HR: 0800h
AN: GC21A-0138    [Abstracts]
TI: An Assessment of Two Statistical Downscaling Techniques for Generating Daily Climate Data for Central Canada
AU: * Koenig, K A
EM: kkoenig@hydro.mb.ca
AF: Manitoba Hydro, 540-444 St. Mary Ave., Winnipeg, MB R3C 3T7, Canada
AU: Rasmussen, P F
EM: rasmusse@cc.umanitoba.ca
AF: University of Manitoba, E1-368A Engineering, 15 Gillson, Winnipeg, MB R3T 5V6, Canada
AB: General Circulation Models, or Global Climate Models (GCMs), are widely used to assess potential impacts of global climate change because they are designed to simulate the present climate and project future climate. They however are not designed for local climate change impact studies and do not permit a good estimation of hydrological responses to climate change by themselves because of their coarse spatial scales. Statistical downscaling techniques have recently emerged as useful tools to convert the GCM outputs into a scale useful for climate change impact studies. These techniques are able to generate scenarios for a local site by using a statistically based model to represent the relationship between large scale climate variables and local climate variables. To date there have been several statistical downscaling techniques proposed in the scientific literature, each having its own advantages and shortcomings. Since there are many factors which can influence a downscaling model, such as the topography of the region, it is essential that a rigorous evaluation of the different statistical downscaling methods be undertaken. This will ensure that the most suitable approach is chosen to meet the conditions of the region. The objective of this study is to test two popular statistical downscaling methods, the Statistical Downscaling Model (SDSM) and the Stochastic Weather Generator (LARS-WG) for their ability to simulate daily time series of local precipitation and temperature for meteorological stations located in Central Canada. The evaluation will not only consist of examining the models ability to simulate means but will also examine their ability to simulate the magnitude and occurrence of extremes. These models will then applied to the GCM output from the Canadian Center for Climate Modeling and Analysis (CCCma) third generation model, CGCM3 T47 using the SRESA1, SRESA1B, and SRESA2 scenarios for two future time periods (2046-2065, 2081-2091) to project future climate change scenarios for these sites.
DE: 1600 GLOBAL CHANGE
DE: 1637 Regional climate change
SC: Global Environmental Change [GC]
MN: 2007 Fall Meeting