Ensemble-based Parameter Estimation in a Coupled Gcm 2 Using the Adaptive Spatial Average Method 3 4 5

37 Ensemble-based parameter estimation for a climate model is emerging as an 38 important topic in climate research. For a complex system as a coupled ocean-atmosphere 39 general circulation model, the sensitivity and response of a model variable to a model 40 parameter could vary spatially and temporally. Here, we propose an adaptive spatial 41 average (ASA) algorithm to increase the efficiency of parameter estimation. Refined 42 from a previous spatial average method, the ASA uses the ensemble spread as the 43 criterion for selecting " good " values from the spatially varying posterior estimated 44 parameter values; the " good " values are then averaged to give the final global uniform 45 posterior parameter. In comparison with existing methods, the ASA parameter estimation 46 has a superior performance: faster convergence and enhanced signal-to-noise ratio.