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An Evaluation of Statistical Downscaling Technique

PI: Kristina Koenig
Institution: University of Manitoba
Abstract:
This study tests two popular SD methods, the Stochastic Weather Generator (LARS-WG) and the Statistical Downscaling Model (SDSM) for their ability to simulate daily time series of local precipitation, and temperature for a range of climatic conditions in Central Canada. The two models will specifically be evaluated by their ability to accurately reconstruct observed local daily precipitation and temperature variability and extremes. The models will be calibrated using observed station data for the period from 1961 to 1985, while the validation period will run from 1986 to 2000. Once calibrated, the GCM output from CGCM1 and HADCM3 will be downscaled using the models to generate future climate change scenarios for this region.
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