This study is about the simulation and observational analysis of a heavy rainfall event (HRE) and its sensitivity to land-use changes. The impact of urbanization on processes and mechanisms of rainfall including cloud processes is discussed. This study is based on high-resolution (2 km), time-ensemble simulation of one of the HREs that occurred on 27 May 2017 over the city of Bengaluru in the southern part of India. The simulations are carried out using the Weather Research and Forecasting (WRF) model, which is coupled with a single-layer urban canopy model (UCM). The high-resolution (30 s) land-use data derived from the Indian Space Research Organization (ISRO) for the year 2016–2017 is shown to be realistic in representing the current land-use scenario with a threefold increase in urbanization when compared to USGS land-use data of 1991–1992. Simulation and analysis of large-scale circulation patterns revealed that the event was triggered and sustained by the low-pressure system and cyclonic circulation over the Bay of Bengal. Simulated rainfall was found to be remarkably sensitive to land-use changes as shown by control (USGS) and test (ISRO) simulations. The rainfall intensity and spatial distribution are close to observation in test simulations with relatively less error at station scale with a correlation of 0.49 (95% significance) when compared to control simulations, indicating the importance of realistic representation of land use in the model and its impact on heavy rainfall processes. The test simulation which represents the current urbanization scenario has shown a significant increase in rainfall by over 100–200%. The surface energy fluxes and thermodynamic indices as shown by test simulations are favorable to HREs, and also consistent with the current land-use scenario with increased urbanization. This study demonstrated how a realistic representation of land-use data in the model can help to improve model skill. The main limitation of this research work is that it is based on the generic parameterization of urbanization using single-layer UCM. An in-depth study based on multi-layer UCM and city-specific parameterization of urbanization using sub-kilometer-scale land-use data including buildings would further enhance our understanding on this subject.

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城市化对暴雨事件的影响：以印度班加罗尔特大城市为例

本研究是关于强降雨事件 (HRE) 及其对土地利用变化的敏感性的模拟和观测分析。讨论了城市化对包括云过程在内的降雨过程和机制的影响。本研究基于对 2017 年 5 月 27 日发生在印度南部班加罗尔市上空的其中一个 HRE 的高分辨率（2 公里）时间集成模拟。模拟是使用天气研究和预测 (WRF) 模型进行的，该模型与单层城市冠层模型 (UCM) 相结合。来自印度空间研究组织 (ISRO) 的 2016-2017 年高分辨率（30 秒）土地利用数据被证明在代表当前土地利用情景方面是现实的，与城市化相比，城市化增加了三倍。 USGS 1991-1992 年土地利用数据。对大规模环流模式的模拟和分析表明，该事件是由孟加拉湾上空的低压系统和气旋环流触发和维持的。控制 (USGS) 和测试 (ISRO) 模拟显示，模拟降雨对土地利用变化非常敏感。与对照模拟相比，试验模拟中降雨强度和空间分布接近观测值，站尺度误差相对较小，相关系数为 0.49（显着性为 95%），表明模型中土地利用的真实表示及其重要性。对强降雨过程的影响。代表当前城市化情景的测试模拟显示，降雨量显着增加了 100-200% 以上。测试模拟显示的表面能通量和热力学指数有利于 HRE，并且也符合当前城市化程度提高的土地利用情景。本研究展示了模型中土地利用数据的真实表示如何有助于提高模型技能。这项研究工作的主要限制是它基于使用单层 UCM 的城市化通用参数化。使用包括建筑物在内的亚公里尺度土地利用数据，基于多层 UCM 和特定于城市的城市化参数化进行深入研究，将进一步增强我们对这一主题的理解。本研究展示了模型中土地利用数据的真实表示如何有助于提高模型技能。这项研究工作的主要限制是它基于使用单层 UCM 的城市化通用参数化。使用包括建筑物在内的亚公里尺度土地利用数据，基于多层 UCM 和特定于城市的城市化参数化进行深入研究，将进一步增强我们对这一主题的理解。本研究展示了模型中土地利用数据的真实表示如何有助于提高模型技能。这项研究工作的主要限制是它基于使用单层 UCM 的城市化通用参数化。使用包括建筑物在内的亚公里尺度土地利用数据，基于多层 UCM 和特定于城市的城市化参数化进行深入研究，将进一步增强我们对这一主题的理解。