Abstract

By 2050, 68% of the world’s population and 90% of the UK’s population are estimated to be living in urban areas. It is widely acknowledged that urban areas tend to be warmer than rural areas (the urban heat island (UHI) effect), and that increased summer temperatures increase morbidity and mortality. It is therefore important to know how the UHI intensity will change in the future. Recent work has used observed daily UHI-temperature relationships to suggest that the UHI intensity may decrease under warming temperatures. Here we analyse the ability of the regional UK Climate Projections, UKCP18-regional, to model the summer nighttime UHI intensity of ten UK cities. When compared to HadUK-Grid observational data, we find that the model accurately simulates both the mean magnitude of the UHI intensities and the daily relationship between urban and rural temperature. In particular, in 9 of the 10 cities, the model and observational data both show a decrease in UHI intensity with warmer temperature over the 1980–2020 period analysed. We then analyse the correlation between the projected future UHI intensities using UKCP18-regional and those inferred from the historical daily UHI-temperature relationships. We find that this relationship is not statistically significant and that the model-projected change in UHI intensity is greater than the change inferred from the historical relationship for all cities analysed. We conclude that using short-term variability to predict future UHI change, as proposed by some recent work, may not be appropriate. Our results motivate further research to understand processes impacting UHI changes on different timescales and in different regions.

Details

Title
Predicting future UK nighttime urban heat islands using observed short-term variability and regional climate projections
Author
Charlotte Doger de Speville 1 ; Seviour, William J M 2   VIAFID ORCID Logo  ; Lo, Y T Eunice 3   VIAFID ORCID Logo 

 Natural Sciences, University of Exeter , Exeter, United Kingdom 
 Department of Mathematics and Statistics and Global Systems Institute, University of Exeter , Exeter, United Kingdom 
 Cabot Institute for the Environment and Elizabeth Blackwell Institute for Health Research, University of Bristol , Bristol, United Kingdom 
First page
104044
Publication year
2023
Publication date
Oct 2023
Publisher
IOP Publishing
e-ISSN
17489326
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2873792437
Copyright
© 2023 The Author(s). Published by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.