A Framework for Quantifying Diverse Multi‐Hazard Interactions to Enhance Climate Resilience
Abstract
ABSTRACT Multi‐hazard events generate impacts exceeding those of individual hazards but remain difficult to assess due to complex interactions. This study presents a generalized framework for analyzing four interaction types—multivariate, preconditioned and triggering, spatially, and temporally compounding events—across current and future climates. Combining extreme‐event detection, Bayesian copula modeling, and spatial analysis, the framework enables consistent multi‐hazard characterization beyond pairwise approaches. Applications to four European case studies reveal strong hazard dependencies and increased multi‐hazard occurrence under future climate scenarios.
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Authors: Mohammed Sarfaraz Gani Adnan, Christopher J. White, Eleonora Perugini, Esther Hlíðar Jensen, Talfan Barnie, Natalia Castillo, Marcello Arosio, Enrico Tubaldi, Matthew James Roberts, Marco Gaetani, YoungHwa Cha, Frederiek Sperna Weiland, Mario Martinelli, John Douglas
Institutions: Heriot-Watt University, University of London, University of Trento, 21c Consultancy (United Kingdom), Brunel University of London, University of Strathclyde, Istituto Universitario di Studi Superiori di Pavia, Deltares, Icelandic Meteorological Office, Istituto Sperimentale per la Zootecnia