Dissemin is shutting down on January 1st, 2025

Published in

IOP Publishing, Environmental Research Letters, 10(18), p. 104044, 2023

DOI: 10.1088/1748-9326/acf94c

Links

Tools

Export citation

Search in Google Scholar

Predicting future UK nighttime urban heat islands using observed short-term variability and regional climate projections

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Green circle
Published version: archiving allowed
Data provided by SHERPA/RoMEO

Abstract

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.