluxes of momentum, heat, and carbon dioxide, and within-canopy carbon dioxide and water vapor concentrations collected at 12 levels between 10 cm and 64 m at the tower located within a logging gap at km 83 Tower Site in the Tapajos National Forest, Para, Brazil. Data were collected over 1.5 years between June 3, 2002 and January 30, 2004. All of the data are contained in one comma separated file.Two towers are located at the km 83 site. The first tower was installed in an intact forest area at this site in June 2000 (the 'intact' tower). In September 2001, the area adjacent to the tower was selectively logged (Bruno et al., 2006). The second tower (the 'gap tower') was installed and operating in June 2002, 400 m east of the intact tower. The gap tower was installed in the middle of a 50 m x 50 m log landing.
This data set reports 30-minute values for above-canopy meteorology and fluxes of momentum, heat, and carbon dioxide, and within-canopy carbon dioxide and water vapor concentrations collected at 12 levels between 10 cm and 64 m at the tower located within a logging gap at km 83 Tower Site in the Tapajos National Forest, Para, Brazil. Data were collected over 1.5 years between June 3, 2002 and January 30, 2004. All of the data are contained in one comma separated file.Two towers are located at the km 83 site. The first tower was installed in an intact forest area at this site in June 2000 (the 'intact' tower). In September 2001, the area adjacent to the tower was selectively logged (Bruno et al., 2006). The second tower (the 'gap tower') was installed and operating in June 2002, 400 m east of the intact tower. The gap tower was installed in the middle of a 50 m x 50 m log landing.
ABSTRACT: This data set reports 30-minute values for above-canopy meteorology and fluxes of momentum, heat, and carbon dioxide, and within-canopy carbon dioxide and water vapor concentrations collected at 12 levels between 10 cm and 64 m at the tower located within a logging gap at km 83 Tower Site in the Tapajos National Forest, Para, Brazil. Data were collected over 1.5 years between June 3, 2002 and January 30, 2004. All of the data are contained in one comma separated file.Two towers are located at the km 83 site. The first tower was installed in an intact forest area at this site in June 2000 (the 'intact' tower). In September 2001, the area adjacent to the tower was selectively logged (Bruno et al., 2006). The second tower (the 'gap tower') was installed and operating in June 2002, 400 m east of the intact tower. The gap tower was installed in the middle of a 50 m x 50 m log landing.
Atmospheric carbon dioxide profiles were measured at 12 levels up to 64 m at the km 83 logged tower site in Tapajos National Forest, Santarem, Para, Brazil. Data were collected over 3.5 years between June 2000-March 2004. An infra-red gas analyzer sequentially measured the concentration of CO2 at 12 heights (0.1, 0.35, 0.7, 1.4, 3, 6, 10.7, 20, 35, 40, 50, 64 m above the ground) on the tower every 48 minutes. The data, reported on a 30 minute interval, are provided in one single comma separated file.
Atmospheric carbon dioxide profiles were measured at 12 levels up to 64 m at the km 83 logged tower site in Tapajos National Forest, Santarem, Para, Brazil. Data were collected over 3.5 years between June 2000-March 2004. An infra-red gas analyzer sequentially measured the concentration of CO2 at 12 heights (0.1, 0.35, 0.7, 1.4, 3, 6, 10.7, 20, 35, 40, 50, 64 m above the ground) on the tower every 48 minutes. The data, reported on a 30 minute interval, are provided in one single comma separated file.
ABSTRACT: Atmospheric carbon dioxide profiles were measured at 12 levels up to 64 m at the km 83 logged tower site in Tapajos National Forest, Santarem, Para, Brazil. Data were collected over 3.5 years between June 2000-March 2004. An infra-red gas analyzer sequentially measured the concentration of CO2 at 12 heights (0.1, 0.35, 0.7, 1.4, 3, 6, 10.7, 20, 35, 40, 50, 64 m above the ground) on the tower every 48 minutes. The data, reported on a 30 minute interval, are provided in one single comma separated file.
A dendrometry study was conducted at the logged forest tower site, km 83 site, Tapajos National Forest, Para, Brazil over a period of 4 years following the implementation of a reduced impact logging management regime. Dendrometer bands were installed to measure diameter growth increments for 234 trees in an 18 ha plot adjacent to the eddy flux tower at the km 83 site. In addition to trees randomly selected for measurements within the plot prior to logging, a set of smaller diameter trees within or adjacent to gaps created during the logging treatment were added to the study in 2002. Selective logging is a major land use in the Amazon Basin. An accurate accounting of the effect of logging on regional carbon balances requires better information on the rates at which the logged forest recovers biomass. There is one comma-delimited data file with this data set.
A dendrometry study was conducted at the logged forest tower site, km 83 site, Tapajos National Forest, Para, Brazil over a period of 4 years following the implementation of a reduced impact logging management regime. Dendrometer bands were installed to measure diameter growth increments for 234 trees in an 18 ha plot adjacent to the eddy flux tower at the km 83 site. In addition to trees randomly selected for measurements within the plot prior to logging, a set of smaller diameter trees within or adjacent to gaps created during the logging treatment were added to the study in 2002. Selective logging is a major land use in the Amazon Basin. An accurate accounting of the effect of logging on regional carbon balances requires better information on the rates at which the logged forest recovers biomass. There is one comma-delimited data file with this data set.
ABSTRACT: A dendrometry study was conducted at the logged forest tower site, km 83 site, Tapajos National Forest, Para, Brazil over a period of 4 years following the implementation of a reduced impact logging management regime. Dendrometer bands were installed to measure diameter growth increments for 234 trees in an 18 ha plot adjacent to the eddy flux tower at the km 83 site. In addition to trees randomly selected for measurements within the plot prior to logging, a set of smaller diameter trees within or adjacent to gaps created during the logging treatment were added to the study in 2002. Selective logging is a major land use in the Amazon Basin. An accurate accounting of the effect of logging on regional carbon balances requires better information on the rates at which the logged forest recovers biomass. There is one comma-delimited data file with this data set.
This data set contains summary data for monthly leaf area index (LAI) and plant area index (PAI) at the km 83 Tower Site, in the Tapajos National Forest, Para, Brazil. LAI was estimated for hemispherical photographs of leaves collected between 2000 and 2003, using the histogram and gap-fraction analysis methods.There are two data files with this data set: one comma-delimited ASCII data file with this data set which contains the monthly summary LAI and PAI data, and one compressed (*.zip) file that contains hemispherical photo images (.bmp) for 2000-2001. The images include those taken pre-logging and post-logging at the measurement site for the purpose of comparing LAI. In addition, there is a companion file containing a program code developed for LAI analysis provided as an ASCII text file.
This data set contains summary data for monthly leaf area index (LAI) and plant area index (PAI) at the km 83 Tower Site, in the Tapajos National Forest, Para, Brazil. LAI was estimated for hemispherical photographs of leaves collected between 2000 and 2003, using the histogram and gap-fraction analysis methods.There are two data files with this data set: one comma-delimited ASCII data file with this data set which contains the monthly summary LAI and PAI data, and one compressed (*.zip) file that contains hemispherical photo images (.bmp) for 2000-2001. The images include those taken pre-logging and post-logging at the measurement site for the purpose of comparing LAI. In addition, there is a companion file containing a program code developed for LAI analysis provided as an ASCII text file.
ABSTRACT: This data set contains summary data for monthly leaf area index (LAI) and plant area index (PAI) at the km 83 Tower Site, in the Tapajos National Forest, Para, Brazil. LAI was estimated for hemispherical photographs of leaves collected between 2000 and 2003, using the histogram and gap-fraction analysis methods.There are two data files with this data set: one comma-delimited ASCII data file with this data set which contains the monthly summary LAI and PAI data, and one compressed (*.zip) file that contains hemispherical photo images (.bmp) for 2000-2001. The images include those taken pre-logging and post-logging at the measurement site for the purpose of comparing LAI. In addition, there is a companion file containing a program code developed for LAI analysis provided as an ASCII text file.
Leaf area index was estimated in an 18 ha plot at the logged forest tower site, km 83, Tapajos National Forest, Para, Brazil. The plot was adjacent to the eddy flux tower at km 83, Tapajos National Forest, Para, Brazil.  Thirty  litter traps were placed at 25-m intervals along two east-west transects in the 18 ha block. Litter samples were collected biweekly from the traps and returned to the lab where they were sorted, air dried, and weighed. The leaf area of a subsample of air-dried leaves was determined using a computer scanner and image processing software. The subsample was then dried in an oven and the air-dried weights were corrected to oven-dried weight. The area of leaf litter collected during each sampling was calculated using the relationship between weight and area measured for the subsample (Goulden et al., 2004). There is one comma-delimited data file with this data set.
Leaf area index was estimated in an 18 ha plot at the logged forest tower site, km 83, Tapajos National Forest, Para, Brazil. The plot was adjacent to the eddy flux tower at km 83, Tapajos National Forest, Para, Brazil.  Thirty  litter traps were placed at 25-m intervals along two east-west transects in the 18 ha block. Litter samples were collected biweekly from the traps and returned to the lab where they were sorted, air dried, and weighed. The leaf area of a subsample of air-dried leaves was determined using a computer scanner and image processing software. The subsample was then dried in an oven and the air-dried weights were corrected to oven-dried weight. The area of leaf litter collected during each sampling was calculated using the relationship between weight and area measured for the subsample (Goulden et al., 2004). There is one comma-delimited data file with this data set.
ABSTRACT: Leaf area index was estimated in an 18 ha plot at the logged forest tower site, km 83, Tapajos National Forest, Para, Brazil. The plot was adjacent to the eddy flux tower at km 83, Tapajos National Forest, Para, Brazil.  Thirty  litter traps were placed at 25-m intervals along two east-west transects in the 18 ha block. Litter samples were collected biweekly from the traps and returned to the lab where they were sorted, air dried, and weighed. The leaf area of a subsample of air-dried leaves was determined using a computer scanner and image processing software. The subsample was then dried in an oven and the air-dried weights were corrected to oven-dried weight. The area of leaf litter collected during each sampling was calculated using the relationship between weight and area measured for the subsample (Goulden et al., 2004). There is one comma-delimited data file with this data set.
Above-ground litter productivity was measured in a 18 ha plot adjacent to the eddy flux tower at the logged forest tower site, km 83, Tapajos National Forest, Para, Brazil. Thirty litter baskets distributed within the grid were visited bi-weekly (Goulden et al., 2004). Oven dry mass of leaves, wood, reproductive parts and miscellaneous components of the collected litter was determined for each collection. Collections covered a pre-harvest period (Sept 2000 - July 2001) and a post- harvest period (Aug 2001-Mar 2003).  There is one comma-delimited data file with this data set.
Above-ground litter productivity was measured in a 18 ha plot adjacent to the eddy flux tower at the logged forest tower site, km 83, Tapajos National Forest, Para, Brazil. Thirty litter baskets distributed within the grid were visited bi-weekly (Goulden et al., 2004). Oven dry mass of leaves, wood, reproductive parts and miscellaneous components of the collected litter was determined for each collection. Collections covered a pre-harvest period (Sept 2000 - July 2001) and a post- harvest period (Aug 2001-Mar 2003).  There is one comma-delimited data file with this data set.
ABSTRACT: Above-ground litter productivity was measured in a 18 ha plot adjacent to the eddy flux tower at the logged forest tower site, km 83, Tapajos National Forest, Para, Brazil. Thirty litter baskets distributed within the grid were visited bi-weekly (Goulden et al., 2004). Oven dry mass of leaves, wood, reproductive parts and miscellaneous components of the collected litter was determined for each collection. Collections covered a pre-harvest period (Sept 2000 - July 2001) and a post- harvest period (Aug 2001-Mar 2003).  There is one comma-delimited data file with this data set.
This data set reports the results of measurements of (1) leaf-level photosynthesis response curves for the effects of temperature, leaf age, warming, irradiation, and circadian rhythm and (2) leaf-level photorespiration rates at 30 and 37 degrees C. Measurements were made between June 2000 and February 2006 at the km 83 Logged Forest Tower site, the km 67 Primary Forest Tower site, and the control site at Seca Floresta, all in the Tapajos National Forest, Para, Brazil. There are 7 comma delimited ASCII data files with this data set.
This data set reports the results of measurements of (1) leaf-level photosynthesis response curves for the effects of temperature, leaf age, warming, irradiation, and circadian rhythm and (2) leaf-level photorespiration rates at 30 and 37 degrees C. Measurements were made between June 2000 and February 2006 at the km 83 Logged Forest Tower site, the km 67 Primary Forest Tower site, and the control site at Seca Floresta, all in the Tapajos National Forest, Para, Brazil. There are 7 comma delimited ASCII data files with this data set.
ABSTRACT: This data set reports the results of measurements of (1) leaf-level photosynthesis response curves for the effects of temperature, leaf age, warming, irradiation, and circadian rhythm and (2) leaf-level photorespiration rates at 30 and 37 degrees C. Measurements were made between June 2000 and February 2006 at the km 83 Logged Forest Tower site, the km 67 Primary Forest Tower site, and the control site at Seca Floresta, all in the Tapajos National Forest, Para, Brazil. There are 7 comma delimited ASCII data files with this data set.
This data set contains the results of a survey of logging damage in a 18 ha plot (300 m N-S, 600 m E-W) east (upwind) of the eddy flux tower at km 83, Tapajos National Forest, Para, Brazil. Data collected include type of damage, snap height, and log dimensions, as well as calculated biomass of stems and canopy either damaged or removed in logging. There are two comma-delimited data files with this data set.
This data set contains the results of a survey of logging damage in a 18 ha plot (300 m N-S, 600 m E-W) east (upwind) of the eddy flux tower at km 83, Tapajos National Forest, Para, Brazil. Data collected include type of damage, snap height, and log dimensions, as well as calculated biomass of stems and canopy either damaged or removed in logging. There are two comma-delimited data files with this data set.
ABSTRACT: This data set contains the results of a survey of logging damage in a 18 ha plot (300 m N-S, 600 m E-W) east (upwind) of the eddy flux tower at km 83, Tapajos National Forest, Para, Brazil. Data collected include type of damage, snap height, and log dimensions, as well as calculated biomass of stems and canopy either damaged or removed in logging. There are two comma-delimited data files with this data set.
Tower flux measurements of carbon dioxide,water vapor, heat, and meteorological variables were obtained at the Tapajos National Forest, km 83 site, Santarem, Para, Brazil. For the period June 29, 2000 through March 11, 2004, 30-minute averaged and calculated quantities of fluxes of momentum, heat, water vapor, and carbon dioxide, storage of carbon dioxide in the air column, are reported. Data are reported in three comma separated files: (1) 30 minute-averages,  (2) the daily (24 hour) averages, and (3) the monthly (calendar) averages.The variables measured on the 67 m tower relate to meteorology, soil moisture, respiration, fluxes of momentum, heat, water vapor, and carbon dioxide, and were used to calculate storage of carbon dioxide, Net Ecosystem Exchange, and Gross Primary Productivity. Most of the variables have not been gap filled. However, CO2 flux and storage have been filled to avoid biases in Net Ecosystem Exchange; a fill index flag is included to indicate which data points were filled. Variables derived from the filled variables (respiration, NEE, GPP) are essentially filled also. Net ecosystem exchange has been filtered for calm nighttime periods.
Tower flux measurements of carbon dioxide,water vapor, heat, and meteorological variables were obtained at the Tapajos National Forest, km 83 site, Santarem, Para, Brazil. For the period June 29, 2000 through March 11, 2004, 30-minute averaged and calculated quantities of fluxes of momentum, heat, water vapor, and carbon dioxide, storage of carbon dioxide in the air column, are reported. Data are reported in three comma separated files: (1) 30 minute-averages,  (2) the daily (24 hour) averages, and (3) the monthly (calendar) averages.The variables measured on the 67 m tower relate to meteorology, soil moisture, respiration, fluxes of momentum, heat, water vapor, and carbon dioxide, and were used to calculate storage of carbon dioxide, Net Ecosystem Exchange, and Gross Primary Productivity. Most of the variables have not been gap filled. However, CO2 flux and storage have been filled to avoid biases in Net Ecosystem Exchange; a fill index flag is included to indicate which data points were filled. Variables derived from the filled variables (respiration, NEE, GPP) are essentially filled also. Net ecosystem exchange has been filtered for calm nighttime periods.
ABSTRACT: Tower flux measurements of carbon dioxide,water vapor, heat, and meteorological variables were obtained at the Tapajos National Forest, km 83 site, Santarem, Para, Brazil. For the period June 29, 2000 through March 11, 2004, 30-minute averaged and calculated quantities of fluxes of momentum, heat, water vapor, and carbon dioxide, storage of carbon dioxide in the air column, are reported. Data are reported in three comma separated files: (1) 30 minute-averages,  (2) the daily (24 hour) averages, and (3) the monthly (calendar) averages.The variables measured on the 67 m tower relate to meteorology, soil moisture, respiration, fluxes of momentum, heat, water vapor, and carbon dioxide, and were used to calculate storage of carbon dioxide, Net Ecosystem Exchange, and Gross Primary Productivity. Most of the variables have not been gap filled. However, CO2 flux and storage have been filled to avoid biases in Net Ecosystem Exchange; a fill index flag is included to indicate which data points were filled. Variables derived from the filled variables (respiration, NEE, GPP) are essentially filled also. Net ecosystem exchange has been filtered for calm nighttime periods.
This data set reports continuous high-resolution frequency-domain reflectometry measurements of soil moisture to 10 m depth and precipitation data near each of the two towers located at the km 83 tower site (logged forest site) in the Tapajos National Forest in the state of Para, Brazil. Measurements were made during 2002 and 2003. Soil moisture and precipitation data are provided in two comma-delimited ASCII files.The first tower was installed in an intact forest area at this site in June 2000 (the 'intact' tower) and instrumented for eddy flux and micrometerological measurements and operated 15 months prior to any logging in the area (Goulden et al., 2004; Miller et al., 2004; Rocha et al., 2004). In September 2001, the area adjacent to the tower was selectively logged (Bruno et al., 2006).The second tower (the 'gap tower' tower) was installed and operating in June 2002, 400 m east of the intact tower. The gap tower was installed in the middle of a 50 m x 50 m log landing.Soil moisture measurements were made in 10 m deep vertical pits (1 x 1 m2) approximately 20 m from the micrometerological tower sites in undisturbed forest patches. Reflectometers were inserted horizontally into shaft walls at 0.15, 0.30, 0.60, 1, 2, 3, 4, 6, 8, and 10 meters beneath the surface. These data were used to determine how soil moisture varies on diel, seasonal and multi-year timescales and to better understand the quantitative and mechanistic relationships between soil moisture and forest evapotranspiration.
This data set reports continuous high-resolution frequency-domain reflectometry measurements of soil moisture to 10 m depth and precipitation data near each of the two towers located at the km 83 tower site (logged forest site) in the Tapajos National Forest in the state of Para, Brazil. Measurements were made during 2002 and 2003. Soil moisture and precipitation data are provided in two comma-delimited ASCII files.The first tower was installed in an intact forest area at this site in June 2000 (the 'intact' tower) and instrumented for eddy flux and micrometerological measurements and operated 15 months prior to any logging in the area (Goulden et al., 2004; Miller et al., 2004; Rocha et al., 2004). In September 2001, the area adjacent to the tower was selectively logged (Bruno et al., 2006).The second tower (the 'gap tower' tower) was installed and operating in June 2002, 400 m east of the intact tower. The gap tower was installed in the middle of a 50 m x 50 m log landing.Soil moisture measurements were made in 10 m deep vertical pits (1 x 1 m2) approximately 20 m from the micrometerological tower sites in undisturbed forest patches. Reflectometers were inserted horizontally into shaft walls at 0.15, 0.30, 0.60, 1, 2, 3, 4, 6, 8, and 10 meters beneath the surface. These data were used to determine how soil moisture varies on diel, seasonal and multi-year timescales and to better understand the quantitative and mechanistic relationships between soil moisture and forest evapotranspiration.
ABSTRACT: This data set reports continuous high-resolution frequency-domain reflectometry measurements of soil moisture to 10 m depth and precipitation data near each of the two towers located at the km 83 tower site (logged forest site) in the Tapajos National Forest in the state of Para, Brazil. Measurements were made during 2002 and 2003. Soil moisture and precipitation data are provided in two comma-delimited ASCII files.The first tower was installed in an intact forest area at this site in June 2000 (the 'intact' tower) and instrumented for eddy flux and micrometerological measurements and operated 15 months prior to any logging in the area (Goulden et al., 2004; Miller et al., 2004; Rocha et al., 2004). In September 2001, the area adjacent to the tower was selectively logged (Bruno et al., 2006).The second tower (the 'gap tower' tower) was installed and operating in June 2002, 400 m east of the intact tower. The gap tower was installed in the middle of a 50 m x 50 m log landing.Soil moisture measurements were made in 10 m deep vertical pits (1 x 1 m2) approximately 20 m from the micrometerological tower sites in undisturbed forest patches. Reflectometers were inserted horizontally into shaft walls at 0.15, 0.30, 0.60, 1, 2, 3, 4, 6, 8, and 10 meters beneath the surface. These data were used to determine how soil moisture varies on diel, seasonal and multi-year timescales and to better understand the quantitative and mechanistic relationships between soil moisture and forest evapotranspiration.
This data set reports on the flux of carbon dioxide from logged forest soils near the eddy flux tower at the km 83 site, Para, Brazil. The automated soil respiration measurements were collected using 15 chambers, installed August 2001 in primary forest. Data were collected between December 19, 2001 and March 1, 2002. There is one comma-delimited data file with this data set.
This data set reports on the flux of carbon dioxide from logged forest soils near the eddy flux tower at the km 83 site, Para, Brazil. The automated soil respiration measurements were collected using 15 chambers, installed August 2001 in primary forest. Data were collected between December 19, 2001 and March 1, 2002. There is one comma-delimited data file with this data set.
ABSTRACT: This data set reports on the flux of carbon dioxide from logged forest soils near the eddy flux tower at the km 83 site, Para, Brazil. The automated soil respiration measurements were collected using 15 chambers, installed August 2001 in primary forest. Data were collected between December 19, 2001 and March 1, 2002. There is one comma-delimited data file with this data set.
This data set reports soil moisture expressed as volumetric water content (VWC), daily precipitation, air temperature, relative humidity, and dew point measurements conducted at the Seca Floresta site, km 67, Tapajos National Forest, Brazil. The measurements were part of the Rainfall Exclusion Experiment (REE) established to study the response of a humid Amazonian forest to severe drought.VWC was measured with continuous high-resolution frequency-domain reflectometry to 11-m depth in two 1-ha plots from 1999 to 2007. One plot was subjected to ~75 percent throughfall exclusion during the rainy season (exclusion) and another monitored under normal conditions (control). Daily precipitation was measured in the control plot and in a nearby clearing between 1999 and 2006 using wedge rain gauges. Air temperature, relative humidity, and dew point were measured along the vertical forest profile of the control and dry plots of the site between 2000 and 2003.There are three comma-delimited data files (.csv) with this data set.
This data set reports soil moisture expressed as volumetric water content (VWC), daily precipitation, air temperature, relative humidity, and dew point measurements conducted at the Seca Floresta site, km 67, Tapajos National Forest, Brazil. The measurements were part of the Rainfall Exclusion Experiment (REE) established to study the response of a humid Amazonian forest to severe drought.VWC was measured with continuous high-resolution frequency-domain reflectometry to 11-m depth in two 1-ha plots from 1999 to 2007. One plot was subjected to ~75 percent throughfall exclusion during the rainy season (exclusion) and another monitored under normal conditions (control). Daily precipitation was measured in the control plot and in a nearby clearing between 1999 and 2006 using wedge rain gauges. Air temperature, relative humidity, and dew point were measured along the vertical forest profile of the control and dry plots of the site between 2000 and 2003.There are three comma-delimited data files (.csv) with this data set.
ABSTRACT: This data set reports soil moisture expressed as volumetric water content (VWC), daily precipitation, air temperature, relative humidity, and dew point measurements conducted at the Seca Floresta site, km 67, Tapajos National Forest, Brazil. The measurements were part of the Rainfall Exclusion Experiment (REE) established to study the response of a humid Amazonian forest to severe drought.VWC was measured with continuous high-resolution frequency-domain reflectometry to 11-m depth in two 1-ha plots from 1999 to 2007. One plot was subjected to ~75 percent throughfall exclusion during the rainy season (exclusion) and another monitored under normal conditions (control). Daily precipitation was measured in the control plot and in a nearby clearing between 1999 and 2006 using wedge rain gauges. Air temperature, relative humidity, and dew point were measured along the vertical forest profile of the control and dry plots of the site between 2000 and 2003.There are three comma-delimited data files (.csv) with this data set.
This data set provides high-resolution (~500 m) gridded land and stream drainage direction maps for the Amazon River basin, excluding the Rio Tocantins basin. These maps are the result of a new topography-independent analysis method (Mayorga et al., 2005) using the vector river network from the Digital Chart of the World (DCW, Danko, 1992) to create a high-resolution flow direction map. The data products include (1) a stream network coverage with stream order assigned to each reach; (2) the basin boundaries of the major tributaries to the Amazon mainstem; (3) the mouths; and (4) the source points of these tributaries.There are 7 ESRI ArcGIS shapefiles provided in compressed *.zip format and 4 GeoTiff image files with this data set.
This data set provides high-resolution (~500 m) gridded land and stream drainage direction maps for the Amazon River basin, excluding the Rio Tocantins basin. These maps are the result of a new topography-independent analysis method (Mayorga et al., 2005) using the vector river network from the Digital Chart of the World (DCW, Danko, 1992) to create a high-resolution flow direction map. The data products include (1) a stream network coverage with stream order assigned to each reach; (2) the basin boundaries of the major tributaries to the Amazon mainstem; (3) the mouths; and (4) the source points of these tributaries.There are 7 ESRI ArcGIS shapefiles provided in compressed *.zip format and 4 GeoTiff image files with this data set.
ABSTRACT: This data set provides high-resolution (~500 m) gridded land and stream drainage direction maps for the Amazon River basin, excluding the Rio Tocantins basin. These maps are the result of a new topography-independent analysis method (Mayorga et al., 2005) using the vector river network from the Digital Chart of the World (DCW, Danko, 1992) to create a high-resolution flow direction map. The data products include (1) a stream network coverage with stream order assigned to each reach; (2) the basin boundaries of the major tributaries to the Amazon mainstem; (3) the mouths; and (4) the source points of these tributaries.There are 7 ESRI ArcGIS shapefiles provided in compressed *.zip format and 4 GeoTiff image files with this data set.
This data set provides measured and calculated variables describing the carbon pools in river waters, CO2 respired from the water and total amount of CO2 evaded, dissolved oxygen isotopes (delta 18O-O2), and concentration of bacterial cells in river water. Samples were collected from 10 white-water rivers, two clear-water streams (one each in Amazonas and Acre), and two black-water rivers in Amazonas from July to September 2005, which coincided with a severe drought in the western and southern regions of the Amazon Basin (Zeng et al. 2008). Eight of these sites were resampled during August through September 2006 of the following year (no drought).
This data set provides measured and calculated variables describing the carbon pools in river waters, CO2 respired from the water and total amount of CO2 evaded, dissolved oxygen isotopes (delta 18O-O2), and concentration of bacterial cells in river water. Samples were collected from 10 white-water rivers, two clear-water streams (one each in Amazonas and Acre), and two black-water rivers in Amazonas from July to September 2005, which coincided with a severe drought in the western and southern regions of the Amazon Basin (Zeng et al. 2008). Eight of these sites were resampled during August through September 2006 of the following year (no drought).
ABSTRACT: This data set provides measured and calculated variables describing the carbon pools in river waters, CO2 respired from the water and total amount of CO2 evaded, dissolved oxygen isotopes (delta 18O-O2), and concentration of bacterial cells in river water. Samples were collected from 10 white-water rivers, two clear-water streams (one each in Amazonas and Acre), and two black-water rivers in Amazonas from July to September 2005, which coincided with a severe drought in the western and southern regions of the Amazon Basin (Zeng et al. 2008). Eight of these sites were resampled during August through September 2006 of the following year (no drought).
This data set provides measurements of carbon dioxide flux rates (FCO2), gas transfer velocity (k), and partial pressures (pCO2) at 75 sites on rivers and streams of the Amazon River system in South America for the period beginning July 1, 2004, and ending January 23, 2007. Several fieldwork campaigns occurred between June 2004 and January 2007 in the Amazon River basin, with discharge conditions ranging from low to high flow. The sampled areas span the spectrum of chemical characteristics observed across the entire basin, including, for example, both low and high pH values and suspended sediment loads. There is one comma-delimited data file in this data set.
This data set provides measurements of carbon dioxide flux rates (FCO2), gas transfer velocity (k), and partial pressures (pCO2) at 75 sites on rivers and streams of the Amazon River system in South America for the period beginning July 1, 2004, and ending January 23, 2007. Several fieldwork campaigns occurred between June 2004 and January 2007 in the Amazon River basin, with discharge conditions ranging from low to high flow. The sampled areas span the spectrum of chemical characteristics observed across the entire basin, including, for example, both low and high pH values and suspended sediment loads. There is one comma-delimited data file in this data set.
ABSTRACT: This data set provides measurements of carbon dioxide flux rates (FCO2), gas transfer velocity (k), and partial pressures (pCO2) at 75 sites on rivers and streams of the Amazon River system in South America for the period beginning July 1, 2004, and ending January 23, 2007. Several fieldwork campaigns occurred between June 2004 and January 2007 in the Amazon River basin, with discharge conditions ranging from low to high flow. The sampled areas span the spectrum of chemical characteristics observed across the entire basin, including, for example, both low and high pH values and suspended sediment loads. There is one comma-delimited data file in this data set.
This data set includes measurements of standard geochemical variables, dissolved CO2, dissolved inorganic carbon (DIC), dissolved organic carbon (DOC), fine particulate organic carbon (FPOC), and coarse particulate organic carbon (CPOC) in samples taken from 60 Amazonian river locations across the Amazon Basin from 1991 to 2003 (Mayorga et al., 2005). The 14C and 13C isotopic composition of DIC was measured on samples collected between 1991 and 2003. The 14C composition of organic carbon fractions was measured on samples collected from 1995 through 1996. There are four comma-delimited data files with this data set. Note that site descriptions include a categorization of each site by topography according to the percentage of the drainage area above 1,000 m elevation (Mayorga et al., 2005). Only means of geochemical and carbon-fraction results are provided. Both individual 13C and 14C measurements and mean results are provided.
This data set includes measurements of standard geochemical variables, dissolved CO2, dissolved inorganic carbon (DIC), dissolved organic carbon (DOC), fine particulate organic carbon (FPOC), and coarse particulate organic carbon (CPOC) in samples taken from 60 Amazonian river locations across the Amazon Basin from 1991 to 2003 (Mayorga et al., 2005). The 14C and 13C isotopic composition of DIC was measured on samples collected between 1991 and 2003. The 14C composition of organic carbon fractions was measured on samples collected from 1995 through 1996. There are four comma-delimited data files with this data set. Note that site descriptions include a categorization of each site by topography according to the percentage of the drainage area above 1,000 m elevation (Mayorga et al., 2005). Only means of geochemical and carbon-fraction results are provided. Both individual 13C and 14C measurements and mean results are provided.
ABSTRACT: This data set includes measurements of standard geochemical variables, dissolved CO2, dissolved inorganic carbon (DIC), dissolved organic carbon (DOC), fine particulate organic carbon (FPOC), and coarse particulate organic carbon (CPOC) in samples taken from 60 Amazonian river locations across the Amazon Basin from 1991 to 2003 (Mayorga et al., 2005). The 14C and 13C isotopic composition of DIC was measured on samples collected between 1991 and 2003. The 14C composition of organic carbon fractions was measured on samples collected from 1995 through 1996. There are four comma-delimited data files with this data set. Note that site descriptions include a categorization of each site by topography according to the percentage of the drainage area above 1,000 m elevation (Mayorga et al., 2005). Only means of geochemical and carbon-fraction results are provided. Both individual 13C and 14C measurements and mean results are provided.
This data set provides a land use/land cover map of the Ji-Parana River Basin in the state of Rondonia, Brazil produced from the digital classification of eight Landsat 7-ETM+ scenes from 1999 acquired from the Tropical Rain Forest Information Center (TRFIC) at Michigan State University. Nine land cover classes covering the Ji-Parana Basin were identified. There is one GeoTiff  file with this data set.
This data set provides a land use/land cover map of the Ji-Parana River Basin in the state of Rondonia, Brazil produced from the digital classification of eight Landsat 7-ETM+ scenes from 1999 acquired from the Tropical Rain Forest Information Center (TRFIC) at Michigan State University. Nine land cover classes covering the Ji-Parana Basin were identified. There is one GeoTiff  file with this data set.
ABSTRACT: This data set provides a land use/land cover map of the Ji-Parana River Basin in the state of Rondonia, Brazil produced from the digital classification of eight Landsat 7-ETM+ scenes from 1999 acquired from the Tropical Rain Forest Information Center (TRFIC) at Michigan State University. Nine land cover classes covering the Ji-Parana Basin were identified. There is one GeoTiff  file with this data set.
This data set contains four land use/land cover maps (1986, 1992, 1996 and 2001) for the Ji-Parana River Basin, derived from the digital classification of 8 Landsat images obtained from The Tropical Rain Forest Information Center (TRFIC).
This data set contains four land use/land cover maps (1986, 1992, 1996 and 2001) for the Ji-Parana River Basin, derived from the digital classification of 8 Landsat images obtained from The Tropical Rain Forest Information Center (TRFIC).
ABSTRACT: This data set contains four land use/land cover maps (1986, 1992, 1996 and 2001) for the Ji-Parana River Basin, derived from the digital classification of 8 Landsat images obtained from The Tropical Rain Forest Information Center (TRFIC).
ABSTRACT: This data set provides estimates of monthly carbon dioxide (CO2) flux from the Amazon mainstem rivers, tributary stream networks, and their associated varzeas (floodplains). CO2 flux was calculated using two aggregation approaches: for defined river basins (data file #2) and for defined river reaches (figure 2). Flux was calculated from (1) estimated surface water area by month for the Amazon mainstem rivers, associated varzeas, and tributary stream networks, (2) mean daily partial pressures of CO2 (pCO2) concentrations for the mainstem rivers, and (3) calculated mean pCO2 values for the varzea waters. Mean monthly discharge data for 11 mainstem rivers are also included. There are five comma-delimited data files with this data set. Amazon mainstem is a region covering the Amazon/Solimoes River mainstem from 70 degrees W to 54 degrees W. Data from the Japanese Earth Resources Satellite-1 (JERS-1) L-band synthetic aperture radar were used to estimate the areal coverage and inundation status of rivers and floodplains over 100 m in width and compiled into mosaics for periods of high and low  water.  For each mosaic, the study area was classified into either flooded or non-flooded areas. Data for the seasonal and spatial distributions of pCO2 within each hydrographic region were utilized from over 1,800 samples taken on 13 Carbon in the Amazon River Experiment (CAMREX) expeditions at different water stages throughout a 2,000 km reach of the central Amazon mainstem, tributary, and floodplain waters (Degens et al., 1991, Devol et al., 1995, Richey et al., 1988).
ABSTRACT: This data set provides estimates of monthly carbon dioxide (CO2) flux from the Amazon mainstem rivers, tributary stream networks, and their associated varzeas (floodplains). CO2 flux was calculated using two aggregation approaches: for defined river basins (data file #2) and for defined river reaches (figure 2). Flux was calculated from (1) estimated surface water area by month for the Amazon mainstem rivers, associated varzeas, and tributary stream networks, (2) mean daily partial pressures of CO2 (pCO2) concentrations for the mainstem rivers, and (3) calculated mean pCO2 values for the varzea waters. Mean monthly discharge data for 11 mainstem rivers are also included. There are five comma-delimited data files with this data set. Amazon mainstem is a region covering the Amazon/Solimoes River mainstem from 70 degrees W to 54 degrees W. Data from the Japanese Earth Resources Satellite-1 (JERS-1) L-band synthetic aperture radar were used to estimate the areal coverage and inundation status of rivers and floodplains over 100 m in width and compiled into mosaics for periods of high and low  water.  For each mosaic, the study area was classified into either flooded or non-flooded areas. Data for the seasonal and spatial distributions of pCO2 within each hydrographic region were utilized from over 1,800 samples taken on 13 Carbon in the Amazon River Experiment (CAMREX) expeditions at different water stages throughout a 2,000 km reach of the central Amazon mainstem, tributary, and floodplain waters (Degens et al., 1991, Devol et al., 1995, Richey et al., 1988).
ABSTRACT: This data set provides estimates of monthly carbon dioxide (CO2) flux from the Amazon mainstem rivers, tributary stream networks, and their associated varzeas (floodplains). CO2 flux was calculated using two aggregation approaches: for defined river basins (data file #2) and for defined river reaches (figure 2). Flux was calculated from (1) estimated surface water area by month for the Amazon mainstem rivers, associated varzeas, and tributary stream networks, (2) mean daily partial pressures of CO2 (pCO2) concentrations for the mainstem rivers, and (3) calculated mean pCO2 values for the varzea waters. Mean monthly discharge data for 11 mainstem rivers are also included. There are five comma-delimited data files with this data set. Amazon mainstem is a region covering the Amazon/Solimoes River mainstem from 70 degrees W to 54 degrees W. Data from the Japanese Earth Resources Satellite-1 (JERS-1) L-band synthetic aperture radar were used to estimate the areal coverage and inundation status of rivers and floodplains over 100 m in width and compiled into mosaics for periods of high and low  water.  For each mosaic, the study area was classified into either flooded or non-flooded areas. Data for the seasonal and spatial distributions of pCO2 within each hydrographic region were utilized from over 1,800 samples taken on 13 Carbon in the Amazon River Experiment (CAMREX) expeditions at different water stages throughout a 2,000 km reach of the central Amazon mainstem, tributary, and floodplain waters (Degens et al., 1991, Devol et al., 1995, Richey et al., 1988).
