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北极气旋的季节、年际变化及其与北极海冰、大气遥相关的关系
引用本文:魏立新,秦听,李珵.北极气旋的季节、年际变化及其与北极海冰、大气遥相关的关系[J].海洋学报(英文版),2017,36(10):1-7.
作者姓名:魏立新  秦听  李珵
作者单位:国家海洋环境预报中心国家海洋局海洋灾害预报技术研究重点实验室, 北京, 100081,国家海洋环境预报中心国家海洋局海洋灾害预报技术研究重点实验室, 北京, 100081,国家海洋环境预报中心国家海洋局海洋灾害预报技术研究重点实验室, 北京, 100081;教育部物理海洋重点实验室中国海洋大学, 青岛, 266100
摘    要:The seasonal and inter-annual variations of Arctic cyclone are investigated. An automatic cyclone tracking algorithm developed by University of Reading was applied on the basis of European Center for Medium-range Weather Forecasts(ECMWF) ERA-interim mean sea level pressure field with 6 h interval for 34 a period. The maximum number of the Arctic cyclones is counted in winter, and the minimum is in spring not in summer.About 50% of Arctic cyclones in summer generated from south of 70°N, moving into the Arctic. The number of Arctic cyclones has large inter-annual and seasonal variabilities, but no significant linear trend is detected for the period 1979–2012. The spatial distribution and linear trends of the Arctic cyclones track density show that the cyclone activity extent is the widest in summer with significant increasing trend in CRU(central Russia)subregion, and the largest track density is in winter with decreasing trend in the same subregion. The linear regressions between the cyclone track density and large-scale indices for the same period and pre-period sea ice area indices show that Arctic cyclone activities are closely linked to large-scale atmospheric circulations, such as Arctic Oscillation(AO), North Atlantic Oscillation(NAO) and Pacific-North American Pattern(PNA). Moreover,the pre-period sea ice area is significantly associated with the cyclone activities in some regions.

关 键 词:北极气旋  气旋自动追踪算法  大尺度气候指数  海冰面积指数  回归分析
收稿时间:2017/6/27 0:00:00

Seasonal and inter-annual variations of Arctic cyclones and their linkage with Arctic sea ice and atmospheric teleconnections
WEI Lixin,QIN Ting and LI Cheng.Seasonal and inter-annual variations of Arctic cyclones and their linkage with Arctic sea ice and atmospheric teleconnections[J].Acta Oceanologica Sinica,2017,36(10):1-7.
Authors:WEI Lixin  QIN Ting and LI Cheng
Institution:1.Key Laboratory of Research on Marine Hazards Forecasting, National Marine Environmental Forecasting Center, State Oceanic Administration, Beijing 100081, China2.Key Laboratory of Research on Marine Hazards Forecasting, National Marine Environmental Forecasting Center, State Oceanic Administration, Beijing 100081, China;Physical Oceanography Laboratory, Ocean University of China, Qingdao 266100, China
Abstract:The seasonal and inter-annual variations of Arctic cyclone are investigated. An automatic cyclone tracking algorithm developed by University of Reading was applied on the basis of European Center for Medium-range Weather Forecasts (ECMWF) ERA-interim mean sea level pressure field with 6 h interval for 34 a period. The maximum number of the Arctic cyclones is counted in winter, and the minimum is in spring not in summer. About 50% of Arctic cyclones in summer generated from south of 70°N, moving into the Arctic. The number of Arctic cyclones has large inter-annual and seasonal variabilities, but no significant linear trend is detected for the period 1979-2012. The spatial distribution and linear trends of the Arctic cyclones track density show that the cyclone activity extent is the widest in summer with significant increasing trend in CRU (central Russia) subregion, and the largest track density is in winter with decreasing trend in the same subregion. The linear regressions between the cyclone track density and large-scale indices for the same period and pre-period sea ice area indices show that Arctic cyclone activities are closely linked to large-scale atmospheric circulations, such as Arctic Oscillation (AO), North Atlantic Oscillation (NAO) and Pacific-North American Pattern (PNA). Moreover, the pre-period sea ice area is significantly associated with the cyclone activities in some regions.
Keywords:Arctic cyclones  automated detection and tracking algorithm  large-scale climate indices  sea ice area index  regression analysis
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