In this paper, a revised method for typhoon precipitation probability forecast, based on the frequency-matching method, is developed by combining the screening and the neighborhood methods. The frequency of the high-resolution precipitation forecasts is used as the reference frequency, and the frequency of the low-resolution ensemble forecasts is used as the forecast frequency. Based on frequency-matching method, the frequency of rainfall above the rainstorm magnitude increases. The forecast members are then selected by using the typhoon tracks of the short-term predictions, and the precipitation probability is calculated for each member using a combination of the neighbor and the traditional probability statistical methods. Moreover, four landfalling typhoons (i.e., STY Lekima and STS Bailu in 2019, and TY Hagupit and Higos in 2020) were chose to test the rainfall probability forecast. The results show that the method performs well with respect to the forecast rainfall area and magnitude for the four typhoons. The Brier and Brier skill scores are almost entirely positive for the probability forecast of 0.1–250 mm rainfall during Bailu, Hagupit and Higos (except for 0.1mm of Hagupit), and for < 100 mm rainfall (except for 25 mm) during Lekima.

本文结合筛选法和邻域法，提出了一种基于频率匹配法的台风降水概率预报修正方法。以高分辨率降水预报的频率作为参考频率，以低分辨率集合预报的频率作为预报频率。基于频率匹配方法，暴雨级以上的降雨频率增加。然后利用短期预报的台风轨迹选择预报成员，结合邻域和传统概率统计方法计算每个成员的降水概率。此外，4 次登陆台风（即 2019 年的 STY Lekima 和 STS Bailu，和 TY Hagupit 和 Higos 在 2020 年）被选择来测试降雨概率预测。结果表明，该方法对四种台风的预测降雨面积和强度均表现良好。Brier 和 Brier 技能得分对于白鹿、黑格比和 Higos（黑格比的 0.1 毫米除外）以及利奇马期间 < 100 毫米的降雨量（25 毫米除外）的概率预测几乎完全为正。