Evaluation of typhoon-induced rainfall using nonparametric Monte Carlo simulation and locally weighted polynomial regression

Typhoons in Korea are the major causes of natural disasters in the Korean peninsula. In this study, rainfall generated by typhoons was quantitatively analysed using various statistical methods. First, the frequency analysis of rainfall induced by typhoons was carried out to calculate the design rainfall. Second, the frequency analysis of simulated rainfall derived by nonparametric Monte Carlo simulation (NMCS) was performed to evaluate the uncertainty of rainfall caused by typhoons. Third, the regression relationship between the physical characteristic factors of typhoons and rainfall was established by locally weighted polynomial regression (LWPR), and the characteristic factors of typhoons were simulated. The simulated characteristic factors were then used to estimate rainfall and to calculate the design rainfall by typhoons. Comparative analyses of design rainfalls as estimated using various statistical methods were performed. The LWPR showed good performance in terms of reproducing typhoon characteristics. Therefore, the combined NMCS and LWPR method suggested in this study can be used as a supplementary technique for assessing extreme rainfall with climate change and reflected variability.