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A new coupled modeling system developed for Arctic sea ice and climate prediction

作者:   时间:2019-06-06   点击:[]

日期(月) 6 日期(日) 12
地址 综合1号实验楼602



题目:A new coupled modeling system developed for Arctic sea ice and climate prediction

报告人:刘骥平教授,美国纽约州立大学大气和环境科学系

Jiping Liu, Professor, University at Albany, State University of New York

报告时间:2019612 10:00-11:00

报告地点:综合1号实验楼602

 

Abstract:

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.

 

刘骥平,美国纽约州立大学大气和环境科学系教授。美国哥伦比亚大学大气科学和物理海洋学博士。在美国乔治亚理工学院从事博士后工作,之"后在美国乔治亚理工学院、中国科学院大气物理研究所和美国纽约州立大学从事科研和教学工作。主要研究领域包括:气候系统模式中海冰-海洋模式的发展、极地气候变化机制及对天气气候的反馈、极地卫星遥感评估及应用。

 

 

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