Implementation of a One-Dimensional Enthalpy Sea-Ice Model in a Simple Pycnocline Prediction Model for Sea-Ice Data Assimilation Studies  

作　　者：Xinrong WU Shaoqing ZHANG Zhengyu LIU 

机构地区：[1]Key Laboratory of Marine Environmental Information Technology,State Oceanic Administration,National Marine Data and Information Service [2]Geophysical Fluid Dynamics Laboratory, National Oceanic and Atmospheric Administration,Princeton University [3]Center for Climate Research and Dept.Atmospheric and Oceanic Sciences,University of Wisconsin-Madison [4]Laboratory of Ocean–Atmosphere Studies, Peking University

出　　处：《Advances in Atmospheric Sciences》2016年第2期193-207,共15页大气科学进展（英文版）

基　　金：co-sponsored by grants from the National Natural Science Foundation (Grant Nos. 41206178, 41306006, 41376015, 41376013 and 41176003);the National Basic Research Program (Grant No. 2013CB430304);the National HighTech R&D Program (Grant No. 2013AA09A505);the Global Change and Air–Sea Interaction Program (Grant No. GASI-01-0112) of China

摘　　要：To further explore enthalpy-based sea-ice assimilation, a one-dimensional （1D） enthalpy sea-ice model is implemented into a simple pycnocline prediction model. The 1D enthalpy sea-ice model includes the physical processes such as brine expulsion, flushing, and salt diffusion. After being coupled with the atmosphere and ocean components, the enthalpy sea-ice model can be integrated stably and serves as an important modulator of model variability. Results from a twin experiment show that the sea-ice data assimilation in the enthalpy space can produce smaller root-mean-square errors of model variables than the traditional scheme that assimilates the observations of ice concentration, especially for slow-varying states. This study provides some insights into the improvement of sea-ice data assimilation in a coupled general circulation model.To further explore enthalpy-based sea-ice assimilation, a one-dimensional （1D） enthalpy sea-ice model is implemented into a simple pycnocline prediction model. The 1D enthalpy sea-ice model includes the physical processes such as brine expulsion, flushing, and salt diffusion. After being coupled with the atmosphere and ocean components, the enthalpy sea-ice model can be integrated stably and serves as an important modulator of model variability. Results from a twin experiment show that the sea-ice data assimilation in the enthalpy space can produce smaller root-mean-square errors of model variables than the traditional scheme that assimilates the observations of ice concentration, especially for slow-varying states. This study provides some insights into the improvement of sea-ice data assimilation in a coupled general circulation model.

关 键 词：sea ice ENTHALPY coupled model data assimilation ensemble Kalman filter 

分 类 号：P731.15[天文地球—海洋科学] P714.1