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Copula-based non-stationarity detection of the precipitation-temperature dependency structure dynamics and possible driving mechanism

文献类型：期刊论文

作者Dong, Haixia1; Huang, Shengzhi1; Fang, Wei1; Leng, Guoyong2; Wang, Hao3; Ren, Kang1; Zhao, Jing1; Ma, Chuanhui1
刊名ATMOSPHERIC RESEARCH
出版日期2021-02-01
卷号249页码:15
ISSN号0169-8095
关键词Precipitation-temperature dependency structure Non-stationarity Copula-based Likelihood-ratio method Double mass curve Teleconnection factors Driving mechanism
DOI10.1016/j.atmosres.2020.105280
通讯作者Huang, Shengzhi(huangshengzhi7788@126.com)
英文摘要In the context of global warming, precipitation (P) and temperature (T) are the most important climate indicators playing important roles in the hydrological cycle. Nevertheless, the response of their dependency structures to the changing environment is not clearly revealed on a regional or global scale. To this end, the non-stationarity of the precipitation-temperature (P-T) dependency structure was identified via the Copula-based Likelihood-ratio (CLR) method, which further verified through the frequently used double mass curve method. Furthermore, local meteorological factors (e.g. wind speed (WS), sunshine duration (SD), relative humidity (RH) and vapour pressure (VP)) and teleconnection factors (e.g. the Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO), El Nino-Southern Oscillation (ENSO) and Sunspots) were selected to explore possible driving forces and mechanism of the P-T dependency structure dynamics. The Datong River Basin (DRB), located in the Qinghai-Tibet Plateau, one of the climate change-sensitive and eco-sensitive areas worldwide, was selected as a case study. Results showed that: (1) the CLR method simultaneously capturing bivariate linear and nonlinear information is more superior than the double mass curve in detecting the non-stationarity of bivariate dependency structure; (2) change points of P-T dependency structure were identified at Qilian and Minhe stations, indicating that its non-stationarity occurred in the DRB; (3) in terms of local meteorological factors, the P-T dependency structure dynamics were directly driven by the VP, which was closely associated with the Clausius-Clapeyron (CC) equation where P and T would be theoretically linked by the atmospheric moisture; (4) in terms of teleconnection factors, the impacts of AO and PDO on local meteorological (VP, WS, and RH) are dominant, which further leads to the change in the P-T dependency structure dynamics. Generally, this study provides important insights into the response of the P-T dependency structure dynamics to a changing environment, where the proposed research framework could be extended to any other watershed and any bivariate hydrometeorological elements.
资助项目National Key Research and Development Program of China[2017YFC0405900] ; National Natural Science Foundation of China[51709221] ; China Postdoctoral Science Foundation[2018M640155] ; Key Laboratory Research Projects of the Education Department of Shaanxi Province[17JS104] ; Planning Project of Science and Technology of Water Resources of Shaanxi[2015slkj-27] ; Planning Project of Science and Technology of Water Resources of Shaanxi[2017slkj-19] ; Open Research Fund of State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin (China Institute of Water Resources and Hydropower Research)[IWHR-SKL-KF201803] ; Belt and Road Special Foundation of the State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering[2018490711]
WOS研究方向Meteorology & Atmospheric Sciences
语种英语
出版者ELSEVIER SCIENCE INC
WOS记录号WOS:000630007700001
资助机构National Key Research and Development Program of China ; National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; Key Laboratory Research Projects of the Education Department of Shaanxi Province ; Planning Project of Science and Technology of Water Resources of Shaanxi ; Open Research Fund of State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin (China Institute of Water Resources and Hydropower Research) ; Belt and Road Special Foundation of the State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering
源URL[http://ir.igsnrr.ac.cn/handle/311030/162144]  
专题中国科学院地理科学与资源研究所
通讯作者Huang, Shengzhi
作者单位1.Xian Univ Technol, State Key Lab Ecohydraul Northwest Arid Reg China, Xian 710048, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
3.China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, Beijing 100038, Peoples R China
推荐引用方式
GB/T 7714		 Dong, Haixia,Huang, Shengzhi,Fang, Wei,et al. Copula-based non-stationarity detection of the precipitation-temperature dependency structure dynamics and possible driving mechanism[J]. ATMOSPHERIC RESEARCH,2021,249:15.
APA Dong, Haixia.,Huang, Shengzhi.,Fang, Wei.,Leng, Guoyong.,Wang, Hao.,...&Ma, Chuanhui.(2021).Copula-based non-stationarity detection of the precipitation-temperature dependency structure dynamics and possible driving mechanism.ATMOSPHERIC RESEARCH,249,15.
MLA Dong, Haixia,et al."Copula-based non-stationarity detection of the precipitation-temperature dependency structure dynamics and possible driving mechanism".ATMOSPHERIC RESEARCH 249(2021):15.

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来源：地理科学与资源研究所

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