CR 27:151-170 (2004)  -  doi:10.3354/cr027151

VEMAP Phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous USA

T. G. F. Kittel1,2,5,*, N. A. Rosenbloom1, J. A. Royle1,6, C. Daly3, W. P. Gibson3, H. H. Fisher1, P. Thornton1, D. N. Yates1, S. Aulenbach1, C. Kaufman1, R. McKeown2, D. Bachelet4, D. S. Schimel1, VEMAP2 Participants§

1National Center for Atmospheric Research, PO Box 3000, Boulder, Colorado 80307, USA
2Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, Colorado 80523, USA
3Spatial Climate Analysis Service and 4Department of Bioengineering, Oregon State University, Corvallis, Oregon 97331, USA
Present addresses: 5INSTAAR, Campus Box 450, University of Colorado, Boulder, Colorado 80309-0450, USA
6USDI Fis and Wildlife Service, Laurel, Maryland 20708, USA
§R. Neilson, J. Lenihan, R. Drapek (USDA Forest Service, Pacific Northwest Research Station, Corvallis, OR, USA); D. S. Ojima, W. J. Parton (Natural Resource Ecology Laboratory, Colorado University, Fort Collins, CO, USA); J. M. Melillo, D. W. Kicklighter, H. Tian (Ecosystems Center, Marine Biological Laboratory, Woods Hole, MA, USA); A. D. McGuire (US Geological Survey, Alaska Cooperative Fish and Wildlife Research Unit, Fairbanks, AK, USA); M. T. Sykes, B. Smith, S. Cowling, T. Hickler (Physical Geography & Ecosystems Analysis, Lund University, Sweden); I. C. Prentice (Max Planck Institute for Biogeochemistry, Jena, Germany); S. Running (University of Montana, Missoula, MT, USA); K. A. Hibbard (College of Forestry, Oregon State University, Corvallis, OR, USA); W. M. Post, A. W. King (Oak Ridge National Laboratory, Oak Ridge, TN, USA); T. Smith, B. Rizzo (Dept. of Environmental Sciences, University of Virginia, Charlottesville, VA, USA); F. I. Woodward (Dept. of Animal and Plant Sciences, University of Sheffield, UK)

ABSTRACT: Analysis and simulation of biospheric responses to historical forcing require surface climate data that capture those aspects of climate that control ecological processes, including key spatial gradients and modes of temporal variability. We developed a multivariate, gridded historical climate dataset for the conterminous USA as a common input database for the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP), a biogeochemical and dynamic vegetation model intercomparison. The dataset covers the period 1895-1993 on a 0.5° latitude/longitude grid. Climate is represented at both monthly and daily timesteps. Variables are: precipitation, mininimum and maximum temperature, total incident solar radiation, daylight-period irradiance, vapor pressure, and daylight-period relative humidity. The dataset was derived from US Historical Climate Network (HCN), cooperative network, and snowpack telemetry (SNOTEL) monthly precipitation and mean minimum and maximum temperature station data. We employed techniques that rely on geostatistical and physical relationships to create the temporally and spatially complete dataset. We developed a local kriging prediction model to infill discontinuous and limited-length station records based on spatial autocorrelation structure of climate anomalies. A spatial interpolation model (PRISM) that accounts for physiographic controls was used to grid the infilled monthly station data. We implemented a stochastic weather generator (modified WGEN) to disaggregate the gridded monthly series to dailies. Radiation and humidity variables were estimated from the dailies using a physically-based empirical surface climate model (MTCLIM3). Derived datasets include a 100 yr model spin-up climate and a historical Palmer Drought Severity Index (PDSI) dataset. The VEMAP dataset exhibits statistically significant trends in temperature, precipitation, solar radiation, vapor pressure, and PDSI for US National Assessment regions. The historical climate and companion datasets are available online at data archive centers.

KEY WORDS: Climate dataset · Climate variability · Climate change · Ecosystem dynamics · Vegetation · Ecological modeling · VEMAP · Geostatistics · Palmer Drought Severity Index · PDSI

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