This data set contains physical, hydrologic, political, demographic, and societal maps for the Ji-Parana River Basin, in the state of Rondonia, Brazil. These data were used as base information in subsequent investigations of land use/land cover, biogeochemistry, soils, and water balance processes (Ballester et al., 2003). This data set includes a Digital Elevation Model (DEM), river networks and morphometric characteristics of the region (derived from the DEM), and a number of social and demographic vector sets (roads as of 2001, county borders, population change from 1970-2000, and settlement projects). The DEM is provided in GeoTIFF format. Other files are provided as shapefiles.
This data set contains physical, hydrologic, political, demographic, and societal maps for the Ji-Parana River Basin, in the state of Rondonia, Brazil. These data were used as base information in subsequent investigations of land use/land cover, biogeochemistry, soils, and water balance processes (Ballester et al., 2003). This data set includes a Digital Elevation Model (DEM), river networks and morphometric characteristics of the region (derived from the DEM), and a number of social and demographic vector sets (roads as of 2001, county borders, population change from 1970-2000, and settlement projects). The DEM is provided in GeoTIFF format. Other files are provided as shapefiles.
ABSTRACT: This data set contains physical, hydrologic, political, demographic, and societal maps for the Ji-Parana River Basin, in the state of Rondonia, Brazil. These data were used as base information in subsequent investigations of land use/land cover, biogeochemistry, soils, and water balance processes (Ballester et al., 2003). This data set includes a Digital Elevation Model (DEM), river networks and morphometric characteristics of the region (derived from the DEM), and a number of social and demographic vector sets (roads as of 2001, county borders, population change from 1970-2000, and settlement projects). The DEM is provided in GeoTIFF format. Other files are provided as shapefiles.
This data set provides a digital map of soil orders for the Ji-Parana River Basin, in the state of Rondonia, Brazil (Western Amazonia). Soil orders were manually digitized from a 1:500,000 map from EMBRAPA originally published in 1983. Oxisols and Ultisols are the predominant soil types in the basin, encompassing 47% and 24% of the total drainage area, respectively. Entisols cover 14%, Alfisols 13% and Eptisols 2% of the basin (Ballester et al., 2003). One data file is provided in ESRI ArcGIS Shapefile format compressed into a single zip file (*.zip).
This data set provides a digital map of soil orders for the Ji-Parana River Basin, in the state of Rondonia, Brazil (Western Amazonia). Soil orders were manually digitized from a 1:500,000 map from EMBRAPA originally published in 1983. Oxisols and Ultisols are the predominant soil types in the basin, encompassing 47% and 24% of the total drainage area, respectively. Entisols cover 14%, Alfisols 13% and Eptisols 2% of the basin (Ballester et al., 2003). One data file is provided in ESRI ArcGIS Shapefile format compressed into a single zip file (*.zip).
ABSTRACT: This data set provides a digital map of soil orders for the Ji-Parana River Basin, in the state of Rondonia, Brazil (Western Amazonia). Soil orders were manually digitized from a 1:500,000 map from EMBRAPA originally published in 1983. Oxisols and Ultisols are the predominant soil types in the basin, encompassing 47% and 24% of the total drainage area, respectively. Entisols cover 14%, Alfisols 13% and Eptisols 2% of the basin (Ballester et al., 2003). One data file is provided in ESRI ArcGIS Shapefile format compressed into a single zip file (*.zip).
This data set provides simulated minimum, average, and maximum monthly rainfall, potential evapotranspiration, water deficit, and water surplus values for the Ji-Parana River basin, Rondonia, Brazil. The Thornthwaite-Mather climatological model integrated into a Geographic Information System (GIS) was used to derive the data by utilizing Advanced Very High Resolution Radar (AVHRR) images for temperatures, rainfall amounts from gauges within and around the basin, soil profiles, and land cover maps as model inputs. The monthly water balance for the Ji-Parana river basin is simulated from February 1995 through December 1996 (Victoria et al., 2007). Data are also provided from the Ji-Parana subbasin stations for total basin rainfall, basin discharge and basin evapotranspiration. This data was used to check the results of the water balance model. There are 2 comma-delimited data files with this data set.
This data set provides simulated minimum, average, and maximum monthly rainfall, potential evapotranspiration, water deficit, and water surplus values for the Ji-Parana River basin, Rondonia, Brazil. The Thornthwaite-Mather climatological model integrated into a Geographic Information System (GIS) was used to derive the data by utilizing Advanced Very High Resolution Radar (AVHRR) images for temperatures, rainfall amounts from gauges within and around the basin, soil profiles, and land cover maps as model inputs. The monthly water balance for the Ji-Parana river basin is simulated from February 1995 through December 1996 (Victoria et al., 2007). Data are also provided from the Ji-Parana subbasin stations for total basin rainfall, basin discharge and basin evapotranspiration. This data was used to check the results of the water balance model. There are 2 comma-delimited data files with this data set.
ABSTRACT: This data set provides simulated minimum, average, and maximum monthly rainfall, potential evapotranspiration, water deficit, and water surplus values for the Ji-Parana River basin, Rondonia, Brazil. The Thornthwaite-Mather climatological model integrated into a Geographic Information System (GIS) was used to derive the data by utilizing Advanced Very High Resolution Radar (AVHRR) images for temperatures, rainfall amounts from gauges within and around the basin, soil profiles, and land cover maps as model inputs. The monthly water balance for the Ji-Parana river basin is simulated from February 1995 through December 1996 (Victoria et al., 2007). Data are also provided from the Ji-Parana subbasin stations for total basin rainfall, basin discharge and basin evapotranspiration. This data was used to check the results of the water balance model. There are 2 comma-delimited data files with this data set.
The LBA-Ecology CD-07 team collected and processed GOES-8 imager data over the LBA region to characterize the incoming radiation and precipitation rates at regional scales. This data set contains surface down-welling solar radiation, photosynthetically active radiation (PAR) and infrared radiation, as well as precipitation rates at 8x8-km and half-hourly resolutions. The data cover the time periods: 01Mar99-30Apr99 and 01Sep99-31Oct99. The data missing from the temporal series was filled using interpolation to create a continuous sequence of data for carbon modeling studies.
The LBA-Ecology CD-07 team collected and processed GOES-8 imager data over the LBA region to characterize the incoming radiation and precipitation rates at regional scales. This data set contains surface down-welling solar radiation, photosynthetically active radiation (PAR) and infrared radiation, as well as precipitation rates at 8x8-km and half-hourly resolutions. The data cover the time periods: 01Mar99-30Apr99 and 01Sep99-31Oct99. The data missing from the temporal series was filled using interpolation to create a continuous sequence of data for carbon modeling studies.
ABSTRACT: The LBA-Ecology CD-07 team collected and processed GOES-8 imager data over the LBA region to characterize the incoming radiation and precipitation rates at regional scales. This data set contains surface down-welling solar radiation, photosynthetically active radiation (PAR) and infrared radiation, as well as precipitation rates at 8x8-km and half-hourly resolutions. The data cover the time periods: 01Mar99-30Apr99 and 01Sep99-31Oct99. The data missing from the temporal series was filled using interpolation to create a continuous sequence of data for carbon modeling studies.
This data set contains carbon isotope signatures from soil organic matter collected from the following sites: the forests of the ZF-2 INPA reserve approximately 80 km north of the city of Manaus, Amazon; the Tapajos National Forest approximately 83 km south of the city of Santarem, Para; and the Fazenda Vitoria, a ranch near the city of Paragominas, Para. Samples from the Fazenda Vitoria were from degraded and managed pasture sites as well as mature and secondary forests. In addition,carbon isotope signatures from roots sorted by size class, hand-picked from soil pits in the Flona Tapajos and Fazenda Vitoria, are included, as are carbon isotope signatures from soil gases from samples collected at the Fazenda Vitoria. There are 4 ASCII data files with this data set.
This data set contains carbon isotope signatures from soil organic matter collected from the following sites: the forests of the ZF-2 INPA reserve approximately 80 km north of the city of Manaus, Amazon; the Tapajos National Forest approximately 83 km south of the city of Santarem, Para; and the Fazenda Vitoria, a ranch near the city of Paragominas, Para. Samples from the Fazenda Vitoria were from degraded and managed pasture sites as well as mature and secondary forests. In addition,carbon isotope signatures from roots sorted by size class, hand-picked from soil pits in the Flona Tapajos and Fazenda Vitoria, are included, as are carbon isotope signatures from soil gases from samples collected at the Fazenda Vitoria. There are 4 ASCII data files with this data set.
ABSTRACT: This data set contains carbon isotope signatures from soil organic matter collected from the following sites: the forests of the ZF-2 INPA reserve approximately 80 km north of the city of Manaus, Amazon; the Tapajos National Forest approximately 83 km south of the city of Santarem, Para; and the Fazenda Vitoria, a ranch near the city of Paragominas, Para. Samples from the Fazenda Vitoria were from degraded and managed pasture sites as well as mature and secondary forests. In addition,carbon isotope signatures from roots sorted by size class, hand-picked from soil pits in the Flona Tapajos and Fazenda Vitoria, are included, as are carbon isotope signatures from soil gases from samples collected at the Fazenda Vitoria. There are 4 ASCII data files with this data set.
This data set reports the ages and growth rates of trees as determined by radiocarbon dating (14C), selected from a logging operation near the city of Itacoatiara, about 250 km east of Manaus, Brazil in 1997. Samples were collected from forty-four trees from 15 species with a basal diameter greater than 100 cm and prepared for radiocarbon dating by Accelerator Mass Spectrometry (AMS) at Lawrence Livermore National Laboratory. There is one comma-separated ASCII data file with this data set.
This data set reports the ages and growth rates of trees as determined by radiocarbon dating (14C), selected from a logging operation near the city of Itacoatiara, about 250 km east of Manaus, Brazil in 1997. Samples were collected from forty-four trees from 15 species with a basal diameter greater than 100 cm and prepared for radiocarbon dating by Accelerator Mass Spectrometry (AMS) at Lawrence Livermore National Laboratory. There is one comma-separated ASCII data file with this data set.
ABSTRACT: This data set reports the ages and growth rates of trees as determined by radiocarbon dating (14C), selected from a logging operation near the city of Itacoatiara, about 250 km east of Manaus, Brazil in 1997. Samples were collected from forty-four trees from 15 species with a basal diameter greater than 100 cm and prepared for radiocarbon dating by Accelerator Mass Spectrometry (AMS) at Lawrence Livermore National Laboratory. There is one comma-separated ASCII data file with this data set.
This data set reports the ages and growth rates of trees determined by radiocarbon dating (14C) in three Amazonia forests. Tree samples were collected from permanent research plots at ZF2 km 34, Manaus, Amazonas, the Catuaba Experimental Farm, Acre, and the km 83 tower site (logged forest site) in the Tapajos National Forest, Para, between 2001-2003.Samples from 97 individual trees were either tree cores (Manaus and Acre) or a combination of tree cores and slabs cut from stems as part of the logging in the Tapajos National Forest (Para). Radiocarbon dating(14C)was used to determine the age and the mean diameter growth increment of samples from individual trees in various diameter size classes.  These measurements can be used to verify and extend short-term diameter increment measurements done with dendrometers and to constrain models of tree demography.There is one comma-separated ASCII  data file with this data set.
This data set reports the ages and growth rates of trees determined by radiocarbon dating (14C) in three Amazonia forests. Tree samples were collected from permanent research plots at ZF2 km 34, Manaus, Amazonas, the Catuaba Experimental Farm, Acre, and the km 83 tower site (logged forest site) in the Tapajos National Forest, Para, between 2001-2003.Samples from 97 individual trees were either tree cores (Manaus and Acre) or a combination of tree cores and slabs cut from stems as part of the logging in the Tapajos National Forest (Para). Radiocarbon dating(14C)was used to determine the age and the mean diameter growth increment of samples from individual trees in various diameter size classes.  These measurements can be used to verify and extend short-term diameter increment measurements done with dendrometers and to constrain models of tree demography.There is one comma-separated ASCII  data file with this data set.
ABSTRACT: This data set reports the ages and growth rates of trees determined by radiocarbon dating (14C) in three Amazonia forests. Tree samples were collected from permanent research plots at ZF2 km 34, Manaus, Amazonas, the Catuaba Experimental Farm, Acre, and the km 83 tower site (logged forest site) in the Tapajos National Forest, Para, between 2001-2003.Samples from 97 individual trees were either tree cores (Manaus and Acre) or a combination of tree cores and slabs cut from stems as part of the logging in the Tapajos National Forest (Para). Radiocarbon dating(14C)was used to determine the age and the mean diameter growth increment of samples from individual trees in various diameter size classes.  These measurements can be used to verify and extend short-term diameter increment measurements done with dendrometers and to constrain models of tree demography.There is one comma-separated ASCII  data file with this data set.
This data set provides diameter at breast height (DBH) measurements made of trees in a dense terra-firme tropical moist forest at the ZF-2 Experimental Station, 90 km north of Manaus, Brazil. DBH was measured over two transects (East to West and North to South) which were established in 1996 by the Jacaranda Project (agreement between the National Institute for Research in the Amazon (INPA) and the Japan International Cooperation Agency, JICA). For each tree, a metal dendrometer band was fixed to the trunk and growth in circumference was measured monthly with digital calipers. The transects measured 20-m x 2500-m, and were stratified by plateau, slope, and baixio (lowland areas near small streams). Topography location, distance along the transect, height at which the band was installed, local tree name, and field notes are also provided in the data files. Measurements were taken between June 1999 and December 2001.
This data set provides diameter at breast height (DBH) measurements made of trees in a dense terra-firme tropical moist forest at the ZF-2 Experimental Station, 90 km north of Manaus, Brazil. DBH was measured over two transects (East to West and North to South) which were established in 1996 by the Jacaranda Project (agreement between the National Institute for Research in the Amazon (INPA) and the Japan International Cooperation Agency, JICA). For each tree, a metal dendrometer band was fixed to the trunk and growth in circumference was measured monthly with digital calipers. The transects measured 20-m x 2500-m, and were stratified by plateau, slope, and baixio (lowland areas near small streams). Topography location, distance along the transect, height at which the band was installed, local tree name, and field notes are also provided in the data files. Measurements were taken between June 1999 and December 2001.
ABSTRACT: This data set provides diameter at breast height (DBH) measurements made of trees in a dense terra-firme tropical moist forest at the ZF-2 Experimental Station, 90 km north of Manaus, Brazil. DBH was measured over two transects (East to West and North to South) which were established in 1996 by the Jacaranda Project (agreement between the National Institute for Research in the Amazon (INPA) and the Japan International Cooperation Agency, JICA). For each tree, a metal dendrometer band was fixed to the trunk and growth in circumference was measured monthly with digital calipers. The transects measured 20-m x 2500-m, and were stratified by plateau, slope, and baixio (lowland areas near small streams). Topography location, distance along the transect, height at which the band was installed, local tree name, and field notes are also provided in the data files. Measurements were taken between June 1999 and December 2001.
This data set includes in one data file the common names, base diameters, and calculated tree masses for almost 3,000 trees on a 5 hectare plot (20 x 2,500 m) located in the Ducke Reserve near Manaus, Brazil in the central Amazon. Measurements were taken during October-December 1999. All diameter measurements were taken at 1.3 meters in height (DBH), or above the buttresses or other stem anomalies.  Forest structure characteristics such as biomass density, stem density, diameter class distribution, and taxonomic information at the family and perhaps genus level, can be derived from these data.
This data set includes in one data file the common names, base diameters, and calculated tree masses for almost 3,000 trees on a 5 hectare plot (20 x 2,500 m) located in the Ducke Reserve near Manaus, Brazil in the central Amazon. Measurements were taken during October-December 1999. All diameter measurements were taken at 1.3 meters in height (DBH), or above the buttresses or other stem anomalies.  Forest structure characteristics such as biomass density, stem density, diameter class distribution, and taxonomic information at the family and perhaps genus level, can be derived from these data.
ABSTRACT: This data set includes in one data file the common names, base diameters, and calculated tree masses for almost 3,000 trees on a 5 hectare plot (20 x 2,500 m) located in the Ducke Reserve near Manaus, Brazil in the central Amazon. Measurements were taken during October-December 1999. All diameter measurements were taken at 1.3 meters in height (DBH), or above the buttresses or other stem anomalies.  Forest structure characteristics such as biomass density, stem density, diameter class distribution, and taxonomic information at the family and perhaps genus level, can be derived from these data.
Leaf, live wood (tree stem), and soil respiration were measured along with additional environmental factors over a 1-yr period in a Central Amazon terra firme forest and are provided in this data set as three comma delimited data files. Investigations were carried out at an INPA reserve located along the ZF2 road at km 34 [LBA 34] on two 20 x 2500 m permanent forest inventory plots referred to as the Jacaranda plots (-2.6091 degrees S, -60.2093 degrees W). These long and narrow plots capture ecosystem variation associated with the undulating local topography. Leaf respiration measurements were also made at the tower located at ZF-2 road (km 14 [LBA 14]. Leaf respiration was measured during July and August 2001, woody respiration in August 2000 and June 2001, and soil respiration between July 2000 and June 2001 at 4 to 6-wk intervals.Understanding how tropical forest carbon balance will respond to global change requires knowledge of individual heterotrophic and autotrophic respiratory sources, together with factors that control respiratory variability. These data were used to estimate ecosystem leaf, live wood and soil respiration with detailed information provided in Chambers et al. (2004).
Leaf, live wood (tree stem), and soil respiration were measured along with additional environmental factors over a 1-yr period in a Central Amazon terra firme forest and are provided in this data set as three comma delimited data files. Investigations were carried out at an INPA reserve located along the ZF2 road at km 34 [LBA 34] on two 20 x 2500 m permanent forest inventory plots referred to as the Jacaranda plots (-2.6091 degrees S, -60.2093 degrees W). These long and narrow plots capture ecosystem variation associated with the undulating local topography. Leaf respiration measurements were also made at the tower located at ZF-2 road (km 14 [LBA 14]. Leaf respiration was measured during July and August 2001, woody respiration in August 2000 and June 2001, and soil respiration between July 2000 and June 2001 at 4 to 6-wk intervals.Understanding how tropical forest carbon balance will respond to global change requires knowledge of individual heterotrophic and autotrophic respiratory sources, together with factors that control respiratory variability. These data were used to estimate ecosystem leaf, live wood and soil respiration with detailed information provided in Chambers et al. (2004).
ABSTRACT: Leaf, live wood (tree stem), and soil respiration were measured along with additional environmental factors over a 1-yr period in a Central Amazon terra firme forest and are provided in this data set as three comma delimited data files. Investigations were carried out at an INPA reserve located along the ZF2 road at km 34 [LBA 34] on two 20 x 2500 m permanent forest inventory plots referred to as the Jacaranda plots (-2.6091 degrees S, -60.2093 degrees W). These long and narrow plots capture ecosystem variation associated with the undulating local topography. Leaf respiration measurements were also made at the tower located at ZF-2 road (km 14 [LBA 14]. Leaf respiration was measured during July and August 2001, woody respiration in August 2000 and June 2001, and soil respiration between July 2000 and June 2001 at 4 to 6-wk intervals.Understanding how tropical forest carbon balance will respond to global change requires knowledge of individual heterotrophic and autotrophic respiratory sources, together with factors that control respiratory variability. These data were used to estimate ecosystem leaf, live wood and soil respiration with detailed information provided in Chambers et al. (2004).
This data set reports the results of soil and vegetation surveys at four distinct areas within the Tapajos National Forest (TNF), 50 to 100 km south of Santarem, Para, Brazil, in November 1999. At 13 individual sites across the four areas, all located in primary forest, core soil samples at 10, 30 and 50 cm depths were collected and analyzed for dry mass, bulk density, texture, percentage carbon (C), percentage organic matter, and percentage nitrogen (N). At these 13 sites, vegetation was characterized for 250 m long by 10 m wide transects. Biomass was estimated for all stems over 10 cm DBH from allometric relationships for species, measured height, canopy dimension, and diameter. LAI was measured along the transect at 26 points with a LICOR LAI-2000. Canopy foliage samples were collected with a shotgun at dawn and leaf water potential was determined with a pressure chamber. Samples of foliage, wood, bark, fine roots, and litter were analyzed for %N, % C, delta 13C, and delta 15N. There are five comma-delimited ASCII data files with this data set.
This data set reports the results of soil and vegetation surveys at four distinct areas within the Tapajos National Forest (TNF), 50 to 100 km south of Santarem, Para, Brazil, in November 1999. At 13 individual sites across the four areas, all located in primary forest, core soil samples at 10, 30 and 50 cm depths were collected and analyzed for dry mass, bulk density, texture, percentage carbon (C), percentage organic matter, and percentage nitrogen (N). At these 13 sites, vegetation was characterized for 250 m long by 10 m wide transects. Biomass was estimated for all stems over 10 cm DBH from allometric relationships for species, measured height, canopy dimension, and diameter. LAI was measured along the transect at 26 points with a LICOR LAI-2000. Canopy foliage samples were collected with a shotgun at dawn and leaf water potential was determined with a pressure chamber. Samples of foliage, wood, bark, fine roots, and litter were analyzed for %N, % C, delta 13C, and delta 15N. There are five comma-delimited ASCII data files with this data set.
ABSTRACT: This data set reports the results of soil and vegetation surveys at four distinct areas within the Tapajos National Forest (TNF), 50 to 100 km south of Santarem, Para, Brazil, in November 1999. At 13 individual sites across the four areas, all located in primary forest, core soil samples at 10, 30 and 50 cm depths were collected and analyzed for dry mass, bulk density, texture, percentage carbon (C), percentage organic matter, and percentage nitrogen (N). At these 13 sites, vegetation was characterized for 250 m long by 10 m wide transects. Biomass was estimated for all stems over 10 cm DBH from allometric relationships for species, measured height, canopy dimension, and diameter. LAI was measured along the transect at 26 points with a LICOR LAI-2000. Canopy foliage samples were collected with a shotgun at dawn and leaf water potential was determined with a pressure chamber. Samples of foliage, wood, bark, fine roots, and litter were analyzed for %N, % C, delta 13C, and delta 15N. There are five comma-delimited ASCII data files with this data set.
This data set contains a single comma separated text file of half-hourly average CO mixing ratios measured from 2001/04/18 to 2003/08/29 in the old-growth upland forest at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil.CO concentrations were measured in air drawn from above the canopy top of tower (approx. 64 meters) using a TEI 48CTL instrument modified for increased stability and sensitivity. The sensor was frequently zeroed by passing ambient air over a CO oxidation catalyst. The span was checked 4 times daily by sampling calibration gases at 100 and 500 ppb. Time in the file is given in UTC (decimal date) at the start of each half hour interval.Associated meteorological parameters, CO2 concentrations and micrometerological fluxes are available in LBA-ECO CD-10 CO2 and H2O Eddy Flux Data at km 67 Tower Site, Tapajos National Forest.
This data set contains a single comma separated text file of half-hourly average CO mixing ratios measured from 2001/04/18 to 2003/08/29 in the old-growth upland forest at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil.CO concentrations were measured in air drawn from above the canopy top of tower (approx. 64 meters) using a TEI 48CTL instrument modified for increased stability and sensitivity. The sensor was frequently zeroed by passing ambient air over a CO oxidation catalyst. The span was checked 4 times daily by sampling calibration gases at 100 and 500 ppb. Time in the file is given in UTC (decimal date) at the start of each half hour interval.Associated meteorological parameters, CO2 concentrations and micrometerological fluxes are available in LBA-ECO CD-10 CO2 and H2O Eddy Flux Data at km 67 Tower Site, Tapajos National Forest.
ABSTRACT: This data set contains a single comma separated text file of half-hourly average CO mixing ratios measured from 2001/04/18 to 2003/08/29 in the old-growth upland forest at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil.CO concentrations were measured in air drawn from above the canopy top of tower (approx. 64 meters) using a TEI 48CTL instrument modified for increased stability and sensitivity. The sensor was frequently zeroed by passing ambient air over a CO oxidation catalyst. The span was checked 4 times daily by sampling calibration gases at 100 and 500 ppb. Time in the file is given in UTC (decimal date) at the start of each half hour interval.Associated meteorological parameters, CO2 concentrations and micrometerological fluxes are available in LBA-ECO CD-10 CO2 and H2O Eddy Flux Data at km 67 Tower Site, Tapajos National Forest.
This data set reports the concentrations of carbon monoxide (CO) and carbon dioxide (CO2), wind direction, wind speed, and air temperature measured at the Maxaranguape Atmospheric Observatory in northeast Brazil, January 4, 2003 - December 27, 2006. The data are 30-minute averages. The concentrations observed at Maxaranguape are representative of upstream atmospheric boundary conditions for the Amazon basin and could be used in conjunction with Santarem data and other data sets to estimate regional budgets for these gasses (Kirchhoff et al., 2003). There is one comma-delimited ASCII text file with this data set.
This data set reports the concentrations of carbon monoxide (CO) and carbon dioxide (CO2), wind direction, wind speed, and air temperature measured at the Maxaranguape Atmospheric Observatory in northeast Brazil, January 4, 2003 - December 27, 2006. The data are 30-minute averages. The concentrations observed at Maxaranguape are representative of upstream atmospheric boundary conditions for the Amazon basin and could be used in conjunction with Santarem data and other data sets to estimate regional budgets for these gasses (Kirchhoff et al., 2003). There is one comma-delimited ASCII text file with this data set.
ABSTRACT: This data set reports the concentrations of carbon monoxide (CO) and carbon dioxide (CO2), wind direction, wind speed, and air temperature measured at the Maxaranguape Atmospheric Observatory in northeast Brazil, January 4, 2003 - December 27, 2006. The data are 30-minute averages. The concentrations observed at Maxaranguape are representative of upstream atmospheric boundary conditions for the Amazon basin and could be used in conjunction with Santarem data and other data sets to estimate regional budgets for these gasses (Kirchhoff et al., 2003). There is one comma-delimited ASCII text file with this data set.
ABSTRACT: This data set reports eddy flux measurements of CO2 and H2O exchange and associated meteorological measurements at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from January 2002 through January 2006.Eddy fluxes of CO2 and H2O were measured at two levels (58m and 47m) using tower-mounted closed-path Licor 6262 gas analyzers and Campbell CSAT3 sonic anemometers (Figure 1). Eddy-flux measurements were made at a sampling  rate of 8 Hz and averaged over a 1 hour interval.. A comprehensive set of meteorological parameters (air temperature, pressure, PAR, net radiation, precipitation, etc) were also measured.Co-located measurements included a third Licor gas analyzer that measured (a) the CO2 and H2O concentration profiles at 8 levels in and above the canopy (1 level every 2 minutes) and (b) the instantaneous integrated canopy storage of CO2 and H2O, using a design that pulled air simultaneously through all 8 inlets (once every 20 minutes). See related data sets.With the permission of the author, Hutyra, L.R. 2007. Carbon and water exchange in Amazonian rainforests. Ph.D. Thesis, Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts., is included as a companion file.
ABSTRACT: This data set reports eddy flux measurements of CO2 and H2O exchange and associated meteorological measurements at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from January 2002 through January 2006.Eddy fluxes of CO2 and H2O were measured at two levels (58m and 47m) using tower-mounted closed-path Licor 6262 gas analyzers and Campbell CSAT3 sonic anemometers (Figure 1). Eddy-flux measurements were made at a sampling  rate of 8 Hz and averaged over a 1 hour interval.. A comprehensive set of meteorological parameters (air temperature, pressure, PAR, net radiation, precipitation, etc) were also measured.Co-located measurements included a third Licor gas analyzer that measured (a) the CO2 and H2O concentration profiles at 8 levels in and above the canopy (1 level every 2 minutes) and (b) the instantaneous integrated canopy storage of CO2 and H2O, using a design that pulled air simultaneously through all 8 inlets (once every 20 minutes). See related data sets.With the permission of the author, Hutyra, L.R. 2007. Carbon and water exchange in Amazonian rainforests. Ph.D. Thesis, Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts., is included as a companion file.
ABSTRACT: This data set reports eddy flux measurements of CO2 and H2O exchange and associated meteorological measurements at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from January 2002 through January 2006.Eddy fluxes of CO2 and H2O were measured at two levels (58m and 47m) using tower-mounted closed-path Licor 6262 gas analyzers and Campbell CSAT3 sonic anemometers (Figure 1). Eddy-flux measurements were made at a sampling  rate of 8 Hz and averaged over a 1 hour interval.. A comprehensive set of meteorological parameters (air temperature, pressure, PAR, net radiation, precipitation, etc) were also measured.Co-located measurements included a third Licor gas analyzer that measured (a) the CO2 and H2O concentration profiles at 8 levels in and above the canopy (1 level every 2 minutes) and (b) the instantaneous integrated canopy storage of CO2 and H2O, using a design that pulled air simultaneously through all 8 inlets (once every 20 minutes). See related data sets.With the permission of the author, Hutyra, L.R. 2007. Carbon and water exchange in Amazonian rainforests. Ph.D. Thesis, Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts., is included as a companion file.
Eddy fluxes of CO2 and H2O are measured at two levels (58m and 47m) using tower-mounted closed-path Licor 6262 analyzers and Campbell CSAT3 sonic anemometers.  A third Licor gas analyzer measures (a) the CO2/H2O concentration profile (1 of 8 levels every 2 minutes) and (b) the instantaneous integrated canopy storage of CO2/H2O, using a design pulling air simultaneously through 8 inlets (once every 20 minutes). Comprehensive meteorological data (air temperature, PAR, net radiation, etc) are also included.  Pressure and temperature of the Licor cells are controlled to 500 torr and 48 degrees C.  Eddy licors are automatically zeroed every 2 hours and the profile licor every 20 minutes.  All Licors are automatically calibrated with span gases (at 325, 400, and 475 ppm) every 6 hours.
Eddy fluxes of CO2 and H2O are measured at two levels (58m and 47m) using tower-mounted closed-path Licor 6262 analyzers and Campbell CSAT3 sonic anemometers.  A third Licor gas analyzer measures (a) the CO2/H2O concentration profile (1 of 8 levels every 2 minutes) and (b) the instantaneous integrated canopy storage of CO2/H2O, using a design pulling air simultaneously through 8 inlets (once every 20 minutes). Comprehensive meteorological data (air temperature, PAR, net radiation, etc) are also included.  Pressure and temperature of the Licor cells are controlled to 500 torr and 48 degrees C.  Eddy licors are automatically zeroed every 2 hours and the profile licor every 20 minutes.  All Licors are automatically calibrated with span gases (at 325, 400, and 475 ppm) every 6 hours.
ABSTRACT: Eddy fluxes of CO2 and H2O are measured at two levels (58m and 47m) using tower-mounted closed-path Licor 6262 analyzers and Campbell CSAT3 sonic anemometers.  A third Licor gas analyzer measures (a) the CO2/H2O concentration profile (1 of 8 levels every 2 minutes) and (b) the instantaneous integrated canopy storage of CO2/H2O, using a design pulling air simultaneously through 8 inlets (once every 20 minutes). Comprehensive meteorological data (air temperature, PAR, net radiation, etc) are also included.  Pressure and temperature of the Licor cells are controlled to 500 torr and 48 degrees C.  Eddy licors are automatically zeroed every 2 hours and the profile licor every 20 minutes.  All Licors are automatically calibrated with span gases (at 325, 400, and 475 ppm) every 6 hours.
This data sets reports properties of fallen course woody debris in an old-growth upland forest at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from April 2001 through July 2001.Standing and Fallen coarse woody debris (CWD), or necromass were measured in a series of ecological plots at the km 67 eddy flux tower site in the Tapajos National Forest (Figure 2). The data set includes different size classes of debris measured in different plot sizes. Size classes were: 2-10cm (in 64 m2 subplots) , 10-30cm (in 1600 m2 subplots), 30cm (in 38400 m2 subplots), standing (in entire 50m by 1000m transects).
This data sets reports properties of fallen course woody debris in an old-growth upland forest at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from April 2001 through July 2001.Standing and Fallen coarse woody debris (CWD), or necromass were measured in a series of ecological plots at the km 67 eddy flux tower site in the Tapajos National Forest (Figure 2). The data set includes different size classes of debris measured in different plot sizes. Size classes were: 2-10cm (in 64 m2 subplots) , 10-30cm (in 1600 m2 subplots), 30cm (in 38400 m2 subplots), standing (in entire 50m by 1000m transects).
ABSTRACT: This data sets reports properties of fallen course woody debris in an old-growth upland forest at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from April 2001 through July 2001.Standing and Fallen coarse woody debris (CWD), or necromass were measured in a series of ecological plots at the km 67 eddy flux tower site in the Tapajos National Forest (Figure 2). The data set includes different size classes of debris measured in different plot sizes. Size classes were: 2-10cm (in 64 m2 subplots) , 10-30cm (in 1600 m2 subplots), 30cm (in 38400 m2 subplots), standing (in entire 50m by 1000m transects).
This data set contains a single text file which reports litter type and mass in the old-growth upland forest at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from July 2000 through June 2005.Litter collection began in July 2000 using 40 circular, mesh screen traps (0.43 m diameter, 0.156 m2) randomly located throughout the 19.75-ha tree-survey area (Rice et al., 2004). Approximately every 14 days, litter was collected, sorted, oven dried at 60 degrees C, and weighed. The litterfall from each trap was sorted into (1) leaves, (2) fruits and flowers, (3) wood , <2 cm diameter, and (4) miscellaneous. Data values reported are the mean and standard error of the 40 mass measurements of each of the litter components and the combined total, that have been converted to the reporting units of Mg/ha/yr.
This data set contains a single text file which reports litter type and mass in the old-growth upland forest at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from July 2000 through June 2005.Litter collection began in July 2000 using 40 circular, mesh screen traps (0.43 m diameter, 0.156 m2) randomly located throughout the 19.75-ha tree-survey area (Rice et al., 2004). Approximately every 14 days, litter was collected, sorted, oven dried at 60 degrees C, and weighed. The litterfall from each trap was sorted into (1) leaves, (2) fruits and flowers, (3) wood , <2 cm diameter, and (4) miscellaneous. Data values reported are the mean and standard error of the 40 mass measurements of each of the litter components and the combined total, that have been converted to the reporting units of Mg/ha/yr.
ABSTRACT: This data set contains a single text file which reports litter type and mass in the old-growth upland forest at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from July 2000 through June 2005.Litter collection began in July 2000 using 40 circular, mesh screen traps (0.43 m diameter, 0.156 m2) randomly located throughout the 19.75-ha tree-survey area (Rice et al., 2004). Approximately every 14 days, litter was collected, sorted, oven dried at 60 degrees C, and weighed. The litterfall from each trap was sorted into (1) leaves, (2) fruits and flowers, (3) wood , <2 cm diameter, and (4) miscellaneous. Data values reported are the mean and standard error of the 40 mass measurements of each of the litter components and the combined total, that have been converted to the reporting units of Mg/ha/yr.
This data sets contains a single text file which reports biometry measurements of the old-growth upland forest at the Para, Western (Santarem)km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from July 1999 through March 2005.To monitor tree woody increment, metal dendrometer bands (Figure 1) were placed on a sub-sample of 1000 trees in December 1999. The data set contains estimates of tree diameter at breast height (cm) based on caliper measurements made approximately every six weeks. The first column of data refers to the tree identification number. For a more detailed description of the biometry study refer to Rice et al. 2004.The data file contains a time series of  DBH (cm) values from July 1999 through March 2005.
This data sets contains a single text file which reports biometry measurements of the old-growth upland forest at the Para, Western (Santarem)km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from July 1999 through March 2005.To monitor tree woody increment, metal dendrometer bands (Figure 1) were placed on a sub-sample of 1000 trees in December 1999. The data set contains estimates of tree diameter at breast height (cm) based on caliper measurements made approximately every six weeks. The first column of data refers to the tree identification number. For a more detailed description of the biometry study refer to Rice et al. 2004.The data file contains a time series of  DBH (cm) values from July 1999 through March 2005.
ABSTRACT: This data sets contains a single text file which reports biometry measurements of the old-growth upland forest at the Para, Western (Santarem)km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from July 1999 through March 2005.To monitor tree woody increment, metal dendrometer bands (Figure 1) were placed on a sub-sample of 1000 trees in December 1999. The data set contains estimates of tree diameter at breast height (cm) based on caliper measurements made approximately every six weeks. The first column of data refers to the tree identification number. For a more detailed description of the biometry study refer to Rice et al. 2004.The data file contains a time series of  DBH (cm) values from July 1999 through March 2005.
This data set contains a single text file which reports vertical profiles of H2O vapor concentrations measured at the Para Western (Santarem) - km 67, Primary Forest Tower Site (Figure 1). This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from January 2002 through January 2006.H2O concentrations were measured at 8 levels on the tower (62.2, 50, 39.4, 28.7, 19.6, 10.4, and 0.91 m). Sample air was drawn at 1000 sccm (standard cubic centimeters per minute) through 8 profile inlets in sequence (2 minutes at each level) and then a mixed air sample was simultaneously drawn from all 8 levels to obtain a total column integral (once every 20 minutes) and analyzed with an infrared gas analyzer (IRGA, LI-6262, Licor, Lincoln, NE). Data were averaged over a 1 hour interval. Calibration for H2O used two independent calibrations for the IRGA concentration measurements: (a) the nighttime relationship between ambient temperature measurements and sonic temperature measurements; (b) a chilled mirror dew point hygrometer mounted on the tower. See Appendix A of  Hutyra (2007) for addition details about calibration methods. Co-located measurements included eddy fluxes of CO2 and H2O were measured at two levels (58m and 47m) using tower-mounted closed-path Licor 6262 gas analyzers and Campbell CSAT3 sonic anemometers. And a comprehensive set of meteorological parameters (air temperature, pressure, PAR, net radiation, precipitation, etc) were also measured. With the permission of the author, Hutyra, L.R. 2007. Carbon and water exchange in Amazonian rainforests. Ph.D. Thesis, Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts., is included as a companion file.
