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Summary:

Many research efforts address the changes in biogeochemical cycles from environmental variability in climate and other drivers in both space and time. One method of inquiry is through development and use of ecosystem simulation models that use spatially referenced information on climate, elevation, soils, vegetation, and water availability to make estimates of important fluxes of carbon, water, and nitrogen. The Global Model Reference Data collection contains a set of reference data that have been used and continue to be used in many published climate change studies. These reference data include elevation, vegetation classification, soil texture, wetland soil types, grid-cell area, and grid-cell classification by continent. Some published articles include:

McGuire AD et al., Equilibrium responses of global net primary production and carbon storage to doubled atmospheric carbon dioxide: Sensitivity to changes in vegetation nitrogen concentration. Global Biogeochemical Cycles 11 1997 pp.173-189.

Melillo et al., Global climate change and terrestrial net primary production, Nature 363 1993 pp.234-240.

McGuire AD et al., Interactions between carbon and nitrogen dynamics in estimating net primary productivity for potential vegetation in North America. Global Biogeochemical Cycles 6 1992 pp.101-124.

Vörösmarty CJ et al., Continental scale models of water balance and fluvial transport: an application to South America. Global Biogeochemical Cycles 3 1989 pp. 241-265.

Overview of data sets:

The Geography dataset contains variables for continent code and grid-cell area that can be used when aggregating other data layers into regions (such as by continents). Area-weighted estimates using on grid-cell area are important to calculate because gridded data based on latitude/longitude boundaries vary in area depending on their location on the globe. Area-weighted estimates are used to determine how much land area is impacted by various environmental changes. The elevation data layer is used in models to determine high-elevation snow cover, or may be used to determine landscape properties or the direction of overland runoff. The Landcover dataset contains the variable "potential vegetation", which is a classification of each grid cell as a natural vegetation type. This data layer does not contain any type of crop, pasture, urban, or other non-natural vegetation types. This data layer has been used to estimate the upper range of net primary production and other ecosystem processes in the absence of human intervention. The Soils dataset contains a soil texture variable used to determine many water-related plant processes, including the depth of the root layer and the water-holding capacity of the soil. Because wetland ecosystems function very differently from dry-land ecosystems, we have included a wetland designation data layer to be used along with the potential vegetation data layer: in some models, such as TEM, wetland areas are not included in global or regional model runs.

The Global Model Reference Data collection includes the following datasets and variables:

References:

Edwards, M.O., 1989. Global gridded elevation and bathymetry on 5-minute geographic grid, (ETOPO5). NOAA, National Geophysical Data Center, Boulder, Colorado, USA.

FAO/UNESCO. 1977. Soil map of the world, 1: 5 000 000. UNESCO, Paris, FRANCE.

Melillo, J.M., McGuire, A.D., Kicklighter, D.W., Moore, B., Vörösmarty, C.J. and Schloss, A.L., 1993. Global climate change and terrestrial net primary production. Nature, 363:234-40.

Saxton et al. (1986) Soil Sci. Soc. Am. J. 50:1031-1036.

For additional information about various modeling projects that have used these and similar data, see:

The TEM model

The VEMAP Project and EOS-WEBSTER VEMAP collections.

Potsdam Institute for Climate Impact Research (PIK) sponsor of the 1995 and 1996 Potsdam Model Intercomparison Workshops, published in a series of articles in Global Change Biology 5 (Suppl. 1) 1999.

Equations used in calculating the area of 0.5 degree latitude x longitude grid-cells.

Area is calculated using the latitude at the upper bound of the grid-cell.

Convert to radians:

lat = latitude of center of the grid cell.

radians = (90.0 - (lat+0.25))*3.141593/180.0

Calculate cosines:

cosines = cosine(radians)-cosine(radians + (0.5*3.141593)/180.0))

Calculate area in square kilometers:

area = (6371221.3*6371221.3*3.141593*cosines/360.0)*1.0e-6

Data Provider:

Annette Schloss, Complex Systems Research Center, Institute for the Study of Earth, Oceans, and Space, Morse Hall, University of New Hampshire, Durham, New Hampshire, USA. Ph: 603.862.1792, Fax: 603.862.0188, Email: annette.schloss@unh.edu.

Last Data Update:

6/22/2000

Last Doc. Updated:

9/18/2001

Doc. Updated By:

Annette Schloss

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