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Activity Number:
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179
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Type:
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Invited
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Date/Time:
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Monday, August 7, 2006 : 2:00 PM to 3:50 PM
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Sponsor:
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WNAR
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| Abstract - #305281 |
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Title:
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Estimating Parametric Uncertainties of the Community Atmospheric Model (CAM3) and Processes Controlling Global Climate Change
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Author(s):
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Charles S. Jackson*+
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Companies:
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The University of Texas at Austin
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Address:
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Institute for Geophysics, Austin, TX, 78759,
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Keywords:
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Bayesian inference ; uncertainty ; climate ; stochastic inversion
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Abstract:
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Computational models of global climate differ widely in their sensitivity to projected increases in greenhouse gases. We do not yet have a clear picture of what processes dominate this uncertainty or how we may make better use of observations to reduce parametric uncertainties in climate models. The climate problem is one example of a broad class of problems in the geosciences currently limited by the lack of sufficient computational resources and/or the dimensionality and size of observational constraints. This talk will emphasize the characterization of the climate problem and present results of a calculation using Bayesian inference and techniques of geophysical stochastic inversion to constrain values of six nonlinearly related parameters important to convection, precipitation, and radiation in the Community Atmospheric Model (CAM3).
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