A Markov-switching model for heat waves

TL;DR

This paper introduces an interpretable Markov-switching extreme value model to analyze heat waves, capturing their frequency, duration, and severity, with applications to notable European and Russian heat waves.

Contribution

The paper develops a novel latent state extreme value model that directly relates parameters to risk management metrics for heat waves.

Findings

Model effectively captures heat wave duration and severity.

Applied to 2003 European and 2010 Russian heat waves with insightful results.

Parameters provide direct risk management insights.

Abstract

Heat waves merit careful study because they inflict severe economic and societal damage. We use an intuitive, informal working definition of a heat wave-a persistent event in the tail of the temperature distribution-to motivate an interpretable latent state extreme value model. A latent variable with dependence in time indicates membership in the heat wave state. The strength of the temporal dependence of the latent variable controls the frequency and persistence of heat waves. Within each heat wave, temperatures are modeled using extreme value distributions, with extremal dependence across time accomplished through an extreme value Markov model. One important virtue of interpretability is that model parameters directly translate into quantities of interest for risk management, so that questions like whether heat waves are becoming longer, more severe or more frequent are easily answered by querying an appropriate fitted model. We demonstrate the latent state model on two recent, calamitous, examples: the European heat wave of 2003 and the Russian heat wave of 2010.