题目：A new coupled modeling system developed for Arctic sea ice and climate prediction
Jiping Liu, Professor, University at Albany, State University of New York
There is a rising demand for Arctic sea ice prediction driven in particular by an increasing accessibility of the Arctic in the context of climate change. To improve our capability to predict Arctic sea ice and climate, we have developed a coupled atmosphere-sea ice-ocean model configured for the Arctic with sufficient flexibility. The Los Alamos sea ice model is coupled with the Weather Research and Forecasting Model and the Regional Ocean Modeling System within the Coupled-Ocean-Atmosphere-Wave-Sediment Transport modeling system. A series of sensitivity experiments with different physics options have been performed to determine the ‘optimal’ physics configuration that provides reasonable simulation of Arctic sea ice, serving as the baseline. It is well known that dynamic models used to predict Arctic sea ice at short-term periods strongly depend on model initial conditions. Thus a data assimilation that integrates sea ice observations to generate realistic and skillful model initialization is needed to improve predictive skill of Arctic sea ice. Parallel Data Assimilation Framework has been implemented into the new modeling system to assimilate SSMIS sea ice concentration, and CyroSat-2 and SMOS sea ice thickness using a localized error subspace transform ensemble Kalman filter. We have conducted Arctic sea ice prediction for the melting seasons of 2017 and 2018. Predictions with improved initial sea ice states show reasonably accurate sea ice evolution and small biases in the minimum sea ice extent.
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