Abstract: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.
Climate change of global warming may affect the water circulation in Korea. Rainfall is occurred with complex of multiple climatic indices. Therefore, the rainfall is one of the most significant index due to climate change in the process of water circulation. In this research, multiple time series data of rainfall events were extracted to represent the rainfall characteristics. In addition, the occurrence of rainfall time series analyzed by annual, seasonal and monthly data. Analysis method used change analysis of mean and standard deviation and trend analysis. Also, changes in rainfall characteristics and the relative error was calculated during the last 10 years for comparison with past data. At the results, significant statistical results weren't showed by randomness of rainfall data. However, amount of rainfall generally increased last 10 years, and number of raining days had trend of decrease. In addition, seasonal and monthly changes in the rainfall characteristics can be found to appear differently.keywords : rainfall events, maximum precipitation, rainfall occurrence frequency, change analysis, trend analysis
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