Healy, Dáire and Tawn, Jonathan and Thorne, Peter and Parnell, Andrew (2024) Inference for extreme spatial temperature events in a changing climate with application to Ireland. Journal of the Royal Statistical Society Series C: Applied Statistics. ISSN 0035-9254

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Abstract

We investigate the changing nature of the frequency, magnitude, and spatial extent of extreme temperatures in Ireland from 1942 to 2020. We develop an extreme value model that captures spatial and temporal non-stationarity in extreme daily maximum temperature data. We model the tails of the marginal variables using the generalised Pareto distribution and the spatial dependence of extreme events by a semi-parametric Brown-Resnick r-Pareto process, with parameters of each model allowed to change over time. We use weather station observations for modelling extreme events since data from climate models (not conditioned on observational data) can over-smooth these events and have trends determined by the specific climate model configuration. However, climate models do provide valuable information about the detailed physiography over Ireland and the associated climate response. We propose novel methods which exploit the climate model data to overcome issues linked to the sparse and biased sampling of the observations. Our analysis identifies a temporal change in the marginal behaviour of extreme temperature events over the study domain, which is much larger than the change in mean temperature levels over this time window. We illustrate how these characteristics result in increased spatial coverage of the events that exceed critical temperatures.

Item Type:	Article
Additional Information:	Healy’s work was supported by SFI grant 18/CRT/6049. Parnell’s work was supported by the SFI awards 17/CDA/4695; 16/IA/4520; 12/RC/2289 P2 and we thank Simon Noone (Maynooth University) for help with data. For access to climate data, we acknowledge the World Climate Research Programme’s Working Groups on Regional Climate and on Coupled Modelling, and the European Network for Earth System Modelling. We would like to thank all three referees who provided helpful and extensive constructive criticisms of the work and which has enormously improved its quality and presentation
Keywords:	Climate change; generalised Pareto distribution; extreme values; heatwaves; missing data; non-stationarity; Pareto processes; spatial extremes; temperatures;
Academic Unit:	Faculty of Science and Engineering > Research Institutes > Hamilton Institute Faculty of Social Sciences > Research Institutes > Irish Climate Analysis and Research Units, ICARUS
Item ID:	19236
Identification Number:	https://doi.org/10.1093/jrsssc/qlae047
Depositing User:	Peter Thorne
Date Deposited:	29 Nov 2024 11:59
Journal or Publication Title:	Journal of the Royal Statistical Society Series C: Applied Statistics
Publisher:	Oxford Academic
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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