Gao, M
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发表期刊ATMOSPHERIC RESEARCH
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ISSN0169-8095
2019-05-15
卷号220页码:46-56
关键词Atmospheric circulationSelf-organizing mapTemperature anomalyQuantitative partitionTeleconnection
研究领域Meteorology & Atmospheric Sciences
DOI10.1016/j.atmosres.2019.01.005
产权排序[Gao, Meng; Yang, Ye; Gao, Zhiqiang] Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China; [Yang, Ye] Univ Chinese Acad Sci, Beijing 100049, Peoples R China; [Shi, Honghua] State Ocean Adm, Inst Oceanog 1, Qingdao 266061, Peoples R China; [Shi, Honghua] Qingdao Natl Lab Marine Sci & Technol, Lab Marine Geol, Qingdao 266061, Peoples R China
作者部门海岸带信息集成与综合管理实验室
英文摘要Anomalous atmospheric circulation patterns in relation to surface air temperature anomalies during 1979-2017 within China arc investigated using the self-organizing map neural network. The SOM-based synoptic analysis begins with classifying the normalized daily anomalies of 500-hPa geopotential height, zonal and meridional winds fields into 4 x 4 SOM arrays in winter and summer, respectively. The synoptic analysis shows that the spatial distributions of anomalous geopotential height (anticyclones or cyclones) are highly consistent with that of surface air temperature anomalies within China. The influences of two teleconnections, the El Nifio-Southern Oscillation and the Arctic Oscillation, on anomalous atmospheric circulation patterns and surface air temperature anomalies are also visually investigated based on the above SOM classification. Changes of node frequencies in winter and summer for the two periods 1979-1998 and 1999-2017 are also observed indicting the changes of regional atmospheric circulations. Our analysis also shows that the decrease of cold extreme and the increase of warm extreme in the two periods are mainly caused by the thermodynamics factor within China, while change in atmospheric circulation sometimes contributes negatively to temperature extreme changes.
文章类型Article
资助机构Youth Innovation Promotion Association of CAS [2016195]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China [31570423]
收录类别SCI
语种英语
关键词[WOS]SELF-ORGANIZING MAP; ARCTIC OSCILLATION; PRECIPITATION EXTREMES; CLIMATE-CHANGE; TRENDS; ENSO; ASSOCIATION; VARIABILITY; PERFORMANCE; FREQUENCY
研究领域[WOS]Meteorology & Atmospheric Sciences
WOS记录号WOS:000459364100005
引用统计被引频次:10[WOS][WOS记录][WOS相关记录]
文献类型期刊论文
条目标识符http://ir.yic.ac.cnhttp://ir.yic.ac.cn/handle/133337/24941
专题中科院海岸带环境过程与生态修复重点实验室_海岸带信息集成与战略规划研究中心
中科院海岸带环境过程与生态修复重点实验室
作者单位1.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China;
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China;
3.State Ocean Adm, Inst Oceanog 1, Qingdao 266061, Peoples R China;
4.Qingdao Natl Lab Marine Sci & Technol, Lab Marine Geol, Qingdao 266061, Peoples R China
推荐引用方式
GB/T 7714Gao, M,Yang, Y,Shi, HH,et al. SOM-based synoptic analysis of atmospheric circulation patterns and temperature anomalies in China[J]. ATMOSPHERIC RESEARCH,2019,220:46-56.
APAGao, M,Yang, Y,Shi, HH,&Gao, ZQ.(2019).SOM-based synoptic analysis of atmospheric circulation patterns and temperature anomalies in China.ATMOSPHERIC RESEARCH,220,46-56.
MLAGao, M,et al."SOM-based synoptic analysis of atmospheric circulation patterns and temperature anomalies in China".ATMOSPHERIC RESEARCH 220(2019):46-56.
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