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In recent years, climate abnormalities have been observed globally. Consequently, the scale and size of natural disasters, such as typhoons, wind wave, heavy snow, downpours, and storms, have increased. However, compared to other disasters, predicting the timing, location and severity of damages associated with typhoons and other extreme wind wave events is difficult. Accurately predicting the damage extent can reduce the damage scale by facilitating a speedy response. Therefore, in this study, a model to estimate the cost of damages associated with wind waves and their impacts during coastal storms was developed for the Republic of Korea. The history of wind wave and typhoon damages for coastal areas in Korea was collected from the disaster annual report (1991–2020), and the damage cost was converted such that it reflected the inflation rate as in 2020. Furthermore, data on ocean meteorological factors were collected for the events of wind wave and typhoon damages. Using logistic and linear regression, a wind wave damage prediction model reflecting the coastal regional characteristics based on 74 regions nationwide was developed. This prediction model enabled damage forecasting and can be utilized for improving the law and policy in disaster management.

In recent years, climate abnormalities have been observed globally. Consequently, the scale and size of natural disasters, such as typhoons, wind wave, heavy snow, downpours, and storms, have increased. However, compared to other disasters, predicting the timing, location and severity of damages associated with typhoons and other extreme wind wave events is difficult. Accurately predicting the damage extent can reduce the damage scale by facilitating a speedy response. Therefore, in this study, a model to estimate the cost of damages associated with wind waves and their impacts during coastal storms was developed for the Republic of Korea. The history of wind wave and typhoon damages for coastal areas in Korea was collected from the disaster annual report (1991–2020), and the damage cost was converted such that it reflected the inflation rate as in 2020. Furthermore, data on ocean meteorological factors were collected for the events of wind wave and typhoon damages. Using logistic and linear regression, a wind wave damage prediction model reflecting the coastal regional characteristics based on 74 regions nationwide was developed. This prediction model enabled damage forecasting and can be utilized for improving the law and policy in disaster management. [ABSTRACT FROM AUTHOR]