This data set contains a single text file which reports vertical profiles of H2O vapor concentrations measured at the Para Western (Santarem) - km 67, Primary Forest Tower Site (Figure 1). This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from January 2002 through January 2006.H2O concentrations were measured at 8 levels on the tower (62.2, 50, 39.4, 28.7, 19.6, 10.4, and 0.91 m). Sample air was drawn at 1000 sccm (standard cubic centimeters per minute) through 8 profile inlets in sequence (2 minutes at each level) and then a mixed air sample was simultaneously drawn from all 8 levels to obtain a total column integral (once every 20 minutes) and analyzed with an infrared gas analyzer (IRGA, LI-6262, Licor, Lincoln, NE). Data were averaged over a 1 hour interval. Calibration for H2O used two independent calibrations for the IRGA concentration measurements: (a) the nighttime relationship between ambient temperature measurements and sonic temperature measurements; (b) a chilled mirror dew point hygrometer mounted on the tower. See Appendix A of  Hutyra (2007) for addition details about calibration methods. Co-located measurements included eddy fluxes of CO2 and H2O were measured at two levels (58m and 47m) using tower-mounted closed-path Licor 6262 gas analyzers and Campbell CSAT3 sonic anemometers. And a comprehensive set of meteorological parameters (air temperature, pressure, PAR, net radiation, precipitation, etc) were also measured. With the permission of the author, Hutyra, L.R. 2007. Carbon and water exchange in Amazonian rainforests. Ph.D. Thesis, Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts., is included as a companion file.
ABSTRACT: This data set contains a single text file which reports vertical profiles of H2O vapor concentrations measured at the Para Western (Santarem) - km 67, Primary Forest Tower Site (Figure 1). This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from January 2002 through January 2006.H2O concentrations were measured at 8 levels on the tower (62.2, 50, 39.4, 28.7, 19.6, 10.4, and 0.91 m). Sample air was drawn at 1000 sccm (standard cubic centimeters per minute) through 8 profile inlets in sequence (2 minutes at each level) and then a mixed air sample was simultaneously drawn from all 8 levels to obtain a total column integral (once every 20 minutes) and analyzed with an infrared gas analyzer (IRGA, LI-6262, Licor, Lincoln, NE). Data were averaged over a 1 hour interval. Calibration for H2O used two independent calibrations for the IRGA concentration measurements: (a) the nighttime relationship between ambient temperature measurements and sonic temperature measurements; (b) a chilled mirror dew point hygrometer mounted on the tower. See Appendix A of  Hutyra (2007) for addition details about calibration methods. Co-located measurements included eddy fluxes of CO2 and H2O were measured at two levels (58m and 47m) using tower-mounted closed-path Licor 6262 gas analyzers and Campbell CSAT3 sonic anemometers. And a comprehensive set of meteorological parameters (air temperature, pressure, PAR, net radiation, precipitation, etc) were also measured. With the permission of the author, Hutyra, L.R. 2007. Carbon and water exchange in Amazonian rainforests. Ph.D. Thesis, Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts., is included as a companion file.
This data set contains a single text file which reports temperature measurements at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from January 2002 through January 2006 (Figure 1).Air temperature measurements were collected at 8 levels on the tower (61.9, 49.8, 39.1, 28.4, 18.3, 10.1, 2.8, and 0.6 m). Temperature measurements were made with aspirated thermistors (Met One 076B-4 aspiration with YSI 44032 thermistors) and averaged over a 1 hour interval.Co-located measurements included a Licor gas analyzer that measured (a) the CO2 and H2O concentration profiles at 8 levels in and above the canopy (1 level every 2 minutes), (b) the instantaneous integrated canopy storage of CO2 and H2O, using a design that pulled air simultaneously through all 8 inlets (once every 20 minutes), and (c) eddy fluxes of CO2 and H2O were measured at two levels (58m and 47m) using tower-mounted closed-path Licor 6262 gas analyzers and Campbell CSAT3 sonic anemometers. A comprehensive set of meteorological parameters (air pressure, PAR, net radiation, precipitation, etc) were also measured. See related data sets.With the permission of the author, Hutyra, L.R. 2007. Carbon and water exchange in Amazonian rainforests. Ph.D. Thesis, Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts., is included as a companion file.
This data set contains a single text file which reports temperature measurements at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from January 2002 through January 2006 (Figure 1).Air temperature measurements were collected at 8 levels on the tower (61.9, 49.8, 39.1, 28.4, 18.3, 10.1, 2.8, and 0.6 m). Temperature measurements were made with aspirated thermistors (Met One 076B-4 aspiration with YSI 44032 thermistors) and averaged over a 1 hour interval.Co-located measurements included a Licor gas analyzer that measured (a) the CO2 and H2O concentration profiles at 8 levels in and above the canopy (1 level every 2 minutes), (b) the instantaneous integrated canopy storage of CO2 and H2O, using a design that pulled air simultaneously through all 8 inlets (once every 20 minutes), and (c) eddy fluxes of CO2 and H2O were measured at two levels (58m and 47m) using tower-mounted closed-path Licor 6262 gas analyzers and Campbell CSAT3 sonic anemometers. A comprehensive set of meteorological parameters (air pressure, PAR, net radiation, precipitation, etc) were also measured. See related data sets.With the permission of the author, Hutyra, L.R. 2007. Carbon and water exchange in Amazonian rainforests. Ph.D. Thesis, Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts., is included as a companion file.
ABSTRACT: This data set contains a single text file which reports temperature measurements at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from January 2002 through January 2006 (Figure 1).Air temperature measurements were collected at 8 levels on the tower (61.9, 49.8, 39.1, 28.4, 18.3, 10.1, 2.8, and 0.6 m). Temperature measurements were made with aspirated thermistors (Met One 076B-4 aspiration with YSI 44032 thermistors) and averaged over a 1 hour interval.Co-located measurements included a Licor gas analyzer that measured (a) the CO2 and H2O concentration profiles at 8 levels in and above the canopy (1 level every 2 minutes), (b) the instantaneous integrated canopy storage of CO2 and H2O, using a design that pulled air simultaneously through all 8 inlets (once every 20 minutes), and (c) eddy fluxes of CO2 and H2O were measured at two levels (58m and 47m) using tower-mounted closed-path Licor 6262 gas analyzers and Campbell CSAT3 sonic anemometers. A comprehensive set of meteorological parameters (air pressure, PAR, net radiation, precipitation, etc) were also measured. See related data sets.With the permission of the author, Hutyra, L.R. 2007. Carbon and water exchange in Amazonian rainforests. Ph.D. Thesis, Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts., is included as a companion file.
This data sets reports diameter at breast height (DBH) measurements in the old-growth upland forest at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements were made periodically from July 1999 through August 2005.Trees with DBH >35cm were measured for ~2600 trees in four 5ha transects. Trees >10cm were measured in a smaller area (Rice et al., 2004). Measurements were made in 1999, 2001, and 2005. Trees are identified by local common names.  A cross reference to scientific names is provided as a companion file.Coarse woody debris and litter samples and measurements were collected same area. See related data sets.
This data sets reports diameter at breast height (DBH) measurements in the old-growth upland forest at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements were made periodically from July 1999 through August 2005.Trees with DBH >35cm were measured for ~2600 trees in four 5ha transects. Trees >10cm were measured in a smaller area (Rice et al., 2004). Measurements were made in 1999, 2001, and 2005. Trees are identified by local common names.  A cross reference to scientific names is provided as a companion file.Coarse woody debris and litter samples and measurements were collected same area. See related data sets.
ABSTRACT: This data sets reports diameter at breast height (DBH) measurements in the old-growth upland forest at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements were made periodically from July 1999 through August 2005.Trees with DBH >35cm were measured for ~2600 trees in four 5ha transects. Trees >10cm were measured in a smaller area (Rice et al., 2004). Measurements were made in 1999, 2001, and 2005. Trees are identified by local common names.  A cross reference to scientific names is provided as a companion file.Coarse woody debris and litter samples and measurements were collected same area. See related data sets.
This data set reports the results of vegetation field surveys that measured tree height and diameter at breast height (DBH) in defined size classes at three study sites -- Santarem, Para; Paragominas, Para; and Alo Brasil, Mato Grosso, Brazil, from 2001-2003.At each site, plots and transects within plots, were defined that represented different types of logging and fire treatments, each including one primary forest plot used as a control. Along each transect all trees with more than 30 cm DBH were measured. Dead standing trees were also measured and classified in three classes of decomposition. A 4 m wide transect was used to measure individuals between 10 and 30 cm DBH. Six small subplots were set along each transect to measure regeneration individuals from 2-10 cm DBH and 0-2 cm DBH. DBH is also provided for stumps found in each of the logged forest plots. There are ten comma-delimited data files with this data set.
This data set reports the results of vegetation field surveys that measured tree height and diameter at breast height (DBH) in defined size classes at three study sites -- Santarem, Para; Paragominas, Para; and Alo Brasil, Mato Grosso, Brazil, from 2001-2003.At each site, plots and transects within plots, were defined that represented different types of logging and fire treatments, each including one primary forest plot used as a control. Along each transect all trees with more than 30 cm DBH were measured. Dead standing trees were also measured and classified in three classes of decomposition. A 4 m wide transect was used to measure individuals between 10 and 30 cm DBH. Six small subplots were set along each transect to measure regeneration individuals from 2-10 cm DBH and 0-2 cm DBH. DBH is also provided for stumps found in each of the logged forest plots. There are ten comma-delimited data files with this data set.
ABSTRACT: This data set reports the results of vegetation field surveys that measured tree height and diameter at breast height (DBH) in defined size classes at three study sites -- Santarem, Para; Paragominas, Para; and Alo Brasil, Mato Grosso, Brazil, from 2001-2003.At each site, plots and transects within plots, were defined that represented different types of logging and fire treatments, each including one primary forest plot used as a control. Along each transect all trees with more than 30 cm DBH were measured. Dead standing trees were also measured and classified in three classes of decomposition. A 4 m wide transect was used to measure individuals between 10 and 30 cm DBH. Six small subplots were set along each transect to measure regeneration individuals from 2-10 cm DBH and 0-2 cm DBH. DBH is also provided for stumps found in each of the logged forest plots. There are ten comma-delimited data files with this data set.
This data set provides mean leaf area index (LAI), dendrometry band measurements, and litterfall mass from samples collected at the km 67 research site, Topajos National Forest, Para, Brazil. Litterfall collections were from January 23, 2004 through December 3, 2004, dendrometer measurements were monthly between December 2003 and December 2004, and LAI measurements were collected from January 26, 2004 through November 3, 2004.All measurements were taken at the km 67 site in the Tapajos National Forest. This site is situated in an area of Amazonian primary tropical forest belonging to the municipality of Belterra, Para, Brazil. The forest is mostly evergreen with a few deciduous species. The canopy is characterized by large emergent trees up to 55-m tall, with a closed canopy at approximately 40-m; there are few indications of recent anthropogenic disturbance other than hunting trails. Measurement plots (50) were established along 4 transects at the site and within each plot, 5 subplots were established. The longest transect (25 m x 500 m) was the location of 20 (25 m x 25 m) plots. The other 3 transects (25 m x 250 m) contain 10 plots per transect. Note that the assignment of plots to transects is not provided.There are four comma-delimited data files (.csv) with this data set.
This data set provides mean leaf area index (LAI), dendrometry band measurements, and litterfall mass from samples collected at the km 67 research site, Topajos National Forest, Para, Brazil. Litterfall collections were from January 23, 2004 through December 3, 2004, dendrometer measurements were monthly between December 2003 and December 2004, and LAI measurements were collected from January 26, 2004 through November 3, 2004.All measurements were taken at the km 67 site in the Tapajos National Forest. This site is situated in an area of Amazonian primary tropical forest belonging to the municipality of Belterra, Para, Brazil. The forest is mostly evergreen with a few deciduous species. The canopy is characterized by large emergent trees up to 55-m tall, with a closed canopy at approximately 40-m; there are few indications of recent anthropogenic disturbance other than hunting trails. Measurement plots (50) were established along 4 transects at the site and within each plot, 5 subplots were established. The longest transect (25 m x 500 m) was the location of 20 (25 m x 25 m) plots. The other 3 transects (25 m x 250 m) contain 10 plots per transect. Note that the assignment of plots to transects is not provided.There are four comma-delimited data files (.csv) with this data set.
ABSTRACT: This data set provides mean leaf area index (LAI), dendrometry band measurements, and litterfall mass from samples collected at the km 67 research site, Topajos National Forest, Para, Brazil. Litterfall collections were from January 23, 2004 through December 3, 2004, dendrometer measurements were monthly between December 2003 and December 2004, and LAI measurements were collected from January 26, 2004 through November 3, 2004.All measurements were taken at the km 67 site in the Tapajos National Forest. This site is situated in an area of Amazonian primary tropical forest belonging to the municipality of Belterra, Para, Brazil. The forest is mostly evergreen with a few deciduous species. The canopy is characterized by large emergent trees up to 55-m tall, with a closed canopy at approximately 40-m; there are few indications of recent anthropogenic disturbance other than hunting trails. Measurement plots (50) were established along 4 transects at the site and within each plot, 5 subplots were established. The longest transect (25 m x 500 m) was the location of 20 (25 m x 25 m) plots. The other 3 transects (25 m x 250 m) contain 10 plots per transect. Note that the assignment of plots to transects is not provided.There are four comma-delimited data files (.csv) with this data set.
This data set is a compilation of carbon and energy eddy covariance flux, meteorology, radiation, canopy temperature, humidity, and CO2 profiles and soil moisture and temperature profile data that were collected at nine towers across the Brazilian Amazon. Independent investigators provided the data from a variety of flux tower projects over the period 1999 thru 2006. The data have been harmonized across projects, additional quality control checks were performed, and the data were aggregated to several time intervals.Two versions of data are provided. One version is as received from the investigators and the second was processed through a series of automated and manual quality control steps.This data set includes 18 compressed (*.zip) data files with the two versions of data files for each of the nine sites.
This data set is a compilation of carbon and energy eddy covariance flux, meteorology, radiation, canopy temperature, humidity, and CO2 profiles and soil moisture and temperature profile data that were collected at nine towers across the Brazilian Amazon. Independent investigators provided the data from a variety of flux tower projects over the period 1999 thru 2006. The data have been harmonized across projects, additional quality control checks were performed, and the data were aggregated to several time intervals.Two versions of data are provided. One version is as received from the investigators and the second was processed through a series of automated and manual quality control steps.This data set includes 18 compressed (*.zip) data files with the two versions of data files for each of the nine sites.
ABSTRACT: This data set is a compilation of carbon and energy eddy covariance flux, meteorology, radiation, canopy temperature, humidity, and CO2 profiles and soil moisture and temperature profile data that were collected at nine towers across the Brazilian Amazon. Independent investigators provided the data from a variety of flux tower projects over the period 1999 thru 2006. The data have been harmonized across projects, additional quality control checks were performed, and the data were aggregated to several time intervals.Two versions of data are provided. One version is as received from the investigators and the second was processed through a series of automated and manual quality control steps.This data set includes 18 compressed (*.zip) data files with the two versions of data files for each of the nine sites.
This data set provides gap-filled meteorological observations from nine Brazilian flux towers for periods between 1999 and 2006. The measurements include: air temperature, specific humidity, module of wind speed, downward long wave and shortwave radiation at the surface, surface pressure, precipitation, and carbon dioxide (CO2). These atmospheric data are provided at 1 hour time-steps. These data were used as the standardized forcing data input for the LBA Model Intercomparison Project (LBA-MIP).The LBA-MIP goal was to gain comparative understanding of ecosystem models that simulate energy, water, and CO2 fluxes over the LBA area. The task was to subject all the models to the same forcing and experimental protocol, and to compare the outputs. The protocol is provided as a companion file, lba_mip_protocol4.0_20100309.pdf.The source meteorological observations for the forcing data, from the nine Brazilian flux towers, were recently published as Saleska, et al. (2013). See related data sets. These source data were gap-filled according to the LBA-MIP standard protocol. Note that the CAX forest tower was not included in the MIP. See the companion file driver_data.pdf for additional gap-filling information.There are 34 data products with this data set and they are provided in both text (.txt) and ALMA-compliant NetCDF (.nc) formats. The files have been compressed into nine *.zip files according to site.
This data set provides gap-filled meteorological observations from nine Brazilian flux towers for periods between 1999 and 2006. The measurements include: air temperature, specific humidity, module of wind speed, downward long wave and shortwave radiation at the surface, surface pressure, precipitation, and carbon dioxide (CO2). These atmospheric data are provided at 1 hour time-steps. These data were used as the standardized forcing data input for the LBA Model Intercomparison Project (LBA-MIP).The LBA-MIP goal was to gain comparative understanding of ecosystem models that simulate energy, water, and CO2 fluxes over the LBA area. The task was to subject all the models to the same forcing and experimental protocol, and to compare the outputs. The protocol is provided as a companion file, lba_mip_protocol4.0_20100309.pdf.The source meteorological observations for the forcing data, from the nine Brazilian flux towers, were recently published as Saleska, et al. (2013). See related data sets. These source data were gap-filled according to the LBA-MIP standard protocol. Note that the CAX forest tower was not included in the MIP. See the companion file driver_data.pdf for additional gap-filling information.There are 34 data products with this data set and they are provided in both text (.txt) and ALMA-compliant NetCDF (.nc) formats. The files have been compressed into nine *.zip files according to site.
ABSTRACT: This data set provides gap-filled meteorological observations from nine Brazilian flux towers for periods between 1999 and 2006. The measurements include: air temperature, specific humidity, module of wind speed, downward long wave and shortwave radiation at the surface, surface pressure, precipitation, and carbon dioxide (CO2). These atmospheric data are provided at 1 hour time-steps. These data were used as the standardized forcing data input for the LBA Model Intercomparison Project (LBA-MIP).The LBA-MIP goal was to gain comparative understanding of ecosystem models that simulate energy, water, and CO2 fluxes over the LBA area. The task was to subject all the models to the same forcing and experimental protocol, and to compare the outputs. The protocol is provided as a companion file, lba_mip_protocol4.0_20100309.pdf.The source meteorological observations for the forcing data, from the nine Brazilian flux towers, were recently published as Saleska, et al. (2013). See related data sets. These source data were gap-filled according to the LBA-MIP standard protocol. Note that the CAX forest tower was not included in the MIP. See the companion file driver_data.pdf for additional gap-filling information.There are 34 data products with this data set and they are provided in both text (.txt) and ALMA-compliant NetCDF (.nc) formats. The files have been compressed into nine *.zip files according to site.
ABSTRACT: This data set contains 20 multispectral surface reflectance images collected by the EO-1 satellite Hyperion sensor at 30-m resolution and covering the entire Amazon Basin for 2002 - 2005. All images were converted to GeoTiff format for distribution. The respective ENVI *.hdr files are included as companion files and contain image projection and band information.The selected multispectral images were processed using ENVI software as described in Chambers et al. (2009). Bands with uncalibrated wavelengths and those with low spectral response were removed leaving a spectral subset of generally 196 bands (some images have fewer). A cloud mask was developed using 2-d scatter plots of variable reflectance bands to highlight clouds as regions of interest (ROIs), allowing clouds and cloud edges to be masked. A de-streaking algorithm was then applied to the image to reduce variance in balance between the vertical columns.  Apparent surface reflectance was calculated for this balanced image using the atmospheric correction algorithm ACORN in 1.5pb mode (AIG-LLC, Boulder, CO).  The images (18 of the 20) were georeferenced using the corresponding Advanced Land Imager (ALI) satellite images.
ABSTRACT: This data set contains 20 multispectral surface reflectance images collected by the EO-1 satellite Hyperion sensor at 30-m resolution and covering the entire Amazon Basin for 2002 - 2005. All images were converted to GeoTiff format for distribution. The respective ENVI *.hdr files are included as companion files and contain image projection and band information.The selected multispectral images were processed using ENVI software as described in Chambers et al. (2009). Bands with uncalibrated wavelengths and those with low spectral response were removed leaving a spectral subset of generally 196 bands (some images have fewer). A cloud mask was developed using 2-d scatter plots of variable reflectance bands to highlight clouds as regions of interest (ROIs), allowing clouds and cloud edges to be masked. A de-streaking algorithm was then applied to the image to reduce variance in balance between the vertical columns.  Apparent surface reflectance was calculated for this balanced image using the atmospheric correction algorithm ACORN in 1.5pb mode (AIG-LLC, Boulder, CO).  The images (18 of the 20) were georeferenced using the corresponding Advanced Land Imager (ALI) satellite images.
ABSTRACT: This data set contains 20 multispectral surface reflectance images collected by the EO-1 satellite Hyperion sensor at 30-m resolution and covering the entire Amazon Basin for 2002 - 2005. All images were converted to GeoTiff format for distribution. The respective ENVI *.hdr files are included as companion files and contain image projection and band information.The selected multispectral images were processed using ENVI software as described in Chambers et al. (2009). Bands with uncalibrated wavelengths and those with low spectral response were removed leaving a spectral subset of generally 196 bands (some images have fewer). A cloud mask was developed using 2-d scatter plots of variable reflectance bands to highlight clouds as regions of interest (ROIs), allowing clouds and cloud edges to be masked. A de-streaking algorithm was then applied to the image to reduce variance in balance between the vertical columns.  Apparent surface reflectance was calculated for this balanced image using the atmospheric correction algorithm ACORN in 1.5pb mode (AIG-LLC, Boulder, CO).  The images (18 of the 20) were georeferenced using the corresponding Advanced Land Imager (ALI) satellite images.
This data set provides the results of fractional land cover analysis for nonphotosynthetic vegetation (NPV) from two Landsat images of Manaus, Brazil, for October 14, 2004, and for July 29, 2005. Both images are from Landsat 5, path 231, row 62. The Manauas area experienced a squall line with intense downbursts from January 16-18, 2005, that resulted in widespread blowdown and tree mortality. The pre- and post-disturbance Landsat images were obtained and processed using spectral mixture analysis (SMA) in order to investigate forest disturbance and tree mortatility resulting from the downburst. SMA was based on scene-derived end-members of green vegetation (GV, photosynthetically active vegetation), NPV ( wood, dead vegetation, and surface litter), soil, and shade obtained using a pixel purity index (PPI) algorithm (Negron-Juarez et al., 2010). Changes in NPV due to disturbance were calculated by subtracting the 2004 NPV image from the 2005 NPV image. This NPV difference image is provided. There are three image files (.tif) with this data set: The two Landsat images that were georectified and converted to reflectance values and the NPV difference image. DATA QUALITY STATEMENT: The Data Center has determined that there are questions about the quality of the data reported in this data set. The data set has missing or incomplete data, metadata, or other documentation that diminishes the usability of the products.KNOWN PROBLEMS: Four additional images were needed to make this data set complete but are unavailable. Specifically, the two images resulting from SMA as applied to the Landsat images collected on the 14th of October, 2004 and the 29th of July, 2005 to determine per-pixel fractional abundance of GV, NPV (wood, dead vegetation, and surface litter), soil, and shade and the 2004 NPV and 2005 NPV images that were used to derive the NPV changes image (which we do provide) (Negron-Juarez, et al., 2010).
This data set provides the results of fractional land cover analysis for nonphotosynthetic vegetation (NPV) from two Landsat images of Manaus, Brazil, for October 14, 2004, and for July 29, 2005. Both images are from Landsat 5, path 231, row 62. The Manauas area experienced a squall line with intense downbursts from January 16-18, 2005, that resulted in widespread blowdown and tree mortality. The pre- and post-disturbance Landsat images were obtained and processed using spectral mixture analysis (SMA) in order to investigate forest disturbance and tree mortatility resulting from the downburst. SMA was based on scene-derived end-members of green vegetation (GV, photosynthetically active vegetation), NPV ( wood, dead vegetation, and surface litter), soil, and shade obtained using a pixel purity index (PPI) algorithm (Negron-Juarez et al., 2010). Changes in NPV due to disturbance were calculated by subtracting the 2004 NPV image from the 2005 NPV image. This NPV difference image is provided. There are three image files (.tif) with this data set: The two Landsat images that were georectified and converted to reflectance values and the NPV difference image. DATA QUALITY STATEMENT: The Data Center has determined that there are questions about the quality of the data reported in this data set. The data set has missing or incomplete data, metadata, or other documentation that diminishes the usability of the products.KNOWN PROBLEMS: Four additional images were needed to make this data set complete but are unavailable. Specifically, the two images resulting from SMA as applied to the Landsat images collected on the 14th of October, 2004 and the 29th of July, 2005 to determine per-pixel fractional abundance of GV, NPV (wood, dead vegetation, and surface litter), soil, and shade and the 2004 NPV and 2005 NPV images that were used to derive the NPV changes image (which we do provide) (Negron-Juarez, et al., 2010).
ABSTRACT: This data set provides the results of fractional land cover analysis for nonphotosynthetic vegetation (NPV) from two Landsat images of Manaus, Brazil, for October 14, 2004, and for July 29, 2005. Both images are from Landsat 5, path 231, row 62. The Manauas area experienced a squall line with intense downbursts from January 16-18, 2005, that resulted in widespread blowdown and tree mortality. The pre- and post-disturbance Landsat images were obtained and processed using spectral mixture analysis (SMA) in order to investigate forest disturbance and tree mortatility resulting from the downburst. SMA was based on scene-derived end-members of green vegetation (GV, photosynthetically active vegetation), NPV ( wood, dead vegetation, and surface litter), soil, and shade obtained using a pixel purity index (PPI) algorithm (Negron-Juarez et al., 2010). Changes in NPV due to disturbance were calculated by subtracting the 2004 NPV image from the 2005 NPV image. This NPV difference image is provided. There are three image files (.tif) with this data set: The two Landsat images that were georectified and converted to reflectance values and the NPV difference image. DATA QUALITY STATEMENT: The Data Center has determined that there are questions about the quality of the data reported in this data set. The data set has missing or incomplete data, metadata, or other documentation that diminishes the usability of the products.KNOWN PROBLEMS: Four additional images were needed to make this data set complete but are unavailable. Specifically, the two images resulting from SMA as applied to the Landsat images collected on the 14th of October, 2004 and the 29th of July, 2005 to determine per-pixel fractional abundance of GV, NPV (wood, dead vegetation, and surface litter), soil, and shade and the 2004 NPV and 2005 NPV images that were used to derive the NPV changes image (which we do provide) (Negron-Juarez, et al., 2010).
This data set provides South American Land Data Assimilation System (SALDAS) forcing data including atmospheric fields necessary for land surface modeling for South America which are derived by combining modeled and observation based sources. The forcing data cover the entire continent of South America at 0.125 degree resolution and are built around the model-calculated values of air temperature, wind speed and specific humidity at two meters, surface pressure, downward shortwave and longwave surface radiation, and precipitation from the South American Regional Reanalysis (SARR). These SARR data (Aravequia et al. 2007), which were released in 2006 by INPE/CPTEC, are a medium-term, dynamically consistent, high-resolution (0.125 degree), high-frequency, atmospheric dataset covering South America. The forcing data are available at a 3-hourly time step for a 5-year period from 2000 to 2004. There are 60 monthly *.zip files with each zipped file containing ~240 3-hourly time step data files for that particular month in NetCDF format. Each zipped file is approximately one GB in size.
This data set provides South American Land Data Assimilation System (SALDAS) forcing data including atmospheric fields necessary for land surface modeling for South America which are derived by combining modeled and observation based sources. The forcing data cover the entire continent of South America at 0.125 degree resolution and are built around the model-calculated values of air temperature, wind speed and specific humidity at two meters, surface pressure, downward shortwave and longwave surface radiation, and precipitation from the South American Regional Reanalysis (SARR). These SARR data (Aravequia et al. 2007), which were released in 2006 by INPE/CPTEC, are a medium-term, dynamically consistent, high-resolution (0.125 degree), high-frequency, atmospheric dataset covering South America. The forcing data are available at a 3-hourly time step for a 5-year period from 2000 to 2004. There are 60 monthly *.zip files with each zipped file containing ~240 3-hourly time step data files for that particular month in NetCDF format. Each zipped file is approximately one GB in size.
ABSTRACT: This data set provides South American Land Data Assimilation System (SALDAS) forcing data including atmospheric fields necessary for land surface modeling for South America which are derived by combining modeled and observation based sources. The forcing data cover the entire continent of South America at 0.125 degree resolution and are built around the model-calculated values of air temperature, wind speed and specific humidity at two meters, surface pressure, downward shortwave and longwave surface radiation, and precipitation from the South American Regional Reanalysis (SARR). These SARR data (Aravequia et al. 2007), which were released in 2006 by INPE/CPTEC, are a medium-term, dynamically consistent, high-resolution (0.125 degree), high-frequency, atmospheric dataset covering South America. The forcing data are available at a 3-hourly time step for a 5-year period from 2000 to 2004. There are 60 monthly *.zip files with each zipped file containing ~240 3-hourly time step data files for that particular month in NetCDF format. Each zipped file is approximately one GB in size.
This data set provides tree age, forest formation, and  land cover classification maps, and estimates of landscape-level above-ground live woody biomass (AGLB) for secondary forests in Rondonia, Brazil. The Threshold Age Mapping Algorithm (TAMA) was applied to a densely spaced time series of Landsat images (1975 to 2003) to derive forest type and age classification maps. The AGLB of the secondary forest was estimated by combining the forest classification map with coincident biomass estimates from the Geoscience Laser Altimeter System (GLAS). There are five raster images and three comma-delimited data files with this data set.
This data set provides tree age, forest formation, and  land cover classification maps, and estimates of landscape-level above-ground live woody biomass (AGLB) for secondary forests in Rondonia, Brazil. The Threshold Age Mapping Algorithm (TAMA) was applied to a densely spaced time series of Landsat images (1975 to 2003) to derive forest type and age classification maps. The AGLB of the secondary forest was estimated by combining the forest classification map with coincident biomass estimates from the Geoscience Laser Altimeter System (GLAS). There are five raster images and three comma-delimited data files with this data set.
ABSTRACT: This data set provides tree age, forest formation, and  land cover classification maps, and estimates of landscape-level above-ground live woody biomass (AGLB) for secondary forests in Rondonia, Brazil. The Threshold Age Mapping Algorithm (TAMA) was applied to a densely spaced time series of Landsat images (1975 to 2003) to derive forest type and age classification maps. The AGLB of the secondary forest was estimated by combining the forest classification map with coincident biomass estimates from the Geoscience Laser Altimeter System (GLAS). There are five raster images and three comma-delimited data files with this data set.
This data set contains the boundaries of the four major cities in the Northern Ecuadorian Amazon, the locations of primary communities in the colonist settlement area, and the locations of the road network, circa 2002. This area in northeastern Ecuador, know as the northern Oriente of Ecuador, borders the Andes Mountains and contains the headwaters of the Amazon River.The road network was originally digitized from 1:50,000 scale topographic maps from 1990. The surface attributes for the majority of the roads have been updated based on later remote sensing and field observations from 1999 and 2002. There are three compressed (*.zip) files with this data set.
This data set contains the boundaries of the four major cities in the Northern Ecuadorian Amazon, the locations of primary communities in the colonist settlement area, and the locations of the road network, circa 2002. This area in northeastern Ecuador, know as the northern Oriente of Ecuador, borders the Andes Mountains and contains the headwaters of the Amazon River.The road network was originally digitized from 1:50,000 scale topographic maps from 1990. The surface attributes for the majority of the roads have been updated based on later remote sensing and field observations from 1999 and 2002. There are three compressed (*.zip) files with this data set.
ABSTRACT: This data set contains the boundaries of the four major cities in the Northern Ecuadorian Amazon, the locations of primary communities in the colonist settlement area, and the locations of the road network, circa 2002. This area in northeastern Ecuador, know as the northern Oriente of Ecuador, borders the Andes Mountains and contains the headwaters of the Amazon River.The road network was originally digitized from 1:50,000 scale topographic maps from 1990. The surface attributes for the majority of the roads have been updated based on later remote sensing and field observations from 1999 and 2002. There are three compressed (*.zip) files with this data set.
This data set provides map images of hydrographic, morphologic, and edaphic features for the northern Amazon Basin in eastern Ecuador. The hydrographic data are available at two scales based on the 1:50,000 and 1:250,000-scale topographic source maps that were generated in 1990 and 1993, respectively. Morphological and edaphological data were digitized from a 1:500,000 map published in 1983. There are 3 compressed (*.zip) data files with this data set.
This data set provides map images of hydrographic, morphologic, and edaphic features for the northern Amazon Basin in eastern Ecuador. The hydrographic data are available at two scales based on the 1:50,000 and 1:250,000-scale topographic source maps that were generated in 1990 and 1993, respectively. Morphological and edaphological data were digitized from a 1:500,000 map published in 1983. There are 3 compressed (*.zip) data files with this data set.
ABSTRACT: This data set provides map images of hydrographic, morphologic, and edaphic features for the northern Amazon Basin in eastern Ecuador. The hydrographic data are available at two scales based on the 1:50,000 and 1:250,000-scale topographic source maps that were generated in 1990 and 1993, respectively. Morphological and edaphological data were digitized from a 1:500,000 map published in 1983. There are 3 compressed (*.zip) data files with this data set.
This data set contains a time series of early Landsat-4 MSS satellite imagery as well as Landsat-5 TM and Landsat-7 ETM+ satellite imagery of the northern Ecuadorian Amazon. Some of the TM and ETM images have been georectified to UTM Zone 18 South, WGS84 Datum. Not all of the images have been georectified.
This data set contains a time series of early Landsat-4 MSS satellite imagery as well as Landsat-5 TM and Landsat-7 ETM+ satellite imagery of the northern Ecuadorian Amazon. Some of the TM and ETM images have been georectified to UTM Zone 18 South, WGS84 Datum. Not all of the images have been georectified.
ABSTRACT: This data set contains a time series of early Landsat-4 MSS satellite imagery as well as Landsat-5 TM and Landsat-7 ETM+ satellite imagery of the northern Ecuadorian Amazon. Some of the TM and ETM images have been georectified to UTM Zone 18 South, WGS84 Datum. Not all of the images have been georectified.
This data set contains Landsat TM imagery for the years 1986, 1989, 1996, and 1999, that have been classified into four land use/land cover (LULC) classes: Forest, Non-Forest Vegetation, Urban/Barren, and Water; and a fifth class of Clouds/Shadows. The areas of interest were the four Intensive Study Areas (ISA) of the University of North Carolina's Carolina Population Center (CPC) Ecuador Projects: Eastern Intensive Study Area; Northern Intensive Study Area; Southern Intensive Study Area, and Southwestern Intensive Study Area. These areas are in the Northern Ecuadorian Amazon, in the area known as the northern Oriente of Ecuador. The resolution of the data is 30 meters. There are 12 image files (.tif) with this data set.
This data set contains Landsat TM imagery for the years 1986, 1989, 1996, and 1999, that have been classified into four land use/land cover (LULC) classes: Forest, Non-Forest Vegetation, Urban/Barren, and Water; and a fifth class of Clouds/Shadows. The areas of interest were the four Intensive Study Areas (ISA) of the University of North Carolina's Carolina Population Center (CPC) Ecuador Projects: Eastern Intensive Study Area; Northern Intensive Study Area; Southern Intensive Study Area, and Southwestern Intensive Study Area. These areas are in the Northern Ecuadorian Amazon, in the area known as the northern Oriente of Ecuador. The resolution of the data is 30 meters. There are 12 image files (.tif) with this data set.
ABSTRACT: This data set contains Landsat TM imagery for the years 1986, 1989, 1996, and 1999, that have been classified into four land use/land cover (LULC) classes: Forest, Non-Forest Vegetation, Urban/Barren, and Water; and a fifth class of Clouds/Shadows. The areas of interest were the four Intensive Study Areas (ISA) of the University of North Carolina's Carolina Population Center (CPC) Ecuador Projects: Eastern Intensive Study Area; Northern Intensive Study Area; Southern Intensive Study Area, and Southwestern Intensive Study Area. These areas are in the Northern Ecuadorian Amazon, in the area known as the northern Oriente of Ecuador. The resolution of the data is 30 meters. There are 12 image files (.tif) with this data set.
This data set contains the national and provincial boundaries of Ecuador as well as the boundaries of two national parks: the Cuyabeno Wildlife Reserve and the Yasuni National Park. There are four data files in ESRI ARCGIS Shapefile format within this data set. Each shape file has been compressed into a single compressed file (*.zip).
This data set contains the national and provincial boundaries of Ecuador as well as the boundaries of two national parks: the Cuyabeno Wildlife Reserve and the Yasuni National Park. There are four data files in ESRI ARCGIS Shapefile format within this data set. Each shape file has been compressed into a single compressed file (*.zip).
ABSTRACT: This data set contains the national and provincial boundaries of Ecuador as well as the boundaries of two national parks: the Cuyabeno Wildlife Reserve and the Yasuni National Park. There are four data files in ESRI ARCGIS Shapefile format within this data set. Each shape file has been compressed into a single compressed file (*.zip).
This data set reports summary statistics from socioeconomic and demographic surveys administered to the male and female heads of household on 767 farm plots. The surveys were performed in the provinces of Sucumbios and Napo/Orellana, in the northern Ecuadorian Amazon colonist settlements (Oriente) in 1999 (Pan and Bilsborrow, 2005). In addition, perception of, and opinions about local climate, soil quality, and environmental contamination were assessed for both the male and female heads of household. There are two comma-delimited (csv) ASCII data files. One file provides summary data from male respondents; the other data file provides summary responses from the female household survey (generally the spousal respondent). The original questionnaire forms are included as companion files (PDF format).
