Flash floods in Batu City, Indonesia on November 4^th, 2021, caused damage to property, agricultural land, settlements, death of livestock, and loss of human life. One of the important factors triggering this flash flood is heavy rainfall. This study aims to analyse the spatial and temporal dynamics of rainfall as a trigger for the event. Rainfall modelling was conducted using the WRF model with 2 microphysical schemes and 3 cumulus schemes. The data used is GFS data on October 30^th, 2021, with a resolution of 0.25 x0.25 degrees which is used to predict rain events until November 4, 2021. Contingency table verification, RMSE value verification, and verification using tolerance limits are used to verify the results of modelling data based on BMKG observation data. The results of this study show that this model can predict rain and non-rain events very well. However, this model is not good enough to predict the thickness of rain until November 4, 2021. The best scheme in modelling rainfall is scheme 5 (Lin and Betts Miller Janjic). Scheme 5 has the smallest RMSE value of 77, the data fit is appropriate and the medium error rate in scheme 5 is 84%. Scheme 5 with GFS data input started from 02 November 2021 can record rain events on 04 November 2021 with extreme rain categories. This extreme rain is influenced by convective clouds. The temperature of the cloud tops changes significantly from 13.00 WIB to 14.00 local time, namely from −4 degrees, and decreases to −76 degrees Celsius.

中文翻译：

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2021 年 11 月 4 日印度尼西亚巴图市山洪爆发期间 WRF 降雨模型的验证

^{2021 年 11 月 4日}，印度尼西亚巴图市发生山洪，造成财产、农田、定居点受损、牲畜死亡和人员伤亡。强降雨是引发此次山洪的重要因素之一。本研究旨在分析降雨作为事件触发因素的时空动态。使用具有 2 个微物理方案和 3 个积云方案的 WRF 模型进行降雨建模。使用的数据是2021年10月30日的GFS数据^，分辨率为0.25 x0.25度，用于预测2021年11月4日之前的降雨事件。使用列联表验证、RMSE值验证和使用容限验证基于BMKG观测数据验证建模数据的结果。这项研究的结果表明，该模型可以很好地预测降雨和非降雨事件。然而，该模型不足以预测 2021 年 11 月 4 日之前的降雨厚度。降雨建模的最佳方案是方案 5（Lin 和 Betts Miller Janjic）。方案5的RMSE值最小为77，数据拟合合适，方案5的中等错误率为84%。方案5从2021年11月2日开始输入GFS数据，可以记录2021年11月4日极端降雨类别的降雨事件。这次极端降雨是受到对流云的影响。云顶温度从当地时间 13 点到 14 点发生显着变化，即从-4 摄氏度降至-76 摄氏度。