In this study, type analysis was conducted along with the advancement of basic data to calculate the maximum damage caused by strong winds during the typhoon period. The result of the damage by region showed that in 2012, the difference in damage was clearly distinguished as the region was classified in detail. In addition, the result of the annual damage in 2011 was strong on the west coast, and in 2016, the damage to the southeast coast was significant. In 2012, the 3-second gust was relatively stronger on the west and southeast coasts than in 2011, and the winds blew stronger along the southeast coast in 2016. Monthly damage data showed that the damage to the west coast was high in August, and the damage to the southeast coast was high in October from 2002 to 2019. The 3-second gust showed the result of wide expansion throughout the southern coast of the Korean Peninsula in October. As a result, the damage differs for type bacause the intensities and paths of typhoons vary depending on their characteristics, the 3-second gust blows differently by region based on regional characteristics, and the sale price is considered in metropolitan cities.

The present study analyzes the characteristics of 43 typhoons that affected the Korean Peninsula between 2002 and 2015. The analysis was based on 3-second gust measurements, which is the maximum wind speed relevant for typhoon disaster prevention, using a typhoon disaster prevention model. And the distribution and characteristics of the 3-second gusts of four typhoons, RUSA, MAEMI, KOMPASU, and BOLAVEN that caused great damage, were also analyzed. The analysis show that between May and October during which typhoons affected the Korean Peninsula, the month with the highest frequency was August(13 times), followed by July and September with 12 occurrences each. Furthermore, the 3-second gust was strongest at 21.2 m/s in September, followed by 19.6 m/s in August. These results show that the Korean Peninsula was most frequently affected by typhoons in August and September, and the 3-second gusts were also the strongest during these two months. Typhoons MAEMI and KOMPASU showed distribution of strong 3-second gusts in the right area of the typhoon path, whereas typhoons RUSA and BOLAVEN showed strong 3-second gusts over the entire Korean Peninsula. Moreover, 3-second gusts amount of the ratio of 0.7 % in case of RUSA, 0.8 % at MAEMI, 3.3 % at KOMPASU, and 21.8 % at BOLAVEN showed as "very strong", based on the typhoon intensity classification criteria of the Korea Meteorological Administration. Based on the results of this study, a database was built with the frequencies of the monthly typhoons and 3-second gust data for all typhoons that affected the Korean Peninsula, which could be used as the basic data for developing a typhoon disaster prevention system.

For this study, WRF numerical modeling was performed, using RDAPS information for input data on typhoons affecting the Korean peninsula to produce wind data of 700hPa. RAM numerical modeling was also used to calculate 3-second gusts as the extreme wind speed. After comparing wind speeds at an altitude of 10 m to evaluate the feasibility of WRF numerical modeling, modeled values were found to be similar with measured ones, reflecting change tendencies well. Therefore, the WRF numerical modeling results were verified. As a result of comparing and analyzing these wind speeds, as calculated through RAM numerical modeling, to evaluate applicability for disaster preparedness, change tendencies were observed to be similar between modeled and measured values. In particular, modeled values were slightly higher than measured ones, indicating applicability for the prevention of possible damage due to gales. Our analysis of 3-second gusts during the study period showed a high distribution of 3-second gusts in the southeast region of the Korean peninsula from 2002-2006. The frequency of 3-second gusts increased in the central north region of Korea as time progressed. Our analysis on the characteristics of 3-second gusts during years characterized by El Niño or La Nina showed greater strength during hurricanes that affected the Korean peninsula in El Niño years.

This study was conducted to investigate the correlation between the distribution chart and input data of the predicted 3-second gust and damage cost, by using the forecast field and analysis field of Regional Data Assimilation Prediction System (RDAPS) as initial input data of Korea risk assessment model (RAM) developed in the preceding study. In this study the cases of typhoon Rusa which caused occurred great damage to the Korean peninsula was analyzed to assess the suitability of initial input data. As a result, this study has found out that the distribution chart from the forecast field and analysis field predicted from the point where the effect due to the typhoon began had similarity in both 3-second gust and damage cost with the course of time. As a result of examining the correlation, the 3-second gust had over 0.8, and it means that the forecast field and analysis field show similar results. This study has shown that utilizing the forecast field as initial input data of Korea RAM could suit the purpose of pre-disaster prevention.

The most efficient measures to reduce damage from natural disasters include activities which prevent disasters in advance, decrease possibility of disasters and minimize the scale of damage. Therefore, developing of the risk assessment model is very important to reduce the natural disaster damage. This study estimated a typhoon damage which is the biggest damage scale among increased natural disasters in Korea along with climate change. The results of 3-second gust at the height of 10 m level from the typhoon 'Maemi' which did considerable damage to Korean in 2003, using the wind data at the height of 700 hPa. September 12th 09 LST∼13th 12 LST period by the time a typhoon Maemi approached to the Korean peninsula. This study estimate damage amount using 'Fragility curve' which is the damage probability curve about a certain wind speed of the each building component factors based on wind load estimation results by using 3-second gust. But the fragility curve is not to Korea. Therefore, we use the fragility curves to FPHLM(FDFS, 2005). The result of houses damage amount is about 11 trillion 5 million won. This values are limit the 1-story detached dwelling, 62.51∼95.56 ㎡ of total area. Therefore, this process is possible application to other type houses.