This data set reports summary statistics from socioeconomic and demographic surveys administered to the male and female heads of household on 767 farm plots. The surveys were performed in the provinces of Sucumbios and Napo/Orellana, in the northern Ecuadorian Amazon colonist settlements (Oriente) in 1999 (Pan and Bilsborrow, 2005). In addition, perception of, and opinions about local climate, soil quality, and environmental contamination were assessed for both the male and female heads of household. There are two comma-delimited (csv) ASCII data files. One file provides summary data from male respondents; the other data file provides summary responses from the female household survey (generally the spousal respondent). The original questionnaire forms are included as companion files (PDF format).
ABSTRACT: This data set reports summary statistics from socioeconomic and demographic surveys administered to the male and female heads of household on 767 farm plots. The surveys were performed in the provinces of Sucumbios and Napo/Orellana, in the northern Ecuadorian Amazon colonist settlements (Oriente) in 1999 (Pan and Bilsborrow, 2005). In addition, perception of, and opinions about local climate, soil quality, and environmental contamination were assessed for both the male and female heads of household. There are two comma-delimited (csv) ASCII data files. One file provides summary data from male respondents; the other data file provides summary responses from the female household survey (generally the spousal respondent). The original questionnaire forms are included as companion files (PDF format).
This data set provides 90-meter resolution Digital Elevation Model data used in the University of North Carolina's Carolina Population Center (CPC) Ecuador Projects. The topographic data were derived from Shuttle Radar Topography Mission (SRTM) C-band and X-band interferometric synthetic aperture radars (IFSARs) data that were acquired over 80% of Earth's land mass in February 2000. This data set includes one image in GeoTiff format that is a subset for the Northern Ecuadorian Amazon region.
This data set provides 90-meter resolution Digital Elevation Model data used in the University of North Carolina's Carolina Population Center (CPC) Ecuador Projects. The topographic data were derived from Shuttle Radar Topography Mission (SRTM) C-band and X-band interferometric synthetic aperture radars (IFSARs) data that were acquired over 80% of Earth's land mass in February 2000. This data set includes one image in GeoTiff format that is a subset for the Northern Ecuadorian Amazon region.
ABSTRACT: This data set provides 90-meter resolution Digital Elevation Model data used in the University of North Carolina's Carolina Population Center (CPC) Ecuador Projects. The topographic data were derived from Shuttle Radar Topography Mission (SRTM) C-band and X-band interferometric synthetic aperture radars (IFSARs) data that were acquired over 80% of Earth's land mass in February 2000. This data set includes one image in GeoTiff format that is a subset for the Northern Ecuadorian Amazon region.
This data set contains topographic/geomorphological data associated with the four Intensive Study Areas (ISAs) in the Northern Ecuadorian Amazon (northern Oriente) that are part of the University of North Carolina's Carolina Population Center (CPC) Ecuador Projects study. Study area boundaries were developed directly from 1:50,000 topographical maps. Point elevation features and 20-meter elevation contours were digitized from these same maps. Digital elevation models (DEMs) were derived from these elevation data and, in turn, terrain aspect and terrain slope were derived from the digital elevation models. Only boundary data were provided for the southwestern ISA. These data are provided in ESRI shapefile format and GeoTiff. There are six compressed (*.zip) data files with this data set.
This data set contains topographic/geomorphological data associated with the four Intensive Study Areas (ISAs) in the Northern Ecuadorian Amazon (northern Oriente) that are part of the University of North Carolina's Carolina Population Center (CPC) Ecuador Projects study. Study area boundaries were developed directly from 1:50,000 topographical maps. Point elevation features and 20-meter elevation contours were digitized from these same maps. Digital elevation models (DEMs) were derived from these elevation data and, in turn, terrain aspect and terrain slope were derived from the digital elevation models. Only boundary data were provided for the southwestern ISA. These data are provided in ESRI shapefile format and GeoTiff. There are six compressed (*.zip) data files with this data set.
ABSTRACT: This data set contains topographic/geomorphological data associated with the four Intensive Study Areas (ISAs) in the Northern Ecuadorian Amazon (northern Oriente) that are part of the University of North Carolina's Carolina Population Center (CPC) Ecuador Projects study. Study area boundaries were developed directly from 1:50,000 topographical maps. Point elevation features and 20-meter elevation contours were digitized from these same maps. Digital elevation models (DEMs) were derived from these elevation data and, in turn, terrain aspect and terrain slope were derived from the digital elevation models. Only boundary data were provided for the southwestern ISA. These data are provided in ESRI shapefile format and GeoTiff. There are six compressed (*.zip) data files with this data set.
This data set provides meteorological measurements collected from 3 different meteorological stations within a radius of 8 km in Rio Branco, Acre  Brazil, for  the periods of  June of 1970 to 1974, December of 1974 to 1980, and  May of 1980 thru May 31, 2001. Daily average values for rainfall, relative humidity, evapotranspiration, maximum and minimum temperature, pressure, wind direction and speed, solar radiation, and cloud cover are reported.  There is one comma-delimited data file with this data set.
This data set provides meteorological measurements collected from 3 different meteorological stations within a radius of 8 km in Rio Branco, Acre  Brazil, for  the periods of  June of 1970 to 1974, December of 1974 to 1980, and  May of 1980 thru May 31, 2001. Daily average values for rainfall, relative humidity, evapotranspiration, maximum and minimum temperature, pressure, wind direction and speed, solar radiation, and cloud cover are reported.  There is one comma-delimited data file with this data set.
ABSTRACT: This data set provides meteorological measurements collected from 3 different meteorological stations within a radius of 8 km in Rio Branco, Acre  Brazil, for  the periods of  June of 1970 to 1974, December of 1974 to 1980, and  May of 1980 thru May 31, 2001. Daily average values for rainfall, relative humidity, evapotranspiration, maximum and minimum temperature, pressure, wind direction and speed, solar radiation, and cloud cover are reported.  There is one comma-delimited data file with this data set.
This data set provides the results of controlled burns conducted to assess the flammability of mature forests on the Catuaba Experimental Farm of the Federal University of Acre - Rio Branco, Acre, Brazil. Controlled burns were conducted in 1998, and the rate of fire spread was calculated based on the duration of the fire and the measured extent of the burned area. Environmental variables measured included type of forest, canopy openness, leaf area index, number of days without rainfall, precipitation, height of litter, litter humidity, brushwood humidity, amount of water in the ground, air temperature, and relative humidity. Results from 50 fires set in 1998 are reported. There is one comma-delimited data file with this data set.These data are part of a larger study reported in the thesis by Elsa Renee Huamon Mendoza, Susceptibility of primary forest to fire in 1998 and 1999: A case study in Acre, south-eastern Amazonia, Brazil. The thesis, in Portuguese, is included as a companion file with this data set.
This data set provides the results of controlled burns conducted to assess the flammability of mature forests on the Catuaba Experimental Farm of the Federal University of Acre - Rio Branco, Acre, Brazil. Controlled burns were conducted in 1998, and the rate of fire spread was calculated based on the duration of the fire and the measured extent of the burned area. Environmental variables measured included type of forest, canopy openness, leaf area index, number of days without rainfall, precipitation, height of litter, litter humidity, brushwood humidity, amount of water in the ground, air temperature, and relative humidity. Results from 50 fires set in 1998 are reported. There is one comma-delimited data file with this data set.These data are part of a larger study reported in the thesis by Elsa Renee Huamon Mendoza, Susceptibility of primary forest to fire in 1998 and 1999: A case study in Acre, south-eastern Amazonia, Brazil. The thesis, in Portuguese, is included as a companion file with this data set.
ABSTRACT: This data set provides the results of controlled burns conducted to assess the flammability of mature forests on the Catuaba Experimental Farm of the Federal University of Acre - Rio Branco, Acre, Brazil. Controlled burns were conducted in 1998, and the rate of fire spread was calculated based on the duration of the fire and the measured extent of the burned area. Environmental variables measured included type of forest, canopy openness, leaf area index, number of days without rainfall, precipitation, height of litter, litter humidity, brushwood humidity, amount of water in the ground, air temperature, and relative humidity. Results from 50 fires set in 1998 are reported. There is one comma-delimited data file with this data set.These data are part of a larger study reported in the thesis by Elsa Renee Huamon Mendoza, Susceptibility of primary forest to fire in 1998 and 1999: A case study in Acre, south-eastern Amazonia, Brazil. The thesis, in Portuguese, is included as a companion file with this data set.
This data set provides hot pixel data, as an indicator of fires that were detected by the GOES-8 satellite for the state of Acre, Brazil. Image data were collected for extended periods over the course of 3 years (1998, 2000 and 2001). Data were filtered to select only pixels identified and processed by the GOES-8 Automated Biomass Burning Algorithm (ABBA), where estimates of sub-pixel fire characteristics including size and temperature were able to be determined. There are three comma-delimited ASCII data files with this data set.
This data set provides hot pixel data, as an indicator of fires that were detected by the GOES-8 satellite for the state of Acre, Brazil. Image data were collected for extended periods over the course of 3 years (1998, 2000 and 2001). Data were filtered to select only pixels identified and processed by the GOES-8 Automated Biomass Burning Algorithm (ABBA), where estimates of sub-pixel fire characteristics including size and temperature were able to be determined. There are three comma-delimited ASCII data files with this data set.
ABSTRACT: This data set provides hot pixel data, as an indicator of fires that were detected by the GOES-8 satellite for the state of Acre, Brazil. Image data were collected for extended periods over the course of 3 years (1998, 2000 and 2001). Data were filtered to select only pixels identified and processed by the GOES-8 Automated Biomass Burning Algorithm (ABBA), where estimates of sub-pixel fire characteristics including size and temperature were able to be determined. There are three comma-delimited ASCII data files with this data set.
This data set reports bi-weekly or monthly depth-to-water measurements for three wells located in a ~1,500 ha forest fragment on the Catuaba Experimental Farm, which is the property of the Federal University of Acre, Brazil. Data were collected between February 1999 and December 2004. There is one comma-delimited ASCII data file with this data set.DATA QUALITY STATEMENT: The Data Center has determined that there are questions about the quality of the data reported in this data set. The data set has missing or incomplete data, metadata, or other documentation that diminishes the usability of the products. KNOWN PROBLEMS: The depth-to-water measurements for the three wells lack ground surface elevation reference points, therefore, the groundwater table elevation for the site cannot be determined.  The depth-to-water measurements are of limited use unless paired with other site data for precipitation, tree growth, etc.
This data set reports bi-weekly or monthly depth-to-water measurements for three wells located in a ~1,500 ha forest fragment on the Catuaba Experimental Farm, which is the property of the Federal University of Acre, Brazil. Data were collected between February 1999 and December 2004. There is one comma-delimited ASCII data file with this data set.DATA QUALITY STATEMENT: The Data Center has determined that there are questions about the quality of the data reported in this data set. The data set has missing or incomplete data, metadata, or other documentation that diminishes the usability of the products. KNOWN PROBLEMS: The depth-to-water measurements for the three wells lack ground surface elevation reference points, therefore, the groundwater table elevation for the site cannot be determined.  The depth-to-water measurements are of limited use unless paired with other site data for precipitation, tree growth, etc.
ABSTRACT: This data set reports bi-weekly or monthly depth-to-water measurements for three wells located in a ~1,500 ha forest fragment on the Catuaba Experimental Farm, which is the property of the Federal University of Acre, Brazil. Data were collected between February 1999 and December 2004. There is one comma-delimited ASCII data file with this data set.DATA QUALITY STATEMENT: The Data Center has determined that there are questions about the quality of the data reported in this data set. The data set has missing or incomplete data, metadata, or other documentation that diminishes the usability of the products. KNOWN PROBLEMS: The depth-to-water measurements for the three wells lack ground surface elevation reference points, therefore, the groundwater table elevation for the site cannot be determined.  The depth-to-water measurements are of limited use unless paired with other site data for precipitation, tree growth, etc.
This data set provides hot pixel data, as an indicator of fires, that were detected by various satellites in the tri-national MAP region (Madre de Dios-Peru, Acre-Brazil, and Pando-Bolivia) in 2003, 2004, 2005, and 2006. Data from the following satellites/sensors were compiled: NOAA-12, NOAA-14, NOAA-15, and NOAA-16, which transports the AVHRR sensor; GOES-8 and GOES- 12, which transports the GOES Imager; and AQUA and TERRA, both which transport the MODIS sensor. These data were made available by the Centro de Previsao do Tempo e Estudos Climaticos (CPTEC) of the Instituto Nacional de Pesquisas Espaciais (INPE) via the internet (http://sigma.cptec.inpe.br/queimadas/). This data set contains 12 comma-delimited ASCII data files.Hot pixel data from satellites can be used as an indicator of fires and for the understanding of fire frequency in remote areas. The publication by Vasconcelos and Brown, 2007, which has been included as a companion file, describes the application of these data in the MAP region. In addition to the the hot pixel data, each observation has a derived vegetation type, susceptibility to fire, recent and past precipitation amounts, and a calculated fire risk value. These data are described in the Fire Risk Factor companion file, by Alberto W. Setzer and Raffi A. Sismanoglu, Version 5, February 2006.
This data set provides hot pixel data, as an indicator of fires, that were detected by various satellites in the tri-national MAP region (Madre de Dios-Peru, Acre-Brazil, and Pando-Bolivia) in 2003, 2004, 2005, and 2006. Data from the following satellites/sensors were compiled: NOAA-12, NOAA-14, NOAA-15, and NOAA-16, which transports the AVHRR sensor; GOES-8 and GOES- 12, which transports the GOES Imager; and AQUA and TERRA, both which transport the MODIS sensor. These data were made available by the Centro de Previsao do Tempo e Estudos Climaticos (CPTEC) of the Instituto Nacional de Pesquisas Espaciais (INPE) via the internet (http://sigma.cptec.inpe.br/queimadas/). This data set contains 12 comma-delimited ASCII data files.Hot pixel data from satellites can be used as an indicator of fires and for the understanding of fire frequency in remote areas. The publication by Vasconcelos and Brown, 2007, which has been included as a companion file, describes the application of these data in the MAP region. In addition to the the hot pixel data, each observation has a derived vegetation type, susceptibility to fire, recent and past precipitation amounts, and a calculated fire risk value. These data are described in the Fire Risk Factor companion file, by Alberto W. Setzer and Raffi A. Sismanoglu, Version 5, February 2006.
ABSTRACT: This data set provides hot pixel data, as an indicator of fires, that were detected by various satellites in the tri-national MAP region (Madre de Dios-Peru, Acre-Brazil, and Pando-Bolivia) in 2003, 2004, 2005, and 2006. Data from the following satellites/sensors were compiled: NOAA-12, NOAA-14, NOAA-15, and NOAA-16, which transports the AVHRR sensor; GOES-8 and GOES- 12, which transports the GOES Imager; and AQUA and TERRA, both which transport the MODIS sensor. These data were made available by the Centro de Previsao do Tempo e Estudos Climaticos (CPTEC) of the Instituto Nacional de Pesquisas Espaciais (INPE) via the internet (http://sigma.cptec.inpe.br/queimadas/). This data set contains 12 comma-delimited ASCII data files.Hot pixel data from satellites can be used as an indicator of fires and for the understanding of fire frequency in remote areas. The publication by Vasconcelos and Brown, 2007, which has been included as a companion file, describes the application of these data in the MAP region. In addition to the the hot pixel data, each observation has a derived vegetation type, susceptibility to fire, recent and past precipitation amounts, and a calculated fire risk value. These data are described in the Fire Risk Factor companion file, by Alberto W. Setzer and Raffi A. Sismanoglu, Version 5, February 2006.
The provided data were generated by the Integrated BIosphere Simulator (IBIS) terrestrial ecosystem model using data from the East Anglia Climate Research Unit climate record for the years 1921-1998. Data are included for the annual net ecosystem exchange of the surface, microbial respiration, root respiration, total soil respiration, soil moisture, leaf area index, drainage, and surface and subsurface runoff, for the entire Amazon and Tocantins basins. The data files are provided in netCDF format and standard ESRI ARCGIS ARC/INFO ASCIIGRID format. The netCDF files consist of either annual or monthly means from 1921 to 1998. The ASCII files are available only for the annual mean files.
The provided data were generated by the Integrated BIosphere Simulator (IBIS) terrestrial ecosystem model using data from the East Anglia Climate Research Unit climate record for the years 1921-1998. Data are included for the annual net ecosystem exchange of the surface, microbial respiration, root respiration, total soil respiration, soil moisture, leaf area index, drainage, and surface and subsurface runoff, for the entire Amazon and Tocantins basins. The data files are provided in netCDF format and standard ESRI ARCGIS ARC/INFO ASCIIGRID format. The netCDF files consist of either annual or monthly means from 1921 to 1998. The ASCII files are available only for the annual mean files.
ABSTRACT: The provided data were generated by the Integrated BIosphere Simulator (IBIS) terrestrial ecosystem model using data from the East Anglia Climate Research Unit climate record for the years 1921-1998. Data are included for the annual net ecosystem exchange of the surface, microbial respiration, root respiration, total soil respiration, soil moisture, leaf area index, drainage, and surface and subsurface runoff, for the entire Amazon and Tocantins basins. The data files are provided in netCDF format and standard ESRI ARCGIS ARC/INFO ASCIIGRID format. The netCDF files consist of either annual or monthly means from 1921 to 1998. The ASCII files are available only for the annual mean files.
This data set provides continental-scale hydrological river flow routing parameter data for the Amazon and Tocantins River basins at 5 minute (~9 km) resolution (Costa et al., 2002). The data set includes four geospatial data files (in standard ESRI Arc/Info ASCII Grid format): (1) the river network (flow direction); (2) sinuosity of each of the main rivers, measured at 111 river sections in the basins; (3) depth to the water table; and (4) transmissivity of the aquifer. The latter two parameters were derived from measurements taken at 81 wells located throughout the basins. There is also a compressed file (*.zip) which contains the time series of monthly mean river discharge and long-term climatology (monthly mean) for the period of record at each of 122 fluviometric stations located throughout the basin. These files are provided in ASCII common-separated (.csv) format. Also included in this data set are two data files in *.csv format; one containing river discharge station location and drainage area information and one containing original well data.
This data set provides continental-scale hydrological river flow routing parameter data for the Amazon and Tocantins River basins at 5 minute (~9 km) resolution (Costa et al., 2002). The data set includes four geospatial data files (in standard ESRI Arc/Info ASCII Grid format): (1) the river network (flow direction); (2) sinuosity of each of the main rivers, measured at 111 river sections in the basins; (3) depth to the water table; and (4) transmissivity of the aquifer. The latter two parameters were derived from measurements taken at 81 wells located throughout the basins. There is also a compressed file (*.zip) which contains the time series of monthly mean river discharge and long-term climatology (monthly mean) for the period of record at each of 122 fluviometric stations located throughout the basin. These files are provided in ASCII common-separated (.csv) format. Also included in this data set are two data files in *.csv format; one containing river discharge station location and drainage area information and one containing original well data.
ABSTRACT: This data set provides continental-scale hydrological river flow routing parameter data for the Amazon and Tocantins River basins at 5 minute (~9 km) resolution (Costa et al., 2002). The data set includes four geospatial data files (in standard ESRI Arc/Info ASCII Grid format): (1) the river network (flow direction); (2) sinuosity of each of the main rivers, measured at 111 river sections in the basins; (3) depth to the water table; and (4) transmissivity of the aquifer. The latter two parameters were derived from measurements taken at 81 wells located throughout the basins. There is also a compressed file (*.zip) which contains the time series of monthly mean river discharge and long-term climatology (monthly mean) for the period of record at each of 122 fluviometric stations located throughout the basin. These files are provided in ASCII common-separated (.csv) format. Also included in this data set are two data files in *.csv format; one containing river discharge station location and drainage area information and one containing original well data.
This data set contains 5-minute land use maps for agricultural activity in Amazonia. The data set was produced by the statistical fusion of agricultural census data from Brazil,Columbia, Bolivia, and Peru with the land cover data product from the Global Land Cover Facility. These land use maps indicate the estimated total amount of cropland and pasture (natural and planted) for the Amazon and Tocantins River basins in 1995 and 1980 and are suitable for use in models or other similar purposes. Data are provided in the netCDF format and the ARC/INFO GRID ASCII format.The 1995 data were generated from a fusion of agricultural census data and a satellite classification, and are described in Cardille, Foley, and Costa (2002).  The fusion technique merges agricultural census data from Brazil, Columbia, Peru, and Bolivia with land cover data from the University of Maryland Global Land Cover Facility 1-km classification. This technique was used to derive an estimate of the mid-1990s total agriculture surface for the region, which was then apportioned according to agriculture census data into cultivated area, natural pasture, and planted pasture.The 1980 maps, including only the Brazilian portion of the Amazon/Tocantins river drainage basins, were created by scaling the mid-1990s snapshots backward in time using the relative increase or decrease in agriculture, as derived from mid-1980s census data and United Nations Food and Agriculture Organization (FAO) data (Cardille and Foley, 2003).
This data set contains 5-minute land use maps for agricultural activity in Amazonia. The data set was produced by the statistical fusion of agricultural census data from Brazil,Columbia, Bolivia, and Peru with the land cover data product from the Global Land Cover Facility. These land use maps indicate the estimated total amount of cropland and pasture (natural and planted) for the Amazon and Tocantins River basins in 1995 and 1980 and are suitable for use in models or other similar purposes. Data are provided in the netCDF format and the ARC/INFO GRID ASCII format.The 1995 data were generated from a fusion of agricultural census data and a satellite classification, and are described in Cardille, Foley, and Costa (2002).  The fusion technique merges agricultural census data from Brazil, Columbia, Peru, and Bolivia with land cover data from the University of Maryland Global Land Cover Facility 1-km classification. This technique was used to derive an estimate of the mid-1990s total agriculture surface for the region, which was then apportioned according to agriculture census data into cultivated area, natural pasture, and planted pasture.The 1980 maps, including only the Brazilian portion of the Amazon/Tocantins river drainage basins, were created by scaling the mid-1990s snapshots backward in time using the relative increase or decrease in agriculture, as derived from mid-1980s census data and United Nations Food and Agriculture Organization (FAO) data (Cardille and Foley, 2003).
ABSTRACT: This data set contains 5-minute land use maps for agricultural activity in Amazonia. The data set was produced by the statistical fusion of agricultural census data from Brazil,Columbia, Bolivia, and Peru with the land cover data product from the Global Land Cover Facility. These land use maps indicate the estimated total amount of cropland and pasture (natural and planted) for the Amazon and Tocantins River basins in 1995 and 1980 and are suitable for use in models or other similar purposes. Data are provided in the netCDF format and the ARC/INFO GRID ASCII format.The 1995 data were generated from a fusion of agricultural census data and a satellite classification, and are described in Cardille, Foley, and Costa (2002).  The fusion technique merges agricultural census data from Brazil, Columbia, Peru, and Bolivia with land cover data from the University of Maryland Global Land Cover Facility 1-km classification. This technique was used to derive an estimate of the mid-1990s total agriculture surface for the region, which was then apportioned according to agriculture census data into cultivated area, natural pasture, and planted pasture.The 1980 maps, including only the Brazilian portion of the Amazon/Tocantins river drainage basins, were created by scaling the mid-1990s snapshots backward in time using the relative increase or decrease in agriculture, as derived from mid-1980s census data and United Nations Food and Agriculture Organization (FAO) data (Cardille and Foley, 2003).
The model output data provided were generated by the THMB 1.2 (Terrestrial Hydrology Model with Biogeochemistry) model which simulates the flow of water through groundwater systems, rivers, lakes and wetlands. The model operates at a 5-minute latitude-by-longitude grid with a 1-hour time step and requires as boundary conditions: topography, evaporation from water surfaces, surface runoff, base flow, and precipitation. Data are included for the mean monthly simulated water height above flood stage, mean monthly simulated river discharge, and mean monthly inundated area for the period 1939-1998 for the entire Amazon and Tocantins River basins. There are three netCDF files (.nc) with this data set.
The model output data provided were generated by the THMB 1.2 (Terrestrial Hydrology Model with Biogeochemistry) model which simulates the flow of water through groundwater systems, rivers, lakes and wetlands. The model operates at a 5-minute latitude-by-longitude grid with a 1-hour time step and requires as boundary conditions: topography, evaporation from water surfaces, surface runoff, base flow, and precipitation. Data are included for the mean monthly simulated water height above flood stage, mean monthly simulated river discharge, and mean monthly inundated area for the period 1939-1998 for the entire Amazon and Tocantins River basins. There are three netCDF files (.nc) with this data set.
ABSTRACT: The model output data provided were generated by the THMB 1.2 (Terrestrial Hydrology Model with Biogeochemistry) model which simulates the flow of water through groundwater systems, rivers, lakes and wetlands. The model operates at a 5-minute latitude-by-longitude grid with a 1-hour time step and requires as boundary conditions: topography, evaporation from water surfaces, surface runoff, base flow, and precipitation. Data are included for the mean monthly simulated water height above flood stage, mean monthly simulated river discharge, and mean monthly inundated area for the period 1939-1998 for the entire Amazon and Tocantins River basins. There are three netCDF files (.nc) with this data set.
This data set reports (1) total aboveground dry biomass based on detailed estimates of all live and dead plant material, (2) results from repeated surveys of aboveground biomass allowing the calculation of above-ground productivity, and (3) soil chemical and physical characteristics for 50 1-ha plots of undisturbed and fragmented central Amazonian rainforest within the Biological Dynamics of Forest Fragments Project (BDFFP) study area. The reported data are plot-level summaries based on plant and soil samples and measurements obtained over the 1997 to 2001 timeframe. The BDFFP study area is an experimentally fragmented landscape spanning 1,000 km2 located 70-90 km north of Manaus, Amazonas, Brazil. For additional information about the BDFFP and research conducted at the site, please visit their web site at http://pdbff.inpa.gov.br/index.html.There are six comma-separated ASCII data files with this data set.
This data set reports (1) total aboveground dry biomass based on detailed estimates of all live and dead plant material, (2) results from repeated surveys of aboveground biomass allowing the calculation of above-ground productivity, and (3) soil chemical and physical characteristics for 50 1-ha plots of undisturbed and fragmented central Amazonian rainforest within the Biological Dynamics of Forest Fragments Project (BDFFP) study area. The reported data are plot-level summaries based on plant and soil samples and measurements obtained over the 1997 to 2001 timeframe. The BDFFP study area is an experimentally fragmented landscape spanning 1,000 km2 located 70-90 km north of Manaus, Amazonas, Brazil. For additional information about the BDFFP and research conducted at the site, please visit their web site at http://pdbff.inpa.gov.br/index.html.There are six comma-separated ASCII data files with this data set.
ABSTRACT: This data set reports (1) total aboveground dry biomass based on detailed estimates of all live and dead plant material, (2) results from repeated surveys of aboveground biomass allowing the calculation of above-ground productivity, and (3) soil chemical and physical characteristics for 50 1-ha plots of undisturbed and fragmented central Amazonian rainforest within the Biological Dynamics of Forest Fragments Project (BDFFP) study area. The reported data are plot-level summaries based on plant and soil samples and measurements obtained over the 1997 to 2001 timeframe. The BDFFP study area is an experimentally fragmented landscape spanning 1,000 km2 located 70-90 km north of Manaus, Amazonas, Brazil. For additional information about the BDFFP and research conducted at the site, please visit their web site at http://pdbff.inpa.gov.br/index.html.There are six comma-separated ASCII data files with this data set.
This data set contains chlorophyll concentration maps of the Amazon River floodplain region from Parintins (Amazonas) to Almeirim (Para). These chlorophyll fraction maps were derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product (MOD09) for 19 months from April 2002 to December 2003. The study was conducted in a floodplain reach upstream from Santarem, Para, in order to assess seasonal changes in phytoplanktonic chlorophyll-a distributions in the floodplain Lake Curuai. MODIS reflectance data were acquired at four river stages: rising (April), high (June), decreasing (September), and low (November). Chlorophyll maps were derived and used to compute the weighted average of chlorophyll concentration from MODIS images in the region. Field measurements of suspended inorganic matter and chlorophyll-a in Lake Curuai were made almost concurrently with satellite overpasses (Barbosa, 2005). The images and the estimated chlorophyll concentrations were compared to measured chlorophyll concentrations at control points for different hydrological states. This data set may be applied to better understand the seasonal dynamics of primary production of the Amazon floodplains. The maps of chlorophyll-a concentration may be used to model spatial and temporal variations of primary production in this region.The monthly chlorophyll-a maps are provided as GeoTIFF files. There are two formats: (1) color-mapped pixels and (2) pixels as chlorophyll-a concentrations. These latter images are not intended for browsing. These images have pixel values that are the chlorophyll-a concentration in mg/m3 and need to be download and opened in GIS software.
This data set contains chlorophyll concentration maps of the Amazon River floodplain region from Parintins (Amazonas) to Almeirim (Para). These chlorophyll fraction maps were derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product (MOD09) for 19 months from April 2002 to December 2003. The study was conducted in a floodplain reach upstream from Santarem, Para, in order to assess seasonal changes in phytoplanktonic chlorophyll-a distributions in the floodplain Lake Curuai. MODIS reflectance data were acquired at four river stages: rising (April), high (June), decreasing (September), and low (November). Chlorophyll maps were derived and used to compute the weighted average of chlorophyll concentration from MODIS images in the region. Field measurements of suspended inorganic matter and chlorophyll-a in Lake Curuai were made almost concurrently with satellite overpasses (Barbosa, 2005). The images and the estimated chlorophyll concentrations were compared to measured chlorophyll concentrations at control points for different hydrological states. This data set may be applied to better understand the seasonal dynamics of primary production of the Amazon floodplains. The maps of chlorophyll-a concentration may be used to model spatial and temporal variations of primary production in this region.The monthly chlorophyll-a maps are provided as GeoTIFF files. There are two formats: (1) color-mapped pixels and (2) pixels as chlorophyll-a concentrations. These latter images are not intended for browsing. These images have pixel values that are the chlorophyll-a concentration in mg/m3 and need to be download and opened in GIS software.
ABSTRACT: This data set contains chlorophyll concentration maps of the Amazon River floodplain region from Parintins (Amazonas) to Almeirim (Para). These chlorophyll fraction maps were derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product (MOD09) for 19 months from April 2002 to December 2003. The study was conducted in a floodplain reach upstream from Santarem, Para, in order to assess seasonal changes in phytoplanktonic chlorophyll-a distributions in the floodplain Lake Curuai. MODIS reflectance data were acquired at four river stages: rising (April), high (June), decreasing (September), and low (November). Chlorophyll maps were derived and used to compute the weighted average of chlorophyll concentration from MODIS images in the region. Field measurements of suspended inorganic matter and chlorophyll-a in Lake Curuai were made almost concurrently with satellite overpasses (Barbosa, 2005). The images and the estimated chlorophyll concentrations were compared to measured chlorophyll concentrations at control points for different hydrological states. This data set may be applied to better understand the seasonal dynamics of primary production of the Amazon floodplains. The maps of chlorophyll-a concentration may be used to model spatial and temporal variations of primary production in this region.The monthly chlorophyll-a maps are provided as GeoTIFF files. There are two formats: (1) color-mapped pixels and (2) pixels as chlorophyll-a concentrations. These latter images are not intended for browsing. These images have pixel values that are the chlorophyll-a concentration in mg/m3 and need to be download and opened in GIS software.
This data set reports measurements of aquatic macrophyte biomass, phenology, leaf characteristics, and length and diameter of stems of both submerged and unsubmerged macrophytes. Data were collected from sites in the Monte Alegre Lake region on the eastern Amazon River floodplain in Para, Brazil. Ten field surveys were made at approximately monthly intervals from December 2003 to November 2004. There is one comma-delimited data file with this data set.
This data set reports measurements of aquatic macrophyte biomass, phenology, leaf characteristics, and length and diameter of stems of both submerged and unsubmerged macrophytes. Data were collected from sites in the Monte Alegre Lake region on the eastern Amazon River floodplain in Para, Brazil. Ten field surveys were made at approximately monthly intervals from December 2003 to November 2004. There is one comma-delimited data file with this data set.
ABSTRACT: This data set reports measurements of aquatic macrophyte biomass, phenology, leaf characteristics, and length and diameter of stems of both submerged and unsubmerged macrophytes. Data were collected from sites in the Monte Alegre Lake region on the eastern Amazon River floodplain in Para, Brazil. Ten field surveys were made at approximately monthly intervals from December 2003 to November 2004. There is one comma-delimited data file with this data set.
The bathymetry data provided represent a continuous surface of interpolated point measurements of depth values of Lago Curuai, an Amazon River floodplain lake, upstream from Santarem, Para, Brazil, from measurements made in June of 2004. The first product contains the actual depth values (in meters) of the interpolated continuous surface saved as real numbers in both ENVI and GeoTIFF formats. Also available is a color scaled depth GeoTIFF image which has an embedded color scale bar. This secondary file is meant only for viewing but has the unique advantage of being a GeoTIFF file. Therefore, this map can be a background image with other projected files of interest in the area. Data provided in this data set were used to develop a methodology for processing and applying high resolution bathymetric data acquired with a Lowrance-480M ecosounder in the Amazon floodplain. This research was supported by the addition of Landast/TM images for planning and executing the survey. 4600 km of transects were processed semi-automatically and integrated into a georeferenced database. A digital elevation model with 15 m horizontal resolution and 1 cm vertical resolution was generated for the floodplain. The changes in inundated area and volume of water on the floodplain were estimated. Regression models were constructed to predict flood area and water stored volume from water level. The results of this research show that water level and flooded area mapped from images are good enough for estimating water stored volume in the Lago Grande de Curuai (Barbosa et al., 2006).
The bathymetry data provided represent a continuous surface of interpolated point measurements of depth values of Lago Curuai, an Amazon River floodplain lake, upstream from Santarem, Para, Brazil, from measurements made in June of 2004. The first product contains the actual depth values (in meters) of the interpolated continuous surface saved as real numbers in both ENVI and GeoTIFF formats. Also available is a color scaled depth GeoTIFF image which has an embedded color scale bar. This secondary file is meant only for viewing but has the unique advantage of being a GeoTIFF file. Therefore, this map can be a background image with other projected files of interest in the area. Data provided in this data set were used to develop a methodology for processing and applying high resolution bathymetric data acquired with a Lowrance-480M ecosounder in the Amazon floodplain. This research was supported by the addition of Landast/TM images for planning and executing the survey. 4600 km of transects were processed semi-automatically and integrated into a georeferenced database. A digital elevation model with 15 m horizontal resolution and 1 cm vertical resolution was generated for the floodplain. The changes in inundated area and volume of water on the floodplain were estimated. Regression models were constructed to predict flood area and water stored volume from water level. The results of this research show that water level and flooded area mapped from images are good enough for estimating water stored volume in the Lago Grande de Curuai (Barbosa et al., 2006).
ABSTRACT: The bathymetry data provided represent a continuous surface of interpolated point measurements of depth values of Lago Curuai, an Amazon River floodplain lake, upstream from Santarem, Para, Brazil, from measurements made in June of 2004. The first product contains the actual depth values (in meters) of the interpolated continuous surface saved as real numbers in both ENVI and GeoTIFF formats. Also available is a color scaled depth GeoTIFF image which has an embedded color scale bar. This secondary file is meant only for viewing but has the unique advantage of being a GeoTIFF file. Therefore, this map can be a background image with other projected files of interest in the area. Data provided in this data set were used to develop a methodology for processing and applying high resolution bathymetric data acquired with a Lowrance-480M ecosounder in the Amazon floodplain. This research was supported by the addition of Landast/TM images for planning and executing the survey. 4600 km of transects were processed semi-automatically and integrated into a georeferenced database. A digital elevation model with 15 m horizontal resolution and 1 cm vertical resolution was generated for the floodplain. The changes in inundated area and volume of water on the floodplain were estimated. Regression models were constructed to predict flood area and water stored volume from water level. The results of this research show that water level and flooded area mapped from images are good enough for estimating water stored volume in the Lago Grande de Curuai (Barbosa et al., 2006).
This data set provides estimates of daily and monthly carbon dioxide (CO2) and methane (CH4) diffusive and ebullitive flux for dry and flooded areas from two study sites, Cuini and Itu, in the interfluvial wetlands of the upper Negro River basin, Brazil. CO2 (ebullitive and diffusive) and CH4 diffusive flux measurements were made one day each month from February 2005 through January 2006 in both permanently and seasonally flooded areas. For the remaining days of each month, fluxes were calculated as the mean of the two measurements bracketing that time period, times the area flooded each day. Total site area, dry area, and seasonally varying flooded area estimates for the two wetlands were determined through analysis of synthetic aperture radar data from Radarsat images. From these estimates, the total flux of CO2 and CH4 for the sites was calculated. Values for CH4 ebullitive flux were determined from a constant for each area based on whether the water was rising or falling and the area flooded. Hydrologic measurements were taken from April 2004 through January, 2006.There are three comma-separated (.csv) data files with this data set.
This data set provides estimates of daily and monthly carbon dioxide (CO2) and methane (CH4) diffusive and ebullitive flux for dry and flooded areas from two study sites, Cuini and Itu, in the interfluvial wetlands of the upper Negro River basin, Brazil. CO2 (ebullitive and diffusive) and CH4 diffusive flux measurements were made one day each month from February 2005 through January 2006 in both permanently and seasonally flooded areas. For the remaining days of each month, fluxes were calculated as the mean of the two measurements bracketing that time period, times the area flooded each day. Total site area, dry area, and seasonally varying flooded area estimates for the two wetlands were determined through analysis of synthetic aperture radar data from Radarsat images. From these estimates, the total flux of CO2 and CH4 for the sites was calculated. Values for CH4 ebullitive flux were determined from a constant for each area based on whether the water was rising or falling and the area flooded. Hydrologic measurements were taken from April 2004 through January, 2006.There are three comma-separated (.csv) data files with this data set.
