Evaluation of Arctic Sea-ice Cover and Thickness Simulated by MITgcm

作     者：Fei ZHENG Yue SUN Qinghua YANG Longjiang MU Fei ZHENG;Yue SUN;Qinghua YANG;Longjiang MU

作者机构：International Center for Climate and Environment ScienceInstitute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjing 210044China University of Chinese Academy of SciencesBeijing 100049China School of Atmospheric SciencesSun Yat-sen Universityand Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Zhuhai 519082China Alfred Wegener InstituteHelmholtz Centre for Polar and Marine ResearchBremerhaven 27515Germany 

出 版 物：《Advances in Atmospheric Sciences》 (大气科学进展（英文版）)

年 卷 期：2021年第38卷第1期

页      面：29-48页

核心收录：

学科分类：07[理学] 0707[理学-海洋科学] 

基　　金：This work was supported by the National Key R&D Program of China(Grant No.2016YFC1402705) the Key Research Program of Frontier Sciences,CAS(Grant No.ZDBS-LY-DQC010) the National Natural Science Foundation of China(Grant Nos.41876012 and 41861144015) the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB42000000) 

主　　题：Arctic sea ice MITgcm simulation and evaluation sources of model error 

摘      要：A regional Arctic Ocean configuration of the Massachusetts Institute of Technology General Circulation Model(MITgcm)is applied to simulate the Arctic sea ice from 1991 to *** simulations are evaluated by comparing them with observations from different *** results show that MITgcm can reproduce the interannual and seasonal variability of the sea-ice extent,but underestimates the trend in sea-ice extent,especially in *** ice concentration and thickness distributions are comparable to those from the observations,with most deviations within the observational uncertainties and less than 0.5 m,*** simulated sea-ice extents are better correlated with observations in September,with a correlation coefficient of 0.95,than in March,with a correlation coefficient of ***,the distributions of sea-ice concentration are better simulated in March,with higher pattern correlation coefficients(0.98)than in *** the model underestimates the atmospheric influence on the sea-ice evolution in March,deviations in the sea-ice concentration arise at the ice edges and are higher than those in *** contrast,when the model underestimates the oceanic boundaries’influence on the September sea-ice evolution,disagreements in the distribution of the sea-ice concentration and its trend are found over most marginal seas in the Arctic *** uncertainties of the model,whereby it fails to incorporate the atmospheric information in March and oceanic information in September,contribute to varying model errors with the seasons.