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Activity Number:
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321
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, July 31, 2007 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics and the Environment
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| Abstract - #309069 |
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Title:
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Modeling Extremes in Regional Climate Model Simulations
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Author(s):
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Daniel Cooley*+ and Stephan Sain
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Companies:
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Colorado State University and National Center for Atmospheric Research
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Address:
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321 Judson St, Longmont, CO, 80501,
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Keywords:
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precipitation ; spatial statistics ; Bayesian hierarchical model
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Abstract:
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Regional climate models (RCM) are designed to capture local climate behavior that general circulation models (GCM) cannot because of their course resolution. Like GCMs, RCMs are tuned so that the weather they simulate resembles that which is currently observed under current climate conditions. Although the RCM-simulated weather pretty closely approximates local climate, there is some question as to whether they accurately represent extreme weather. In this work, we build a Bayesian hierarchical model for the extreme precipitation data from a RCM for the Western United States. We compare the extremes of a control run of the RCM to those of a run simulated under increased carbon dioxide scenarios. We also compare the extremes produced by the RCM to those recorded at weather stations over the last half of the twentieth century.
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