ABSTRACT: This data set provides estimates of daily and monthly carbon dioxide (CO2) and methane (CH4) diffusive and ebullitive flux for dry and flooded areas from two study sites, Cuini and Itu, in the interfluvial wetlands of the upper Negro River basin, Brazil. CO2 (ebullitive and diffusive) and CH4 diffusive flux measurements were made one day each month from February 2005 through January 2006 in both permanently and seasonally flooded areas. For the remaining days of each month, fluxes were calculated as the mean of the two measurements bracketing that time period, times the area flooded each day. Total site area, dry area, and seasonally varying flooded area estimates for the two wetlands were determined through analysis of synthetic aperture radar data from Radarsat images. From these estimates, the total flux of CO2 and CH4 for the sites was calculated. Values for CH4 ebullitive flux were determined from a constant for each area based on whether the water was rising or falling and the area flooded. Hydrologic measurements were taken from April 2004 through January, 2006.There are three comma-separated (.csv) data files with this data set.
This data set provides three Amazon Basin wetland image products: (1) a Central Amazon Wetlands Mask, (2) a Central Amazon Wetlands Vegetative-hydrologic Land Cover Map, and (3) an Amazon Basin Wetlands Mask. All three were derived from the Global Rain Forest Mapping Project (GRFM) dry and wet season mosaics (August-September 1995 and May-August 1996) of the Japanese Earth Resources Satellite-1 (JERS-1) Synthetic Aperture Radar (SAR) imagery data (Rosenqvist et al., 2000 and Chapman et al., 2001). There are 6 GeoTIFF image files with this data set.
This data set provides three Amazon Basin wetland image products: (1) a Central Amazon Wetlands Mask, (2) a Central Amazon Wetlands Vegetative-hydrologic Land Cover Map, and (3) an Amazon Basin Wetlands Mask. All three were derived from the Global Rain Forest Mapping Project (GRFM) dry and wet season mosaics (August-September 1995 and May-August 1996) of the Japanese Earth Resources Satellite-1 (JERS-1) Synthetic Aperture Radar (SAR) imagery data (Rosenqvist et al., 2000 and Chapman et al., 2001). There are 6 GeoTIFF image files with this data set.
ABSTRACT: This data set provides three Amazon Basin wetland image products: (1) a Central Amazon Wetlands Mask, (2) a Central Amazon Wetlands Vegetative-hydrologic Land Cover Map, and (3) an Amazon Basin Wetlands Mask. All three were derived from the Global Rain Forest Mapping Project (GRFM) dry and wet season mosaics (August-September 1995 and May-August 1996) of the Japanese Earth Resources Satellite-1 (JERS-1) Synthetic Aperture Radar (SAR) imagery data (Rosenqvist et al., 2000 and Chapman et al., 2001). There are 6 GeoTIFF image files with this data set.
This data set reports lake sediment texture and porosity, carbon (C), nitrogen (N), and phosphorus (P) content of surficial sediments, 210Pb-derived nutrient accumulation rates in sediments, and burial rates of C, N, and P in sediments at eleven locations in Lake Calado, Amazonas, Brazil. Field samples were collected between February 1982 and August 1984. There are eight comma-delimited ASCII data files with this data set.
This data set reports lake sediment texture and porosity, carbon (C), nitrogen (N), and phosphorus (P) content of surficial sediments, 210Pb-derived nutrient accumulation rates in sediments, and burial rates of C, N, and P in sediments at eleven locations in Lake Calado, Amazonas, Brazil. Field samples were collected between February 1982 and August 1984. There are eight comma-delimited ASCII data files with this data set.
ABSTRACT: This data set reports lake sediment texture and porosity, carbon (C), nitrogen (N), and phosphorus (P) content of surficial sediments, 210Pb-derived nutrient accumulation rates in sediments, and burial rates of C, N, and P in sediments at eleven locations in Lake Calado, Amazonas, Brazil. Field samples were collected between February 1982 and August 1984. There are eight comma-delimited ASCII data files with this data set.
This data set provides flux measurements of methane (CH4) and carbon dioxide (CO2) from surface waters to the atmosphere. It also provides CH4, CO2, and oxygen (O2) concentrations of surface water, and concentrations measured at several depths of the Balbina Reservoir in the central Amazon Basin, Amazonas, Brazil. The Balbina Reservoir was formed by impounding the Uatuma River in 1987.  Reservoir surface water samples, bottom water samples, and gas samples from static flux enclosures were collected at 10 to 14 sites at monthly intervals between April and November of 2005, and 6 times in February, 2006. Water samples to determine the vertical profiles of temperature, dissolved O2, CH4, and CO2 were collected during the rainy and dry seasons immediately above the dam between September 2004 and February 2006. Water samples were collected downstream from the dam from July 2004 - November 2005 for analysis of CH4 and CO2 concentrations.There are three comma-delimited data files with this data set.
This data set provides flux measurements of methane (CH4) and carbon dioxide (CO2) from surface waters to the atmosphere. It also provides CH4, CO2, and oxygen (O2) concentrations of surface water, and concentrations measured at several depths of the Balbina Reservoir in the central Amazon Basin, Amazonas, Brazil. The Balbina Reservoir was formed by impounding the Uatuma River in 1987.  Reservoir surface water samples, bottom water samples, and gas samples from static flux enclosures were collected at 10 to 14 sites at monthly intervals between April and November of 2005, and 6 times in February, 2006. Water samples to determine the vertical profiles of temperature, dissolved O2, CH4, and CO2 were collected during the rainy and dry seasons immediately above the dam between September 2004 and February 2006. Water samples were collected downstream from the dam from July 2004 - November 2005 for analysis of CH4 and CO2 concentrations.There are three comma-delimited data files with this data set.
ABSTRACT: This data set provides flux measurements of methane (CH4) and carbon dioxide (CO2) from surface waters to the atmosphere. It also provides CH4, CO2, and oxygen (O2) concentrations of surface water, and and concentrations measured at several depths of the Balbina Reservoir in the central Amazon Basin, Amazonas, Brazil. The Balbina Reservoir was formed by impounding the Uatuma River in 1987.  Reservoir surface water samples, bottom water samples, and gas samples from static flux enclosures were collected at 10 to 14 sites at monthly intervals between April and November of 2005, and 6 times in February, 2006. Water samples to determine the vertical profiles of temperature, dissolved O2, CH4, and CO2 were collected during the rainy and dry seasons immediately above dam between September 2004 and February 2006. Water samples were collected downstream from the dam from July 2004 - November 2005 for analysis of CH4 and CO2 concentrations.There are three comma-delimited data files with this data set.
This data set reports methane (CH4) fluxes at the water-air interface and concentrations and isotopic signals of CH4 in the bubbles stirred up from the sediment in Tucurui and Samuel reservoirs in 2000 and 2001. Tucurui (deep) reservoir is located near Belem city in the Tocantins-Araguaia basin in the eastern Amazon. Samuel (shallow) reservoir is situated near Porto Velho city in the Jamari River, a tributary of the Madeira River in the western Amazon. Field samples were collected between June 2000 and September 2001. There are two comma-delimited ASCII data files in this data set. This study was carried out to identify differences in methane cycling between deep and shallow reservoirs (Lima, 2005). Isotopic and concentration analyses of methane in bubbles, dissolved in the water column, and emitted to the atmosphere demonstrate that water depth is critical regarding methane emissions from hydroreservoirs in the Amazon. Methanotrophic activities are greater in Tucurui (deep) while light isotopic methane is directly released from Samuel (shallow). Therefore, the methanotrophic layer of the deep reservoir is more efficient in oxidizing methane before reaching the atmosphere, since the quantity of methane in the sediments of the reservoirs were equivalent.
This data set reports methane (CH4) fluxes at the water-air interface and concentrations and isotopic signals of CH4 in the bubbles stirred up from the sediment in Tucurui and Samuel reservoirs in 2000 and 2001. Tucurui (deep) reservoir is located near Belem city in the Tocantins-Araguaia basin in the eastern Amazon. Samuel (shallow) reservoir is situated near Porto Velho city in the Jamari River, a tributary of the Madeira River in the western Amazon. Field samples were collected between June 2000 and September 2001. There are two comma-delimited ASCII data files in this data set. This study was carried out to identify differences in methane cycling between deep and shallow reservoirs (Lima, 2005). Isotopic and concentration analyses of methane in bubbles, dissolved in the water column, and emitted to the atmosphere demonstrate that water depth is critical regarding methane emissions from hydroreservoirs in the Amazon. Methanotrophic activities are greater in Tucurui (deep) while light isotopic methane is directly released from Samuel (shallow). Therefore, the methanotrophic layer of the deep reservoir is more efficient in oxidizing methane before reaching the atmosphere, since the quantity of methane in the sediments of the reservoirs were equivalent.
ABSTRACT: This data set reports methane (CH4) fluxes at the water-air interface and concentrations and isotopic signals of CH4 in the bubbles stirred up from the sediment in Tucurui and Samuel reservoirs in 2000 and 2001. Tucurui (deep) reservoir is located near Belem city in the Tocantins-Araguaia basin in the eastern Amazon. Samuel (shallow) reservoir is situated near Porto Velho city in the Jamari River, a tributary of the Madeira River in the western Amazon. Field samples were collected between June 2000 and September 2001. There are two comma-delimited ASCII data files in this data set. This study was carried out to identify differences in methane cycling between deep and shallow reservoirs (Lima, 2005). Isotopic and concentration analyses of methane in bubbles, dissolved in the water column, and emitted to the atmosphere demonstrate that water depth is critical regarding methane emissions from hydroreservoirs in the Amazon. Methanotrophic activities are greater in Tucurui (deep) while light isotopic methane is directly released from Samuel (shallow). Therefore, the methanotrophic layer of the deep reservoir is more efficient in oxidizing methane before reaching the atmosphere, since the quantity of methane in the sediments of the reservoirs were equivalent.
This data set reports the monthly record of inundated area, in square km, for six floodplain and open water regions in South America. The following floodplains were analyzed: (1) mainstem Amazon River floodplain in Brazil; (2) Llanos de Mojos (Beni and Mamore rivers) in Bolivia; (3) Bananal Island (Araguaia River) in Brazil; (4) Roraima savannas (Branco and Rupununi rivers) in Brazil and Guyana; (5) Llanos del Orinoco (Apure and Meta rivers) in Venezuela and Colombia; and (6) Pantanal wetland (Paraguay River) in Brazil. Flooded area was estimated at monthly intervals from December 1978 through August 1987 for the Amazon mainstem region and from January 1979 through August 1987 for the other five regions. Inundated area was determined from SMMR (Scanning Multichannel Microwave Radiometer) passive microwave data. Area estimates include permanent open water as well as land subject to seasonal inundation. This data set contains five data files: two comma-delimited (.csv) ASCII data files providing the monthly inundation area values for six floodplain and open water regions in South America; a compressed (.zip) file providing seventeen ESRI Shape files for the region bounding polygons; and two .csv files providing information about the region bounding polygons and latitude/longitude verticies.
This data set reports the monthly record of inundated area, in square km, for six floodplain and open water regions in South America. The following floodplains were analyzed: (1) mainstem Amazon River floodplain in Brazil; (2) Llanos de Mojos (Beni and Mamore rivers) in Bolivia; (3) Bananal Island (Araguaia River) in Brazil; (4) Roraima savannas (Branco and Rupununi rivers) in Brazil and Guyana; (5) Llanos del Orinoco (Apure and Meta rivers) in Venezuela and Colombia; and (6) Pantanal wetland (Paraguay River) in Brazil. Flooded area was estimated at monthly intervals from December 1978 through August 1987 for the Amazon mainstem region and from January 1979 through August 1987 for the other five regions. Inundated area was determined from SMMR (Scanning Multichannel Microwave Radiometer) passive microwave data. Area estimates include permanent open water as well as land subject to seasonal inundation. This data set contains five data files: two comma-delimited (.csv) ASCII data files providing the monthly inundation area values for six floodplain and open water regions in South America; a compressed (.zip) file providing seventeen ESRI Shape files for the region bounding polygons; and two .csv files providing information about the region bounding polygons and latitude/longitude verticies.
ABSTRACT: This data set reports the monthly record of inundated area, in square km, for six floodplain and open water regions in South America. The following floodplains were analyzed: (1) mainstem Amazon River floodplain in Brazil; (2) Llanos de Mojos (Beni and Mamore rivers) in Bolivia; (3) Bananal Island (Araguaia River) in Brazil; (4) Roraima savannas (Branco and Rupununi rivers) in Brazil and Guyana; (5) Llanos del Orinoco (Apure and Meta rivers) in Venezuela and Colombia; and (6) Pantanal wetland (Paraguay River) in Brazil. Flooded area was estimated at monthly intervals from December 1978 through August 1987 for the Amazon mainstem region and from January 1979 through August 1987 for the other five regions. Inundated area was determined from SMMR (Scanning Multichannel Microwave Radiometer) passive microwave data. Area estimates include permanent open water as well as land subject to seasonal inundation. This data set contains five data files: two comma-delimited (.csv) ASCII data files providing the monthly inundation area values for six floodplain and open water regions in South America; a compressed (.zip) file providing seventeen ESRI Shape files for the region bounding polygons; and two .csv files providing information about the region bounding polygons and latitude/longitude verticies.
This data set reports monthly mean inundation areas (square kilometers) for four cover classes of Central Amazon wetlands habitat: Open water (OW),  river channel (RC) class, macrophyte (MA) class, and a flooded forest (FF) class, which also incorporates a flooded shrub class. The full study area was a 1.77 million km2 quadrant covering the Central Amazon Basin. Inundation was also calculated from three subsets of this area: (1) covering only the Amazon/Solimoes River mainstem and (2) the Eastern and (3) the Western halves of this mainstem area. There is one comma-delimited ASCII data file in this data set.
This data set reports monthly mean inundation areas (square kilometers) for four cover classes of Central Amazon wetlands habitat: Open water (OW),  river channel (RC) class, macrophyte (MA) class, and a flooded forest (FF) class, which also incorporates a flooded shrub class. The full study area was a 1.77 million km2 quadrant covering the Central Amazon Basin. Inundation was also calculated from three subsets of this area: (1) covering only the Amazon/Solimoes River mainstem and (2) the Eastern and (3) the Western halves of this mainstem area. There is one comma-delimited ASCII data file in this data set.
ABSTRACT: This data set reports monthly mean inundation areas (square kilometers) for four cover classes of Central Amazon wetlands habitat: Open water (OW),  river channel (RC) class, macrophyte (MA) class, and a flooded forest (FF) class, which also incorporates a flooded shrub class. The full study area was a 1.77 million km2 quadrant covering the Central Amazon Basin. Inundation was also calculated from three subsets of this area: (1) covering only the Amazon/Solimoes River mainstem and (2) the Eastern and (3) the Western halves of this mainstem area. There is one comma-delimited ASCII data file in this data set.
This data set includes bidirectional reflectance (BDR) spectra and water-quality data of floodplain lakes of the Solimoes and Negro Rivers in the central Amazon basin, Amazonas, Brazil. Samples and measurements were collected during July 2000 to August 2000. Bidirectional reflectance factors were recorded, at 3 nm intervals from 400 to 900 nm, concurrently with in situ measurements of water temperature and Secchi depth, and collection of samples for analysis of optically active components including total suspended solids, chlorophyll, and dissolved organic carbon (DOC).The lakes sampled were in the low-lying varzea of the Solimoes River ("varzea" is the local name for the floodplain formed by the overflow of white-water rivers) and igapo ("igapo" is the local name for the floodplain formed by the overflow of black-water rivers) of the Negro River.There are two comma-delimited data files with this data set.
This data set includes bidirectional reflectance (BDR) spectra and water-quality data of floodplain lakes of the Solimoes and Negro Rivers in the central Amazon basin, Amazonas, Brazil. Samples and measurements were collected during July 2000 to August 2000. Bidirectional reflectance factors were recorded, at 3 nm intervals from 400 to 900 nm, concurrently with in situ measurements of water temperature and Secchi depth, and collection of samples for analysis of optically active components including total suspended solids, chlorophyll, and dissolved organic carbon (DOC).The lakes sampled were in the low-lying varzea of the Solimoes River ("varzea" is the local name for the floodplain formed by the overflow of white-water rivers) and igapo ("igapo" is the local name for the floodplain formed by the overflow of black-water rivers) of the Negro River.There are two comma-delimited data files with this data set.
ABSTRACT: This data set includes bidirectional reflectance (BDR) spectra and water-quality data of floodplain lakes of the Solimoes and Negro Rivers in the central Amazon basin, Amazonas, Brazil. Samples and measurements were collected during July 2000 to August 2000. Bidirectional reflectance factors were recorded, at 3 nm intervals from 400 to 900 nm, concurrently with in situ measurements of water temperature and Secchi depth, and collection of samples for analysis of optically active components including total suspended solids, chlorophyll, and dissolved organic carbon (DOC).The lakes sampled were in the low-lying varzea of the Solimoes River ("varzea" is the local name for the floodplain formed by the overflow of white-water rivers) and igapo ("igapo" is the local name for the floodplain formed by the overflow of black-water rivers) of the Negro River.There are two comma-delimited data files with this data set.
This data set reports (1) concentrations of total, organic, and inorganic suspended solids; dissolved inorganic, and organic carbon; chlorophyll-a and (2) measurements of turbidity, ph, temperature, transparency, conductivity, and calculated carbon dioxide (CO2) in water samples collected from Lago Curuai (Lake Curuai), in the floodplain of the Amazon River south of Obidos, Para, Brazil. Approximately 70 stations were sampled during four phases of the hydrological cycle: receding (September 2003), low (November 2003), rising (February 2004), and high water (June 2004). There is one comma-delimited data file with this data set.
This data set reports (1) concentrations of total, organic, and inorganic suspended solids; dissolved inorganic, and organic carbon; chlorophyll-a and (2) measurements of turbidity, ph, temperature, transparency, conductivity, and calculated carbon dioxide (CO2) in water samples collected from Lago Curuai (Lake Curuai), in the floodplain of the Amazon River south of Obidos, Para, Brazil. Approximately 70 stations were sampled during four phases of the hydrological cycle: receding (September 2003), low (November 2003), rising (February 2004), and high water (June 2004). There is one comma-delimited data file with this data set.
ABSTRACT: This data set reports (1) concentrations of total, organic, and inorganic suspended solids; dissolved inorganic, and organic carbon; chlorophyll-a and (2) measurements of turbidity, ph, temperature, transparency, conductivity, and calculated carbon dioxide (CO2) in water samples collected from Lago Curuai (Lake Curuai), in the floodplain of the Amazon River south of Obidos, Para, Brazil. Approximately 70 stations were sampled during four phases of the hydrological cycle: receding (September 2003), low (November 2003), rising (February 2004), and high water (June 2004). There is one comma-delimited data file with this data set.
This data set provides Ecosystem Demography Model (ED) estimates of potential above-ground net primary production (NPP) (kg C/m2/y), potential average live biomass (kg C/m2), and potential average soil carbon (kg C/m2) for the Brazilian Amazon at 1 degree resolution. Ecosystem Demography Model predicts both ecosystem structure (e.g. above and below-ground biomass, vegetation height and basal area, and soil carbon stocks) and corresponding ecosystem fluxes (e.g. NPP, NEP, and evapotranspiration) from climate, soil, and land-use inputs. Estimates for the Brazilian Amazon include the effects of natural disturbances such as windthrow and fire, but do not include the effects of human land use. To produce these estimates, ED was forced with ISLSCP I data for 1987 and 1988 and averaged into a single average year (Moorcroft et al., 2001).The data are provided for the three estimates in both ASCII text and in NetCDF formatted files.
This data set provides Ecosystem Demography Model (ED) estimates of potential above-ground net primary production (NPP) (kg C/m2/y), potential average live biomass (kg C/m2), and potential average soil carbon (kg C/m2) for the Brazilian Amazon at 1 degree resolution. Ecosystem Demography Model predicts both ecosystem structure (e.g. above and below-ground biomass, vegetation height and basal area, and soil carbon stocks) and corresponding ecosystem fluxes (e.g. NPP, NEP, and evapotranspiration) from climate, soil, and land-use inputs. Estimates for the Brazilian Amazon include the effects of natural disturbances such as windthrow and fire, but do not include the effects of human land use. To produce these estimates, ED was forced with ISLSCP I data for 1987 and 1988 and averaged into a single average year (Moorcroft et al., 2001).The data are provided for the three estimates in both ASCII text and in NetCDF formatted files.
ABSTRACT: This data set provides Ecosystem Demography Model (ED) estimates of potential above-ground net primary production (NPP) (kg C/m2/y), potential average live biomass (kg C/m2), and potential average soil carbon (kg C/m2) for the Brazilian Amazon at 1 degree resolution. Ecosystem Demography Model predicts both ecosystem structure (e.g. above and below-ground biomass, vegetation height and basal area, and soil carbon stocks) and corresponding ecosystem fluxes (e.g. NPP, NEP, and evapotranspiration) from climate, soil, and land-use inputs. Estimates for the Brazilian Amazon include the effects of natural disturbances such as windthrow and fire, but do not include the effects of human land use. To produce these estimates, ED was forced with ISLSCP I data for 1987 and 1988 and averaged into a single average year (Moorcroft et al., 2001).The data are provided for the three estimates in both ASCII text and in NetCDF formatted files.
This data set reports observations of fires in the vicinity of Maraba, Para, Brazil, from November 3-5th, 2001, and in Mato Grosso, Brazil, between Cuiaba and Alta Floresta, for July 12-15th, 2002. These ground-based data were collected by visual inspection from roads primarily during daylight hours. Data include fire position and time, estimates of fire size, and type of vegetation burned. There is one comma-delimited ASCII file with this data set.
This data set reports observations of fires in the vicinity of Maraba, Para, Brazil, from November 3-5th, 2001, and in Mato Grosso, Brazil, between Cuiaba and Alta Floresta, for July 12-15th, 2002. These ground-based data were collected by visual inspection from roads primarily during daylight hours. Data include fire position and time, estimates of fire size, and type of vegetation burned. There is one comma-delimited ASCII file with this data set.
ABSTRACT: This data set reports observations of fires in the vicinity of Maraba, Para, Brazil, from November 3-5th, 2001, and in Mato Grosso, Brazil, between Cuiaba and Alta Floresta, for July 12-15th, 2002. These ground-based data were collected by visual inspection from roads primarily during daylight hours. Data include fire position and time, estimates of fire size, and type of vegetation burned. There is one comma-delimited ASCII file with this data set.
This data set provides (1) soil maps for Brazil that are digital versions of the MAPA DE SOLOS DO BRASIL (EMBRAPA, 1981) classified at three levels of detail, 19-class, 70-class and 249-class; (2) vegetation maps for Brazil that are digital versions of the MAPA DE VEGETACAO DO BRASIL (IBGE, 1988) classified at three levels of detail, 13-class, 59-class, and an overprint (combination) class; and (3) a land cover map for all of South America that was derived from National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data over the time period 1987 through 1991 (Stone et al., 1994).The seven soil, vegetation, and general land cover classification maps are provided as GeoTIFF files (*.tif) files. There are also three companion files (.pdf), one each, for the soil, vegetation, and land cover maps, with information on  map units, class values, codes, and descriptions.
This data set provides (1) soil maps for Brazil that are digital versions of the MAPA DE SOLOS DO BRASIL (EMBRAPA, 1981) classified at three levels of detail, 19-class, 70-class and 249-class; (2) vegetation maps for Brazil that are digital versions of the MAPA DE VEGETACAO DO BRASIL (IBGE, 1988) classified at three levels of detail, 13-class, 59-class, and an overprint (combination) class; and (3) a land cover map for all of South America that was derived from National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data over the time period 1987 through 1991 (Stone et al., 1994).The seven soil, vegetation, and general land cover classification maps are provided as GeoTIFF files (*.tif) files. There are also three companion files (.pdf), one each, for the soil, vegetation, and land cover maps, with information on  map units, class values, codes, and descriptions.
ABSTRACT: This data set provides (1) soil maps for Brazil that are digital versions of the MAPA DE SOLOS DO BRASIL (EMBRAPA, 1981) classified at three levels of detail, 19-class, 70-class and 249-class; (2) vegetation maps for Brazil that are digital versions of the MAPA DE VEGETACAO DO BRASIL (IBGE, 1988) classified at three levels of detail, 13-class, 59-class, and an overprint (combination) class; and (3) a land cover map for all of South America that was derived from National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data over the time period 1987 through 1991 (Stone et al., 1994).The seven soil, vegetation, and general land cover classification maps are provided as GeoTIFF files (*.tif) files. There are also three companion files (.pdf), one each, for the soil, vegetation, and land cover maps, with information on  map units, class values, codes, and descriptions.
This data set reports daily total precipitation data retrieved from Brazilian National Institute of Meteorology (INMET) network for three stations near two Amazonian research sites: Altamira, and Santarem, from 1961-1998.Daily precipitation totals are provided in one comma-separated ASCII file for three stations in Para, including two sites in Altamira: Altamira City and on the Transamazon Highway at Km 100 near Medicilandia (operated by EMBRAPA); and, one site in Santarem: Taperinha. Data availability varies by station (sublocation): Altamira City from 1961-1990, Transamazon Km 100 from 1982-1998,  and Taperinha from 1983-1992.
This data set reports daily total precipitation data retrieved from Brazilian National Institute of Meteorology (INMET) network for three stations near two Amazonian research sites: Altamira, and Santarem, from 1961-1998.Daily precipitation totals are provided in one comma-separated ASCII file for three stations in Para, including two sites in Altamira: Altamira City and on the Transamazon Highway at Km 100 near Medicilandia (operated by EMBRAPA); and, one site in Santarem: Taperinha. Data availability varies by station (sublocation): Altamira City from 1961-1990, Transamazon Km 100 from 1982-1998,  and Taperinha from 1983-1992.
ABSTRACT: This data set reports daily total precipitation data retrieved from Brazilian National Institute of Meteorology (INMET) network for three stations near two Amazonian research sites: Altamira, and Santarem, from 1961-1998.Daily precipitation totals are provided in one comma-separated ASCII file for three stations in Para, including two sites in Altamira: Altamira City and on the Transamazon Highway at Km 100 near Medicilandia (operated by EMBRAPA); and, one site in Santarem: Taperinha. Data availability varies by station (sublocation): Altamira City from 1961-1990, Transamazon Km 100 from 1982-1998,  and Taperinha from 1983-1992.
This data set includes classified land cover transition maps at 30-m resolution derived from Landsat TM, MSS, ETM+ imagery and aerial photos of Altamira, Santarem, and Ponta de Pedras, in the state of Para, Brazil. The Landsat images were classified into several types of land use (e.g., forest, secondary succession, pasture, annual crops, perennial crops, and water) and subjected to change detection analysis to create transition matrices of land cover change. Dates of acquired images represent the most cloud-free image retrievals from 1970-2001 for each site and are therefore not continuous. There are 3 GeoTIFF files (.tif) with this data set.
This data set includes classified land cover transition maps at 30-m resolution derived from Landsat TM, MSS, ETM+ imagery and aerial photos of Altamira, Santarem, and Ponta de Pedras, in the state of Para, Brazil. The Landsat images were classified into several types of land use (e.g., forest, secondary succession, pasture, annual crops, perennial crops, and water) and subjected to change detection analysis to create transition matrices of land cover change. Dates of acquired images represent the most cloud-free image retrievals from 1970-2001 for each site and are therefore not continuous. There are 3 GeoTIFF files (.tif) with this data set.
ABSTRACT: This data set includes classified land cover transition maps at 30-m resolution derived from Landsat TM, MSS, ETM+ imagery and aerial photos of Altamira, Santarem, and Ponta de Pedras, in the state of Para, Brazil. The Landsat images were classified into several types of land use (e.g., forest, secondary succession, pasture, annual crops, perennial crops, and water) and subjected to change detection analysis to create transition matrices of land cover change. Dates of acquired images represent the most cloud-free image retrievals from 1970-2001 for each site and are therefore not continuous. There are 3 GeoTIFF files (.tif) with this data set.
This data set includes 15 zipped archives of rectified .tif format Landsat 5 TM and Landsat 7 ETM+ scenes from near the study sites of Altamira, Santarem, Ponta de Pedras, and Bragantina in the state of Para, Brazil and Machadinho D'Oeste in Rondonia, Brazil. Dates represent the most cloud-free image retrievals from 1985-2004 and are therefore not continuous. These images may be useful to evaluate potential environmental impacts resulting from the establishment of colonization projects in the Amazon.
This data set includes 15 zipped archives of rectified .tif format Landsat 5 TM and Landsat 7 ETM+ scenes from near the study sites of Altamira, Santarem, Ponta de Pedras, and Bragantina in the state of Para, Brazil and Machadinho D'Oeste in Rondonia, Brazil. Dates represent the most cloud-free image retrievals from 1985-2004 and are therefore not continuous. These images may be useful to evaluate potential environmental impacts resulting from the establishment of colonization projects in the Amazon.
ABSTRACT: This data set includes 15 zipped archives of rectified .tif format Landsat 5 TM and Landsat 7 ETM+ scenes from near the study sites of Altamira, Santarem, Ponta de Pedras, and Bragantina in the state of Para, Brazil and Machadinho D'Oeste in Rondonia, Brazil. Dates represent the most cloud-free image retrievals from 1985-2004 and are therefore not continuous. These images may be useful to evaluate potential environmental impacts resulting from the establishment of colonization projects in the Amazon.
This data set includes 16 zipped archives of shapefiles of cities, rivers and streams, roads, and study area boundaries of several Amazonian study sites: Altamira, Santarem, Bragantina, and Ponta de Pedras, in the state of Para, and 1 site at Machadinho D'Oeste, in the state of Rondonia. Data from Brazil were digitized from Instituto Nacional de Colonizacao e Reforma Agraria (INCRA) maps and other data from Instituto Brasileiro de Geografia e Estatistica (IBGE). These products were prepared in the 2000-2004 time period. The data of creation for the source material is unknown.
This data set includes 16 zipped archives of shapefiles of cities, rivers and streams, roads, and study area boundaries of several Amazonian study sites: Altamira, Santarem, Bragantina, and Ponta de Pedras, in the state of Para, and 1 site at Machadinho D'Oeste, in the state of Rondonia. Data from Brazil were digitized from Instituto Nacional de Colonizacao e Reforma Agraria (INCRA) maps and other data from Instituto Brasileiro de Geografia e Estatistica (IBGE). These products were prepared in the 2000-2004 time period. The data of creation for the source material is unknown.
ABSTRACT: This data set includes 16 zipped archives of shapefiles of cities, rivers and streams, roads, and study area boundaries of several Amazonian study sites: Altamira, Santarem, Bragantina, and Ponta de Pedras, in the state of Para, and 1 site at Machadinho D'Oeste, in the state of Rondonia. Data from Brazil were digitized from Instituto Nacional de Colonizacao e Reforma Agraria (INCRA) maps and other data from Instituto Brasileiro de Geografia e Estatistica (IBGE). These products were prepared in the 2000-2004 time period. The data of creation for the source material is unknown.
This data set contains two files with vegetation data for five Amazonian sites: Altamira, Bragantina, Tome-Acu, and Ponta de Pedras, all in the state of Para, and Yapu, Colombia. One file describes vegetation composition and structure (basal area, biomass, species composition) with different land use histories for all five study sites; the second file describes more specific information about individual plant characteristics (family/species names, DBH, stem and total plant height) within each plot.
This data set contains two files with vegetation data for five Amazonian sites: Altamira, Bragantina, Tome-Acu, and Ponta de Pedras, all in the state of Para, and Yapu, Colombia. One file describes vegetation composition and structure (basal area, biomass, species composition) with different land use histories for all five study sites; the second file describes more specific information about individual plant characteristics (family/species names, DBH, stem and total plant height) within each plot.
ABSTRACT: This data set contains two files with vegetation data for five Amazonian sites: Altamira, Bragantina, Tome-Acu, and Ponta de Pedras, all in the state of Para, and Yapu, Colombia. One file describes vegetation composition and structure (basal area, biomass, species composition) with different land use histories for all five study sites; the second file describes more specific information about individual plant characteristics (family/species names, DBH, stem and total plant height) within each plot.
This data set includes Landsat TM scenes from across the Legal Amazon region.  A single image is provided for each spatial tile, representing the most cloud-free retrieval from 9/21/86 to 9/17/94.  All files are in a single directory, including one band-sequential (bsq) file and one database (ddr) file for each scene.
This data set includes Landsat TM scenes from across the Legal Amazon region.  A single image is provided for each spatial tile, representing the most cloud-free retrieval from 9/21/86 to 9/17/94.  All files are in a single directory, including one band-sequential (bsq) file and one database (ddr) file for each scene.
ABSTRACT: This data set includes Landsat TM scenes from across the Legal Amazon region.  A single image is provided for each spatial tile, representing the most cloud-free retrieval from 9/21/86 to 9/17/94.  All files are in a single directory, including one band-sequential (bsq) file and one database (ddr) file for each scene.
This data set includes orthorectified Landsat ETM+ scenes across the Legal Amazon region. At least one scene is provided for each spatial tile, representing the most cloud-free retrievals from mid-1999 through late 2001 (Fig. 1). Dates are therefore not continuous but include scenes from July 8, 1999 to November 13, 2001. Data have been atmospherically corrected and orthorectified. The individual images should be highly useful as they include very little cloud cover, but they should not be mosaicked together since retrieval dates vary.Data files (and format) included for each scene are: six multispectral bands (tif), two thermal bands (tif), one panchromatic band (tif), two preview files (jpg), and one metadata file (txt). The individual Geotiff files have been g-zipped and subsequently all of the files for a scene have been g-zipped together for ordering convenience.
This data set includes orthorectified Landsat ETM+ scenes across the Legal Amazon region. At least one scene is provided for each spatial tile, representing the most cloud-free retrievals from mid-1999 through late 2001 (Fig. 1). Dates are therefore not continuous but include scenes from July 8, 1999 to November 13, 2001. Data have been atmospherically corrected and orthorectified. The individual images should be highly useful as they include very little cloud cover, but they should not be mosaicked together since retrieval dates vary.Data files (and format) included for each scene are: six multispectral bands (tif), two thermal bands (tif), one panchromatic band (tif), two preview files (jpg), and one metadata file (txt). The individual Geotiff files have been g-zipped and subsequently all of the files for a scene have been g-zipped together for ordering convenience.
ABSTRACT: This data set includes orthorectified Landsat ETM+ scenes across the Legal Amazon region. At least one scene is provided for each spatial tile, representing the most cloud-free retrievals from mid-1999 through late 2001 (Fig. 1). Dates are therefore not continuous but include scenes from July 8, 1999 to November 13, 2001. Data have been atmospherically corrected and orthorectified. The individual images should be highly useful as they include very little cloud cover, but they should not be mosaicked together since retrieval dates vary.Data files (and format) included for each scene are: six multispectral bands (tif), two thermal bands (tif), one panchromatic band (tif), two preview files (jpg), and one metadata file (txt). The individual Geotiff files have been g-zipped and subsequently all of the files for a scene have been g-zipped together for ordering convenience.
This data set contains GIS coverage constructed from measurements taken of four logged areas in Cauaxi, Para, Brazil. Logged areas were selectively harvested either using conventional logging techniques or using reduced-impact logging (RIL) techniques (Pereira et al., 2002). Two areas were harvested with each technique in 1996 and two additional areas were harvested in 1998. Coverage includes log decks (patios), roads, skids trails, tree-fall locations, and logging area (block) boundary. These field surveys were conducted as part of an investigation of canopy damage following selective logging by two different techniques (Asner et al., 2004).Coverage is in ArcInfo interchange format (*.e00). The geographic projection of the data is UTM zone 22, South WGS84 datum.
This data set contains GIS coverage constructed from measurements taken of four logged areas in Cauaxi, Para, Brazil. Logged areas were selectively harvested either using conventional logging techniques or using reduced-impact logging (RIL) techniques (Pereira et al., 2002). Two areas were harvested with each technique in 1996 and two additional areas were harvested in 1998. Coverage includes log decks (patios), roads, skids trails, tree-fall locations, and logging area (block) boundary. These field surveys were conducted as part of an investigation of canopy damage following selective logging by two different techniques (Asner et al., 2004).Coverage is in ArcInfo interchange format (*.e00). The geographic projection of the data is UTM zone 22, South WGS84 datum.
ABSTRACT: This data set contains GIS coverage constructed from measurements taken of four logged areas in Cauaxi, Para, Brazil. Logged areas were selectively harvested either using conventional logging techniques or using reduced-impact logging (RIL) techniques (Pereira et al., 2002). Two areas were harvested with each technique in 1996 and two additional areas were harvested in 1998. Coverage includes log decks (patios), roads, skids trails, tree-fall locations, and logging area (block) boundary. These field surveys were conducted as part of an investigation of canopy damage following selective logging by two different techniques (Asner et al., 2004).Coverage is in ArcInfo interchange format (*.e00). The geographic projection of the data is UTM zone 22, South WGS84 datum.
This data set contains GIS coverages constructed from measurements taken of  logged areas in Juruena, Mato Grosso. Classes include roads, skids trails, tree crowns, tree-fall locations, and block boundary (Asner et al., 2004). Coverages are in ArcInfo SHAPE format (*.shp), UTM projection, using the WGS84 datum.
This data set contains GIS coverages constructed from measurements taken of  logged areas in Juruena, Mato Grosso. Classes include roads, skids trails, tree crowns, tree-fall locations, and block boundary (Asner et al., 2004). Coverages are in ArcInfo SHAPE format (*.shp), UTM projection, using the WGS84 datum.
ABSTRACT: This data set contains GIS coverages constructed from measurements taken of  logged areas in Juruena, Mato Grosso. Classes include roads, skids trails, tree crowns, tree-fall locations, and block boundary (Asner et al., 2004). Coverages are in ArcInfo SHAPE format (*.shp), UTM projection, using the WGS84 datum.
