Ensemble-based parameter estimation in a coupled GCM using the adaptive spatial average method

Abstract

Ensemble-based parameter estimation for a climate model is emerging as an important topic in climate research. For a complex systemsuch as a coupled ocean-atmosphere general circulationmodel, the sensitivity and response of amodel variable to amodel parameter could vary spatially and temporally.Here, an adaptive spatial average (ASA) algorithmis proposed to increase the efciency of parameter estimation.Rened 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 nal global uniform posterior parameter. In comparison with existing methods, the ASA pa-rameter estimation has a superior performance: faster convergence and enhanced signal-to-noise ratio. © 2014 American Meteorological Society.