Canadian Forest Service Publications

High resolution interpolation of climate scenarios for the conterminous USA and Alaska derived from general circulation model simulations. 2011. Joyce, L.A.; Price, D.T.; McKenney, D.W.; Siltanen, R.M.; Papadopol, P.; Lawerence, K.; Coulson, D.P. USDA Forest Service, Rocky Mountain Research Station, Fort Collins, Colorado. United States Department of Agriculture, Forest Service, General Technical Report RMRS-GTR-263. 100 pages.

The Canadian version of this report is available in this database at: https://cfs.nrcan.gc.ca/publications?id=32971

Year: 2011

Available from: Northern Forestry Centre

Catalog ID: 33012

Language: English

Abstract

Projections of future climate were selected for four well-established general circulation models (GCM) forced by each of three greenhouse gas (GHG) emissions scenarios, namely A2, A1B, and B1 from the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES). Monthly data for the period 1961–2100 were downloaded mainly from the web portal of Third Coupled Model Intercomparison Project (Phase 3) of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and subsets of data covering North America were extracted. Climate variables included monthly mean daily maximum and minimum temperatures, precipitation, incident surface solar radiation, wind speed, and specific humidity. All variables were expressed as changes relative to the simulated monthly means for 1961–1990, which corrected for GCM bias in reproducing past climate and allowed future projected trends to be compared directly. The downscaling procedure used the ANUSPLIN software package to fit a two-dimensional spline function to each month’s change data for each climate variable at a spatial resolution of 5 arcminutes (0.0833º) longitude and latitude. The A2 emission scenario invariably generated the greatest warming by 2100 and the B1 the least. Alaska is projected to undergo the greatest regional increases in temperature and precipitation. Differences across the projections were generally greater from the different GHG forcings than those resulting from the different GCMs, although the consistency varied spatially. Gridded datasets are publicly available. The downscaled change factors from this study are being used with historical climatology developed from the PRISM climate data set to develop the climate projections for the RPA scenarios in the USDA FS RPA assessment. A companion report and data set will be issued by Natural Resources Canada (Canadian Forest Service) for Canada.