This data set contains GIS coverages constructed from measurements taken of logged areas in the Tapajos National Forest region of Para, Brazil in 1996 and 1998 (Asner et al., 2004). Coverages include log decks (patios), roads, skids trails, tree-fall locations, and block boundary. They are in ArcInfo SHAPE format (*.shp). The Tapajos data are in latitude/longitude using the WGS84 datum.
This data set contains GIS coverages constructed from measurements taken of logged areas in the Tapajos National Forest region of Para, Brazil in 1996 and 1998 (Asner et al., 2004). Coverages include log decks (patios), roads, skids trails, tree-fall locations, and block boundary. They are in ArcInfo SHAPE format (*.shp). The Tapajos data are in latitude/longitude using the WGS84 datum.
ABSTRACT: This data set contains GIS coverages constructed from measurements taken of logged areas in the Tapajos National Forest region of Para, Brazil in 1996 and 1998 (Asner et al., 2004). Coverages include log decks (patios), roads, skids trails, tree-fall locations, and block boundary. They are in ArcInfo SHAPE format (*.shp). The Tapajos data are in latitude/longitude using the WGS84 datum.
This data set reports forest biophysical measurements from a rainfall exclusion experiment conducted at the km 67 Seca Floresta site, Tapajos National Forest, Brazil from 1998 to 2006. The purpose was to observe the potential effects of severe water stress on a humid Amazonian forest (Nepstad 2002). Data are reported for stem inventory, tree diameter at breast height (DBH) and height, dendrometer measurements of tree diameter growth increments, canopy density, leaf area index (LAI), and coarse and fine litter mass.The measurements were made monthly from September 28, 1998 through November 10, 2006. There are six comma-delimited data files (.csv), and one text file (.txt) with this data set.
This data set reports forest biophysical measurements from a rainfall exclusion experiment conducted at the km 67 Seca Floresta site, Tapajos National Forest, Brazil from 1998 to 2006. The purpose was to observe the potential effects of severe water stress on a humid Amazonian forest (Nepstad 2002). Data are reported for stem inventory, tree diameter at breast height (DBH) and height, dendrometer measurements of tree diameter growth increments, canopy density, leaf area index (LAI), and coarse and fine litter mass.The measurements were made monthly from September 28, 1998 through November 10, 2006. There are six comma-delimited data files (.csv), and one text file (.txt) with this data set.
ABSTRACT: This data set reports forest biophysical measurements from a rainfall exclusion experiment conducted at the km 67 Seca Floresta site, Tapajos National Forest, Brazil from 1998 to 2006. The purpose was to observe the potential effects of severe water stress on a humid Amazonian forest (Nepstad 2002). Data are reported for stem inventory, tree diameter at breast height (DBH) and height, dendrometer measurements of tree diameter growth increments, canopy density, leaf area index (LAI), and coarse and fine litter mass.The measurements were made monthly from September 28, 1998 through November 10, 2006. There are six comma-delimited data files (.csv), and one text file (.txt) with this data set.
This data set provides the results of the two modeled scenarios for future patterns of deforestation across the Amazon Basin from 2002 to 2050. This larger defined Amazon Basin (PanAmazon area) includes the Amazon River watershed, the Legal Amazon in Brazil, and the Guiana region. The model SimAmazonia was used to simulate monthly deforestation in the Amazon Basin from 2002 to 2050 for two scenarios: (1) a "Business-as-Usual" scenario, which considered the deforestation trends across the basin and projected the rates by using historical images and their variations from 1997 to 2002 and then added to that the effect of paving a set of major roads, and (2) a "Governance" scenario, that also considered the current deforestation trends, but assumed a 50% limit  imposed for deforested land within each basin's subregion, and that existing and proposed Protected Areas (PAs), play a decisive role in limiting deforestation as well (Soares et al., 2006).The provided data products include one GeoTiff (*.tif) for each year (2002 to 2050) for both model scenarios for a total of 98 files. The files have been compressed in two *.zip files, one for each model scenario. There is also one comma-delimited file that contains the model input data derived from satellite deforestation maps.
This data set provides the results of the two modeled scenarios for future patterns of deforestation across the Amazon Basin from 2002 to 2050. This larger defined Amazon Basin (PanAmazon area) includes the Amazon River watershed, the Legal Amazon in Brazil, and the Guiana region. The model SimAmazonia was used to simulate monthly deforestation in the Amazon Basin from 2002 to 2050 for two scenarios: (1) a "Business-as-Usual" scenario, which considered the deforestation trends across the basin and projected the rates by using historical images and their variations from 1997 to 2002 and then added to that the effect of paving a set of major roads, and (2) a "Governance" scenario, that also considered the current deforestation trends, but assumed a 50% limit  imposed for deforested land within each basin's subregion, and that existing and proposed Protected Areas (PAs), play a decisive role in limiting deforestation as well (Soares et al., 2006).The provided data products include one GeoTiff (*.tif) for each year (2002 to 2050) for both model scenarios for a total of 98 files. The files have been compressed in two *.zip files, one for each model scenario. There is also one comma-delimited file that contains the model input data derived from satellite deforestation maps.
ABSTRACT: This data set provides the results of the two modeled scenarios for future patterns of deforestation across the Amazon Basin from 2002 to 2050. This larger defined Amazon Basin (PanAmazon area) includes the Amazon River watershed, the Legal Amazon in Brazil, and the Guiana region. The model SimAmazonia was used to simulate monthly deforestation in the Amazon Basin from 2002 to 2050 for two scenarios: (1) a "Business-as-Usual" scenario, which considered the deforestation trends across the basin and projected the rates by using historical images and their variations from 1997 to 2002 and then added to that the effect of paving a set of major roads, and (2) a "Governance" scenario, that also considered the current deforestation trends, but assumed a 50% limit  imposed for deforested land within each basin's subregion, and that existing and proposed Protected Areas (PAs), play a decisive role in limiting deforestation as well (Soares et al., 2006).The provided data products include one GeoTiff (*.tif) for each year (2002 to 2050) for both model scenarios for a total of 98 files. The files have been compressed in two *.zip files, one for each model scenario. There is also one comma-delimited file that contains the model input data derived from satellite deforestation maps.
A simple GIS soil-water balance model for the Amazon Basin, called RisQue (Risco de Queimadasa -- Fire Risk), was used to conduct an analysis of spatial and temporal patterns of drought in moist tropical forests and the complex relationships between patterns of drought and forest fire regimes from 1995 through 2001. The provided data products are the model output estimates of maximum plant-available soil water (PAWmax) at 10 m depth at 8 km resolution and model data inputs of monthly precipitation and evapotranspiration. RisQue estimates PAWmax at 10 m depth starting with a map of PAWmax (1-2 m depth) developed using 1,565 RADAMBRASIL soil texture profiles and empirical relationships between soil texture and critical soil water parameters and then interpolated to 8 km resolution. In RisQue, plant-available soil water (PAW) is depleted by monthly evapotranspiration estimated using the Penman Monteith equation and satellite-derived radiation and recharged by monthly precipitation.There are three data files with this data set, two *.zip, and one GeoTIFF image (.tif). The *.zip files expand to 83 *.asc files of evapotranspiration and 89 *.asc files for precipitation data. The image (.tif) is a map of  maximum percent available water at 10 m depth. All the files in this data set are in standard arc/info asciigrid format at 8 km resolution.
A simple GIS soil-water balance model for the Amazon Basin, called RisQue (Risco de Queimadasa -- Fire Risk), was used to conduct an analysis of spatial and temporal patterns of drought in moist tropical forests and the complex relationships between patterns of drought and forest fire regimes from 1995 through 2001. The provided data products are the model output estimates of maximum plant-available soil water (PAWmax) at 10 m depth at 8 km resolution and model data inputs of monthly precipitation and evapotranspiration. RisQue estimates PAWmax at 10 m depth starting with a map of PAWmax (1-2 m depth) developed using 1,565 RADAMBRASIL soil texture profiles and empirical relationships between soil texture and critical soil water parameters and then interpolated to 8 km resolution. In RisQue, plant-available soil water (PAW) is depleted by monthly evapotranspiration estimated using the Penman Monteith equation and satellite-derived radiation and recharged by monthly precipitation.There are three data files with this data set, two *.zip, and one GeoTIFF image (.tif). The *.zip files expand to 83 *.asc files of evapotranspiration and 89 *.asc files for precipitation data. The image (.tif) is a map of  maximum percent available water at 10 m depth. All the files in this data set are in standard arc/info asciigrid format at 8 km resolution.
ABSTRACT: A simple GIS soil-water balance model for the Amazon Basin, called RisQue (Risco de Queimadasa -- Fire Risk), was used to conduct an analysis of spatial and temporal patterns of drought in moist tropical forests and the complex relationships between patterns of drought and forest fire regimes from 1995 through 2001. The provided data products are the model output estimates of maximum plant-available soil water (PAWmax) at 10 m depth at 8 km resolution and model data inputs of monthly precipitation and evapotranspiration. RisQue estimates PAWmax at 10 m depth starting with a map of PAWmax (1-2 m depth) developed using 1,565 RADAMBRASIL soil texture profiles and empirical relationships between soil texture and critical soil water parameters and then interpolated to 8 km resolution. In RisQue, plant-available soil water (PAW) is depleted by monthly evapotranspiration estimated using the Penman Monteith equation and satellite-derived radiation and recharged by monthly precipitation.There are three data files with this data set, two *.zip, and one GeoTIFF image (.tif). The *.zip files expand to 83 *.asc files of evapotranspiration and 89 *.asc files for precipitation data. The image (.tif) is a map of  maximum percent available water at 10 m depth. All the files in this data set are in standard arc/info asciigrid format at 8 km resolution.
This data set provides measurements of specific leaf area and monthly phenological observations for selected tree and vine species at the km 67 Seca Floresta site, Tapajos National Forest, Para, Brazil. The study site was part of a rainfall exclusion experiment that was conducted from 1999-2006 to develop an understanding of the physical processes driving the observed soil water dynamics at the site. Phenological observations were made from 2001-2004 in rainfall exclusion and control plots. In total, 3,224 leaves were observed across 223 individuals and 56 species. The phenological observations included the month and year when a given leaf was first observed fully expanded and last observed alive. Starting in July 2004 and continuing through January 2006, leaves that had been followed in the phenology study were sampled and leaf area and mass were determined and the specific leaf area was calculated.There are two comma-delimited data files with this data set.
This data set provides measurements of specific leaf area and monthly phenological observations for selected tree and vine species at the km 67 Seca Floresta site, Tapajos National Forest, Para, Brazil. The study site was part of a rainfall exclusion experiment that was conducted from 1999-2006 to develop an understanding of the physical processes driving the observed soil water dynamics at the site. Phenological observations were made from 2001-2004 in rainfall exclusion and control plots. In total, 3,224 leaves were observed across 223 individuals and 56 species. The phenological observations included the month and year when a given leaf was first observed fully expanded and last observed alive. Starting in July 2004 and continuing through January 2006, leaves that had been followed in the phenology study were sampled and leaf area and mass were determined and the specific leaf area was calculated.There are two comma-delimited data files with this data set.
ABSTRACT: This data set provides measurements of specific leaf area and monthly phenological observations for selected tree and vine species at the km 67 Seca Floresta site, Tapajos National Forest, Para, Brazil. The study site was part of a rainfall exclusion experiment that was conducted from 1999-2006 to develop an understanding of the physical processes driving the observed soil water dynamics at the site. Phenological observations were made from 2001-2004 in rainfall exclusion and control plots. In total, 3,224 leaves were observed across 223 individuals and 56 species. The phenological observations included the month and year when a given leaf was first observed fully expanded and last observed alive. Starting in July 2004 and continuing through January 2006, leaves that had been followed in the phenology study were sampled and leaf area and mass were determined and the specific leaf area was calculated.There are two comma-delimited data files with this data set.
This data set provides physical roughness maps of vegetation canopies in the Amazon Basin. The images are estimates of aerodynamic roughness length (Z0) and zero plane displacement height (D0) at 1-km spatial resolution. The aerodynamic roughness length (Z0) is an important parameter to determine the vertical gradients of mean wind speed and the conditions for momentum transfer over a vegetated or bare rough surface.The maps were produced from a multivariate regression model algorithm developed from field-measured vegetation structure and remote-sensing data. The data input sources included Shuttle Radar Topography Mission (SRTM) (Saatchi, 2013), JERS-1, MODIS, and field data from vegetation biomass plots over the Amazon basin, as well as tower-based wind profile measurements, and roughness parameters from LBA tower sites. There are two GeoTIFF (.tif) files with this data set.
This data set provides physical roughness maps of vegetation canopies in the Amazon Basin. The images are estimates of aerodynamic roughness length (Z0) and zero plane displacement height (D0) at 1-km spatial resolution. The aerodynamic roughness length (Z0) is an important parameter to determine the vertical gradients of mean wind speed and the conditions for momentum transfer over a vegetated or bare rough surface.The maps were produced from a multivariate regression model algorithm developed from field-measured vegetation structure and remote-sensing data. The data input sources included Shuttle Radar Topography Mission (SRTM) (Saatchi, 2013), JERS-1, MODIS, and field data from vegetation biomass plots over the Amazon basin, as well as tower-based wind profile measurements, and roughness parameters from LBA tower sites. There are two GeoTIFF (.tif) files with this data set.
ABSTRACT: This data set provides physical roughness maps of vegetation canopies in the Amazon Basin. The images are estimates of aerodynamic roughness length (Z0) and zero plane displacement height (D0) at 1-km spatial resolution. The aerodynamic roughness length (Z0) is an important parameter to determine the vertical gradients of mean wind speed and the conditions for momentum transfer over a vegetated or bare rough surface.The maps were produced from a multivariate regression model algorithm developed from field-measured vegetation structure and remote-sensing data. The data input sources included Shuttle Radar Topography Mission (SRTM) (Saatchi, 2013), JERS-1, MODIS, and field data from vegetation biomass plots over the Amazon basin, as well as tower-based wind profile measurements, and roughness parameters from LBA tower sites. There are two GeoTIFF (.tif) files with this data set.
This data set provides a single raster image containing the spatial distribution of aboveground live forest biomass of the Amazon basin. This product was derived using a methodology based on a combination of land cover map, remote sensing derived metrics, and more than 500 forest plots distributed over the basin (Saatchi, et al., 2007).The distributed map was produced in ENVI, in Tiff format and it contains forest biomass divided among 11 classes at 1 km spatial resolution with reasonable accuracy (better than 70%). Remote sensing and ground data used in this product were collected from 1990-2000. The Biomass map represents average biomass distribution over the Amazon basin over this period and was used to estimate the total carbon stock of the basin, including the dead and belowground biomass.
This data set provides a single raster image containing the spatial distribution of aboveground live forest biomass of the Amazon basin. This product was derived using a methodology based on a combination of land cover map, remote sensing derived metrics, and more than 500 forest plots distributed over the basin (Saatchi, et al., 2007).The distributed map was produced in ENVI, in Tiff format and it contains forest biomass divided among 11 classes at 1 km spatial resolution with reasonable accuracy (better than 70%). Remote sensing and ground data used in this product were collected from 1990-2000. The Biomass map represents average biomass distribution over the Amazon basin over this period and was used to estimate the total carbon stock of the basin, including the dead and belowground biomass.
ABSTRACT: This data set provides a single raster image containing the spatial distribution of aboveground live forest biomass of the Amazon basin. This product was derived using a methodology based on a combination of land cover map, remote sensing derived metrics, and more than 500 forest plots distributed over the basin (Saatchi, et al., 2007).The distributed map was produced in ENVI, in Tiff format and it contains forest biomass divided among 11 classes at 1 km spatial resolution with reasonable accuracy (better than 70%). Remote sensing and ground data used in this product were collected from 1990-2000. The Biomass map represents average biomass distribution over the Amazon basin over this period and was used to estimate the total carbon stock of the basin, including the dead and belowground biomass.
This data set provides a subset of the SRTM30 Digital Elevation Model (DEM) elevation and standard deviation data for the Amazon Basin. SRTM30 is a near-global digital elevation model (DEM) comprising a combination of data from the Shuttle Radar Topography Mission (SRTM), flown in February, 2000, and the earlier U.S. Geological Survey's GTOPO30 data set. The SRTM30 resolution is 30 arc-sec or about 1 km. In processing the SRTM data, to combine with GTOPO30, the data were resampled from 3 arc-sec to 30 arc-sec. Provided here are the mean elevation and the standard deviation (STD) of the data points used in the averaging. The STD is thus an indication of topographic roughness useful in some applications. There are two GeoTIFF (.tif) files with this data set.
This data set provides a subset of the SRTM30 Digital Elevation Model (DEM) elevation and standard deviation data for the Amazon Basin. SRTM30 is a near-global digital elevation model (DEM) comprising a combination of data from the Shuttle Radar Topography Mission (SRTM), flown in February, 2000, and the earlier U.S. Geological Survey's GTOPO30 data set. The SRTM30 resolution is 30 arc-sec or about 1 km. In processing the SRTM data, to combine with GTOPO30, the data were resampled from 3 arc-sec to 30 arc-sec. Provided here are the mean elevation and the standard deviation (STD) of the data points used in the averaging. The STD is thus an indication of topographic roughness useful in some applications. There are two GeoTIFF (.tif) files with this data set.
ABSTRACT: This data set provides a subset of the SRTM30 Digital Elevation Model (DEM) elevation and standard deviation data for the Amazon Basin. SRTM30 is a near-global digital elevation model (DEM) comprising a combination of data from the Shuttle Radar Topography Mission (SRTM), flown in February, 2000, and the earlier U.S. Geological Survey's GTOPO30 data set. The SRTM30 resolution is 30 arc-sec or about 1 km. In processing the SRTM data, to combine with GTOPO30, the data were resampled from 3 arc-sec to 30 arc-sec. Provided here are the mean elevation and the standard deviation (STD) of the data points used in the averaging. The STD is thus an indication of topographic roughness useful in some applications. There are two GeoTIFF (.tif) files with this data set.
This data set contains proportional estimates for the vegetative cover types of woody vegetation, herbaceous vegetation, and bare ground over the Amazon Basin for the period 2000-2001. These products were derived from all seven bands of the Moderate-resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA's Terra satellite. A set of MODIS 32-day composites were used to create the vegetation cover types using the Vegetation Continuous Fields (VCF) (Hansen et al., 2002) approach which shows how much of a land cover such as "forest" or "grassland" exists anywhere on the land surface.  The VCF product may depict areas of heterogeneous land cover better than traditional discrete classification schemes which shows where land cover types are concentrated.The original MODIS products are 500-m spatial resolution and are derived from 2000-2001 data products. The data were resampled to 1-km resolution for the regional study under this project, and provided as 3 separate cover type files in ENVI and GeoTIFF file formats that are provided in six zipped files. These products are registered to the rest of the regional data sets over the Amazon basin. These data are also available for download from the Global Land Cover Facility Website (http://modis.umiacs.umd.edu/).
This data set contains proportional estimates for the vegetative cover types of woody vegetation, herbaceous vegetation, and bare ground over the Amazon Basin for the period 2000-2001. These products were derived from all seven bands of the Moderate-resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA's Terra satellite. A set of MODIS 32-day composites were used to create the vegetation cover types using the Vegetation Continuous Fields (VCF) (Hansen et al., 2002) approach which shows how much of a land cover such as "forest" or "grassland" exists anywhere on the land surface.  The VCF product may depict areas of heterogeneous land cover better than traditional discrete classification schemes which shows where land cover types are concentrated.The original MODIS products are 500-m spatial resolution and are derived from 2000-2001 data products. The data were resampled to 1-km resolution for the regional study under this project, and provided as 3 separate cover type files in ENVI and GeoTIFF file formats that are provided in six zipped files. These products are registered to the rest of the regional data sets over the Amazon basin. These data are also available for download from the Global Land Cover Facility Website (http://modis.umiacs.umd.edu/).
ABSTRACT: This data set contains proportional estimates for the vegetative cover types of woody vegetation, herbaceous vegetation, and bare ground over the Amazon Basin for the period 2000-2001. These products were derived from all seven bands of the Moderate-resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA's Terra satellite. A set of MODIS 32-day composites were used to create the vegetation cover types using the Vegetation Continuous Fields (VCF) (Hansen et al., 2002) approach which shows how much of a land cover such as "forest" or "grassland" exists anywhere on the land surface.  The VCF product may depict areas of heterogeneous land cover better than traditional discrete classification schemes which shows where land cover types are concentrated.The original MODIS products are 500-m spatial resolution and are derived from 2000-2001 data products. The data were resampled to 1-km resolution for the regional study under this project, and provided as 3 separate cover type files in ENVI and GeoTIFF file formats that are provided in six zipped files. These products are registered to the rest of the regional data sets over the Amazon basin. These data are also available for download from the Global Land Cover Facility Website (http://modis.umiacs.umd.edu/).
This image was collected by the Hyperion sensor on 10-July-2004 at 13:16:16 GMT.  It was calibrated to apparent surface reflectance using the ACORN atmospheric model.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) (http://eo1.usgs.gov/sensors.php).  Through these large number of spectral bands, complex land ecosystems can be imaged and accurately classified.Data from the EO-1 Hyperion imaging spectrometer may greatly increase our ability to estimate the presence and structural attributes of selective logging in the Amazon Basin using four biogeophysical indicators not yet derived simultaneously from any satellite sensor: 1) green canopy leaf area index; 2) degree of shadowing; 3) presence of exposed soil and; 4) non-photosynthetic vegetation material. Airborne, field and modeling studies have shown that the optical reflectance continuum (400-2500 nm) contains sufficient information to derive estimates of each of these indicators. Our ongoing studies in the eastern Amazon basin also suggest that these four indicators are sensitive to logging intensity. Satellite-based estimates of these indicators should provide a means to quantify both the presence and degree of structural disturbance caused by various logging regimes.
This image was collected by the Hyperion sensor on 10-July-2004 at 13:16:16 GMT.  It was calibrated to apparent surface reflectance using the ACORN atmospheric model.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) (http://eo1.usgs.gov/sensors.php).  Through these large number of spectral bands, complex land ecosystems can be imaged and accurately classified.Data from the EO-1 Hyperion imaging spectrometer may greatly increase our ability to estimate the presence and structural attributes of selective logging in the Amazon Basin using four biogeophysical indicators not yet derived simultaneously from any satellite sensor: 1) green canopy leaf area index; 2) degree of shadowing; 3) presence of exposed soil and; 4) non-photosynthetic vegetation material. Airborne, field and modeling studies have shown that the optical reflectance continuum (400-2500 nm) contains sufficient information to derive estimates of each of these indicators. Our ongoing studies in the eastern Amazon basin also suggest that these four indicators are sensitive to logging intensity. Satellite-based estimates of these indicators should provide a means to quantify both the presence and degree of structural disturbance caused by various logging regimes.
ABSTRACT: This image was collected by the Hyperion sensor on 10-July-2004 at 13:16:16 GMT.  It was calibrated to apparent surface reflectance using the ACORN atmospheric model.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) (http://eo1.usgs.gov/sensors.php).  Through these large number of spectral bands, complex land ecosystems can be imaged and accurately classified.Data from the EO-1 Hyperion imaging spectrometer may greatly increase our ability to estimate the presence and structural attributes of selective logging in the Amazon Basin using four biogeophysical indicators not yet derived simultaneously from any satellite sensor: 1) green canopy leaf area index; 2) degree of shadowing; 3) presence of exposed soil and; 4) non-photosynthetic vegetation material. Airborne, field and modeling studies have shown that the optical reflectance continuum (400-2500 nm) contains sufficient information to derive estimates of each of these indicators. Our ongoing studies in the eastern Amazon basin also suggest that these four indicators are sensitive to logging intensity. Satellite-based estimates of these indicators should provide a means to quantify both the presence and degree of structural disturbance caused by various logging regimes.
This data set provides Landsat Enhanced Thematic Mapper Plus (ETM+) imagery, derived classified land cover products, and cloud-water masks for selected Brazilian states (Acre, Amapa, Amazonas, Maranhao, Mato Grosso, Para, Rondonia, and Roraima) for the years 1999-2002. The Landsat ETM+ images were processed to derive fractional land cover types (photosynthetic vegetation [PV], non-photosynthetic vegetation [NPV], and bare substrate) by application of the Carnegie Landsat Analysis System (CLAS) methodology (Asner et al., 2005). CLAS utilizes a quantitative determination of fractional land cover at the subpixel scale (e.g., within each Landsat 30 x 30 m pixel). The resulting images display estimates of subpixel land cover fraction values including free of clouds, cloud shadows, and water. There are 584 *.zip files in this data set which when expanded, contain a total of 1,717 (*.tif) images files (GeoTiff Standard format).
This data set provides Landsat Enhanced Thematic Mapper Plus (ETM+) imagery, derived classified land cover products, and cloud-water masks for selected Brazilian states (Acre, Amapa, Amazonas, Maranhao, Mato Grosso, Para, Rondonia, and Roraima) for the years 1999-2002. The Landsat ETM+ images were processed to derive fractional land cover types (photosynthetic vegetation [PV], non-photosynthetic vegetation [NPV], and bare substrate) by application of the Carnegie Landsat Analysis System (CLAS) methodology (Asner et al., 2005). CLAS utilizes a quantitative determination of fractional land cover at the subpixel scale (e.g., within each Landsat 30 x 30 m pixel). The resulting images display estimates of subpixel land cover fraction values including free of clouds, cloud shadows, and water. There are 584 *.zip files in this data set which when expanded, contain a total of 1,717 (*.tif) images files (GeoTiff Standard format).
ABSTRACT: This data set provides Landsat Enhanced Thematic Mapper Plus (ETM+) imagery, derived classified land cover products, and cloud-water masks for selected Brazilian states (Acre, Amapa, Amazonas, Maranhao, Mato Grosso, Para, Rondonia, and Roraima) for the years 1999-2002. The Landsat ETM+ images were processed to derive fractional land cover types (photosynthetic vegetation [PV], non-photosynthetic vegetation [NPV], and bare substrate) by application of the Carnegie Landsat Analysis System (CLAS) methodology (Asner et al., 2005). CLAS utilizes a quantitative determination of fractional land cover at the subpixel scale (e.g., within each Landsat 30 x 30 m pixel). The resulting images display estimates of subpixel land cover fraction values including free of clouds, cloud shadows, and water. There are 584 *.zip files in this data set which when expanded, contain a total of 1,717 (*.tif) images files (GeoTiff Standard format).
This data set provides the results of analyses of Landsat Enhanced Thematic Mapper Plus (ETM+) images for selective logging activity in the Brazilian states of Para, Mato Gross, Rondonia, Roraima, and Acre over the years 1999 through 2001. Images were analyzed using the Carnegie Landsat Analysis System (CLAS) to detect and to quantify the amount of damage due to selective logging in the major timber-production states of the Brazilian Amazon. This approach provided automated image analysis using atmospheric modeling for detection of forest canopy openings, surface debris, and bare soil exposed by forest disturbances; and pattern-recognition techniques. CLAS provides detailed measurements of forest-canopy damage at a spatial resolution of 30 x 30m. Fifteen GeoTiff format files are included -- one for each of the three years from 1999-2001 for each of the five states. Each GeoTiff is a single band image where each pixel represents if logging activity was or was not detected. A zero (0) value indicates that no logging was detected, while a value of one (1) indicates that damage from logging was detected. The 15 GeoTiff (*.tif) files have been compressed into one *.zip file.
This data set provides the results of analyses of Landsat Enhanced Thematic Mapper Plus (ETM+) images for selective logging activity in the Brazilian states of Para, Mato Gross, Rondonia, Roraima, and Acre over the years 1999 through 2001. Images were analyzed using the Carnegie Landsat Analysis System (CLAS) to detect and to quantify the amount of damage due to selective logging in the major timber-production states of the Brazilian Amazon. This approach provided automated image analysis using atmospheric modeling for detection of forest canopy openings, surface debris, and bare soil exposed by forest disturbances; and pattern-recognition techniques. CLAS provides detailed measurements of forest-canopy damage at a spatial resolution of 30 x 30m. Fifteen GeoTiff format files are included -- one for each of the three years from 1999-2001 for each of the five states. Each GeoTiff is a single band image where each pixel represents if logging activity was or was not detected. A zero (0) value indicates that no logging was detected, while a value of one (1) indicates that damage from logging was detected. The 15 GeoTiff (*.tif) files have been compressed into one *.zip file.
ABSTRACT: This data set provides the results of analyses of Landsat Enhanced Thematic Mapper Plus (ETM+) images for selective logging activity in the Brazilian states of Para, Mato Gross, Rondonia, Roraima, and Acre over the years 1999 through 2001. Images were analyzed using the Carnegie Landsat Analysis System (CLAS) to detect and to quantify the amount of damage due to selective logging in the major timber-production states of the Brazilian Amazon. This approach provided automated image analysis using atmospheric modeling for detection of forest canopy openings, surface debris, and bare soil exposed by forest disturbances; and pattern-recognition techniques. CLAS provides detailed measurements of forest-canopy damage at a spatial resolution of 30 x 30m. Fifteen GeoTiff format files are included -- one for each of the three years from 1999-2001 for each of the five states. Each GeoTiff is a single band image where each pixel represents if logging activity was or was not detected. A zero (0) value indicates that no logging was detected, while a value of one (1) indicates that damage from logging was detected. The 15 GeoTiff (*.tif) files have been compressed into one *.zip file.
This data set provides land cover classifications for Mato Grosso, Brazil, for the years 2000-2001 and 2003-2004. The classifications were derived from annual vegetation phenology information from a time series of Collection 4, 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI), and the Enhanced Vegetation Index (EVI) vegetation data, at 250-m resolution. A decision tree classifier was trained using field observations and Landsat TM data of land cover from 2003-2004 to identify seven land-cover classes. The classifier was applied to the 2000-2001 and 2003-2004 MODIS ENVI and EVI data.There are two GeoTIFF (.tif) files with this data set.
This data set provides land cover classifications for Mato Grosso, Brazil, for the years 2000-2001 and 2003-2004. The classifications were derived from annual vegetation phenology information from a time series of Collection 4, 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI), and the Enhanced Vegetation Index (EVI) vegetation data, at 250-m resolution. A decision tree classifier was trained using field observations and Landsat TM data of land cover from 2003-2004 to identify seven land-cover classes. The classifier was applied to the 2000-2001 and 2003-2004 MODIS ENVI and EVI data.There are two GeoTIFF (.tif) files with this data set.
ABSTRACT: This data set provides land cover classifications for Mato Grosso, Brazil, for the years 2000-2001 and 2003-2004. The classifications were derived from annual vegetation phenology information from a time series of Collection 4, 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI), and the Enhanced Vegetation Index (EVI) vegetation data, at 250-m resolution. A decision tree classifier was trained using field observations and Landsat TM data of land cover from 2003-2004 to identify seven land-cover classes. The classifier was applied to the 2000-2001 and 2003-2004 MODIS ENVI and EVI data.There are two GeoTIFF (.tif) files with this data set.
This data set provides (1) areal estimates of deforestation events (>25 ha) that were identified from 2001-2004 in Mato Grosso by the Brazilian Institute for Space Research (INPE) as part of the Program for the Estimation of Deforestation in the Brazilian Amazon (PRODES) and (2) the classification of the post-deforestation land use as either cropland, cattle pasture, or not in production (deforested areas that were never fully cleared or returned immediately to secondary forest) in the years after the large deforestation events from 2002-2005. Data are provided in ESRI shapefile format. There are five compressed (*.zip) data files with this data set. Each shapefile represents one year of post-deforestation land use. Land use in the years following deforestation was estimated using annual time series of MODIS NDVI (normalized difference vegetation index) and EVI (enhanced vegetation index). Metrics of vegetation phenology derived annual time series of MODIS NDVI and EVI data were analyzed using a decision-tree classifier to characterize the major cover type in each area of new deforestation. Post-deforestation land use for each large deforestation event was classified based on the classification of MODIS phenology metrics for all years following deforestation during 2002-2005.
This data set provides (1) areal estimates of deforestation events (>25 ha) that were identified from 2001-2004 in Mato Grosso by the Brazilian Institute for Space Research (INPE) as part of the Program for the Estimation of Deforestation in the Brazilian Amazon (PRODES) and (2) the classification of the post-deforestation land use as either cropland, cattle pasture, or not in production (deforested areas that were never fully cleared or returned immediately to secondary forest) in the years after the large deforestation events from 2002-2005. Data are provided in ESRI shapefile format. There are five compressed (*.zip) data files with this data set. Each shapefile represents one year of post-deforestation land use. Land use in the years following deforestation was estimated using annual time series of MODIS NDVI (normalized difference vegetation index) and EVI (enhanced vegetation index). Metrics of vegetation phenology derived annual time series of MODIS NDVI and EVI data were analyzed using a decision-tree classifier to characterize the major cover type in each area of new deforestation. Post-deforestation land use for each large deforestation event was classified based on the classification of MODIS phenology metrics for all years following deforestation during 2002-2005.
ABSTRACT: This data set provides (1) areal estimates of deforestation events (>25 ha) that were identified from 2001-2004 in Mato Grosso by the Brazilian Institute for Space Research (INPE) as part of the Program for the Estimation of Deforestation in the Brazilian Amazon (PRODES) and (2) the classification of the post-deforestation land use as either cropland, cattle pasture, or not in production (deforested areas that were never fully cleared or returned immediately to secondary forest) in the years after the large deforestation events from 2002-2005. Data are provided in ESRI shapefile format. There are five compressed (*.zip) data files with this data set. Each shapefile represents one year of post-deforestation land use. Land use in the years following deforestation was estimated using annual time series of MODIS NDVI (normalized difference vegetation index) and EVI (enhanced vegetation index). Metrics of vegetation phenology derived annual time series of MODIS NDVI and EVI data were analyzed using a decision-tree classifier to characterize the major cover type in each area of new deforestation. Post-deforestation land use for each large deforestation event was classified based on the classification of MODIS phenology metrics for all years following deforestation during 2002-2005.
This data set contains proportional estimates for the vegetative cover types of tree cover, herbaceous vegetation, and bare ground over South America for the period 2000-2001. These products were derived from all seven bands of the Moderate-resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA's Terra satellite. A set of 500-m MOD09A1 Surface Reflectance 8-day minimum blue reflectance composites were used as input data. To reduce the presence of cloud shadows, The data were converted to 40-day composites using a second darkest albedo (sum of blue, green, and red bands), and the Vegetation Continuous Fields (VCF) algorithmn  was utilized (Hansen et al., 2002). The VCF shows how much of a land cover such as forest or grassland exists anywhere on the land surface. The VCF product may depict areas of heterogeneous land cover better than traditional discrete classification schemes which shows where land cover types are concentrated. There are three images provided in GeoTIFF format.
This data set contains proportional estimates for the vegetative cover types of tree cover, herbaceous vegetation, and bare ground over South America for the period 2000-2001. These products were derived from all seven bands of the Moderate-resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA's Terra satellite. A set of 500-m MOD09A1 Surface Reflectance 8-day minimum blue reflectance composites were used as input data. To reduce the presence of cloud shadows, The data were converted to 40-day composites using a second darkest albedo (sum of blue, green, and red bands), and the Vegetation Continuous Fields (VCF) algorithmn  was utilized (Hansen et al., 2002). The VCF shows how much of a land cover such as forest or grassland exists anywhere on the land surface. The VCF product may depict areas of heterogeneous land cover better than traditional discrete classification schemes which shows where land cover types are concentrated. There are three images provided in GeoTIFF format.
ABSTRACT: This data set contains proportional estimates for the vegetative cover types of tree cover, herbaceous vegetation, and bare ground over South America for the period 2000-2001. These products were derived from all seven bands of the Moderate-resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA's Terra satellite. A set of 500-m MOD09A1 Surface Reflectance 8-day minimum blue reflectance composites were used as input data. To reduce the presence of cloud shadows, The data were converted to 40-day composites using a second darkest albedo (sum of blue, green, and red bands), and the Vegetation Continuous Fields (VCF) algorithmn  was utilized (Hansen et al., 2002). The VCF shows how much of a land cover such as forest or grassland exists anywhere on the land surface. The VCF product may depict areas of heterogeneous land cover better than traditional discrete classification schemes which shows where land cover types are concentrated. There are three images provided in GeoTIFF format.
This data set contains data associated with MODIS fire maps generated using two different algorithms and compared against fire maps produced by ASTER. These data relate to a paper (Morisette et al., 2005) that describes the use of high spatial resolution ASTER data to evaluate the characteristics of two fire detection algorithms, both applied to MODIS-Terra data and both operationally producing publicly available fire locations. The two algorithms are NASA's operational Earth Observing System MODIS fire detection product and Brazil's National Institute for Space Research (INPE) algorithm. These data are the ASCII files used in the logistic regression and error matrices presented in the paper.
This data set contains data associated with MODIS fire maps generated using two different algorithms and compared against fire maps produced by ASTER. These data relate to a paper (Morisette et al., 2005) that describes the use of high spatial resolution ASTER data to evaluate the characteristics of two fire detection algorithms, both applied to MODIS-Terra data and both operationally producing publicly available fire locations. The two algorithms are NASA's operational Earth Observing System MODIS fire detection product and Brazil's National Institute for Space Research (INPE) algorithm. These data are the ASCII files used in the logistic regression and error matrices presented in the paper.
ABSTRACT: This data set contains data associated with MODIS fire maps generated using two different algorithms and compared against fire maps produced by ASTER. These data relate to a paper (Morisette et al., 2005) that describes the use of high spatial resolution ASTER data to evaluate the characteristics of two fire detection algorithms, both applied to MODIS-Terra data and both operationally producing publicly available fire locations. The two algorithms are NASA's operational Earth Observing System MODIS fire detection product and Brazil's National Institute for Space Research (INPE) algorithm. These data are the ASCII files used in the logistic regression and error matrices presented in the paper.
