Tropical cyclone (TC) rainfall results in damages to properties and loss of lives. It is also a significant source of freshwater in the Philippines. This study describes a method in forecasting accumulated TC rainfall using analogous TCs from historical datasets. A TC rainfall database where precipitation within 5^∘ of TC centers was created for all landfalling TCs from 1951 to 2015. To predict TC rainfall, the mean rainfall of all past TCs with similar tracks included in the database, referred to as analog TCs, is calculated. Landfalling TCs from 2016 to 2018 are used to optimize the selection of past analog TCs. Each past TC member was also adjusted according to a target TC's intensity and movement speed. The optimized analog method is then applied to landfalling TCs from 2019 to November 2020. Results show that the composite rainfall from past TCs within 1.8^∘ of the forecast TC yields the best hit rate of intense rainfall. The analog TC rainfall forecast generally has a similar spatial distribution as the observed TC rain. However, this method tends to miss extreme rainfall values due to a “smoothing” effect caused by the variability of extreme rain locations of each TC member and constraints in the rainfall data used in the database. Nevertheless, forecast assessment results show that analog TC rainfall forecasting performed better than the WRF model in predicting intense and inland rainfall. In addition to it being computationally inexpensive, it can complement the inherent biases of dynamical models.

热带气旋（TC）降雨导致财产损失和生命损失。它也是菲律宾的重要淡水来源。这项研究描述了一种使用来自历史数据集的类似TC预测TC累积降雨量的方法。一个TC降雨量数据库，其中在5个沉淀^∘从1951年到2015年，为所有登陆的TC创建了TC中心。为预测TC降雨量，计算了数据库中包含相似轨迹的所有过去TC的平均降雨量，称为模拟TC。使用2016年至2018年的降落TC来优化过去模拟TC的选择。每个过去的TC成员也都根据目标TC的强度和移动速度进行了调整。然后优化的模拟方法应用于登陆热带气旋从2019到2020年十一月结果表明，从内1.8过去的TC复合雨量^∘预测的TC产生强降雨的最佳命中率。模拟TC降雨预报通常具有与观测到的TC降雨相似的空间分布。但是，由于每个TC成员的极端降雨位置的可变性以及数据库中使用的降雨数据的限制引起的“平滑”效应，该方法往往会错过极端降雨值。尽管如此，预报评估结果表明，模拟TC降雨量预报在预报强降雨和内陆降雨量方面比WRF模型要好。除了计算上便宜之外，它还可以补充动力学模型的固有偏差。