*Article* **Statistical Prediction of Typhoon-Induced Rainfall over China Using Historical Rainfall, Tracks, and Intensity of Typhoon in the Western North Pacific**

#### **Jong-Suk Kim 1,\*, Anxiang Chen <sup>1</sup> , Junghwan Lee <sup>2</sup> , Il-Ju Moon <sup>3</sup> and Young-Il Moon <sup>2</sup>**


Received: 19 November 2020; Accepted: 11 December 2020; Published: 17 December 2020

**Abstract:** Typhoons or mature tropical cyclones (TCs) can affect inland areas of up to hundreds of kilometers with heavy rains and strong winds, along with landslides causing numerous casualties and property damage due to concentrated precipitation over short time periods. To reduce these damages, it is necessary to accurately predict the rainfall induced by TCs in the western North Pacific Region. However, despite dramatic advances in observation and numerical modeling, the accuracy of prediction of typhoon-induced rainfall and spatial distribution remains limited. The present study offers a statistical approach to predicting the accumulated rainfall associated with typhoons based on a historical storm track and intensity data along with observed rainfall data for 55 typhoons affecting the southeastern coastal areas of China from 1961 to 2017. This approach is shown to provide an average root mean square error of 51.2 mm across 75 meteorological stations in the southeast coastal area of China (ranging from 15.8 to 87.3 mm). Moreover, the error is less than 70 mm for most stations, and significantly lower in the three verification cases, thus demonstrating the feasibility of this approach. Furthermore, the use of fuzzy C-means clustering, ensemble averaging, and corrections to typhoon intensities, can provide more accurate rainfall predictions from the method applied herein, thus allowing for improvements to disaster preparedness and emergency response.

**Keywords:** typhoon-induced rainfall; prediction; statistical model; fuzzy C-means clustering; China
