4.4 Article

Seasonal and inter-annual variations of Arctic cyclones and their linkage with Arctic sea ice and atmospheric teleconnections

期刊

ACTA OCEANOLOGICA SINICA
卷 36, 期 10, 页码 1-7

出版社

SPRINGER
DOI: 10.1007/s13131-017-1117-9

关键词

Arctic cyclones; automated detection and tracking algorithm; large-scale climate indices; sea ice area index; regression analysis

资金

  1. Chinese Polar Environment Comprehensive Investigation and Assessment Programmes [2016-04-03]
  2. National Key Research and Development Program of China [2016YFC1402701]

向作者/读者索取更多资源

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 degrees 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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.4
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据