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Multiple timescale analysis of the urban heat island effect based on the Community Land Model: a case study of the city of Xi’an, China

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Abstract

Urban heat islands (UHIs) are the phenomenon of urban regions usually being warmer than rural regions, which significantly impacts both the regional ecosystem and societal activities. Numerical simulation can provide spatially and temporally continuous datasets for UHI analysis. In this study, a spatially and temporally continuous ground temperature dataset of Xi’an, China was obtained through numerical simulation based on the Community Land Model version 4.5 (CLM4.5), at a temporal resolution of 30 min and a spatial resolution of 0.05× 0.05. Based on the ground temperature, the seasonal average UHI intensity (UHII) was calculated and the seasonal variation of the UHI effect was analyzed. The monthly variation tendency of the urban heat stress was also investigated. Based on the diurnal cycle of ground temperature and the UHI effect in each season, the variation tendencies of the maximum, minimum, and average UHII were analyzed. The results show that the urban heat stress in summer is the strongest among all four seasons. The heat stress in urban areas is very significant in July, and the UHII is the weakest in January. Regarding the diurnal cycle of UHII, the maximum always appears at 06:30 UTC to 07:30 UTC, while the minimum intensity of the UHI effect occurs at different times in the different seasons. The results of this study could provide a reference for policymakers about how to reduce the damage caused by heat stress.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (41422108, 41661134015); Cross-disciplinary Collaborative Teams Program for Science, Technology and Innovation of the Chinese Academy of Sciences.

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Correspondence to Huanfeng Shen.

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Gao, M., Shen, H., Han, X. et al. Multiple timescale analysis of the urban heat island effect based on the Community Land Model: a case study of the city of Xi’an, China. Environ Monit Assess 190, 8 (2018). https://doi.org/10.1007/s10661-017-6320-9

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