Satellite fire detection was determined from two sensors, the Advanced Very High Resolution Radiometer (AVHRR) on NOAA-12 and the Moderate Resolution Imaging Spectroradiometer (MODIS) on both the Terra and Aqua platforms, for 2001- 2003 to characterize fire activity in Brazil, giving special emphasis to the Amazon region. Active fire data for AVHRR/NOAA-12 was produced using a fixed threshold fire detection technique based on the algorithm developed by the Centro de Previsao do Tempo e Estudos Climaticos (CPTEC/INPE) (Setzer and Pereira, 1991; Setzer et al., 1994; Setzer and Malingreau, 1996). Active fire data for MODIS/Terra and MODIS/Aqua was produced using a contextual fire detection technique based on NASA-University of Maryland algorithm (Justice et al., 2003; Giglio et al.2003).Resulting fire counts were compared for major biomes of Brazil (Figure 1), the nine states of the Legal Amazon (e.g., Tocantins, Figure 2), and two important road corridors in the Amazon region (Figure 3). In evaluating the daily fire counts, there is a dependence on variations in satellite viewing geometry, overpass time, atmospheric conditions, and fire characteristics (Schroeder et al., 2005). The data provided are the coordinates of daily active vegetation fires in Brazil for 2001 through 2003 at 1km resolution for both AVHRR and MODIS sensors.  Data are provided in both Arcview (shape file format) and ASCII comma separated file formats. Vector files for the major biomes of Brazil, the nine states of the Legal Amazon, and two important road corridors in the Amazon region are also included.
Satellite fire detection was determined from two sensors, the Advanced Very High Resolution Radiometer (AVHRR) on NOAA-12 and the Moderate Resolution Imaging Spectroradiometer (MODIS) on both the Terra and Aqua platforms, for 2001- 2003 to characterize fire activity in Brazil, giving special emphasis to the Amazon region. Active fire data for AVHRR/NOAA-12 was produced using a fixed threshold fire detection technique based on the algorithm developed by the Centro de Previsao do Tempo e Estudos Climaticos (CPTEC/INPE) (Setzer and Pereira, 1991; Setzer et al., 1994; Setzer and Malingreau, 1996). Active fire data for MODIS/Terra and MODIS/Aqua was produced using a contextual fire detection technique based on NASA-University of Maryland algorithm (Justice et al., 2003; Giglio et al.2003).Resulting fire counts were compared for major biomes of Brazil (Figure 1), the nine states of the Legal Amazon (e.g., Tocantins, Figure 2), and two important road corridors in the Amazon region (Figure 3). In evaluating the daily fire counts, there is a dependence on variations in satellite viewing geometry, overpass time, atmospheric conditions, and fire characteristics (Schroeder et al., 2005). The data provided are the coordinates of daily active vegetation fires in Brazil for 2001 through 2003 at 1km resolution for both AVHRR and MODIS sensors.  Data are provided in both Arcview (shape file format) and ASCII comma separated file formats. Vector files for the major biomes of Brazil, the nine states of the Legal Amazon, and two important road corridors in the Amazon region are also included.
ABSTRACT: Satellite fire detection was determined from two sensors, the Advanced Very High Resolution Radiometer (AVHRR) on NOAA-12 and the Moderate Resolution Imaging Spectroradiometer (MODIS) on both the Terra and Aqua platforms, for 2001- 2003 to characterize fire activity in Brazil, giving special emphasis to the Amazon region. Active fire data for AVHRR/NOAA-12 was produced using a fixed threshold fire detection technique based on the algorithm developed by the Centro de Previsao do Tempo e Estudos Climaticos (CPTEC/INPE) (Setzer and Pereira, 1991; Setzer et al., 1994; Setzer and Malingreau, 1996). Active fire data for MODIS/Terra and MODIS/Aqua was produced using a contextual fire detection technique based on NASA-University of Maryland algorithm (Justice et al., 2003; Giglio et al.2003).Resulting fire counts were compared for major biomes of Brazil (Figure 1), the nine states of the Legal Amazon (e.g., Tocantins, Figure 2), and two important road corridors in the Amazon region (Figure 3). In evaluating the daily fire counts, there is a dependence on variations in satellite viewing geometry, overpass time, atmospheric conditions, and fire characteristics (Schroeder et al., 2005). The data provided are the coordinates of daily active vegetation fires in Brazil for 2001 through 2003 at 1km resolution for both AVHRR and MODIS sensors.  Data are provided in both Arcview (shape file format) and ASCII comma separated file formats. Vector files for the major biomes of Brazil, the nine states of the Legal Amazon, and two important road corridors in the Amazon region are also included.
This data set contains ASTER sensor Level-1B satellite imagery over controlled burns in the State of Roraima in Northern Brazil on January 19 and 28, 2003, plus simultaneously collected soil and near-surface air temperature profiles on January 28th. The ASTER imagery is provided in 14 zipped files containing HDF-EOS files (*.hdf and *.met file pairs), while the sample-based temperature profiles, one for the air the other for the ground, are provided as comma separated ASCII files.
This data set contains ASTER sensor Level-1B satellite imagery over controlled burns in the State of Roraima in Northern Brazil on January 19 and 28, 2003, plus simultaneously collected soil and near-surface air temperature profiles on January 28th. The ASTER imagery is provided in 14 zipped files containing HDF-EOS files (*.hdf and *.met file pairs), while the sample-based temperature profiles, one for the air the other for the ground, are provided as comma separated ASCII files.
ABSTRACT: This data set contains ASTER sensor Level-1B satellite imagery over controlled burns in the State of Roraima in Northern Brazil on January 19 and 28, 2003, plus simultaneously collected soil and near-surface air temperature profiles on January 28th. The ASTER imagery is provided in 14 zipped files containing HDF-EOS files (*.hdf and *.met file pairs), while the sample-based temperature profiles, one for the air the other for the ground, are provided as comma separated ASCII files.
This data set provides the number of hot spots detected across the legal Amazon Basin at 5- km resolution by the AVHRR (Advanced Very High Resolution Radiometer) on NOAA 12, 14, 15, 16, 17, and 18 satellites for the entirety of 2001 (January 1 - December 31).  Only hot spots detected at night are included. This data is useful for modeling fire events and evaluating human impacts on the Amazon Basin using fire as an indicator of anthropogenic disturbance (Arima et al., 2007).
This data set provides the number of hot spots detected across the legal Amazon Basin at 5- km resolution by the AVHRR (Advanced Very High Resolution Radiometer) on NOAA 12, 14, 15, 16, 17, and 18 satellites for the entirety of 2001 (January 1 - December 31).  Only hot spots detected at night are included. This data is useful for modeling fire events and evaluating human impacts on the Amazon Basin using fire as an indicator of anthropogenic disturbance (Arima et al., 2007).
ABSTRACT: This data set provides the number of hot spots detected across the legal Amazon Basin at 5- km resolution by the AVHRR (Advanced Very High Resolution Radiometer) on NOAA 12, 14, 15, 16, 17, and 18 satellites for the entirety of 2001 (January 1 - December 31).  Only hot spots detected at night are included. This data is useful for modeling fire events and evaluating human impacts on the Amazon Basin using fire as an indicator of anthropogenic disturbance (Arima et al., 2007).
This data set contains a shapefile of a digitized map of the land parcel information of the original properties of the Uruara colonization site, Para, Brazil, acquired from the Instituto de Colonizacao e Reforma Agraria, or the Colonization and Agrarian Reform Institute (INCRA). The Uruara settlement geometry was initially designed by INCRA, and consists of mostly 100 hectare lots (400 x 2500 meters, and 500 x 2000 meters), running north and south of the Trans-Amazon Highway, as a fine network of small, narrow rectangles. The other parcels in the landscape are the so-called glebas that range up to 3,000 hectares. The map was in the form of a paper map without a projection (a spherical geographic coordinate system) in the South American 1969 datum (SAD 1969). This paper map was digitized in Environmental Science Research Institute (ESRI) ArcInfo 8.1 using a digitizing table, and the digital cadastral data were geo-referenced and projected to match the Universal Transverse Mercator projection (Zone 22 South, World Geodetic System 1984 datum) of Landsat imagery (Landsat.org). There is one compressed (*.zip) file with this data set.
This data set contains a shapefile of a digitized map of the land parcel information of the original properties of the Uruara colonization site, Para, Brazil, acquired from the Instituto de Colonizacao e Reforma Agraria, or the Colonization and Agrarian Reform Institute (INCRA). The Uruara settlement geometry was initially designed by INCRA, and consists of mostly 100 hectare lots (400 x 2500 meters, and 500 x 2000 meters), running north and south of the Trans-Amazon Highway, as a fine network of small, narrow rectangles. The other parcels in the landscape are the so-called glebas that range up to 3,000 hectares. The map was in the form of a paper map without a projection (a spherical geographic coordinate system) in the South American 1969 datum (SAD 1969). This paper map was digitized in Environmental Science Research Institute (ESRI) ArcInfo 8.1 using a digitizing table, and the digital cadastral data were geo-referenced and projected to match the Universal Transverse Mercator projection (Zone 22 South, World Geodetic System 1984 datum) of Landsat imagery (Landsat.org). There is one compressed (*.zip) file with this data set.
ABSTRACT: This data set contains a shapefile of a digitized map of the land parcel information of the original properties of the Uruara colonization site, Para, Brazil, acquired from the Instituto de Colonizacao e Reforma Agraria, or the Colonization and Agrarian Reform Institute (INCRA). The Uruara settlement geometry was initially designed by INCRA, and consists of mostly 100 hectare lots (400 x 2500 meters, and 500 x 2000 meters), running north and south of the Trans-Amazon Highway, as a fine network of small, narrow rectangles. The other parcels in the landscape are the so-called glebas that range up to 3,000 hectares. The map was in the form of a paper map without a projection (a spherical geographic coordinate system) in the South American 1969 datum (SAD 1969). This paper map was digitized in Environmental Science Research Institute (ESRI) ArcInfo 8.1 using a digitizing table, and the digital cadastral data were geo-referenced and projected to match the Universal Transverse Mercator projection (Zone 22 South, World Geodetic System 1984 datum) of Landsat imagery (Landsat.org). There is one compressed (*.zip) file with this data set.
This data set contains forest cover information for 2001 for all of South America. The data were collected by the MODIS sensor onboard the TERRA platform and released by the MODIS team as an image showing percent canopy cover. This information was then reclassified so that all pixels with a percent canopy cover greater than 40% (40% after the 1973 UNESCO standard) were classified as forest (a value of 1), and all other pixels were classified as non-forest (a value of 2). Water features were given a value of 3. This data has a pixel resolution of 500 meters and is unprojected with the WGS-1984 datum (Hansen et al. 2006). There is one GeoTIFF data file for this data set.
This data set contains forest cover information for 2001 for all of South America. The data were collected by the MODIS sensor onboard the TERRA platform and released by the MODIS team as an image showing percent canopy cover. This information was then reclassified so that all pixels with a percent canopy cover greater than 40% (40% after the 1973 UNESCO standard) were classified as forest (a value of 1), and all other pixels were classified as non-forest (a value of 2). Water features were given a value of 3. This data has a pixel resolution of 500 meters and is unprojected with the WGS-1984 datum (Hansen et al. 2006). There is one GeoTIFF data file for this data set.
ABSTRACT: This data set contains forest cover information for 2001 for all of South America. The data were collected by the MODIS sensor onboard the TERRA platform and released by the MODIS team as an image showing percent canopy cover. This information was then reclassified so that all pixels with a percent canopy cover greater than 40% (40% after the 1973 UNESCO standard) were classified as forest (a value of 1), and all other pixels were classified as non-forest (a value of 2). Water features were given a value of 3. This data has a pixel resolution of 500 meters and is unprojected with the WGS-1984 datum (Hansen et al. 2006). There is one GeoTIFF data file for this data set.
This data set contains ESRI shapefiles of historical roads (basin-wide federal and state roads) in nine Brazilian states for the Legal Amazon: Amazonas, Para, Acre, Rondonia, Roraima, Tocantins, Amapa, Matto Grosso, and Maranhao. There are 48 compressed (*.zip) files for the years 1968, 1975, 1981, 1985, 1987, and 1993 in GCS South American 1969 projection.
This data set contains ESRI shapefiles of historical roads (basin-wide federal and state roads) in nine Brazilian states for the Legal Amazon: Amazonas, Para, Acre, Rondonia, Roraima, Tocantins, Amapa, Matto Grosso, and Maranhao. There are 48 compressed (*.zip) files for the years 1968, 1975, 1981, 1985, 1987, and 1993 in GCS South American 1969 projection.
ABSTRACT: This data set contains ESRI shapefiles of historical roads (basin-wide federal and state roads) in nine Brazilian states for the Legal Amazon: Amazonas, Para, Acre, Rondonia, Roraima, Tocantins, Amapa, Matto Grosso, and Maranhao. There are 48 compressed (*.zip) files for the years 1968, 1975, 1981, 1985, 1987, and 1993 in GCS South American 1969 projection.
This data set provides course land cover classifications derived from Landsat TM images for 1986, 1988, and 1991 for the area surrounding the municipality of Uruara, Para, Brazil. Five land cover classes (Water, Clouds/Shadow, Forest, Not Forest, and Background) were derived (Aldrich et al. 2006). The Land Cover is in a compressed (*.zip) GeoTIFF file for each year.
This data set provides course land cover classifications derived from Landsat TM images for 1986, 1988, and 1991 for the area surrounding the municipality of Uruara, Para, Brazil. Five land cover classes (Water, Clouds/Shadow, Forest, Not Forest, and Background) were derived (Aldrich et al. 2006). The Land Cover is in a compressed (*.zip) GeoTIFF file for each year.
ABSTRACT: This data set provides course land cover classifications derived from Landsat TM images for 1986, 1988, and 1991 for the area surrounding the municipality of Uruara, Para, Brazil. Five land cover classes (Water, Clouds/Shadow, Forest, Not Forest, and Background) were derived (Aldrich et al. 2006). The Land Cover is in a compressed (*.zip) GeoTIFF file for each year.
This data set contains a 1999 Landsat ETM+ mosaic image land of cover classification showing forested and deforestation areas in Uruara, Para, Brazil. This image may be overlain with the cadastral property map of the same area (see related data set LBA-ECO LC-24 Cadastral Property Map of Uruara, Para, Brazil: ca.1975). This data sets contains a single geotiff image distributed as deforested_large.zip.
This data set contains a 1999 Landsat ETM+ mosaic image land of cover classification showing forested and deforestation areas in Uruara, Para, Brazil. This image may be overlain with the cadastral property map of the same area (see related data set LBA-ECO LC-24 Cadastral Property Map of Uruara, Para, Brazil: ca.1975). This data sets contains a single geotiff image distributed as deforested_large.zip.
ABSTRACT: This data set contains a 1999 Landsat ETM+ mosaic image land of cover classification showing forested and deforestation areas in Uruara, Para, Brazil. This image may be overlain with the cadastral property map of the same area (see related data set LBA-ECO LC-24 Cadastral Property Map of Uruara, Para, Brazil: ca.1975). This data sets contains a single geotiff image distributed as deforested_large.zip.
This data set is a five-class land cover for Southern Para for the years 1984 (Landsat MSS), 1988 (Landsat TM), 1996, and 2003 (Landsat ETM+). The final classification shows five classes derived using visual comparison (Water, Clouds/Shadow, Forest, Not Forest, Background). These data were used in 2007 to illustrate the nature of deforestation in Southern Para, Brazil over the past twenty years (Simmons et al. 2007). There are four annual GeoTIFF files distributed with this data set. Each GeoTIFF file and accompanying *.tfw file have been compressed into a single *.zip file.
This data set is a five-class land cover for Southern Para for the years 1984 (Landsat MSS), 1988 (Landsat TM), 1996, and 2003 (Landsat ETM+). The final classification shows five classes derived using visual comparison (Water, Clouds/Shadow, Forest, Not Forest, Background). These data were used in 2007 to illustrate the nature of deforestation in Southern Para, Brazil over the past twenty years (Simmons et al. 2007). There are four annual GeoTIFF files distributed with this data set. Each GeoTIFF file and accompanying *.tfw file have been compressed into a single *.zip file.
ABSTRACT: This data set is a five-class land cover for Southern Para for the years 1984 (Landsat MSS), 1988 (Landsat TM), 1996, and 2003 (Landsat ETM+). The final classification shows five classes derived using visual comparison (Water, Clouds/Shadow, Forest, Not Forest, Background). These data were used in 2007 to illustrate the nature of deforestation in Southern Para, Brazil over the past twenty years (Simmons et al. 2007). There are four annual GeoTIFF files distributed with this data set. Each GeoTIFF file and accompanying *.tfw file have been compressed into a single *.zip file.
This model product provides the Fortran source code and input data for the Simple Tropical Ecosystem Model (SITE). SITE is a simplified point model of vegetation dynamics that uses an integration interval of one hour to estimate the fluxes of CO2, water, and energy. Model forcing data are hourly meteorological parameters. SITE is a simplified model of vegetation dynamics for tropical ecosystems developed by Santos and Costa (2004).Model input data measurements of temperature, wind velocity, precipitation, latent heat, sensible heat, downward incident solar flux, and downward incident infrared flux were collected at the km 67 Tapajos National Forest site, Para, Brazil, from 2002 to 2003.SITE is structured with a canopy layer and two soil layers, and incorporates the following processes:*infrared radiation balance in the canopy and balance of solar radiation*aerodynamic processes*plant physiology*transpiration*balance of water intercepted by the canopy*transport of mass and energy fluxes*soil heat flux and soil moisture*carbon balance There are five files provided with this data set: the Fortran source code (version 1.1-0d), one file for the main program that declares variables and input parameters, one file that initializes vegetation parameters, one file used to compile the SITE model, and the km 67 input data file in comma-delimited (.csv) format. The four SITE files are provided in the compressed file SITE_Model.zip.  One companion file is also provided that  describes the collection and processing of the meteorological and flux measurements at the km 67 Tapajos National Forest site and the use of the data to calibrate SITE.
This model product provides the Fortran source code and input data for the Simple Tropical Ecosystem Model (SITE). SITE is a simplified point model of vegetation dynamics that uses an integration interval of one hour to estimate the fluxes of CO2, water, and energy. Model forcing data are hourly meteorological parameters. SITE is a simplified model of vegetation dynamics for tropical ecosystems developed by Santos and Costa (2004).Model input data measurements of temperature, wind velocity, precipitation, latent heat, sensible heat, downward incident solar flux, and downward incident infrared flux were collected at the km 67 Tapajos National Forest site, Para, Brazil, from 2002 to 2003.SITE is structured with a canopy layer and two soil layers, and incorporates the following processes:*infrared radiation balance in the canopy and balance of solar radiation*aerodynamic processes*plant physiology*transpiration*balance of water intercepted by the canopy*transport of mass and energy fluxes*soil heat flux and soil moisture*carbon balance There are five files provided with this data set: the Fortran source code (version 1.1-0d), one file for the main program that declares variables and input parameters, one file that initializes vegetation parameters, one file used to compile the SITE model, and the km 67 input data file in comma-delimited (.csv) format. The four SITE files are provided in the compressed file SITE_Model.zip.  One companion file is also provided that  describes the collection and processing of the meteorological and flux measurements at the km 67 Tapajos National Forest site and the use of the data to calibrate SITE.
ABSTRACT: This model product provides the Fortran source code and input data for the Simple Tropical Ecosystem Model (SITE). SITE is a simplified point model of vegetation dynamics that uses an integration interval of one hour to estimate the fluxes of CO2, water, and energy. Model forcing data are hourly meteorological parameters. SITE is a simplified model of vegetation dynamics for tropical ecosystems developed by Santos and Costa (2004).Model input data measurements of temperature, wind velocity, precipitation, latent heat, sensible heat, downward incident solar flux, and downward incident infrared flux were collected at the km 67 Tapajos National Forest site, Para, Brazil, from 2002 to 2003.SITE is structured with a canopy layer and two soil layers, and incorporates the following processes:*infrared radiation balance in the canopy and balance of solar radiation*aerodynamic processes*plant physiology*transpiration*balance of water intercepted by the canopy*transport of mass and energy fluxes*soil heat flux and soil moisture*carbon balance There are five files provided with this data set: the Fortran source code (version 1.1-0d), one file for the main program that declares variables and input parameters, one file that initializes vegetation parameters, one file used to compile the SITE model, and the km 67 input data file in comma-delimited (.csv) format. The four SITE files are provided in the compressed file SITE_Model.zip.  One companion file is also provided that  describes the collection and processing of the meteorological and flux measurements at the km 67 Tapajos National Forest site and the use of the data to calibrate SITE.
This data set is an active fire detection product resulting from the application of The Wildfire Automated Biomass Burning Algorithm (WF_ABBA) to Geostationary Environmental Operational Satellite (GOES) imager data for all of South America from 2000 through 2005. GOES imager data are available at 30 minute intervals with a nominal 4 x 4-km resolution. The data provided are the latitude/longitude, brightness temperature, estimates of sub-pixel fire size and temperature, Global Land Cover Characterization (GLCC) ecosystem type, and a pixel-fire flag (0-5, information regarding the probability of a fire or processing characteristics) for each active fire detected by WF_ABBA for a 30 minute imager interval. Spatial area coverage data files are provided as a complement to individual fire detection data files because the area of the latter varied according to the GOES imager scan mode in use. Versions 5.9 and 6.0 WF_ABBA data are provided. Differences between the two versions are assumed to be small though (typically less than 10%). An in-line temporal filter has been added to the algorithm to screen out false alarms associated with noise in the imagery and cloud edge issues in version 6.0. This is especially important for screening false alarms due to reflection off clouds at extreme view angles and at sunrise and sunset.There are nine compressed (*.zip) files with this data set which expand to the filtered ASCII text data files (.filt), and seven coverage files text (.txt).
This data set is an active fire detection product resulting from the application of The Wildfire Automated Biomass Burning Algorithm (WF_ABBA) to Geostationary Environmental Operational Satellite (GOES) imager data for all of South America from 2000 through 2005. GOES imager data are available at 30 minute intervals with a nominal 4 x 4-km resolution. The data provided are the latitude/longitude, brightness temperature, estimates of sub-pixel fire size and temperature, Global Land Cover Characterization (GLCC) ecosystem type, and a pixel-fire flag (0-5, information regarding the probability of a fire or processing characteristics) for each active fire detected by WF_ABBA for a 30 minute imager interval. Spatial area coverage data files are provided as a complement to individual fire detection data files because the area of the latter varied according to the GOES imager scan mode in use. Versions 5.9 and 6.0 WF_ABBA data are provided. Differences between the two versions are assumed to be small though (typically less than 10%). An in-line temporal filter has been added to the algorithm to screen out false alarms associated with noise in the imagery and cloud edge issues in version 6.0. This is especially important for screening false alarms due to reflection off clouds at extreme view angles and at sunrise and sunset.There are nine compressed (*.zip) files with this data set which expand to the filtered ASCII text data files (.filt), and seven coverage files text (.txt).
ABSTRACT: This data set is an active fire detection product resulting from the application of The Wildfire Automated Biomass Burning Algorithm (WF_ABBA) to Geostationary Environmental Operational Satellite (GOES) imager data for all of South America from 2000 through 2005. GOES imager data are available at 30 minute intervals with a nominal 4 x 4-km resolution. The data provided are the latitude/longitude, brightness temperature, estimates of sub-pixel fire size and temperature, Global Land Cover Characterization (GLCC) ecosystem type, and a pixel-fire flag (0-5, information regarding the probability of a fire or processing characteristics) for each active fire detected by WF_ABBA for a 30 minute imager interval. Spatial area coverage data files are provided as a complement to individual fire detection data files because the area of the latter varied according to the GOES imager scan mode in use. Versions 5.9 and 6.0 WF_ABBA data are provided. Differences between the two versions are assumed to be small though (typically less than 10%). An in-line temporal filter has been added to the algorithm to screen out false alarms associated with noise in the imagery and cloud edge issues in version 6.0. This is especially important for screening false alarms due to reflection off clouds at extreme view angles and at sunrise and sunset.There are nine compressed (*.zip) files with this data set which expand to the filtered ASCII text data files (.filt), and seven coverage files text (.txt).
This data set provides active fire detection images and associated summary information derived from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images for various locations in Brazilian Amazonia during 2001-2003. There are two image types: (1) GeoTiff images (masks) of active fire pixels, and (2) GeoTiff images (masks) of clustered active fire pixels where a distinct cluster identification number has been assigned to each individual group of contiguous active fire pixels. There are 122 GeoTiff format files of each type of fire mask; a total of 244 images. The spatial resolution of the fire mask images is 30 meters. ETM+ images were selected based on data quality, availability, as well as on the occurrence of vegetation fires.In addition to the two image types, there are also two types of fire pixel summary information provided in text files: (1) one file of active fire pixel summary information derived from the active fire pixel images, and (2) 122 files of clustered active fire pixel information derived from individual clustered fire pixel masks, each of which correspond to a clustered image.
This data set provides active fire detection images and associated summary information derived from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images for various locations in Brazilian Amazonia during 2001-2003. There are two image types: (1) GeoTiff images (masks) of active fire pixels, and (2) GeoTiff images (masks) of clustered active fire pixels where a distinct cluster identification number has been assigned to each individual group of contiguous active fire pixels. There are 122 GeoTiff format files of each type of fire mask; a total of 244 images. The spatial resolution of the fire mask images is 30 meters. ETM+ images were selected based on data quality, availability, as well as on the occurrence of vegetation fires.In addition to the two image types, there are also two types of fire pixel summary information provided in text files: (1) one file of active fire pixel summary information derived from the active fire pixel images, and (2) 122 files of clustered active fire pixel information derived from individual clustered fire pixel masks, each of which correspond to a clustered image.
ABSTRACT: This data set provides active fire detection images and associated summary information derived from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images for various locations in Brazilian Amazonia during 2001-2003. There are two image types: (1) GeoTiff images (masks) of active fire pixels, and (2) GeoTiff images (masks) of clustered active fire pixels where a distinct cluster identification number has been assigned to each individual group of contiguous active fire pixels. There are 122 GeoTiff format files of each type of fire mask; a total of 244 images. The spatial resolution of the fire mask images is 30 meters. ETM+ images were selected based on data quality, availability, as well as on the occurrence of vegetation fires.In addition to the two image types, there are also two types of fire pixel summary information provided in text files: (1) one file of active fire pixel summary information derived from the active fire pixel images, and (2) 122 files of clustered active fire pixel information derived from individual clustered fire pixel masks, each of which correspond to a clustered image.
This data set contains modeled estimates of carbon flux, biomass, and annual burning emissions across the Brazilian state of Mato Grosso from 2000-2006. The model, DEforestation CArbon Flux (DECAF), was used to provide annual carbon fluxes from large deforestation events (>25 ha) based on post-deforestation land use, and the frequency and duration of active fires during the deforestation process. Carbon fluxes associated with the conversion of Cerrado to mechanized crop production, fires in Cerrado, and managed pasture cover types were also estimated. Model data outputs provided include:  * Estimated aboveground live biomass from DECAF in 2000 and 2004.* Annual biomass burning emissions estimates for 2001-2005 from low, middle, and high emissions scenarios with DECAF. There are 15 GeoTIFF files for annual emissions which represent the carbon emissions per pixel in grams of carbon per m2 (g C m-2). Model data inputs provided include: * Annual burn trajectories for 2001 - 2005, including deforestation, Cerrado land cover conversion, and fires in pasture and Cerrado ecosystems unrelated to agricultural expansion. These data were assembled from three sources: MODIS 500-m burned area maps, annual deforestation based on data from the INPE PRODES program, and the conversion of Cerrado savannah/woodland to cropland estimated from land cover information from MODIS phenology metrics.* Annual land cover data 2001-2004 for the portion of Mato Grosso covered by MODIS phenology metrics, tile h12v10, updated based on annual land cover changes in Amazon forest and Cerrado cover types.* Monthly Normalized Difference Vegetation Index (NDVI) for MODIS tile h12v10 from 10/2000 - 09/2006, based on cloud and gap-filled 16-day NDVI data from MODIS Collection 4 16-day NDVI composites  MOD13 product (Huete et al., 2002).There are six compressed (*.gz) files with this data set.
This data set contains modeled estimates of carbon flux, biomass, and annual burning emissions across the Brazilian state of Mato Grosso from 2000-2006. The model, DEforestation CArbon Flux (DECAF), was used to provide annual carbon fluxes from large deforestation events (>25 ha) based on post-deforestation land use, and the frequency and duration of active fires during the deforestation process. Carbon fluxes associated with the conversion of Cerrado to mechanized crop production, fires in Cerrado, and managed pasture cover types were also estimated. Model data outputs provided include:  * Estimated aboveground live biomass from DECAF in 2000 and 2004.* Annual biomass burning emissions estimates for 2001-2005 from low, middle, and high emissions scenarios with DECAF. There are 15 GeoTIFF files for annual emissions which represent the carbon emissions per pixel in grams of carbon per m2 (g C m-2). Model data inputs provided include: * Annual burn trajectories for 2001 - 2005, including deforestation, Cerrado land cover conversion, and fires in pasture and Cerrado ecosystems unrelated to agricultural expansion. These data were assembled from three sources: MODIS 500-m burned area maps, annual deforestation based on data from the INPE PRODES program, and the conversion of Cerrado savannah/woodland to cropland estimated from land cover information from MODIS phenology metrics.* Annual land cover data 2001-2004 for the portion of Mato Grosso covered by MODIS phenology metrics, tile h12v10, updated based on annual land cover changes in Amazon forest and Cerrado cover types.* Monthly Normalized Difference Vegetation Index (NDVI) for MODIS tile h12v10 from 10/2000 - 09/2006, based on cloud and gap-filled 16-day NDVI data from MODIS Collection 4 16-day NDVI composites  MOD13 product (Huete et al., 2002).There are six compressed (*.gz) files with this data set.
ABSTRACT: This data set contains modeled estimates of carbon flux, biomass, and annual burning emissions across the Brazilian state of Mato Grosso from 2000-2006. The model, DEforestation CArbon Flux (DECAF), was used to provide annual carbon fluxes from large deforestation events (>25 ha) based on post-deforestation land use, and the frequency and duration of active fires during the deforestation process. Carbon fluxes associated with the conversion of Cerrado to mechanized crop production, fires in Cerrado, and managed pasture cover types were also estimated. Model data outputs provided include:  * Estimated aboveground live biomass from DECAF in 2000 and 2004.* Annual biomass burning emissions estimates for 2001-2005 from low, middle, and high emissions scenarios with DECAF. There are 15 GeoTIFF files for annual emissions which represent the carbon emissions per pixel in grams of carbon per m2 (g C m-2). Model data inputs provided include: * Annual burn trajectories for 2001 - 2005, including deforestation, Cerrado land cover conversion, and fires in pasture and Cerrado ecosystems unrelated to agricultural expansion. These data were assembled from three sources: MODIS 500-m burned area maps, annual deforestation based on data from the INPE PRODES program, and the conversion of Cerrado savannah/woodland to cropland estimated from land cover information from MODIS phenology metrics.* Annual land cover data 2001-2004 for the portion of Mato Grosso covered by MODIS phenology metrics, tile h12v10, updated based on annual land cover changes in Amazon forest and Cerrado cover types.* Monthly Normalized Difference Vegetation Index (NDVI) for MODIS tile h12v10 from 10/2000 - 09/2006, based on cloud and gap-filled 16-day NDVI data from MODIS Collection 4 16-day NDVI composites  MOD13 product (Huete et al., 2002).There are six compressed (*.gz) files with this data set.
This data set provides active fire locations and estimates of annual fire frequencies for South America from 2000-2007. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors aboard the Terra (2000-2007) and Aqua (2003-2007) satellite platforms were analyzed to determine spatial and temporal patterns in satellite fire detections. The analysis considered a high-confidence subset of all MODIS fire detections to reduce the influence of false fire detections over small forest clearings in Amazonia (Schroeder et al., 2008). The number of unique days on which the active fire detections were recorded within a 1 km radius was estimated from the subset of active fire detections and the ArcGIS neighborhood variety algorithm. There are 14 data files with this data set: 7 GeoTIFF (.tif) files of fire frequency at MODIS 250 m resolution, where each grid cell value represents the number of days in that year on which active fires were detected, and 7 shape files of active fire locations for the years 2001-2007.
This data set provides active fire locations and estimates of annual fire frequencies for South America from 2000-2007. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors aboard the Terra (2000-2007) and Aqua (2003-2007) satellite platforms were analyzed to determine spatial and temporal patterns in satellite fire detections. The analysis considered a high-confidence subset of all MODIS fire detections to reduce the influence of false fire detections over small forest clearings in Amazonia (Schroeder et al., 2008). The number of unique days on which the active fire detections were recorded within a 1 km radius was estimated from the subset of active fire detections and the ArcGIS neighborhood variety algorithm. There are 14 data files with this data set: 7 GeoTIFF (.tif) files of fire frequency at MODIS 250 m resolution, where each grid cell value represents the number of days in that year on which active fires were detected, and 7 shape files of active fire locations for the years 2001-2007.
ABSTRACT: This data set provides active fire locations and estimates of annual fire frequencies for South America from 2000-2007. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors aboard the Terra (2000-2007) and Aqua (2003-2007) satellite platforms were analyzed to determine spatial and temporal patterns in satellite fire detections. The analysis considered a high-confidence subset of all MODIS fire detections to reduce the influence of false fire detections over small forest clearings in Amazonia (Schroeder et al., 2008). The number of unique days on which the active fire detections were recorded within a 1 km radius was estimated from the subset of active fire detections and the ArcGIS neighborhood variety algorithm. There are 14 data files with this data set: 7 GeoTIFF (.tif) files of fire frequency at MODIS 250 m resolution, where each grid cell value represents the number of days in that year on which active fires were detected, and 7 shape files of active fire locations for the years 2001-2007.
ABSTRACT: This data set provides annual spatial patterns of cropland, natural pasture, and planted pasture land uses across Amazonia for the period 1940/1950-1995. Two series of 5-minute grid cell historical maps were generated starting from land use classification products for 1995. Annual data are the fraction of natural pasture, planted pasture, and cropland in each 5-min grid cell. The annual maps are provided in two NetCDF (.nc) format file at 5-minute resolution. The AMZ-C.nc file covers the Brazilian portion of Amazon and Tocantins Rivers basins, and is based on the 1995 land use classification of Cardille et al. (2002), generated through the fusion of remote sensing (AVHRR) and agricultural census data. The second file, AMZ-R.nc, covers the entire Legal Amazon region and adjacent areas and is based on the 1995 land use classification by Ramankutty et al. (2008). The land use classification was generated by the fusion of satellite imagery (MODIS and VEGETATION-SPOT) and data from the agricultural census. A historical land-use reconstruction algorithm was used to generate the annual spatial patterns (based on work from Ramunkutty and Foley, 1999).
ABSTRACT: This data set provides annual spatial patterns of cropland, natural pasture, and planted pasture land uses across Amazonia for the period 1940/1950-1995. Two series of 5-minute grid cell historical maps were generated starting from land use classification products for 1995. Annual data are the fraction of natural pasture, planted pasture, and cropland in each 5-min grid cell. The annual maps are provided in two NetCDF (.nc) format file at 5-minute resolution. The AMZ-C.nc file covers the Brazilian portion of Amazon and Tocantins Rivers basins, and is based on the 1995 land use classification of Cardille et al. (2002), generated through the fusion of remote sensing (AVHRR) and agricultural census data. The second file, AMZ-R.nc, covers the entire Legal Amazon region and adjacent areas and is based on the 1995 land use classification by Ramankutty et al. (2008). The land use classification was generated by the fusion of satellite imagery (MODIS and VEGETATION-SPOT) and data from the agricultural census. A historical land-use reconstruction algorithm was used to generate the annual spatial patterns (based on work from Ramunkutty and Foley, 1999).
ABSTRACT: This data set provides annual spatial patterns of cropland, natural pasture, and planted pasture land uses across Amazonia for the period 1940/1950-1995. Two series of 5-minute grid cell historical maps were generated starting from land use classification products for 1995. Annual data are the fraction of natural pasture, planted pasture, and cropland in each 5-min grid cell. The annual maps are provided in two NetCDF (.nc) format file at 5-minute resolution. The AMZ-C.nc file covers the Brazilian portion of Amazon and Tocantins Rivers basins, and is based on the 1995 land use classification of Cardille et al. (2002), generated through the fusion of remote sensing (AVHRR) and agricultural census data. The second file, AMZ-R.nc, covers the entire Legal Amazon region and adjacent areas and is based on the 1995 land use classification by Ramankutty et al. (2008). The land use classification was generated by the fusion of satellite imagery (MODIS and VEGETATION-SPOT) and data from the agricultural census. A historical land-use reconstruction algorithm was used to generate the annual spatial patterns (based on work from Ramunkutty and Foley, 1999).
This data set provides soil physical and chemical properties, and grass nutrient measurements of samples collected from 17 pasture sites located within the state of Rondonia in the southwestern Brazilian Amazon. Soil data includes bulk density, class, texture, and measurements of carbon (C), phosphorus (P), calcium (Ca), magnesium (mg), and potassium (K) concentrations.  Foliar data includes nitrogen (N), P, Ca, Mg, and K concentrations.The 17 pasture sites were cattle ranches selected within the region between Porto Velho and Presidente Medici of Rondonia. Four of the ranches with Ultisols support dairy cattle, and the rest have beef cattle pastures dispersed across three soil orders: Oxisols, Ultisols, and Alfisols.  Nearby primary forest sites were also sampled to provide data on the original soil properties for each soil order. Soil samples were collected in May 2003, July through August 2003, and May 2004, which covered the late rainy season (May) and the dry season (July through August). Grass species sampled included Brachiaria brizantha, Brachiaria decumbens, B. brizantha, and Pennestum clandestinum, and represented three phenologically distinct grass materials: wet-season live grass, collected in May 2004, dry-season live grass and dry-season senesced grass, both collected between the end of July and the beginning of August 2003. There are 4 comma-delimited data files with this data set.
