Models for temporal clustering of extreme events with applications to mid-latitude winter cyclones

TL;DR

This paper develops a flexible model for the timing of extreme weather events like winter cyclones, capturing clustering behavior and distinguishing between different underlying mechanisms to improve understanding and prediction.

Contribution

It introduces a general model for inter-exceedance times that combines multiple mechanisms, enhancing the analysis of clustered extreme events.

Findings

Model effectively distinguishes between dependent and independent event mechanisms.

Application to winter cyclones demonstrates practical utility.

Modified Cramér-von Mises distance improves model fitting.

Abstract

The occurrence of extreme events like heavy precipitation or storms at a certain location often shows a clustering behaviour and is thus not described well by a Poisson process. We construct a general model for the inter-exceedance times in between such events which combines different candidate models for such behaviour. This allows us to distinguish data generating mechanisms leading to clusters of dependent events with exponential inter-exceedance times in between clusters from independent events with heavy-tailed inter-exceedance times, and even allows us to combine these two mechanisms for better descriptions of such occurrences. We propose a modification of the Cram\'er-von Mises distance for model fitting. An application to mid-latitude winter cyclones illustrates the usefulness of our work.