VEMAP Phase 2 Bioclimatic Database. I. Gridded Historical (20th century) Climate for Modeling Ecosystem Dynamics Across the Conterminous USA

Analysis and simulation of biospheric responses to historical forcing require surface cli- mate 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 VegetationlEcosystem Model- ing 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, mininirnum and maximum tempera- ture, total incident solar radiation, daylight-period irradiance, vapor pressure, and daylight-period rel- ative humidity. The dataset was derived from US Historical Climate Network (HCN), cooperative net- work, and snowpack telemetry (SNOTEL) monthly precipitation and mean nninirnw and maximum temperature station data. We employed techniques that rely on geostatistical and physical relation- ships to create the temporally and spatially complete dataset. We developed a local kriging prediction model to iniill discontinuous and limited-length station records based on spatial autocorrelation struc- ture of climate anomalies. A spatial interpolation model (PRISM) that accounts for physiographic con- trols was used to grid the infilled monthly station data. We implemented a stochastic weather genera- tor (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 tempera- ture, precipitation, solar radiation, vapor pressure, and PDSI for US Nationd Assessment regions. The historical climate and companion datasets are available online at data archive centers.

[1]  Noel A Cressie,et al.  Statistics for Spatial Data. , 1992 .

[2]  Henry F. Diaz,et al.  Creating a Serially Complete, National Daily Time Series of Temperature and Precipitation for the Western United States , 2000 .

[3]  W. Parton,et al.  A general model for soil organic matter dynamics: sensitivity to litter chemistry, texture and management. , 1994 .

[4]  Corinne Le Quéré,et al.  An efficient and accurate representation of complex oceanic and biospheric models of anthropogenic carbon uptake , 1996 .

[5]  S. Running,et al.  An improved method for estimating surface humidity from daily minimum temperature , 1997 .

[6]  Christopher Daly,et al.  Development of a 103-year high-resolution climate data set for the conterminous United States , 2000 .

[7]  Henry F. Diaz,et al.  TEMPERATURE VARIATIONS DURING THE LAST CENTURY AT HIGH ELEVATION SITES , 1997 .

[8]  D. Easterling,et al.  Indices of Climate Change for the United States , 1996 .

[9]  D. Wilks.  Conditioning stochastic daily precipitation models on total monthly precipitation , 1989 .

[10]  L. M. Berliner,et al.  Studies in the Atmospheric Sciences , 2000 .

[11]  Makiko Sato,et al.  A closer look at United States and global surface temperature change , 2001 .

[12]  S. Running,et al.  An improved algorithm for estimating incident daily solar radiation from measurements of temperature, humidity, and precipitation , 1999 .

[13]  Timothy G. F. Kittel,et al.  Validation of Simulated Runoff From Six Terrestrial Ecosystem Models: Results From Vemap , 2004 .

[14]  I. C. Prentice,et al.  Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model , 2003 .

[15]  David Yates,et al.  Comparing the Correlative Holdridge Model to Mechanistic Biogeographical Models for Assessing Vegetation Distribution Response to Climatic Change , 2000 .

[16]  G. L. Johnson,et al.  GEM (Generation of weather Elements for Multiple applications) : its application in areas of complex terrain , 1998 .

[17]  D. Lettenmaier,et al.  Evaluation of the land surface water budget in NCEP/NCAR and NCEP/DOE reanalyses using an off‐line hydrologic model , 2001 .

[18]  Dominique Bachelet,et al.  DYNAMIC SIMULATION OF TREE–GRASS INTERACTIONS FOR GLOBAL CHANGE STUDIES , 2000 .

[19]  W. Alley.  The Palmer Drought Severity Index: Limitations and Assumptions , 1984 .

[20]  Peter E. Thornton,et al.  Simultaneous estimation of daily solar radiation and humidity from observed temperature and precipitation: an application over complex terrain in Austria. , 2000 .

[21]  Peter E. Thornton,et al.  Modeling and measuring the effects of disturbance history and climate on carbon and water budgets in evergreen needleleaf forests , 2002 .

