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Parameter Sensitivity of a Coupled Climate Model Estimated Through Data Assimilation

This study explores the parameter sensitivity of a coupled climate model using data assimilation, with a focus on decadal prediction and minimizing systematic model biases. The use of control variables and greenhouse gas forcing is assessed to improve hindcasts and provide insights into future climate trends.

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Parameter Sensitivity of a Coupled Climate Model Estimated Through Data Assimilation

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  1. Parameter Sensitivity of a Coupled Climate Model Estimated Through Data Assimilation Xueyuan Liu A. Köhl, D. Stammer CEN (Center für Erdsystemfurschung und Nachhaltigkeit) Hamburg University

  2. Decadal Prediction The highlights of decadal climate predictions up to date: 1)initialization 2)uncertainties 3) minimizing the influence of systematic model biases 4)measurements of the skill of hindcasts Approach: A fully-coupled data assimilation was used to get the optimal oceanic initial conditions and control variables(JAMSTEC). Based on those, ensembles of hindcasts with implimentation of greenhouse gas forcing are carried out every one year to assess how the strategy works. A 20C run from 1913 shall also be done. Extra ensembles might be necessary in order to give statistics. Ensembles of decadal prediction is expected to give information on the climate of the coming century.

  3. Contribution of Control Variables The two patterns of mean bias of SST(1980-1989) are almost opposite. Despite the differences in the amplitude, we can come to a conclusion that control alphas contribute to the improvement of a hindcast. alphas=0 against alphas=climatology hindcasts (alphas=0) against HadISST

  4. Annual-mean SST over 9 Years

  5. Thanks for your attention!

  6. K7 System from Japan Agency for Marine-Earth Science and Technology (JAMSTEC) • Coupled Model---CFES (Coupled model for the Earth Simulator) ●T42L24 AFES (Atmospheric GCM for the Earth Simulator) for AGCM ● 1*1 degree, 45 vertical layers MOM3 for OGCM ●IARC (International Arctic Research Center) Sea-ice model ●MATSIRO (Minimal Advanced Treatments of Surface Interaction and Runoff) Model for land • Assimilation Method-----4D-VAR forward backward Obs Obs Best guess trajectory Obs First guess field Assimilation period

  7. Improving Decadal Predictions 1980 1990 2000 1970 Spinup run by IAU …… First guess I.C. First guess I.C. First guess I.C. 9 mon 1.5 month First guess Exp. (Free run) 9 mon In all:1980-2007 optimized Assimilation Exp. by 4D-VAR optimized 10 yr optimized Ensemble Exp. (each with 3 members- shifted atmosphere) optimized 10 yr 10 yr … … Schematic view of the experimental configuration: Jan 1982 Jan 1980 Jan 1981

  8. The research leading to these results has received funding from the European Union 7th Framework Programme (FP7 2007-2013), under grant agreement n.308299 NACLIM www.naclim.eu

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