J5.4
Regional climate change scenarios in Atlantic Canada utilizing statistical downscaling techniques: Preliminary Results
Gary S. Lines, MSC, Dartmouth, NS, Canada; and E. Barrow
Atlantic Canada is situated in a very diverse environmental area along the east coast of Canada, spanning almost 20 degrees of latitude and 20 degrees of longitude. The climate of the region is varied, encompassing both coastal and continental regimes and influenced by several major ocean currents and mountain ranges. In order to best describe the expected climate change impacts for the region, climate change scenarios and climate variables must be developed on a regional, or even site-specific, scale.
Two methods exist that would potentially provide this information, output from a Regional Climate Model (RCM) and statistical techniques to "downscale" climate variables from global climate models. Since the RCM capability for Canadian territory is presently being developed and output for Atlantic Canada is not readily available, the statistical techniques were explored to generate the downscaled climate variables in that region.
Homogonized daily mean, maximum and minimum temperature data for 14 sites across Atlantic Canada over the last 30 years was taken from the Historical Canadian Climate Database and used as the basis for developing the initial statistical relationships. Essentially, a predictor-predictand relationship is defined between global climate model values and the observed values at specific sites. Future climate variables (predictors) are then extracted from various model experiments. Those predictors are used to provide downscaled climate variables (predictand) that are applicable to those specific observed data sites. The resulting values are intended for use by climate change impacts researchers who want to apply climate variables on a regional scale in future climate impact studies. These researchers’ interests span many sectors including agriculture, forestry, biodiversity and natural resources.
The statistical techniques are embodied in the Statistical Downscaling Model (SDSM) developed by Rob Wilby et al., King’s College, London. The model results are primarily from the Canadian coupled global climate model version 1 (CGCM1) from the University of Victoria, in British Columbia.
Future work intends to expand this database to other climate variables as well as deliver climate variables on a small-scale grid as well as at specific sites.
Joint Session 5, Statistical Downscaling (Joint with the 16th Conference on Probability and Statistics and the 13th Symposium on Global Change and Climate Variations)
Tuesday, 15 January 2002, 4:00 PM-5:30 PM
Previous paper Next paper