Smooth Copula-based Generalized Extreme Value model and Spatial Interpolation for Sparse Extreme Rainfall in Central Eastern Canada - Laboratoire Jean-Alexandre Dieudonné Accéder directement au contenu
Article Dans Une Revue Environmetrics Année : 2023

Smooth Copula-based Generalized Extreme Value model and Spatial Interpolation for Sparse Extreme Rainfall in Central Eastern Canada

Résumé

This paper proposes a smooth copula-based Generalized Extreme Value (GEV) model to map and predict extreme rainfall in central eastern Canada. Furthermore, we provide a comparison with different classical interpolation-based approaches. The considered data represents a station network particularly spatially sparse. Furthermore, one observes several missing values and non-concomitant record periods at different stations. We compare the classical GEV parameter interpolation approaches with our smooth GEV modeling approach, in which the parameters are modeled as smooth functions in space through the use of spatial covariates and by using copula-clustering techniques recently introduced in the literature.
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Dates et versions

hal-03355026 , version 1 (27-09-2021)
hal-03355026 , version 2 (25-01-2023)

Identifiants

  • HAL Id : hal-03355026 , version 2

Citer

Fatima Palacios-Rodriguez, Elena Di Bernardino, Mélina Mailhot. Smooth Copula-based Generalized Extreme Value model and Spatial Interpolation for Sparse Extreme Rainfall in Central Eastern Canada. Environmetrics, In press. ⟨hal-03355026v2⟩
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