## 1 Introduction  
It was reported in the World Urbanization Prospects that more than 54% of the global population currently lives in cities, and this percentage is projected to reach 66% by 2050 [1]. The 2014 Intergovernmental Panel on Climate Change (IPCC) predicted that several large metropolitan areas around the world may experience a temperature rise of greater than 1.5 \({}^{\circ}\)C under the Representative Concentration Pathway (RCP) 2.6 scenario, which introduces additional challenges for cities with respect to coping with climate change and its impact [2, 3]. Under the influence of anthropogenic factors, cities are very sensitive and vulnerable to heavy rainstorms [4, 5], floods [6, 7], heat waves [8] and other weather-related hazards that are likely to be exacerbated by climate change [9, 10]. In particular, changes in \"urban heat island (UHIs)\" associated with anthropogenic land use and land cover (LULC) in megacities have raised great concerns with regard to their impact on urban precipitation [11, 12, 13]. By 2030, the urban land cover will increase by 1.2 million km\({}^{2}\), which is nearly triple the situation in 2000 [14; 15]. More densely built impervious underlying surface, such as road, building and concrete, have replaced the natural vegetation during rapid urbanization [16; 17], which leads to changes in precipitation due to changes in the urban thermal environment, e.g., albedo effects [18; 19], anthropogenic heat [20; 21; 22] and the increase in emission of artificial aerosols [23; 24; 25; 26]. These changes in the underlying urban surface have exacerbated the destabilization of the boundary layer, thereby altering local precipitation processes [27; 28]. For instance, [PERSON] et al. [29] used cloud-resolving models (CRMs) and found that an increase in convective precipitation depends on the amount of heat energy released at the surface. Moreover, it was demonstrated that high precipitation rates are sensitive to the amount of surface heat that is released [30]. Currently, high accuracy LULC data are an important parameter in the precise simulation of precipitation processes in most climate models [31; 32; 33], such as the Weather Research and Forecasting (WRF) model [34]. Specifically, the WRF model incorporates the urban canopy model (UCM) parameterization scheme option with Noah land surface beginning from WRF-UCM version 2.2 [35]. However, it has been demonstrated in some instances that simulated precipitation does not accurately represent the actual precipitation process due to the coarser spatial [36; 37; 38; 39] and temporal [40] resolution of the LULC data. In particular, [PERSON] et al. [41] simulated a precipitation process in 2012 that occurred during a heavy rainstorm in Beijing based on the WRF model, and they concluded that the simulated results could be sensitive to the accuracies of LULC data. Over the past decades, China has experienced rapid urbanization [42]. The unprecedented LULC changes across urban areas of China have exerted substantial impacts on regional climate and precipitation [43; 44; 45; 46]. Previous studies in some urban agglomerations such as the Yangtze River Delta [47], Pearl River Delta [48; 49] and Beijing-Tianjin-Hebei [50] have revealed that rapid urban expansion may cause significant increases in the amount of total precipitation in urban areas. Moreover, extreme precipitation may be intensified in the center of metropolitan areas [51], especially in the cities of Beijing, Guangzhou and Shanghai. In addition, precipitation intensity [52] and frequency [53] are more likely to increase in the metropolitan areas of these cities during the phase of rapid urbanization. Since the 1980s, Shanghai's built-up area has ranked second in China under the rapid urbanization process. [PERSON] et al. [54] found that the speed of urbanization exerts significant influences on the spatial distribution of annual and extreme precipitation.