A geostatistical extreme-value framework for fast simulation of natural hazard events

We develop a statistical framework for simulating natural hazard events that combines extreme value theory and geostatistics. Robust generalized additive model forms represent generalized Pareto marginal distribution parameters while a Student's t-process captures spatial dependence and gives a...

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Bibliographic Details
Published inProceedings of the Royal Society. A, Mathematical, physical, and engineering sciences Vol. 472; no. 2189; pp. 1 - 20
Main Authors Youngman, Benjamin D., Stephenson, David B.
Format Journal Article
LanguageEnglish
Published THE ROYAL SOCIETY 01.05.2016
Subjects
Catastrophe modeling
Geostatistics
Gusts
Natural hazards
Quantile regression
Simulations
Spatial models
Statistics
Wind
Wind velocity
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Summary:We develop a statistical framework for simulating natural hazard events that combines extreme value theory and geostatistics. Robust generalized additive model forms represent generalized Pareto marginal distribution parameters while a Student's t-process captures spatial dependence and gives a continuous-space framework for natural hazard event simulations. Efficiency of the simulation method allows many years of data (typically over 10000) to be obtained at relatively little computational cost. This makes the model viable for forming the hazard module of a catastrophe model. We illustrate the framework by simulating maximum wind gusts for European windstorms, which are found to have realistic marginal and spatial properties, and validate well against wind gust measurements.
ISSN:1364-5021
1471-2946