globalchange  > 气候变化与战略
DOI: 10.1016/j.atmosres.2020.104897
Title:
An alternative approach for quantitatively estimating climate variability over China under the effects of ENSO events
Author: Zhou P.; Liu Z.; Cheng L.
Source Publication: Atmospheric Research
ISSN: 1698095
Publishing Year: 2020
Volume: 238
Language: 英语
Keyword: China ; Climate variability ; Conditional copula ; ENSO ; Multivariate
Scopus Keyword: Atmospheric pressure ; China ; Climate variability ; Conditional copula ; ENSO ; Multivariate ; Climatology ; climate variation ; El Nino-Southern Oscillation ; estimation method ; multivariate analysis ; precipitation (climatology) ; quantitative analysis ; China
English Abstract: Previous studies generally use the traditional composite analysis to diagnose the physical interrelationships between the El Niño-Southern Oscillation (ENSO) and climate variables such as temperature and precipitation. This study presents a simple probabilistic tool for quantifying changes in precipitation and temperature in the wet season over China during either developing or decaying phases of El Niño and La Niña events with a particular focus on the extreme conditions. We first construct the joint dependence structure between each climate variable (e.g. precipitation and temperature) and ENSO using a variety of bivariate copulas. We then examine variations of climate variables related to ENSO conditions through the conditioning sets of bivariate copulas. This approach allows a quantitative estimation of precipitation and temperature anomalies and a delineation of their spatial pattern across the country under individual effects of the developing and decaying phases of ENSO events. Comparison of results produced by the conditional probabilistic approach with those by conventional composite analysis reveals large similarity, highlighting the robustness of the presented approach in examining the response of climate variations to ENSO phases and its potential for a broader application in other regional/global diagnoses. Of particular importance is that this approach offers a way to yield probabilistic predictive information on extreme climate anomalies conditioned by ENSO signals. Despite only ENSO's effect considered in the current study, the presented approach could also be used to detect the effect of other large-scale climate signals on regional or global climate variations. © 2020 Elsevier B.V.
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被引频次[WOS]:2   [查看WOS记录]     [查看WOS中相关记录]
Document Type: 期刊论文
Identifier: http://119.78.100.158/handle/2HF3EXSE/158072
Appears in Collections:气候变化与战略

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Affiliation: Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou Institute of Geography, Guangzhou, 510070, China; Center for Water Resources and Environment, School of Civil Engineering, Sun Yat-Sen University, Guangzhou, 510275, China; Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519082, China; Guangdong Engineering Technology Research Center of Water Security Regulation and Control for Southern China, Sun Yat-sen University, Guangzhou, 510275, China; Department of Geosciences, University of Arkansas, Fayetteville, AR 72701, United States

Recommended Citation:
Zhou P.,Liu Z.,Cheng L.. An alternative approach for quantitatively estimating climate variability over China under the effects of ENSO events[J]. Atmospheric Research,2020-01-01,238
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