Ensemble-Based Parameter Estimation in a Coupled GCM Using the Adaptive Spatial Average Method [electronic resource].
- Washington, D.C. : United States. Dept. of Energy. Office of Science, 2014.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy
- Physical Description:
- pages 4,002-4,014 : digital, PDF file
- Additional Creators:
- Argonne National Laboratory
United States. Department of Energy. Office of Science
United States. Department of Energy. Office of Scientific and Technical Information
- Ensemble-based parameter estimation for a climate model is emerging as an important topic in climate research. And for a complex system such as a coupled ocean–atmosphere general circulation model, the sensitivity and response of a model variable to a model parameter could vary spatially and temporally. An adaptive spatial average (ASA) algorithm is proposed to increase the efficiency of parameter estimation. Refined from a previous spatial average method, the ASA uses the ensemble spread as the criterion for selecting “good” values from the spatially varying posterior estimated parameter values; these good values are then averaged to give the final global uniform posterior parameter. In comparison with existing methods, the ASA parameter estimation has a superior performance: faster convergence and enhanced signal-to-noise ratio.
- Published through SciTech Connect.
Journal of Climate 27 11 ISSN 0894-8755 AM
Y. Liu; Z. Liu; S. Zhang; X. Rong; R. Jacob; S. Wu; F. Lu.
- Funding Information:
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