globalchange  > 科学计划与规划
DOI: 10.1002/2016GL069445
论文题名:
On the emergence of rainfall extremes from ordinary events
作者: Zorzetto E.; Botter G.; Marani M.
刊名: Geophysical Research Letters
ISSN: 0094-8772
EISSN: 1944-8503
出版年: 2016
卷: 43, 期:15
起始页码: 8076
结束页码: 8082
语种: 英语
英文关键词: extremes ; metastatistics ; rainfall
Scopus关键词: Earth sciences ; Geophysics ; Central problems ; Daily rainfall ; Extreme value theory ; Extremes ; Generation process ; Metastatistics ; Predictive power ; Rainfall extremes ; Rain ; Mink enteritis virus
英文摘要: The analysis and estimation of extreme event occurrences is a central problem in many fields of geoscience. Advancements in the study of extreme events have recently been limited, arguably in connection with asymptotic assumptions in the traditional extreme value theory (EVT) and with its focusing on a small fraction of the available observations representing the tail properties of the underlying event generation process. Here we develop a Metastatistical Extreme Value framework (MEV) which relaxes limiting assumptions at the basis of the traditional EVT and accounts for the full distribution of the underlying “ordinary” events. We apply this general approach to the relevant case of daily rainfall and find that the MEV approach reduces the uncertainty in the estimation of high-quantile extremes by up to 50% with respect to the classical EVT. The improved predictive power of the MEV framework is connected with its recognizing that extremes emerge from repeated sampling of ordinary events, thereby being able to use all available observations. ©2016. American Geophysical Union. All Rights Reserved.
URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84981549816&doi=10.1002%2f2016GL069445&partnerID=40&md5=15dd1b60203adb2e9e0e02d5a2b279b8
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/9735
Appears in Collections:科学计划与规划
气候变化与战略

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作者单位: Nicholas School of the Environment, Duke University, Durham, NC, United States

Recommended Citation:
Zorzetto E.,Botter G.,Marani M.. On the emergence of rainfall extremes from ordinary events[J]. Geophysical Research Letters,2016-01-01,43(15).
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