|As of September 16, 2014|
The Boreal Ecosystem-Atmosphere Study was a large-scale international interdisciplinary experiment in the boreal forests of central Canada. Its focus was improving our understanding of the exchanges of radiative energy, sensible heat, water, CO2 and trace gases between the boreal forest and the lower atmosphere. A primary objective of BOREAS was to collect the data needed to improve computer simulation models of the important processes controlling these exchanges so that scientists can anticipate the effects of global change, principally altered temperature and precipitation patterns, on the biome.
The Boreal Ecosystem-Atmosphere Study (BOREAS) Follow-On Project extended and built upon the original BOREAS goal to investigate interactions between the boreal forest biome and the atmosphere in order to clarify their roles in global change. A common set of existing BOREAS in-situ and remote-sensing data were compiled at point, study area, and regional scales for use by Follow-On investigators. Follow-On investigations were integrative, interdisciplinary, and focused on modeling and regional-scale analyses. The development and intercomparison of the various carbon, water, and energy flux models was a major objective. Additional information on the BOREAS Follow-On project is available in the campaign guide document.
The FIFE Project was a large-scale climatology project set in the prairies of central Kansas in 1987 and 1989. This project was designed to improve understanding of carbon and water cycles; to coordinate data collected by satellites, aircraft, and ground instruments; and to use satellites to measure these cycles.
The First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) project conducted field studies on a prairie site in Kansas from 1987 to 1989. The FIFE Follow-on work included additional analyses of data collected during the initial field campaigns and additional field measurements. The objectives of both FIFE and FIFE Follow-on were to understand the biophysical processes controlling the fluxes of radiation, moisture, and carbon dioxide between the land surface and the atmosphere, and to develop remote-sensing methodologies for observing these processes.
The Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) is an intensive scientific investigation of the tropical rainforest of Brazil and portions of adjacent countries. Like FIFE and BOREAS, this project uses intensive remote-sensing techniques and ground-based experiments to investigate the atmosphere-biosphere-hydrosphere dynamics of this large tropical region. The LBA Project encompasses several scientific disciplines, or components. The LBA-ECO component focuses on the question: "How do tropical forest conversion, regrowth, and selective logging influence carbon storage, nutrient dynamics, trace gas fluxes, and the prospect for sustainable land use in Amazonia?"
|NACP||NORTH AMERICAN CARBON PROGRAM|
The North American Carbon Program (NACP) is a multidisciplinary research program designed to obtain scientific understanding of North America's carbon sources and sinks and of changes in carbon stocks needed to meet societal concerns and to provide tools for decision makers.
The Oregon Transect Ecosystem Research (OTTER) project was a collaborative effort between NASA and several universities to study the ecology of western coniferous forests using remote sensing technology supported by ground observations. The primary objective of the OTTER project was to estimate major fluxes of carbon, nitrogen, and water in coniferous forests using an ecosystem process model.
The SAFARI 2000 project was an international science initiative to study the linkages between land and atmosphere processes in the southern African region. In addition, SAFARI 2000 examined the relationship of biogenic, pyrogenic, and anthropogenic emissions and the consequences of their deposition to the functioning of the biogeophysical and biogeochemical systems of southern Africa. This initiative, which was conducted in 1999-2001, was built around a number of ongoing, already-funded activities by NASA, the international community, and African nations in the southern African region.
|SNF||SUPERIOR NATIONAL FOREST|
Biophysical, Morphological, Canopy Optical Property, and Productivity Data From the Superior National Forest
|ACCP||CANOPY CHEMISTRY (ACCP)|
The Accelerated Canopy Chemistry Program (ACCP) compiled a database of canopy chemistry for sites in the United States. The ACCP data consist of AVIRIS images, laboratory chemical analysis of field samples, laboratory spectra and chemical analyses from several mini-canopy experiments, and canopy modeling data. The Oak Ridge DAAC is interested in adding additional canopy chemistry data from sites around the world as contributed by investigators.
The objective of BigFoot is to provide ground validation of MODLand (MODIS Land Discipline Group) land cover, leaf area index (LAI), fAPAR, and net primary production (NPP) products. The name BigFoot was selected to describe the multiple scales, or footprints, of ground validation that the project will undertake. The current BigFoot study plan covers measurement, mapping, and modeling activities at four sites, each equipped with a meteorological flux tower that makes continuous measurements of energy, water, and carbon fluxes for a roughly 1-km2 footprint.
