Palacios-Rodriguez F. auteur aut IRD Toulemonde G. auteur aut IRD Carreau Julie auteur aut IRD Opitz T. auteur aut IRD text journalArticle eng text/pdf born digital access 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 simulations of realistic spatio-temporal extreme fields 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 arising as limits for event magnitudes exceeding a high threshold. Specifically, we exploit asymptotic stability properties by decomposing extreme event episodes into a scalar magnitude variable (that is resampled), and an empirical profile process representing space-time variability. For illustration on hourly gridded precipitation data in Mediterranean France, we calculate various risk measures using extreme event simulations for yet unobserved magnitudes, and we highlight contrasted behavior for different definitions of the magnitude variable. specialized Extreme-value theory Precipitation Risk analysis Space-time Pareto processes Stochastic simulation 062 020 34 12 2033-2052 2020 1436-3240 https://www.documentation.ird.fr/hor/fdi:010079834 10.1007/s00477-020-01895-w 1436-3240 [F B010079834] https://www.documentation.ird.fr/hor/fdi:010079834 https://www.documentation.ird.fr/intranet/publi/2020/10/010079834.pdf Accès réservé (Intranet de l'IRD) IRD - Base Horizon / Pleins textes 2020-11-12 2025-02-24 fdi:010079834 fre