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| Titel |
A two-step framework for over-threshold modelling of environmental extremes |
| VerfasserIn |
P. Bernardara, F. Mazas, X. Kergadallan, L. Hamm |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Sciences ; 14, no. 3 ; Nr. 14, no. 3 (2014-03-20), S.635-647 |
| Datensatznummer |
250118337
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| Publikation (Nr.) |
 copernicus.org/nhess-14-635-2014.pdf |
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| Zusammenfassung |
| The evaluation of the probability of occurrence of extreme natural events is
important for the protection of urban areas, industrial facilities and
others. Traditionally, the extreme value theory (EVT) offers a valid
theoretical framework on this topic. In an over-threshold modelling (OTM)
approach, Pickands' theorem, (Pickands, 1975) states that, for a sample
composed by independent and identically distributed (i.i.d.) values, the
distribution of the data exceeding a given threshold converges through a
generalized Pareto distribution (GPD). Following this theoretical result, the
analysis of realizations of environmental variables exceeding a threshold
spread widely in the literature. However, applying this theorem to an
auto-correlated time series logically involves two successive and
complementary steps: the first one is required to build a sample of i.i.d.
values from the available information, as required by the EVT; the second
to set the threshold for the optimal convergence toward the GPD. In the past,
the same threshold was often employed both for sampling observations and for
meeting the hypothesis of extreme value convergence. This confusion can
lead to an erroneous understanding of methodologies and tools available in
the literature. This paper aims at clarifying the conceptual framework
involved in threshold selection, reviewing the available methods for the
application of both steps and illustrating it with a double threshold
approach. |
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