Long-term measurements of carbon dioxide, water vapor, and energy exchange from a variety of worldwide ecosystems integrated into consistent, quality assured, documented data sets.
|LAND VAL||EOS LAND VALIDATION|
In-situ and aircraft measurements for validating satellite products
|MODIS||MODIS Land Products Subsets|
The goal of the MODIS Land Products Subsets activity is to prepare summaries of selected MODIS Land Products for the community to use for validation in conjunction with FLUXNET and other field data. These summaries show pixel values of MODIS land products for a 7-km x 7-km area centered on flux towers or field sites from around the world.
The Prototype Validation Exercise (PROVE) consists of two mini-field campaigns involving investigators from three different NASA Earth Observing System (EOS) instrument teams. MODIS (Moderate-resolution Imaging Spectrometer), MISR (Multi-angle Imaging Spectro Radiometer), and ASTER (Advanced Space-borne Thermal Emission and Reflectance Radiometer) coordinate field, aircraft, and satellite measurements to maximize data collection and conduct cross comparisons. The 1997 campaigns were conducted in a grassland-shrub site on the Jornada Experimental Range near Las Cruces, New Mexico, and in a deciduous forest on the Walker Branch Watershed site near Oak Ridge, Tennessee. Project information and photos are available from the PROVE Web page http://pratmos.gsfc.nasa.gov/~justice/modland/valid/prove/grass/prove.html, an inventory of data collection is maintained by the ORNL DAAC, and controlled access is provided to PROVE data maintained by the ORNL DAAC.
The ORNL DAAC compiles, archives, and distributes data on temperature, precipitation, humidity, radiation, wind velocity, and cloud cover. These data are monthly and are either station or gridded data.
Daymet is a collection of gridded estimates of daily weather parameters generated by interpolation and extrapolation from daily meteorological observations. Weather parameters in Daymet include daily surfaces of minimum and maximum temperature, precipitation, humidity, and radiation produced on a 1 km x 1 km gridded surface over the conterminous United States, Mexico, and Southern Canada.
The ORNL DAAC compiles, archives, and distributes data on streamflow and climatology. The data are from a range of time scales (daily and monthly) and are from meteorological stations or streamflow discharge stations.
|ISLSCP II||ISLSCP II|
The International Satellite Land-Surface Climatology Project
|NPP||NET PRIMARY PRODUCTIVITY (NPP)|
NPP (net primary production) data from existing field measurements are being compiled for approximately 100 study sites covering several major world ecosystem types. These data are used by global change modelers to develop and validate models of vegetation-soil-atmosphere interactions within the global carbon cycle and to help calibrate remote sensing of vegetation worldwide
|RIVDIS||RIVER DISCHARGE (RIVDIS)|
Global River Discharge Database (RivDIS v1.1)
|RLC||RUSSIAN LAND COVER|
The Russian Land Cover database consists of land use and land cover satellite-based map products of Russia and of the Former Soviet Union. The GIS products included provide scientists and resource managers with the information needed in the management, characterization, and measurement of Russian forest resources as well as the land use and land cover data needed for Russian land management.
The ORNL DAAC compiles, archives, and distributes data on the physical and chemical properties of soils. The data are gridded at spatial scales ranging from regional to global.
The Atmospheric Tracer Model Intercomparison Project
The ORNL DAAC compiles, archives, and distributes gridded data on vegetation from regional to continental scales.
|VEMAP||VEGETATION-ECOSYSTEM MODELING (VEMAP)|
A multi-institutional, international effort whose goal is to evaluate the sensitivity of terrestrial ecosystem and vegetation processes to altered climate forcing and elevated atmospheric CO2. Phase 1 of the VEMAP project developed a model database of climate, soils, and vegetation compatible with the requirements of three ecosystem physiology models and three vegetation lifeform distribution models. Phase 2 developed a historical (1895-1994) gridded data set of climate (temperature, precipitation, solar radiation, humidity, and wind speed) and transient climate change scenarios based on coupled atmosphere-ocean GCM experiments, such as those with elevated greenhouse gases and sulfate aerosols.
The Model Archive allows users to evaluate the uncertainties of model results in comparison to results from other models in assessment/policy studies. In addition, the archived models allow users to see how models treat individual processes (source code) and what the model inputs were (state parameters, spin-up data, driving variables). For each model the DAAC will have documentation, source code (with version number), input data, example output data, and post-processing or analysis code (if applicable).