Assessment of Arctic sea ice simulations in CMIP5 models using a synthetical skill scoring method

作     者：Liping Wu Xiao-Yi Yang Jianyu Hu 

作者机构：State Key Laboratory of Marine Environmental Science College of Ocean and Earth Sciences Xiamen University Xiamen 361102 China Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) Zhuhai 519000 China 

出 版 物：《Acta Oceanologica Sinica》 (海洋学报（英文版）)

年 卷 期：2019年第38卷第9期

页      面：48-58页

核心收录：

学科分类：07[理学] 

基　　金：The National Natural Science Foundation of China under contract Nos 41576178 and 41630963 the National Basic Research Program(973 program)of China under contract No.2015CB954004 

主　　题：Arctic sea ice climate model Barents and Kara Seas multi-model ensemble mean 

摘      要：The Arctic sea ice cover has declined at an unprecedented pace since the late 20th century. As a result, the feedback of sea ice anomalies for atmospheric circulation has been increasingly evidenced. While climatic models almost consistently reproduced a decreasing trend of sea ice cover, the reported results show a large distribution. To evaluate the performance of models for simulating Arctic sea ice cover and its potential role in climate change, this study constructed a reasonable metric by synthesizing both linear trends and anomalies of sea ice. This study particularly focused on the Barents Sea and the Kara Sea, where sea ice anomalies have the highest potential to affect the atmosphere. The investigated models can be grouped into three categories according to their normalized skill scores. The strong contrast among the multi-model ensemble means of different groups demonstrates the robustness and rationality of this method. Potential factors that account for the different performances of climate models are further explored. The results show that model performance depends more on the ozone datasets that are prescribed by the model rather than on the chemical representation of ozone.