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Steve Vavrus

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The availability of output from climate model ensembles,such as phases 3 and 5 of the Coupled Model Intercomparison Project(CMIP3 and CMIP5), has greatly expanded information about future projections,but there is no accepted blueprint for how this data should be utilized.The multi-model average is themost commonly cited single estimate of future conditions,but higher-order moments representing thevariance and skewness of the distribution of projections provide important information about uncertainty. We have analyzed a set of statistically downscaled climate model projections from the CMIP3 archive to assess extreme weather events at a level aimed to be appropriate for decisionmakers. Our analysis uses the distribution...
Abstract (from American Meteorological Society): Projected changes in lake-effect snowfall by the mid- and late twenty-first century are explored for the Laurentian Great Lakes basin. Simulations from two state-of-the-art global climate models within phase 5 of the Coupled Model Intercomparison Project (CMIP5) are dynamically downscaled according to the representative concentration pathway 8.5 (RCP8.5). The downscaling is performed using the Abdus Salam International Centre for Theoretical Physics (ICTP) Regional Climate Model version 4 (RegCM4) with 25-km grid spacing, interactively coupled to a one-dimensional lake model. Both downscaled models produce atmospheric warming and increased cold-season precipitation....
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This project analyzies projected changes in the frequency and intensity of extreme weather events across the Great Lakes region, namely heat waves, cold spells, heavy precipitation events, and droughts, using a statistically downscaled climate product produced by the Climate Working Group of the Wisconsin Initiative on Climate Change Impacts (WICCI). It will perform a probabilistic exploration of weather extremes, ideally tailored toward decision-makers who are developing impact assessments at a regional scale across the Great Lakes region.
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