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VEMAP Release

The ORNL DAAC announces the release of data from the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP).

VEMAP is an international project studying the response of biogeochemical models and vegetation-type distribution models (i.e., biogeographical models) to variability in climate and to other spatial and temporal factors. Phase 1 compared the results of six models under various climate and vegetation scenarios. Phase 2 compares time-dependent ecological responses of models to historical and projected transient scenarios of climate and atmospheric carbon dioxide.

Regional and Global Data in Mercury

Regional and global biogeochemical dynamics data can now be located and acquired through a metadata search system at the ORNL DAAC.

Climate, hydroclimatology, soil, and vegetation data held by data centers around the world are available through a Web-based system called "Mercury." Mercury allows users to search metadata files to identify data sets of interest, and it directs the users to the data.

BOREAS Nov 16 Release

The ORNL DAAC recently released six additional data sets from the Boreal Ecosystem-Atmosphere Study (BOREAS). The newest data sets include remote-sensing images from the Landsat Thematic Mapper (TM), the Advanced Solid-state Array Spectroradiometer (ASAS), the Airborne Synthetic Aperture Radar (AIRSAR), and the Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS).

BOREAS Sep. 27 Release

The ORNL DAAC released seven additional data sets from the Boreal Ecosystem-Atmosphere Study (BOREAS). The newest data sets include POLDER and GOES-7 images, soil carbon data, and information about the study sites.

BOREAS was an intensive remote-sensing and field study of a Canadian boreal forest. Investigators measured exchanges of energy, water, heat, carbon dioxide, and trace gases between the forest and the atmosphere from 1993 to 1996.

New Global Climate Data

The ORNL DAAC announces the addition of "Global Monthly Climatology for the Twentieth Century (New et al.)" to its collection of climate data.

The newest addition contains gridded data related to monthly surface climate over global land areas at 0.5-degree resolution. Precipitation, mean temperature, and diurnal temperature range are interpolated directly from station time-series. Wet-day frequency, vapor pressure, cloud cover, and ground-frost frequency are interpolated where data are available and estimated for regions with no data.

Global Soils Data Increased

The ORNL DAAC expanded its global data holdings to include the three additional data sets related to soil characteristics.

Dunne Soil Data Set

The ORNL DAAC now offers a data set entitled "Global Distribution of Plant-Extractable Water Capacity of Soil (Dunne)." The data set was added to the holdings in the Soil Collections on August 18, 2000.

New Canopy Chemistry Data

The ORNL DAAC has added a data set to its holdings from the Accelerated Canopy Chemistry Program (ACCP). The new data set is entitled "Site AVIRIS Images, 1992 (ACCP)."

ACCP was an investigation to determine the theoretical and empirical basis for remote sensing of nitrogen and lignin concentrations in vegetation canopies of various ecosystems in the United States.


The ORNL DAAC now offers a 12-volume CD-ROM set of compiled measurement data and selected image data from the Boreal Ecosystem-Atmosphere Study (BOREAS), conducted from 1993 to 1996.

In addition, Compact Airborne Spectrographic Imager (CASI) data for BOREAS are available on-line. During selected periods in 1994 and 1996, CASI was used for observing seasonal changes in the radiometric reflectance properties of the boreal forest landscape. The CASI images are in the Remote Sensing Science holdings within BOREAS.

Flux and Meteorological Data

The ORNL DAAC announces the first release of data from the FLUXNET project. Flux and meteorology data are available for 11 research sites in Europe and the United States, with an average of two years of data per site.

The data have been quality assured, documented, and integrated into uniform data sets. Measurements were recorded usually on a half-hour basis. Missing values were obtained by means of common algorithms. The half-hourly values were then aggregated to produce daily, weekly, monthly, and annual sums.