Ensemble-Based Parameter Estimation In A Coupled GCM Using The Adaptive Spatial Average Method

TitleEnsemble-Based Parameter Estimation In A Coupled GCM Using The Adaptive Spatial Average Method
Publication TypeJournal Article
Year of Publication2014
AuthorsLiu, Y, Liu, Z, Zhang, S, Rong, X, Jacob, RL, Wu, S, Lu, F
JournalJournal of Climate
Volume27
Issue11
Pagination4002-4014
Date Published06/2014
ISSN1520-0442
Other NumbersANL/MCS-P5084-0214
AbstractEnsemble-based parameter estimation for a climate model is emerging as an important topic in climate research. For a complex system 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. Here, we propose an adaptive spatial average (ASA) algorithm 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; the “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.  
URLhttp://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-13-00091.1
DOI10.1175/JCLI-D-13-00091.1
PDFhttp://www.mcs.anl.gov/papers/P5084-0214.pdf