[22]  C. Daly,et al.  A knowledge-based approach to the statistical mapping of climate , 2002 .

[23]  Ramakrishna R. Nemani,et al.  Extrapolation of synoptic meteorological data in mountainous terrain and its use for simulating forest evapotranspiration and photosynthesis , 1987 .

[24]  Jeff Dozier,et al.  Climate and energy exchange at the snow surface in the Alpine Region of the Sierra Nevada: 2. Snow cover energy balance , 1992 .

[25]  Mike Rees,et al.  5. Statistics for Spatial Data , 1993 .

[26]  S. Barnes,et al.  A Technique for Maximizing Details in Numerical Weather Map Analysis , 1964 .

[27]  Noel A Cressie,et al.  Aggregation in Geostatistical Problems , 1993 .

[28]  P. Lamb,et al.  A Climate Change Database for Biological Assessments in the Southeastern United States: Development and Case Study , 2000 .

[29]  D. Schimel,et al.  CONTINENTAL SCALE VARIABILITY IN ECOSYSTEM PROCESSES: MODELS, DATA, AND THE ROLE OF DISTURBANCE , 1997 .

[30]  James W. Hurrell,et al.  Decadal atmosphere-ocean variations in the Pacific , 1994 .

[31]  Thomas C. Peterson,et al.  Maximum and Minimum Temperature Trends for the Globe , 1997 .

[32]  W. Post,et al.  Historical variations in terrestrial biospheric carbon storage , 1997 .

[33]  M. Parlange,et al.  An Extended Version of the Richardson Model for Simulating Daily Weather Variables , 2000 .

[34]  S. Running,et al.  Contribution of increasing CO2 and climate to carbon storage by ecosystems in the United States. , 2000, Science.

[35]  T. C. Haas,et al.  Local Prediction of a Spatio-Temporal Process with an Application to Wet Sulfate Deposition , 1995 .

[36]  George H. Taylor,et al.  High-quality spatial climate data sets for the United States and beyond , 2000 .

[37]  Steven W. Running,et al.  Modeled responses of terrestrial ecosystems to elevated atmospheric CO2: a comparison of simulations by the biogeochemistry models of the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) , 1998, Oecologia.

[38]  Ramakrishna R. Nemani,et al.  The VEMAP integrated database for modelling United States ecosystem/vegetation sensitivity to climate change , 1995 .

[39]  G. Campbell,et al.  On the relationship between incoming solar radiation and daily maximum and minimum temperature , 1984 .

[40]  Hanqin Tian,et al.  The sensitivity of terrestrial carbon storage to historical climate variability and atmospheric CO2 in the United States , 1999 .

[41]  C. Daly,et al.  A Statistical-Topographic Model for Mapping Climatological Precipitation over Mountainous Terrain , 1994 .

[42]  T. Fenton.  Quantitative Modeling of Soil-Forming Processes , 1995 .

[43]  J. Andrew Royle.  Multivariate Spatial Models , 2000 .

[44]  Peter E. Thornton,et al.  Generating surfaces of daily meteorological variables over large regions of complex terrain , 1997 .

[45]  C. W. Richardson.  Stochastic simulation of daily precipitation, temperature, and solar radiation , 1981 .

[46]  David R. Easterling,et al.  United States Historical Climatology Network (US HCN) monthly temperature and precipitation data , 1996 .

[47]  T. C. Haas,et al.  Lognormal and Moving Window Methods of Estimating Acid Deposition , 1990 .

[48]  Thomas R. Karl,et al.  Is recent climate change across the United States related to rising levels of anthropogenic greenhouse gases , 1990 .

[49]  R. Katz.  Use of conditional stochastic models to generate climate change scenarios , 1996 .

[50]  Vemap Participants.  Vegetation/ecosystem modeling and analysis project: Comparing biogeography and biogeochemistry models in a continental-scale study of terrestrial ecosystem responses to climate change and CO2 doubling , 1995 .

[51]  P. Jones,et al.  Representing Twentieth-Century Space-Time Climate Variability. Part II: Development of 1901-96 Monthly Grids of Terrestrial Surface Climate , 2000 .