Abstract A stochastic rainfall generator is required to provide rainfall inputs for the analysis and mitigation of such hydrological or geologic hazards as floods and rain-induced landslides. This paper presents a new spatial-temporal rainstorm generator for generating simultaneous rainfall processes at numerous locations considering the spatial correlation among these locations and interpolating the point processes into an areal rain field. The generator is able to include the effect of climate change by adjusting the parameters of the marginal distributions of variables constituting rainfall events. A case study on the Guangdong-Hong Kong-Macau Greater Bay Area (GBA), one of the regions that are most prone to storm-related disasters in the world, is presented. The performance of the proposed generator is excellent in reproducing the historical statistical characteristics of regional rainfall. The model is adapted to climate change through extrapolation of the variation trend of the model parameters in the observation period to explore possible future scenarios of regional rainfall in GBA. The simulation results indicate a significant increase in rainfall extremes, especially for short-duration rainfall, at the end of 21st century in GBA.

中文翻译：

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考虑气候变化的粤港澳大湾区时空雨场生成

摘要 随机降雨发生器需要提供降雨输入，用于分析和减轻洪水和降雨引发的滑坡等水文或地质灾害。本文提出了一种新的时空暴雨发生器，用于在多个位置同时生成降雨过程，考虑到这些位置之间的空间相关性，并将点过程插入到区域雨场中。生成器能够通过调整构成降雨事件的变量的边际分布参数来包括气候变化的影响。介绍了粤港澳大湾区（GBA）的案例研究，这是世界上最容易发生风暴相关灾害的地区之一。所提出的发生器的性能在再现区域降雨的历史统计特征方面表现出色。该模型通过对观测期内模型参数变化趋势的外推来适应气候变化，探索大湾区未来可能出现的区域降雨情景。模拟结果表明，21 世纪末大湾区极端降雨量显着增加，尤其是短时降雨。