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中国大范围海气型与年际地表风速变化的遥联关系:区域和季节特征。

Teleconnections between large-scale oceanic-atmospheric patterns and interannual surface wind speed variability across China: Regional and seasonal patterns.

机构信息

Key Laboratory of Humid Subtropical Eco-geographical Process (Ministry of Education), College of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China.

Centro de Investigaciones sobre Desertificación, Consejo Superior de Investigaciones Científicas (CIDE, CSIC-UV-Generalitat Valenciana), Moncada, Valencia, Spain; Regional Climate Group, Department of Earth Sciences, University of Gothenburg, Box 460, S-405 30 Gothenburg, Sweden.

出版信息

Sci Total Environ. 2022 Sep 10;838(Pt 1):156023. doi: 10.1016/j.scitotenv.2022.156023. Epub 2022 May 18.

DOI:10.1016/j.scitotenv.2022.156023
PMID:35595142
Abstract

Great attention has been paid to the long-term decline in terrestrial near-surface wind speed (SWS) in China. However, how the SWS varies with regions and seasons and what modulates these changes remain unclear. Based on quality-controlled and homogenized terrestrial SWS data from 596 stations, the covarying SWS patterns during the Asian Summer Monsoon (ASM) and the Asian Winter Monsoon (AWM) seasons are defined for China using empirical orthogonal function (EOF) analysis for 1961-2016. The dominant SWS features represented by EOF1 patterns in both seasons show a clear decline over most regions of China. The interannual variability of the EOF1 patterns is closely related to the Northeast Asia Low Pressure (NEALP) and the Arctic Oscillation (AO), respectively. The EOF2 and EOF3 patterns during ASM (AWM) season describe a dipole mode of SWS between East Tibetan Plateau and East China Plain (between East Tibetan Plateau and Northeast China), and between Southeast and Northeast China (between Northeast China and the coastal areas of Southeast China), respectively. These dipole structures of SWS changes are closely linked with the oceanic-atmospheric oscillations on interannual scale.

摘要

人们高度关注中国陆地区域近地表风速(SWS)的长期下降。然而,SWS 如何随地区和季节变化,以及哪些因素调节这些变化尚不清楚。本研究基于 1961 年至 2016 年期间 596 个站点经过质量控制和均一化处理的陆地区域 SWS 数据,采用经验正交函数(EOF)分析方法,定义了中国在亚洲夏季风(ASM)和亚洲冬季风(AWM)季节的共变 SWS 模式。EOF1 模式代表两个季节的主导 SWS 特征,表明中国大部分地区的 SWS 呈明显下降趋势。EOF1 模式的年际变化与东北亚低气压(NEALP)和北极涛动(AO)密切相关。ASM(AWM)季节的 EOF2 和 EOF3 模式分别描述了青藏高原东部和中国东部平原(青藏高原东部和东北地区之间)以及东南和东北地区(东北地区和中国东南沿海地区之间)之间的 SWS 偶极子模式变化。这些 SWS 变化的偶极子结构与海洋大气在年际尺度上的振荡密切相关。

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