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In this study, we examine the impacts of urbanization and open water surface on heavy convective rainfall based on numerical modeling experiments using the Weather Research and Forecasting model. We focus on a severe storm event over the emerging Xiong'an City in northern China. The storm event consists of two episodes and features intense moisture transport and strong large‐scale forcing. A set of Weather Research and Forecasting simulations were implemented to examine the sensitivity of spatiotemporal rainfall variability in and around the urban area to different land use scenarios. Modeling results highlight contrasting roles of open water and urban surface in dictating space‐time organizations of convective rainfall under strong large‐scale forcing. Dynamic perturbation to atmospheric forcing dominates the impacts of open water and urban surface on spatial rainfall distribution during the second storm episode, while urban surface promotes early initiation of convection during the first storm episode through enhanced buoyant energy. Open water surface contributes to convective inhibition through evaporative cooling but can enhance moist convection when the impact of urban surface is also considered. The synergistic effect of open water and urban surface leads to rainfall enhancement both over and in the downwind urban area. Changes in rainfall accumulation with different spatial extents of urban coverage highlight strong dependence of urban‐induced rainfall anomalies on urbanization stages. Our results provide improved understandings on hydrometeorological impacts due to emerging cities in complex physiographic settings and emphasize the importance of atmospheric forcing in urban rainfall modification studies.

The cloud energy storage system (CES) is a shared distributed energy storage resource. The random disordered charging and discharging of large-scale distributed energy storage equipment has a great impact on the power grid. This paper solves two problems. On one hand, to present detailed plans for designing an orderly controlled CES system in a realistic power system. On the other hand, Monte Carlo simulation (MCS) is used for analyzing the load curves of five types of distributed energy storage systems to manage and operate the CES system. A method of its planning and the principles of CES for applied in a power grid, are presented by analyzing the impact based on five load curves including the electric vehicle (EV), the ice storage system, the demand response, the heat storage system, and the decentralized electrochemical energy storage system. The MCS simulates the random charging and discharging of the system over a five-year planned scaling of distributed energy storage from 2021 through 2025. The influence of distributed energy storage systems on power grid capacity, load characteristics, and safety margins is researched to summarize the applicable fields of CES in supporting large power grids. Finally, important conclusions are summarized and other research possibilities in this field are presented. This paper represents a significant reference for planners.