A spatio-temporal statistical framework for heatwave attribution under climate change

Kamal Gasser, Johan Segers () and Francesco Ragone
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Kamal Gasser: Université catholique de Louvain, LIDAM/ISBA, Belgium
Johan Segers: Université catholique de Louvain, LIDAM/ISBA, Belgium
Francesco Ragone: University of Leicester

No 2026013, LIDAM Discussion Papers ISBA from Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA)

Abstract: We develop a unified statistical framework for attributing heatwaves as spatio-temporal phenomena under climate change. We quantify the impact of anthropogenic forcing on the probability and persistence of heatwaves not captured by standard marginal extreme-value approaches. Our methodology constructs a generative model for daily temperature fields that separates marginal nonstationarity from spatio-temporal dependence. We combine three components: a Bayesian spatial quantile regression model for the bulk of the data; a nonstationary spatial generalized extreme value model for tail behavior; and a copula-based model capturing both asymptotic dependence and independence in the extremes. The framework is applied to the CMIP6 MRI-ESM2 climate model, contrasting factual and counterfactual scenarios for probabilistic attribution. Our results show that the approach captures key heatwave characteristics inaccessible to traditional methods, enabling direct estimation of event-level attribution metrics. Overall, it provides a flexible basis for analyzing and attributing complex climate extremes as space-time objects.

Pages: 62
Date: 2026-04-30
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Persistent link: https://EconPapers.repec.org/RePEc:aiz:louvad:2026013

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