The Predictability of Ocean Environments that Contributed to the 2020/21 Extreme Cold Events in China:2020/21 La Niña and 2020 Arctic Sea Ice Loss
在中国贡献了 2020/21 极端寒冷事件的海洋环境的可预测性: 2020/21 La Ni ? 一 and 2020 北极海冰损失作者机构：International Center for Climate and Environment Science(ICCES)Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science&TechnologyNanjing 210044China Department of Atmospheric and Environmental Sciences University at AlbanyState University of New YorkAlbanyNY 12222USA Department of Atmospheric and Oceanic Sciences&Institute of Atmospheric SciencesFudan UniversityShanghai 200438China State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG)Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China School of Atmospheric SciencesSun Yat-sen UniversityZhuhai 519082China National Climate CenterBeijing 100081China University of Chinese Academy of SciencesBeijing 100049China Beijing Municipal Climate CenterBeijing 100089China
出 版 物：《Advances in Atmospheric Sciences》 (大气科学进展（英文版）)
年 卷 期：2022年第39卷第4期
页 面：658-675页
核心收录：
基 金：supported by the Key Research Program of Frontier Sciences,CAS (Grant No. ZDBS-LY-DQC010) the National Natural Science Foundation of China (Grant Nos. 41876012 and 41861144015,42175045) the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No.XDB42000000)
主 题：extreme cold event predictability La Niña Arctic sea ice loss
摘 要：Several consecutive extreme cold events impacted China during the first half of winter 2020/21,breaking the low-temperature records in many *** to make accurate climate predictions of extreme cold events is still an urgent *** synergistic effect of the warm Arctic and cold tropical Pacific has been demonstrated to intensify the intrusions of cold air from polar regions into middle-high latitudes,further influencing the cold conditions in ***,climate models failed to predict these two ocean environments at expected lead *** seasonal climate forecasts only predicted the 2020/21 La Niña after the signal had already become apparent and significantly underestimated the observed Arctic sea ice loss in autumn 2020 with a 1-2 month *** this work,the corresponding physical factors that may help improve the accuracy of seasonal climate predictions are further *** the 2020/21 La Niña prediction,through sensitivity experiments involving different atmospheric-oceanic initial conditions,the predominant southeasterly wind anomalies over the equatorial Pacific in spring of 2020 are diagnosed to play an irreplaceable role in triggering this cold event.A reasonable inclusion of atmospheric surface winds into the initialization will help the model predict La Niña development from the early spring of *** predicting the Arctic sea ice loss in autumn 2020,an anomalously cyclonic circulation from the central Arctic Ocean predicted by the model,which swept abnormally hot air over Siberia into the Arctic Ocean,is recognized as an important contributor to successfully predicting the minimum Arctic sea ice extent.
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