DOI: 10.1073/pnas.1913049117
论文题名: Probabilistic reanalysis of storm surge extremes in Europe
作者: Calafat F.M. ; Marcos M.
刊名: Proceedings of the National Academy of Sciences of the United States of America
ISSN: 0027-8424
出版年: 2020
卷: 117, 期: 4 起始页码: 1877
结束页码: 1883
语种: 英语
英文关键词: Bayesian hierarchical model
; Extremes
; Flooding
; Sea level
; Storm surge
Scopus关键词: Article
; Atlantic Ocean
; Bayes theorem
; coastal waters
; distribution parameters
; Europe
; extreme weather
; North Sea
; priority journal
; reduction (chemistry)
; space
; storm surge
; time
; computer simulation
; disaster planning
; flooding
; flow kinetics
; oceanography
; procedures
; risk assessment
; sea
; statistical model
; Bayes Theorem
; Computer Simulation
; Disaster Planning
; Europe
; Floods
; Models, Statistical
; Oceanography
; Oceans and Seas
; Rheology
; Risk Assessment
英文摘要: Extreme sea levels are a significant threat to life, property, and the environment. These threats are managed by coastal planers through the implementation of risk mitigation strategies. Central to such strategies is knowledge of extreme event probabilities. Typically, these probabilities are estimated by fitting a suitable distribution to the observed extreme data. Estimates, however, are often uncertain due to the small number of extreme events in the tide gauge record and are only available at gauged locations. This restricts our ability to implement cost-effective mitigation. A remarkable fact about sea-level extremes is the existence of spatial dependences, yet the vast majority of studies to date have analyzed extremes on a site-by-site basis. Here we demonstrate that spatial dependences can be exploited to address the limitations posed by the spatiotemporal sparseness of the observational record. We achieve this by pooling all of the tide gauge data together through a Bayesian hierarchical model that describes how the distribution of surge extremes varies in time and space. Our approach has two highly desirable advantages: 1) it enables sharing of information across data sites, with a consequent drastic reduction in estimation uncertainty; 2) it permits interpolation of both the extreme values and the extreme distribution parameters at any arbitrary ungauged location. Using our model, we produce an observation-based probabilistic reanalysis of surge extremes covering the entire Atlantic and North Sea coasts of Europe for the period 1960-2013. © 2020 National Academy of Sciences. All rights reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/164344
Appears in Collections: 气候变化与战略
There are no files associated with this item.
作者单位: Calafat, F.M., Department of Marine Physics and Ocean Climate, National Oceanography Centre, Liverpool, L3 5DA, United Kingdom; Marcos, M., Department of Oceanography and Global Change, Mediterranean Institute for Advanced Studies, Spanish National Research Council and University of the Balearic Islands (CSIC-UIB), Esporles, 07190, Spain, Department of Physics, University of the Balearic Islands, Palma, 07122, Spain
Recommended Citation:
Calafat F.M.,Marcos M.. Probabilistic reanalysis of storm surge extremes in Europe[J]. Proceedings of the National Academy of Sciences of the United States of America,2020-01-01,117(4)