This data set provides soil physical and chemical properties, and grass nutrient measurements of samples collected from 17 pasture sites located within the state of Rondonia in the southwestern Brazilian Amazon. Soil data includes bulk density, class, texture, and measurements of carbon (C), phosphorus (P), calcium (Ca), magnesium (mg), and potassium (K) concentrations.  Foliar data includes nitrogen (N), P, Ca, Mg, and K concentrations.The 17 pasture sites were cattle ranches selected within the region between Porto Velho and Presidente Medici of Rondonia. Four of the ranches with Ultisols support dairy cattle, and the rest have beef cattle pastures dispersed across three soil orders: Oxisols, Ultisols, and Alfisols.  Nearby primary forest sites were also sampled to provide data on the original soil properties for each soil order. Soil samples were collected in May 2003, July through August 2003, and May 2004, which covered the late rainy season (May) and the dry season (July through August). Grass species sampled included Brachiaria brizantha, Brachiaria decumbens, B. brizantha, and Pennestum clandestinum, and represented three phenologically distinct grass materials: wet-season live grass, collected in May 2004, dry-season live grass and dry-season senesced grass, both collected between the end of July and the beginning of August 2003. There are 4 comma-delimited data files with this data set.
ABSTRACT: This data set provides soil physical and chemical properties, and grass nutrient measurements of samples collected from 17 pasture sites located within the state of Rondonia in the southwestern Brazilian Amazon. Soil data includes bulk density, class, texture, and measurements of carbon (C), phosphorus (P), calcium (Ca), magnesium (mg), and potassium (K) concentrations.  Foliar data includes nitrogen (N), P, Ca, Mg, and K concentrations.The 17 pasture sites were cattle ranches selected within the region between Porto Velho and Presidente Medici of Rondonia. Four of the ranches with Ultisols support dairy cattle, and the rest have beef cattle pastures dispersed across three soil orders: Oxisols, Ultisols, and Alfisols.  Nearby primary forest sites were also sampled to provide data on the original soil properties for each soil order. Soil samples were collected in May 2003, July through August 2003, and May 2004, which covered the late rainy season (May) and the dry season (July through August). Grass species sampled included Brachiaria brizantha, Brachiaria decumbens, B. brizantha, and Pennestum clandestinum, and represented three phenologically distinct grass materials: wet-season live grass, collected in May 2004, dry-season live grass and dry-season senesced grass, both collected between the end of July and the beginning of August 2003. There are 4 comma-delimited data files with this data set.
This data set provides fractional land cover type images for shade, green vegetation (GV), non-photosynthetic vegetation (NPV), and soil for the regions of JiParana, PortoVelho, Luiza, Ariquemes, and Cacoal in the state of Rondonia, Brazil, for the period 1984 to 2000. The images were derived with a spectral mixture analysis (SMA) of Landsat Thematic Mapper (TM) time series scenes for each of these areas. There were 249 TM scenes and one Landsat Multispectral Scanner (MSS) scene acquired for these analyses. The images are 30-m Landsat resolution and were georectified to the Brazilian space agency 1998 and 1999 PRODES imagery. There are 250 GeoTIIF image files (*.tif) in this data set. Files are grouped by region and year/month/day scene was taken.
This data set provides fractional land cover type images for shade, green vegetation (GV), non-photosynthetic vegetation (NPV), and soil for the regions of JiParana, PortoVelho, Luiza, Ariquemes, and Cacoal in the state of Rondonia, Brazil, for the period 1984 to 2000. The images were derived with a spectral mixture analysis (SMA) of Landsat Thematic Mapper (TM) time series scenes for each of these areas. There were 249 TM scenes and one Landsat Multispectral Scanner (MSS) scene acquired for these analyses. The images are 30-m Landsat resolution and were georectified to the Brazilian space agency 1998 and 1999 PRODES imagery. There are 250 GeoTIIF image files (*.tif) in this data set. Files are grouped by region and year/month/day scene was taken.
ABSTRACT: This data set provides fractional land cover type images for shade, green vegetation (GV), non-photosynthetic vegetation (NPV), and soil for the regions of JiParana, PortoVelho, Luiza, Ariquemes, and Cacoal in the state of Rondonia, Brazil, for the period 1984 to 2000. The images were derived with a spectral mixture analysis (SMA) of Landsat Thematic Mapper (TM) time series scenes for each of these areas. There were 249 TM scenes and one Landsat Multispectral Scanner (MSS) scene acquired for these analyses. The images are 30-m Landsat resolution and were georectified to the Brazilian space agency 1998 and 1999 PRODES imagery. There are 250 GeoTIIF image files (*.tif) in this data set. Files are grouped by region and year/month/day scene was taken.
ABSTRACT: This data set provides a 27-year land cover time series of 28.5-m resolution products derived from Landsat images for 80% of Rondonia, Brazil, for the period 1984 to 2010. Selected Landsat Thematic Mapper (TM) and Landsat Multispectral Scanner (MSS) images from the years 1984 through 2010, for seven path/row scenes (PortoVelho, Ariquemes, Jiparana, Luiza (or Urupa), Cacoal, Chapuingaia, and Vilhena) were mosaicked for each year. Each mosaicked image was georectified and classified into seven land-cover classes--savanna/rock, pasture, secondary forest, primary forest, cloud, urban, or water. This 27-year time series allows the long-term assessment of land-cover variation across the state. There are27 GeoTIFF image files (.tif) and one accompanying .xml file for each GeoTIFF file, compressed and available as *.zip files, one file for each year for the period 1984-2010, with this data set.
ABSTRACT: This data set provides a 27-year land cover time series of 28.5-m resolution products derived from Landsat images for 80% of Rondonia, Brazil, for the period 1984 to 2010. Selected Landsat Thematic Mapper (TM) and Landsat Multispectral Scanner (MSS) images from the years 1984 through 2010, for seven path/row scenes (PortoVelho, Ariquemes, Jiparana, Luiza (or Urupa), Cacoal, Chapuingaia, and Vilhena) were mosaicked for each year. Each mosaicked image was georectified and classified into seven land-cover classes--savanna/rock, pasture, secondary forest, primary forest, cloud, urban, or water. This 27-year time series allows the long-term assessment of land-cover variation across the state. There are27 GeoTIFF image files (.tif) and one accompanying .xml file for each GeoTIFF file, compressed and available as *.zip files, one file for each year for the period 1984-2010, with this data set.
ABSTRACT: This data set provides a 27-year land cover time series of 28.5-m resolution products derived from Landsat images for 80% of Rondonia, Brazil, for the period 1984 to 2010. Selected Landsat Thematic Mapper (TM) and Landsat Multispectral Scanner (MSS) images from the years 1984 through 2010, for seven path/row scenes (PortoVelho, Ariquemes, Jiparana, Luiza (or Urupa), Cacoal, Chapuingaia, and Vilhena) were mosaicked for each year. Each mosaicked image was georectified and classified into seven land-cover classes--savanna/rock, pasture, secondary forest, primary forest, cloud, urban, or water. This 27-year time series allows the long-term assessment of land-cover variation across the state. There are27 GeoTIFF image files (.tif) and one accompanying .xml file for each GeoTIFF file, compressed and available as *.zip files, one file for each year for the period 1984-2010, with this data set.
This data set provides a time series of Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) scenes for five (Path/Row) areas in Rondonia, Brazil. The scenes are from the period June 1975 through June 2000, but all areas do not have scenes for all the years. The areas and Landsat Path/Rows included are as follows: Ariquemes (P232,R67), Ji-Parana (P231, R67), Luiza (P231, R68), Cacoal (P230, R68), and Porto Velho (P232, R66). TM images are available for all five areas. Because of a paucity of digital Landsat MSS imagery from the 1970s, only two scenes could be included, a 1975 scene from Ariquemes and a 1978 scene from Ji-Parana. Each of the Landsat scenes has been coregistered to a Path/Row-specific georectified PRODES Landsat file obtained from the Brazilian Government's National Institute for Space Research (INPE) program. For each scene, the coregistration is accurate to within (plus or minus)1 pixel (30-m Landsat resolution) in most places. The five INPE PRODES Landsat scenes used in the georectification process are included with this data set. There are five compressed files (tar.gz format) with this data set. When expanded, each compressed file (which corresponds to one of the five areas) contains a directory for each scene with GeoTIFF files for individual Landsat bands, a text file of tie points, and another text file of slope and intercept values for converting radiance to reflectance. There are two dates for Landsat MSS scenes, 45 dates for TM scenes, and six dates for ETM+ scenes.
This data set provides a time series of Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) scenes for five (Path/Row) areas in Rondonia, Brazil. The scenes are from the period June 1975 through June 2000, but all areas do not have scenes for all the years. The areas and Landsat Path/Rows included are as follows: Ariquemes (P232,R67), Ji-Parana (P231, R67), Luiza (P231, R68), Cacoal (P230, R68), and Porto Velho (P232, R66). TM images are available for all five areas. Because of a paucity of digital Landsat MSS imagery from the 1970s, only two scenes could be included, a 1975 scene from Ariquemes and a 1978 scene from Ji-Parana. Each of the Landsat scenes has been coregistered to a Path/Row-specific georectified PRODES Landsat file obtained from the Brazilian Government's National Institute for Space Research (INPE) program. For each scene, the coregistration is accurate to within (plus or minus)1 pixel (30-m Landsat resolution) in most places. The five INPE PRODES Landsat scenes used in the georectification process are included with this data set. There are five compressed files (tar.gz format) with this data set. When expanded, each compressed file (which corresponds to one of the five areas) contains a directory for each scene with GeoTIFF files for individual Landsat bands, a text file of tie points, and another text file of slope and intercept values for converting radiance to reflectance. There are two dates for Landsat MSS scenes, 45 dates for TM scenes, and six dates for ETM+ scenes.
ABSTRACT: This data set provides a time series of Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) scenes for five (Path/Row) areas in Rondonia, Brazil. The scenes are from the period June 1975 through June 2000, but all areas do not have scenes for all the years. The areas and Landsat Path/Rows included are as follows: Ariquemes (P232,R67), Ji-Parana (P231, R67), Luiza (P231, R68), Cacoal (P230, R68), and Porto Velho (P232, R66). TM images are available for all five areas. Because of a paucity of digital Landsat MSS imagery from the 1970s, only two scenes could be included, a 1975 scene from Ariquemes and a 1978 scene from Ji-Parana. Each of the Landsat scenes has been coregistered to a Path/Row-specific georectified PRODES Landsat file obtained from the Brazilian Government's National Institute for Space Research (INPE) program. For each scene, the coregistration is accurate to within (plus or minus)1 pixel (30-m Landsat resolution) in most places. The five INPE PRODES Landsat scenes used in the georectification process are included with this data set. There are five compressed files (tar.gz format) with this data set. When expanded, each compressed file (which corresponds to one of the five areas) contains a directory for each scene with GeoTIFF files for individual Landsat bands, a text file of tie points, and another text file of slope and intercept values for converting radiance to reflectance. There are two dates for Landsat MSS scenes, 45 dates for TM scenes, and six dates for ETM+ scenes.
This data set provides classified land cover transition images (maps) derived from Landsat Thematic Mapper (TM) and Multispectral Scanner (MSS) imagery for Ariquemes, Luiza, and Ji-Parana areas in Rondonia, Brazil, at 30-m resolution. Images depict the age relative to the year 2000, of cleared land from the date the land was cut, to the date when primary forests transitioned into nonforest class (for example,  25 = cut by 1975, or 25 years before the year 2000). Temporal changes in three regions are represented by 31 TM scenes acquired between 1984 and 1999, and a pair of MSS scenes from 1975 and 1978. Data are provided as three GeoTiff (*.tif) images, one for each of the three areas.
This data set provides classified land cover transition images (maps) derived from Landsat Thematic Mapper (TM) and Multispectral Scanner (MSS) imagery for Ariquemes, Luiza, and Ji-Parana areas in Rondonia, Brazil, at 30-m resolution. Images depict the age relative to the year 2000, of cleared land from the date the land was cut, to the date when primary forests transitioned into nonforest class (for example,  25 = cut by 1975, or 25 years before the year 2000). Temporal changes in three regions are represented by 31 TM scenes acquired between 1984 and 1999, and a pair of MSS scenes from 1975 and 1978. Data are provided as three GeoTiff (*.tif) images, one for each of the three areas.
ABSTRACT: This data set provides classified land cover transition images (maps) derived from Landsat Thematic Mapper (TM) and Multispectral Scanner (MSS) imagery for Ariquemes, Luiza, and Ji-Parana areas in Rondonia, Brazil, at 30-m resolution. Images depict the age relative to the year 2000, of cleared land from the date the land was cut, to the date when primary forests transitioned into nonforest class (for example,  25 = cut by 1975, or 25 years before the year 2000). Temporal changes in three regions are represented by 31 TM scenes acquired between 1984 and 1999, and a pair of MSS scenes from 1975 and 1978. Data are provided as three GeoTiff (*.tif) images, one for each of the three areas.
This data set provides the results of spectral reflectance (350 to 2,500 nm at 1-nm increments) and biophysical measurements on grass pastures in eight cattle ranches in the state of Rondonia, located in the southwestern Brazilian Amazon. The ranches are located near the cities of Porto Velho, Ariquemes, Ouro Preto, Ji-Parana, and Presidente Medici. Field measurements were collected in July and August 2003. The primary grass species sampled were Brachiaria brizantha and Brachiaria decumbens. Spectrometer measurements were taken at 5-m intervals along 100 m transects on the pastures - fourteen total transects. Vegetation was sampled at 20-m intervals along the transects. All standing biomass and litter on the soil surface were collected and separated into live and senesced biomass and then dried to calculate water content. Sixty-eight reflectance spectra coincided with grass biophysical samples.Note that the research was done on private lands in Rondonia, and to protect the privacy of those land owners no geographic information is associated with the reported measurements. Three data files are included: an ENVI spectral library file with reflectance data for 484 pasture sampling points, an ASCII comma-separated file with reflectance data for the 484 pasture sampling points, and an ASCII comma-separated file with the biophysical measurements.
This data set provides the results of spectral reflectance (350 to 2,500 nm at 1-nm increments) and biophysical measurements on grass pastures in eight cattle ranches in the state of Rondonia, located in the southwestern Brazilian Amazon. The ranches are located near the cities of Porto Velho, Ariquemes, Ouro Preto, Ji-Parana, and Presidente Medici. Field measurements were collected in July and August 2003. The primary grass species sampled were Brachiaria brizantha and Brachiaria decumbens. Spectrometer measurements were taken at 5-m intervals along 100 m transects on the pastures - fourteen total transects. Vegetation was sampled at 20-m intervals along the transects. All standing biomass and litter on the soil surface were collected and separated into live and senesced biomass and then dried to calculate water content. Sixty-eight reflectance spectra coincided with grass biophysical samples.Note that the research was done on private lands in Rondonia, and to protect the privacy of those land owners no geographic information is associated with the reported measurements. Three data files are included: an ENVI spectral library file with reflectance data for 484 pasture sampling points, an ASCII comma-separated file with reflectance data for the 484 pasture sampling points, and an ASCII comma-separated file with the biophysical measurements.
ABSTRACT: This data set provides the results of spectral reflectance (350 to 2,500 nm at 1-nm increments) and biophysical measurements on grass pastures in eight cattle ranches in the state of Rondonia, located in the southwestern Brazilian Amazon. The ranches are located near the cities of Porto Velho, Ariquemes, Ouro Preto, Ji-Parana, and Presidente Medici. Field measurements were collected in July and August 2003. The primary grass species sampled were Brachiaria brizantha and Brachiaria decumbens. Spectrometer measurements were taken at 5-m intervals along 100 m transects on the pastures - fourteen total transects. Vegetation was sampled at 20-m intervals along the transects. All standing biomass and litter on the soil surface were collected and separated into live and senesced biomass and then dried to calculate water content. Sixty-eight reflectance spectra coincided with grass biophysical samples.Note that the research was done on private lands in Rondonia, and to protect the privacy of those land owners no geographic information is associated with the reported measurements. Three data files are included: an ENVI spectral library file with reflectance data for 484 pasture sampling points, an ASCII comma-separated file with reflectance data for the 484 pasture sampling points, and an ASCII comma-separated file with the biophysical measurements.
This data set provides the results of (1) synoptic streamwater sampling and analyses from numerous sites across Rondonia and (2) corresponding watershed characteristics derived from remote sensing and historical/available data sources. Sixty streams, in both forested and non-forested sites, were sampled once during the dry season in August of 1998 and 49 of the same streams were sampled again during the wet season in January-February of 1999. Analyses included sodium (Na), calcium (Ca), magnesium (Mg), potassium (K), silica (Si), chloride (Cl), sulfate, pH, and acid neutralizing capacity. Watershed characteristics, including soil cation content, pH, watershed lithology, area, percent deforested, and urban watershed population density, were derived and calculated from digitized soil maps and available soil profile analyses, digitized topographic maps, land use mosaics from Landsat Thematic Mapper (TM) images, and Brazilian census data. The objective of the study was to determine the relative influence of watershed soil exchangeable cation content, rock type, deforestation, and urban population density on stream concentrations of base cations, dissolved silicon, chloride and sulfate in both the dry and wet seasons in a humid tropical region undergoing regional land use transformation. There are three comma-delimited data files with this data set.
This data set provides the results of (1) synoptic streamwater sampling and analyses from numerous sites across Rondonia and (2) corresponding watershed characteristics derived from remote sensing and historical/available data sources. Sixty streams, in both forested and non-forested sites, were sampled once during the dry season in August of 1998 and 49 of the same streams were sampled again during the wet season in January-February of 1999. Analyses included sodium (Na), calcium (Ca), magnesium (Mg), potassium (K), silica (Si), chloride (Cl), sulfate, pH, and acid neutralizing capacity. Watershed characteristics, including soil cation content, pH, watershed lithology, area, percent deforested, and urban watershed population density, were derived and calculated from digitized soil maps and available soil profile analyses, digitized topographic maps, land use mosaics from Landsat Thematic Mapper (TM) images, and Brazilian census data. The objective of the study was to determine the relative influence of watershed soil exchangeable cation content, rock type, deforestation, and urban population density on stream concentrations of base cations, dissolved silicon, chloride and sulfate in both the dry and wet seasons in a humid tropical region undergoing regional land use transformation. There are three comma-delimited data files with this data set.
ABSTRACT: This data set provides the results of (1) synoptic streamwater sampling and analyses from numerous sites across Rondonia and (2) corresponding watershed characteristics derived from remote sensing and historical/available data sources. Sixty streams, in both forested and non-forested sites, were sampled once during the dry season in August of 1998 and 49 of the same streams were sampled again during the wet season in January-February of 1999. Analyses included sodium (Na), calcium (Ca), magnesium (Mg), potassium (K), silica (Si), chloride (Cl), sulfate, pH, and acid neutralizing capacity. Watershed characteristics, including soil cation content, pH, watershed lithology, area, percent deforested, and urban watershed population density, were derived and calculated from digitized soil maps and available soil profile analyses, digitized topographic maps, land use mosaics from Landsat Thematic Mapper (TM) images, and Brazilian census data. The objective of the study was to determine the relative influence of watershed soil exchangeable cation content, rock type, deforestation, and urban population density on stream concentrations of base cations, dissolved silicon, chloride and sulfate in both the dry and wet seasons in a humid tropical region undergoing regional land use transformation. There are three comma-delimited data files with this data set.
This data set provides estimates of watershed deforestation, as a proportion of the total area of watersheds, in Rondonia, Brazil for 1999. Deforestation maps were determined for the main agricultural and surrounding forested areas of Rondonia using multiple Landsat TM scenes (Biggs et al. 2008). Cumulative deforestation estimates were derived from this time series of Landsat scenes from 1975 to 1999. To obtain watershed-level estimates of deforestation, watershed boundaries and stream networks were delineated by a flow accumulation algorithm using a 90-m resolution digital elevation model (DEM) from NASA's Shuttle Radar Topography Mission (SRTM). The results were watersheds of seven Strahler stream orders (1-7) with stream networks that closely matched those of the 1:100,000 topographic maps for the area. The watershed boundaries, classified by stream order, were overlain on the time series of deforestation maps to determine the cumulative deforestation extent in 1999. This data set contains six ESRI ArcGIS shapefiles of the watershed boundaries for streams orders 2-7, the smallest watershed (second order) to the largest inclusive watershed (seventh order). The cumulative deforestation estimates, as a proportion of total area for each watershed, are available as a comma-delimited text file that can be related to the individual watershed boundary shapefiles. Cumulative deforestation data are available for first order streams, although not as a shapefile. There are six zipped ESRI ArcGIS shapefiles (*.zip) and one ASCII comma separated file with this data set.
This data set provides estimates of watershed deforestation, as a proportion of the total area of watersheds, in Rondonia, Brazil for 1999. Deforestation maps were determined for the main agricultural and surrounding forested areas of Rondonia using multiple Landsat TM scenes (Biggs et al. 2008). Cumulative deforestation estimates were derived from this time series of Landsat scenes from 1975 to 1999. To obtain watershed-level estimates of deforestation, watershed boundaries and stream networks were delineated by a flow accumulation algorithm using a 90-m resolution digital elevation model (DEM) from NASA's Shuttle Radar Topography Mission (SRTM). The results were watersheds of seven Strahler stream orders (1-7) with stream networks that closely matched those of the 1:100,000 topographic maps for the area. The watershed boundaries, classified by stream order, were overlain on the time series of deforestation maps to determine the cumulative deforestation extent in 1999. This data set contains six ESRI ArcGIS shapefiles of the watershed boundaries for streams orders 2-7, the smallest watershed (second order) to the largest inclusive watershed (seventh order). The cumulative deforestation estimates, as a proportion of total area for each watershed, are available as a comma-delimited text file that can be related to the individual watershed boundary shapefiles. Cumulative deforestation data are available for first order streams, although not as a shapefile. There are six zipped ESRI ArcGIS shapefiles (*.zip) and one ASCII comma separated file with this data set.
ABSTRACT: This data set provides estimates of watershed deforestation, as a proportion of the total area of watersheds, in Rondonia, Brazil for 1999. Deforestation maps were determined for the main agricultural and surrounding forested areas of Rondonia using multiple Landsat TM scenes (Biggs et al. 2008). Cumulative deforestation estimates were derived from this time series of Landsat scenes from 1975 to 1999. To obtain watershed-level estimates of deforestation, watershed boundaries and stream networks were delineated by a flow accumulation algorithm using a 90-m resolution digital elevation model (DEM) from NASA's Shuttle Radar Topography Mission (SRTM). The results were watersheds of seven Strahler stream orders (1-7) with stream networks that closely matched those of the 1:100,000 topographic maps for the area. The watershed boundaries, classified by stream order, were overlain on the time series of deforestation maps to determine the cumulative deforestation extent in 1999. This data set contains six ESRI ArcGIS shapefiles of the watershed boundaries for streams orders 2-7, the smallest watershed (second order) to the largest inclusive watershed (seventh order). The cumulative deforestation estimates, as a proportion of total area for each watershed, are available as a comma-delimited text file that can be related to the individual watershed boundary shapefiles. Cumulative deforestation data are available for first order streams, although not as a shapefile. There are six zipped ESRI ArcGIS shapefiles (*.zip) and one ASCII comma separated file with this data set.
This data set reports the results of a study to measure soil emissions of the carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), and nitric oxide (NO) throughout an entire cropping cycle in (1) slash-and-burn and (2) chop-and-mulch prepared agricultural fields from 2001-2004.  An adjacent 15-year-old fallow field with secondary forest vegetation served as the control.  The study site is within the municipality of Igarape Acu, Para, Brazil, at the Experimental Farm of the Federal Rural University of Amazonia. Flux data are reported in one comma-separated file.
This data set reports the results of a study to measure soil emissions of the carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), and nitric oxide (NO) throughout an entire cropping cycle in (1) slash-and-burn and (2) chop-and-mulch prepared agricultural fields from 2001-2004.  An adjacent 15-year-old fallow field with secondary forest vegetation served as the control.  The study site is within the municipality of Igarape Acu, Para, Brazil, at the Experimental Farm of the Federal Rural University of Amazonia. Flux data are reported in one comma-separated file.
ABSTRACT: This data set reports the results of a study to measure soil emissions of the carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), and nitric oxide (NO) throughout an entire cropping cycle in (1) slash-and-burn and (2) chop-and-mulch prepared agricultural fields from 2001-2004.  An adjacent 15-year-old fallow field with secondary forest vegetation served as the control.  The study site is within the municipality of Igarape Acu, Para, Brazil, at the Experimental Farm of the Federal Rural University of Amazonia. Flux data are reported in one comma-separated file.
This data set provides a time series of calcium, magnesium, and potassium extracted from soil samples from a laboratory column extraction study conducted in 2002. Soils used in the columns were originally collected in 1998 in Fazenda Vitoria, a cattle ranch 6 km north of the town of Paragominas, Para, Brazil. The soils were from contrasting land uses of primary forest (mata), secondary forest (capoeira), or pasture (pasto). Water equilibrated with increasing concentrations of CO2 was used to extract cations from the soil columns. Data represent the time series of cation concentrations in the extract solutions as well as the total content of cations removed from the soils. There is one comma-delimited ASCII file with this data set.
This data set provides a time series of calcium, magnesium, and potassium extracted from soil samples from a laboratory column extraction study conducted in 2002. Soils used in the columns were originally collected in 1998 in Fazenda Vitoria, a cattle ranch 6 km north of the town of Paragominas, Para, Brazil. The soils were from contrasting land uses of primary forest (mata), secondary forest (capoeira), or pasture (pasto). Water equilibrated with increasing concentrations of CO2 was used to extract cations from the soil columns. Data represent the time series of cation concentrations in the extract solutions as well as the total content of cations removed from the soils. There is one comma-delimited ASCII file with this data set.
ABSTRACT: This data set provides a time series of calcium, magnesium, and potassium extracted from soil samples from a laboratory column extraction study conducted in 2002. Soils used in the columns were originally collected in 1998 in Fazenda Vitoria, a cattle ranch 6 km north of the town of Paragominas, Para, Brazil. The soils were from contrasting land uses of primary forest (mata), secondary forest (capoeira), or pasture (pasto). Water equilibrated with increasing concentrations of CO2 was used to extract cations from the soil columns. Data represent the time series of cation concentrations in the extract solutions as well as the total content of cations removed from the soils. There is one comma-delimited ASCII file with this data set.
This data set reports soil CO2 flux and results of physical and chemical characterization of soils from pastures, secondary forests, and mature forests near Rio Branco, Acre, Brazil. CO2 flux measurements were made in the field on a monthly basis at 16 sites from June of 1999 to January 2001. In addition, a set of diel CO2 flux measurements were made at 1-hour intervals at selected pasture, mature and secondary forest sites in June and July 2000. Litter was collected monthly from 2001-2002 at each of the mature forest sites and at four of the secondary forest sites, and mean litter mass is reported. Soil samples were collected and analyzed from several land cover types at two sites during this same time period. There are six comma-delimited ASCII data files with this data set.
This data set reports soil CO2 flux and results of physical and chemical characterization of soils from pastures, secondary forests, and mature forests near Rio Branco, Acre, Brazil. CO2 flux measurements were made in the field on a monthly basis at 16 sites from June of 1999 to January 2001. In addition, a set of diel CO2 flux measurements were made at 1-hour intervals at selected pasture, mature and secondary forest sites in June and July 2000. Litter was collected monthly from 2001-2002 at each of the mature forest sites and at four of the secondary forest sites, and mean litter mass is reported. Soil samples were collected and analyzed from several land cover types at two sites during this same time period. There are six comma-delimited ASCII data files with this data set.
ABSTRACT: This data set reports soil CO2 flux and results of physical and chemical characterization of soils from pastures, secondary forests, and mature forests near Rio Branco, Acre, Brazil. CO2 flux measurements were made in the field on a monthly basis at 16 sites from June of 1999 to January 2001. In addition, a set of diel CO2 flux measurements were made at 1-hour intervals at selected pasture, mature and secondary forest sites in June and July 2000. Litter was collected monthly from 2001-2002 at each of the mature forest sites and at four of the secondary forest sites, and mean litter mass is reported. Soil samples were collected and analyzed from several land cover types at two sites during this same time period. There are six comma-delimited ASCII data files with this data set.
This data set provides Landsat images of the county of Sao Francisco do Para located in the Bragantina region of Para, Brazil, the oldest agriculture frontier in Amazonia. These images are subsets for the municipio (county) and immediate region. There are seven GeoTIFF files (.tif) with this data set which includes two for July 24, 1984 multispectral scanner (MSS), one for June 21, 1994 thematic mapper Landsat 5 (TM5),  three for July 13, 1999 thematic mapper Landsat 7 (TM7), and one TM for June 21, 1994.
This data set provides Landsat images of the county of Sao Francisco do Para located in the Bragantina region of Para, Brazil, the oldest agriculture frontier in Amazonia. These images are subsets for the municipio (county) and immediate region. There are seven GeoTIFF files (.tif) with this data set which includes two for July 24, 1984 multispectral scanner (MSS), one for June 21, 1994 thematic mapper Landsat 5 (TM5),  three for July 13, 1999 thematic mapper Landsat 7 (TM7), and one TM for June 21, 1994.
ABSTRACT: This data set provides Landsat images of the county of Sao Francisco do Para located in the Bragantina region of Para, Brazil, the oldest agriculture frontier in Amazonia. These images are subsets for the municipio (county) and immediate region. There are seven GeoTIFF files (.tif) with this data set which includes two for July 24, 1984 multispectral scanner (MSS), one for June 21, 1994 thematic mapper Landsat 5 (TM5),  three for July 13, 1999 thematic mapper Landsat 7 (TM7), and one TM for June 21, 1994.
This data set reports field estimated saturated hydraulic conductivity measurements from June 12 through June 20, 2001. This study was part of a rainfall exclusion experiment that was conducted from 1999-2001 at the km 67 Seca Floresta site, Tapajos National Forest, Para, Brazil. The objective of this component of the study was to develop an understanding of the physical processes driving the observed soil water dynamics at the site. There is one comma-delimited ASCII data file with this data set.
This data set reports field estimated saturated hydraulic conductivity measurements from June 12 through June 20, 2001. This study was part of a rainfall exclusion experiment that was conducted from 1999-2001 at the km 67 Seca Floresta site, Tapajos National Forest, Para, Brazil. The objective of this component of the study was to develop an understanding of the physical processes driving the observed soil water dynamics at the site. There is one comma-delimited ASCII data file with this data set.
ABSTRACT: This data set reports field estimated saturated hydraulic conductivity measurements from June 12 through June 20, 2001. This study was part of a rainfall exclusion experiment that was conducted from 1999-2001 at the km 67 Seca Floresta site, Tapajos National Forest, Para, Brazil. The objective of this component of the study was to develop an understanding of the physical processes driving the observed soil water dynamics at the site. There is one comma-delimited ASCII data file with this data set.
This data set reports biomass from small stems and non-woody vegetation measured from 1999 to 2005 in plots of a secondary-growth forest fertilization experiment. The study location was Fazenda Vitoria, 6.5-km northwest of the town of Paragominas, Para, Brazil, in a 6-year old secondary-growth forest. Vegetation life-forms with diameters less than or equal to 2 cm (grasses, herbs, vines and dead material) were destructively sampled in November 1999, June 2000, June 2001, July 2003, July 2004, and July 2005. All data are provided in a single comma-separated file. The site was divided into three blocks with four treatment plots (each 20m x 20m) located in each block (3 reps x 4 treatments = 12 plots). Three of the twelve plots were fertilized with nitrogen (100 kg N/ha as urea), three were fertilized with phosphorus (50 kg P/ha as superphosphate), three were fertilized with both nitrogen and phosphorus. The remaining three plots were not fertilized and served as the experimental control.
This data set reports biomass from small stems and non-woody vegetation measured from 1999 to 2005 in plots of a secondary-growth forest fertilization experiment. The study location was Fazenda Vitoria, 6.5-km northwest of the town of Paragominas, Para, Brazil, in a 6-year old secondary-growth forest. Vegetation life-forms with diameters less than or equal to 2 cm (grasses, herbs, vines and dead material) were destructively sampled in November 1999, June 2000, June 2001, July 2003, July 2004, and July 2005. All data are provided in a single comma-separated file. The site was divided into three blocks with four treatment plots (each 20m x 20m) located in each block (3 reps x 4 treatments = 12 plots). Three of the twelve plots were fertilized with nitrogen (100 kg N/ha as urea), three were fertilized with phosphorus (50 kg P/ha as superphosphate), three were fertilized with both nitrogen and phosphorus. The remaining three plots were not fertilized and served as the experimental control.
ABSTRACT: This data set reports biomass from small stems and non-woody vegetation measured from 1999 to 2005 in plots of a secondary-growth forest fertilization experiment. The study location was Fazenda Vitoria, 6.5-km northwest of the town of Paragominas, Para, Brazil, in a 6-year old secondary-growth forest. Vegetation life-forms with diameters less than or equal to 2 cm (grasses, herbs, vines and dead material) were destructively sampled in November 1999, June 2000, June 2001, July 2003, July 2004, and July 2005. All data are provided in a single comma-separated file. The site was divided into three blocks with four treatment plots (each 20m x 20m) located in each block (3 reps x 4 treatments = 12 plots). Three of the twelve plots were fertilized with nitrogen (100 kg N/ha as urea), three were fertilized with phosphorus (50 kg P/ha as superphosphate), three were fertilized with both nitrogen and phosphorus. The remaining three plots were not fertilized and served as the experimental control.
This data set provides tree diameters and heights measured from 1999 to 2005 in plots of a secondary-growth forest fertilization experiment located 6.5-km northwest of the town of Paragominas, Para, Brazil. In the 6-year old secondary-growth forest, all trees greater than 2 cm diameter at breast height (DBH) were tagged, identified, and measured for diameter and height in November 1999. Fertilizer was applied to selected plots in January 2000 and February 2001. Tree heights and diameters were remeasured in May 2000, June 2001, July 2002, July 2004, and July 2005. All data are provided in a single comma-separated file.The site was divided into three blocks, with four treatment plots (each 20m x 20m) located in each block (3 reps x 4 treatments = 12 plots). Three of the twelve plots were fertilized with nitrogen (100 kg N/ha as urea); three were fertilized with phosphorus (50 kg P/ha as superphosphate); three were fertilized with both nitrogen and phosphorus. The remaining three plots were not fertilized and served as the experimental control..
This data set provides tree diameters and heights measured from 1999 to 2005 in plots of a secondary-growth forest fertilization experiment located 6.5-km northwest of the town of Paragominas, Para, Brazil. In the 6-year old secondary-growth forest, all trees greater than 2 cm diameter at breast height (DBH) were tagged, identified, and measured for diameter and height in November 1999. Fertilizer was applied to selected plots in January 2000 and February 2001. Tree heights and diameters were remeasured in May 2000, June 2001, July 2002, July 2004, and July 2005. All data are provided in a single comma-separated file.The site was divided into three blocks, with four treatment plots (each 20m x 20m) located in each block (3 reps x 4 treatments = 12 plots). Three of the twelve plots were fertilized with nitrogen (100 kg N/ha as urea); three were fertilized with phosphorus (50 kg P/ha as superphosphate); three were fertilized with both nitrogen and phosphorus. The remaining three plots were not fertilized and served as the experimental control..
ABSTRACT: This data set provides tree diameters and heights measured from 1999 to 2005 in plots of a secondary-growth forest fertilization experiment located 6.5-km northwest of the town of Paragominas, Para, Brazil. In the 6-year old secondary-growth forest, all trees greater than 2 cm diameter at breast height (DBH) were tagged, identified, and measured for diameter and height in November 1999. Fertilizer was applied to selected plots in January 2000 and February 2001. Tree heights and diameters were remeasured in May 2000, June 2001, July 2002, July 2004, and July 2005. All data are provided in a single comma-separated file.The site was divided into three blocks, with four treatment plots (each 20m x 20m) located in each block (3 reps x 4 treatments = 12 plots). Three of the twelve plots were fertilized with nitrogen (100 kg N/ha as urea); three were fertilized with phosphorus (50 kg P/ha as superphosphate); three were fertilized with both nitrogen and phosphorus. The remaining three plots were not fertilized and served as the experimental control..
This data set reports soil carbon dioxide (CO2) and nitrous oxide (N2O) concentrations and soil volumetric water content (VWC) from a rainfall exclusion experiment that was conducted at the km 67 Seca Floresta site, Tapajos National Forest, Brazil. Samples were collected every two to three months. The purpose was to observe the potential effects of severe water stress on a humid Amazonian forest (Nepstad 2002).Data provided are from December 9, 1999, and April 2, 2000-June 14, 2002. There is one comma-delimited data file with this data set.
This data set reports soil carbon dioxide (CO2) and nitrous oxide (N2O) concentrations and soil volumetric water content (VWC) from a rainfall exclusion experiment that was conducted at the km 67 Seca Floresta site, Tapajos National Forest, Brazil. Samples were collected every two to three months. The purpose was to observe the potential effects of severe water stress on a humid Amazonian forest (Nepstad 2002).Data provided are from December 9, 1999, and April 2, 2000-June 14, 2002. There is one comma-delimited data file with this data set.
ABSTRACT: This data set reports soil carbon dioxide (CO2) and nitrous oxide (N2O) concentrations and soil volumetric water content (VWC) from a rainfall exclusion experiment that was conducted at the km 67 Seca Floresta site, Tapajos National Forest, Brazil. Samples were collected every two to three months. The purpose was to observe the potential effects of severe water stress on a humid Amazonian forest (Nepstad 2002).Data provided are from December 9, 1999, and April 2, 2000-June 14, 2002. There is one comma-delimited data file with this data set.