The EOS-WEBSTER VEMAP2 Data Collection contains several datasets which provide historical and future climate variables, and monthly and annual biogeochemical model outputs.
The TResults Dataset group contains 4 individual datasets, which include two differerent GCM Climate prediction model inputs and two different CO2 scenarios. Holdings in these four datasets ... include annual and monthly biogeography/biogeochemical model estimates of ecosystem response from 1895 to 2100. Six different ecosystem process models are represented in the holdings.
The two different GCM models used for climate inputs to the ecosystem process models are:
1) Canadian Climate Center -- CGCM1 scenario: constant CO2 (1895 level; 294.842 ppm); 1895-2100 increasing CO2 (IS92a global yearly dataset); 1895-2100
2) UKMO/Hadley Center -- HadCM2 scenario: constant CO2 (1895 level; 294.842 ppm); 1895-2099 increasing CO2 (IS92a global yearly dataset); 1895-2099
The Following Biogeochemical Variables are predicted by the six ecosystem models:
1) Net Primary Production (NPP): Annual & Monthly data 2) Actual Evapotranspiration (AET): Annual & Monthly data 3) Net Ecosystem Productivity (NEP): Monthly data 4) Net Nitrogen Mineralization (NNM): Annual data 5) Total Carbon Storage (TCS): Annual data 6) Total Vegetation Carbon (TVC): Annual data 7) Leaf Area Index (LAI): Monthly data
The following six biogeochemical models are represented in the holdings, and the associated predicted variables:
Data provided by the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) at the National Center for Atmospheric Research (NCAR) are gridded monthly time series climate data for the Conterminous United States at 0.5 x 0.5 degree spatial resolution. Visit the VEMAP2 website for complete information about the VEMAP2 project and datasets.
The VEMAP2 Collection contains the following dataset groups.
1) TClimate - monthly historical climate dataset from 1895 to 1993. Release: r3.
2) TScenario - monthly climate data of possible future values based on different model scenarios.
3) TClimate + TScenario - annual historical climate data + possible future values based on the above different model scenarios.
4) TResults - annual and monthly biogeography/biogeochemical model estimates of ecosystem response from 1895 to 2100.
Please see the individual dataset group DIFs, for more detailed information.
Use of the VEMAP dataset is subject to the following guidelines and restrictions:
(1) Users may confer with the NCAR VEMAP Data Group to ensure that the intended application of the dataset is consistent with the generation and limitations of the data.
(2) To help us identify dataset errors or inconsistencies, we ... request that users contact the NCAR VEMAP Data Group regarding problems with data files, data access, or the dataset's representation of climate. For problems with data access or file format, please refer to http://www.cgd.ucar.edu/vemap/contacts.html
(3) Credit in publications resulting from the use of the VEMAP2 data will be given (a) by citation of VEMAP data set (http://www.eos-webster.sr.unh.edu) and appropriate VEMAP data papers (http://www.cgd.ucar.edu/vemap/acknowledgments2.html) and (b) by acknowledgement of VEMAP sponsors (NASA Earth Science Enterprise, EPRI, and the USDA Forest Service Global Change Program) and the VEMAP Data Group (T. Kittel, D. Schimel, A. Royle, N. Rosenbloom, H. Fisher, S. Aulenbach, and C. Kaufman, NCAR, and C. Daly, Oregon State University) for access to the data.
(4) The HADCM2 data may only be used for purposes related to VEMAP or the U. S. National Assessment. For any other purposes, you must get permission directly from David Viner at LINK (firstname.lastname@example.org).
Complex Systems Research Center
Institute for the Study of Earth, Oceans, and Space
University of New Hampshire
Province or State:
Thornton, P.E., H. Hasenauer, and M.A. White (in review). Simultaneous estimation of daily solar radiation and humidity from observed temperature and precipitation: an application over complex terrain in Austria. Agricultural and Forest Meteorology.
Thornton, P.E., and S.W. Running, 1999. An improved algorithm for estimating incident daily solar radiation from ... measurements of temperature, humidity, and precipitation. Agricultural and Forest Meteorology, 93:211-228.
Kimball, J.S., S.W. Running, and R. Nemani, 1997. An improved algorithm for estimating surface humidity from daily minimum temperature. Agricultural and Forest Meteorology, 85:87-98.
Glassy, J.M., and S.W. Running, 1994. Validating diurnal climatology of the MT-CLIM model across a climatic gradient in Oregon. Ecological Applications, 4(2):248-257.
Running, S.W., R.R. Nemani, and R.D. Hungerford, 1987. Extrapolation of synoptic meteorological data in mountainous terrain and its use for simulating forest evaporation and photosynthesis. Canadian Journal of Forest Research, 17:472-483.
Bristow, K.L., and G.S. Campbell, 1984. On the relationship between incoming solar radiation and daily maximum and minimum temperature. Agricultural and Forest Meteorology, 31:159-166.