Generalized Pareto processes for simulating space-time extreme events: an application to precipitation reanalyses

Abstract : To better manage the risks of destructive natural disasters, impact models can be fed with simulations of extreme scenarios to study the sensitivity to temporal and spatial variability. We propose a semi-parametric stochastic framework that enables simulation of realistic spatio-temporal extreme felds using a moderate number of observed extreme space-time episodes to generate an unlimited number of extreme scenarios of any magnitude. Our framework draws sound theoretical justification from extreme value theory, building on generalized Pareto limit processes. For illustration on hourly gridded precipitation data in Mediterranean France, we calculate risk measures using extreme event simulations for yet unobserved magnitudes.
Complete list of metadatas

Cited literature [54 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-02136681
Contributor : Fatima Palacios Rodriguez <>
Submitted on : Wednesday, December 18, 2019 - 12:34:52 PM
Last modification on : Tuesday, January 21, 2020 - 10:32:02 AM

File

PalaciosRodriguezToulemondeCar...
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02136681, version 2

Citation

Fátima Palacios-Rodríguez, Gwladys Toulemonde, Julie Carreau, Thomas Opitz. Generalized Pareto processes for simulating space-time extreme events: an application to precipitation reanalyses. 2019. ⟨hal-02136681v2⟩

Share

Metrics

Record views

47

Files downloads

41