Surface urban heat island detected by all-weather satellite land surface temperature

Yangsiyu Liao; Xi Shen; Ji Zhou; Jin Ma; Xiaodong Zhang; Wenbin Tang; Yongren Chen; Lirong Ding; Ziwei Wang

doi:10.1016/j.scitotenv.2021.151405

Surface urban heat island detected by all-weather satellite land surface temperature

Sci Total Environ. 2022 Mar 10:811:151405. doi: 10.1016/j.scitotenv.2021.151405. Epub 2021 Nov 12.

Authors

Yangsiyu Liao¹, Xi Shen², Ji Zhou³, Jin Ma¹, Xiaodong Zhang⁴, Wenbin Tang¹, Yongren Chen⁵, Lirong Ding¹, Ziwei Wang¹

Affiliations

¹ School of Resources and Environment, Center for Information Geoscience, University of Electronic Science and Technology of China, Chengdu 611731, China.
² Yunnan Provincial Mapping Institute, Kunming 650034, China.
³ School of Resources and Environment, Center for Information Geoscience, University of Electronic Science and Technology of China, Chengdu 611731, China; Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China, Huzhou 313001, China. Electronic address: jzhou233@uestc.edu.cn.
⁴ Shanghai Aerospace Electronic Technology Institute, Shanghai 201109, China; Shanghai Spaceflight Institute of TT&C and Telecommunication, Shanghai 201109, China.
⁵ Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province, Meteorological Disaster Defense Technology Center of Sichuan Province, Chengdu 610072, China.

PMID: 34780819
DOI: 10.1016/j.scitotenv.2021.151405

Abstract

Since the existing satellite thermal infrared (TIR) land surface temperature (LST) is susceptible to cloud contamination and other factors, surface urban heat island (SUHI) studies based on TIR LST are limited to clear-sky conditions and are not representative of SUHI under all-weather conditions, which result in a possible clear-sky bias for SUHI. This study introduces a newly released 1-km all-weather LST product (TRIMS LST), which is spatiotemporally seamless, to investigate the real SUHI under all-weather conditions for five megacities (i.e. Harbin, Beijing, Shanghai, Guangzhou, and Chengdu) in China. Firstly, this study compares TRIMS SUHI with MODIS SUHI under clear-sky, partial-cloudy, and cloudy conditions. Secondly, the extent of the influence of cloudiness on SUHI is quantified. Finally, the monthly TRIMS SUHI is used to analyze the clear-sky bias that is caused by using only clear-sky data for the SUHI. Results indicate that (i) the absence of pixel data leads to negative offsets in the SUHI intensities calculated by MODIS LST, and these offsets expand gradually with increases in the number of missing-pixel data, causing the maximum offset to reach -1.83 °C under cloudy conditions in Chengdu; (ii) cloud can mitigate the SUHI for most cities: when the cloud coverage in Guangzhou reaches 90-100%, the daytime SUHI intensity decreases from 2.66 °C for clear-sky conditions to 1.70 °C; the mitigating effect differs at daytime and nighttime; and (iii) clear-sky bias varies significantly across climate zones and seasons, with a varying range of -1.6-1.2 °C for the five selected cities.

Keywords: All-weather; Cloud; Land surface temperature; MODIS; Surface urban heat island.

MeSH terms

China
Cities
Environmental Monitoring*
Hot Temperature*
Temperature