Abstract
Urban surface expansion affects land–atmosphere interactions as well as rainfall. Both the subregional area-averaged daily (DRAIN) and the subregional cumulative volumetric (VRAIN) rainfall amounts are important in this context for hydrological applications and management. Conducted at the city (Beijing, Shanghai, and Guangzhou), city cluster (Beijing–Tianjin–Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD)), and national levels in China, numerical experiments were performed in this study using a regional climate model. The analysis revealed that urban-related changes in rainfall variability were more distinct for stronger rainfall among rainfalls of various intensity levels whereas changes in rainfall intensity were more pronounced for weaker rainfall. Furthermore, urban-induced changes in heavy storm rain were more prominent among rainfalls of various intensity levels, for which changes in the variability in DRAIN and VRAIN were more distinct than changes in their intensities, and exhibited marked subregional characteristics. The risk of heavy storm rain increased because of strengthened urban-induced DRAIN and VRAIN variability over Beijing, and urban areas of the YRD and China. However, the risk of heavy storm rain decreased because of decreased DRAIN and VRAIN variability and the reduced intensity of DRAIN over urban areas of Shanghai, nonurban areas of BTH, and nonurban and the entire areas of Guangzhou, the YRD, and the PRD. The urban-induced drying tendency in the lower troposphere and wetting tendency in the low–middle troposphere, and enhanced vertical motions played an important role in determining the changes in DRAIN and VRAIN in case of storm rain and heavy storm rain.
Acknowledgement
The work was support from the National Key Research and Development Program of China (no. 2016YFA0600403 and 2018YFA0606004), the Chinese Natural Science Foundation (grant 41775087, 41875178 and 41675149), the Chinese Academy of Sciences Strategic Priority Program (no. XDA05090206), the National Key Basic Research Program on Global Change (no. 2011CB952003), China Postdoctoral Science Foundation (no. 2019M660761), the Program for Special Research Assistant Project of Chinese Academy of Sciences, and the Chinese Jiangsu Collaborative Innovation Center for Climate Change. The authors thank Y. Hu from the Institute of Remote Sensing and Digital Earth (funded by the project grant XDA05090203) and G. Jia from the Institute of Atmospheric Physics (funded by the project no. XDA05090201), Chinese Academy of Sciences for the urban data. The authors thank the reviewers for their numerous valuable comments to improve the manuscript.
Disclosure statement
No potential conflict of interest was reported by the authors.
Supplemental data
Supplemental data for this article can be accessed at 10.1080/16000870.2020.1745532