Using analogues to predict changes in future UK heatwaves

Yule, E. L. ORCID: https://orcid.org/0000-0002-5492-2217, Hegerl, G. C. ORCID: https://orcid.org/0000-0002-4159-1295, Schurer, A. ORCID: https://orcid.org/0000-0002-9176-3622, Ballinger, A. ORCID: https://orcid.org/0000-0003-3704-1976 and Hawkins, E. ORCID: https://orcid.org/0000-0001-9477-3677 (2024) Using analogues to predict changes in future UK heatwaves. Environmental Research: Climate, 3 (4). 045001. ISSN 2752-5295 doi: 10.1088/2752-5295/ad57e3

Abstract/Summary

The intensity and frequency of extreme heat events is increasing due to climate change, resulting in a range of societal impacts. In this paper, we use temporal analogues to analyse how past UK heatwave events, such as during the summer of 1923, may change if they were to occur under different global warming scenarios. We find that the six most intense early heat events are caused by circulation patterns similar to that of 1923, which can cause intense heat over the UK and parts of NW Europe. Circulation analogues for the 1923 heatwave are also linked to intense heat events in the future, although not all analogues are anomalously hot. At 4 degrees of global warming, mean summer temperatures in England over the duration of the 1923 heatwave are between 4.9 and 6.4 degrees warmer than pre-industrial levels across the three models used. At that global mean warming level, future heat events with similar circulation as 1923 over England are estimated to be on average 6.9 to 10.7 degrees hotter than those at pre-industrial levels, with the most intense up 19.6 degrees higher. Exploring how the intensity of events similar to past events may change in the future could be an effective risk communication tool for adaptation decision making, particularly if past events are stored in society's memory, for example, due to high impacts.

Item Type	Article
URI	https://centaur.reading.ac.uk/id/eprint/116982
Identification Number/DOI	10.1088/2752-5295/ad57e3
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > NCAS Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	IOP Science
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