Application of regional frequency analysis to the estimation of extreme storm surges
Identifieur interne : 000713 ( France/Analysis ); précédent : 000712; suivant : 000714Application of regional frequency analysis to the estimation of extreme storm surges
Auteurs : Pietro Bernardara [France] ; Marc Andreewsky [France] ; Michel Benoit [France]Source :
- Journal of Geophysical Research: Oceans [ 0148-0227 ] ; 2011-02.
Abstract
Traditionally, extreme value theory is applied to single‐site series of surge observations in order to estimate the probability of occurrence of extreme events at that particular site. However, single‐site analyses give uncertain estimation of extreme quantiles, mainly because of the limited duration of observation periods. In order to reduce this uncertainty, regional frequency analysis (RFA) approaches suggest collecting information not only from a single‐site series but also from all (statistically) similar available series of observation. The use of RFA is widely increasing in geosciences, but few applications have been attempted yet for surge estimation. The aim of this study is to examine the applicability of RFA to extreme storm surges. The surge data observed at 18 French harbors, located on the Atlantic coast from the Spanish to Belgian borders, were collected. The series span a period of 30 years, on average, with the longest series going back to the 19th century. Stationary and independent samples of extreme surges (peaks over a given threshold) are extracted and their (statistical) homogeneity has been tested via heterogeneity and discordancy measures based on L moments. Homogeneous regions have been identified and, in order to merge information on frequency of occurrence of surges from all the sites, a surge index pooling method is defined. Finally, a regional frequency distribution has been estimated. The hypothesis and the applicability of RFA application are discussed, with some ideas for future developments in the research direction.
Url:
DOI: 10.1029/2010JC006229
Affiliations:
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Geophys. Res.</title><idno type="ISSN">0148-0227</idno><idno type="eISSN">2156-2202</idno><imprint><publisher>Blackwell Publishing Ltd</publisher><date type="published" when="2011-02">2011-02</date><biblScope unit="volume">116</biblScope><biblScope unit="issue">C2</biblScope><biblScope unit="page" from="/">n/a</biblScope><biblScope unit="page" to="/">n/a</biblScope></imprint><idno type="ISSN">0148-0227</idno></series><idno type="istex">AF8CFDA8EDD75D7008BADDDD64A8E7AF0B2B3219</idno><idno type="DOI">10.1029/2010JC006229</idno><idno type="ArticleID">2010JC006229</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0148-0227</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract">Traditionally, extreme value theory is applied to single‐site series of surge observations in order to estimate the probability of occurrence of extreme events at that particular site. However, single‐site analyses give uncertain estimation of extreme quantiles, mainly because of the limited duration of observation periods. In order to reduce this uncertainty, regional frequency analysis (RFA) approaches suggest collecting information not only from a single‐site series but also from all (statistically) similar available series of observation. The use of RFA is widely increasing in geosciences, but few applications have been attempted yet for surge estimation. The aim of this study is to examine the applicability of RFA to extreme storm surges. The surge data observed at 18 French harbors, located on the Atlantic coast from the Spanish to Belgian borders, were collected. The series span a period of 30 years, on average, with the longest series going back to the 19th century. Stationary and independent samples of extreme surges (peaks over a given threshold) are extracted and their (statistical) homogeneity has been tested via heterogeneity and discordancy measures based on L moments. Homogeneous regions have been identified and, in order to merge information on frequency of occurrence of surges from all the sites, a surge index pooling method is defined. Finally, a regional frequency distribution has been estimated. 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