Gao, Meng
; Zheng, Hongzhen发表期刊STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
ISSN1436-3240
2018-05
卷号32期号:5页码:1299-1315
关键词Temperature extremesGEVNon-stationarityReturn levelAtmospheric circulation
研究领域Engineering, Environmental; Engineering, Civil; Environmental Sciences; Statistics & Probability; Water Resources
DOI10.1007/s00477-017-1482-0
产权排序[Gao, Meng; Zheng, Hongzhen] Chinese Acad Sci, Yantai Inst Coastal Zone Res, 17 Chunhui Rd, Yantai 264003, Peoples R China; [Zheng, Hongzhen] Univ Chinese Acad Sci, Beijing 100049, 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In a changing climate, the common assumption of stationarity of climate extremes has been increasingly challenged, raising the need to incorporate non-stationarity in extreme value modeling. In this study, quantile regression is used to identify the trends of annual temperature extremes and their correlations with two large climate patterns, the western Pacific subtropical high (WPSH) and the Arctic Oscillation (AO) at 357 stations in China. Statistical significant positive trends and correlations between warm (or cold) temperature extremes and WPSH (or AO) have been detected at most stations. The influence of WPSH on warm extremes is significant in southern China, while the AO mainly affects the cold extremes in northern and eastern China. Then, annual temperature extremes are fitted to generalized extreme value (GEV) distributions with time-varying parameters. The summer (or winter) mean daily maximum (or minimum) temperatures and two climate indices, the WPSH index and the AO index, are chosen as covariates. In total, 16 candidate GEV distribution models are constructed, and the best fitting model with the lowest Bayesian information criterion (BIC) is selected. The 20-year return levels of annual warm (or cold) extremes in the period 1961-1980 and 1991-2010 are computed and compared. The changes of 20-year return levels of annual warm and cold extremes are jointly determined by trend and distributional changes of annual temperature extremes. Analysis of large scale atmospheric circulation changes indicate that a strengthening anticyclonic circulation and increasing geopotential height in recent decades may have contributed to the changes in temperature extremes in China.
文章类型Article
资助机构Youth Innovation Promotion Association of CAS [2016195]; CAS Knowledge Innovation Project [KZCX2-EW-QN209]; National Natural Science Foundation of China [31570423]
收录类别SCI
语种英语
关键词[WOS]CLIMATE-CHANGE; QUANTILE REGRESSION; PRECIPITATION EXTREMES; ARCTIC OSCILLATION; FREQUENCY-ANALYSIS; TRENDS; RISK; SIMULATIONS; VARIABILITY; STATIONARY
研究领域[WOS]Engineering; Environmental Sciences & Ecology; Mathematics; Water Resources
WOS记录号WOS:000429464900007
引用统计被引频次：13[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/133337/24371
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, 17 Chunhui Rd, Yantai 264003, Peoples R China;
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714Gao, Meng,Zheng, Hongzhen. Nonstationary extreme value analysis of temperature extremes in China[J]. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT,2018,32(5):1299-1315.
APAGao, Meng,&Zheng, Hongzhen.(2018).Nonstationary extreme value analysis of temperature extremes in China.STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT,32(5),1299-1315.
MLAGao, Meng,et al."Nonstationary extreme value analysis of temperature extremes in China".STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT 32.5(2018):1299-1315.
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