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Name: Peng Zhong

Talk Title: Modeling and exact simulation of non-stationary temperature maxima with max-infinitely divisible processes

Abstract: The modeling of spatio-temporal trends in temperature extremes can help better understand the structure and frequency of heatwaves in a changing climate. Here, we study annual temperature maxima over Southern Europe using a century-spanning dataset observed at 44 monitoring stations. Extending the spectral representation of max-stable processes, our modeling framework relies on a novel construction of max-infinitely divisible (max-id) processes, which include covariates to capture spatio-temporal non-stationarities. Our new model keeps a popular max-stable process on the boundary of the parameter space, while flexibly capturing weakening extremal dependence at increasing quantile levels and asymptotic independence. This is achieved by linking the overall magnitude of a spatial event to its spatial correlation range, in such a way that more extreme events become less spatially dependent, thus more localized. Our model reveals salient features of the spatio-temporal variability of European temperature extremes, and it clearly outperforms natural alternative models. As risk assessment of spatial extreme events is often reported in terms of long-term return levels or return periods for spatial aggregates, which generally cannot be computed in explicit form for the proposed max-id processes, it is natural to rely on simulation to estimate such risk measures. If time allows, we will also describe novel exact simulation algorithms for general classes of max-id processes that are both fast and highly accurate.

This talk is a contributed talk at EVA 2021.