Return Period of Nonconcurrent Climate Compound Events: A Nonparametric Bivariate Generalized Pareto Approach

Abstract

Compound events (CEs), commonly defined as the “combination of multiple drivers and/or hazards that contributes to societal or environmental risk”, often result in amplified impacts compared to individual hazards. In order to estimate the return period of bivariate CEs, a novel nonparametric approach employing bivariate Generalized Pareto distributions (bi-GPD) is proposed and compared to a copula-based approach. Special attention is given to account for temporal dependencies and nonconcurrent compound events. The latter are defined as excess of variables over a threshold at a relatively close time. The return period of such bivariate events is carefully defined and closed-form expressions are obtained for both approaches. Simulations reveal the bi-GPD approach is effective in case of positive asymptotic dependence and should be avoided in case of asymptotic independence. The novel approach is then applied to ERA5 reanalysis data to analyze two types of compound events: a spatial CE with simultaneous floods due to accumulated precipitation across two large watersheds in France and a preconditioned CE consisting of a devastating flood triggered by extreme precipitation over a saturated soil.