Preprints
https://doi.org/10.5194/nhess-2016-378
https://doi.org/10.5194/nhess-2016-378

  27 Feb 2017

27 Feb 2017

Review status: this preprint has been withdrawn by the authors.

Homogenous regions based on extremogram for regional frequency analysis of extreme skew storm surges

Marc Andreewsky1, Samuel Griolet2, Yasser Hamdi3, Pietro Bernardara4, and Roberto Frau1 Marc Andreewsky et al.
  • 1Department EDF-R&D-LNHE, Chatou, 78401, France
  • 2Polytech Lyon, Rochetaillée sur Saône, 69270, France
  • 3IRSN, Fontenay-Aux-Roses, BP17, 92262, France
  • 4EDF Energy R&D UK Center, SW1E5JL, UK

Abstract. To resist marine submersion, coastal protection must be designed by taking into account the most accurate estimate of the return levels of extreme events, such as storm surges. However, because of the paucity of data, local statistical analyses often lead to poor frequency estimations. Regional Frequency Analysis (RFA) reduces the uncertainties associated with these estimations, by extending the dataset from local (only available data at the target site) to regional (data at all the neighboring sites including the target site) and by assuming, at the scale of a region, a similar extremal behavior. RFA, based on the index flood method, assumes that, in a homogeneous region, observations at sites, normalized by a local index, follow the same probability distribution. In this work, the spatial extremogram approach is used to form a physically homogeneous region centered on the target site. The approach is applied on a database of extreme skew storm surges and used to carry out a RFA.

This preprint has been withdrawn.

Marc Andreewsky et al.

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Marc Andreewsky et al.

Marc Andreewsky et al.

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This preprint has been withdrawn.

Short summary
The aim of our study is to achieve extreme statistics on skew storm surges and to reduce uncertainties that are found in a local analysis by using a regional frequency analysis, for which, an important step, is to form a physically homogeneous region. Our method, which allows one to shape those physical homogeneous regions, is based on the use of the spatial extremogram, a correlation between extremes from two sites, and the regions found are consistent geographically and without border effect.
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