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Comparisons of urban-related warming for Shenzhen and Guangzhou

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journal contribution
posted on 2018-10-12, 11:22 authored by Deming ZHAO, Jinlin ZHA, Jian WU

Urban-related warming in two first-tier cities (Guangzhou and Shenzhen) in southern China with similar large-scale climatic backgrounds was compared using the nested weather research and forecasting regional climate model. The default urban data in the model were replaced by reconstructed annual urban data retrieved from satellite-based images for both coarse- (including all of China) and fine-resolution domains (eastern China and three city clusters in China: Beijing–Tianjin–Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD)), which reproduced urban surface expansion during the past few decades. The results showed that the 37-year (1980–2016) area-averaged annual urban-related warming was similar (0.69°C/0.64°C) between the urban areas of Guangzhou/Shenzhen; however, the values across the entire area of the two cities varied (0.21°C/0.45°C). Seasonal characteristics could be detected for mean surface air temperatures (SAT) at 2 m, SAT maximum and minimum, and diurnal temperature range (DTR). Both the SAT maximum and minimum generally increased, especially over urban areas; however, changes in the SAT minimum were larger, which induced a decrease in DTR. The DTR in summer decreased by −0.25°C/−0.86°C across the entire area of the two cities and decreased by −0.93°C/−1.15°C over urban areas. The contributions of urban surface expansion to regional warming across the entire area of the two cities were approximately 17%/35% of the overall warming and much greater over Shenzhen. However, the values over urban areas were much closer to the values from total warming (35%/44%).

Funding

This work was supported by the National Natural Science Foundation of China (Grant Nos. 41775087 and 41675149), the National Key Research and Development Program of China (Grant No. 2016YFA0600403), the Chinese Academy of Sciences Strategic Priority Program (Grant No. XDA05090206), and the Jiangsu Collaborative Innovation Center for Climatic Change.

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