Predicting future UK nighttime urban heat islands using observed short-term variability and regional climate projections
Predicting future UK nighttime urban heat islands using observed short-term variability and regional climate projections
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使用观测到的短期变化和区域气候预测预测未来英国夜间城市热岛
DOI:
10.1088/1748-9326/acf94c
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发表时间:
2023
影响因子:
6.7
通讯作者:
Doger De Speville C
中科院分区:
文献类型:
--
作者:
Doger De Speville C
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.
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DOI:
10.1002/joc.2402
发表时间:
2012-10-01
期刊:
INTERNATIONAL JOURNAL OF CLIMATOLOGY
影响因子:
--
作者:
McCarthy, M. P.;Harpham, C.;Jones, P. D.
通讯作者:
Jones, P. D.
DOI:
--
发表时间:
2005-08
期刊:
Lawrence Berkeley National Laboratory
影响因子:
--
作者:
H. Akbari
通讯作者:
H. Akbari
影响因子:
4.6
作者:
W. J. Keat;E. Kendon;S. Bohnenstengel
通讯作者:
S. Bohnenstengel
DOI:
--
发表时间:
2016
期刊:
影响因子:
--
作者:
K. Schlünzen;S. Bohnenstengel
通讯作者:
S. Bohnenstengel
影响因子:
8.9
作者:
A. Porson;Peter Clark;Ian N. Harman;Martin Best;Stephen E. Belcher
通讯作者:
A. Porson;Peter Clark;Ian N. Harman;Martin Best;Stephen E. Belcher