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.

Presenter Profile

Prof. Liu Jiping received his Ph.D. in atmospheric sciences and physical oceanography from Columbia University in 2003. Hi is now a professor at the Department of Atmospheric and Environmental Sciences in State University of New York at Albany. His research interests include Climate-Cryosphere Dynamics, Feedbacks and Modeling, Atmosphere-Ice-Ocean Interactions, Application of Remote Sensing in Oceans.