Although most natural disaster related studies conducted in Korea recently have been related to typhoons or severe rainstorms, the occurrence frequency of disasters due to windstorms or rainstorms is also high. To reduce the strong wind damage caused by strong windstorms due to climate change, basic studies of strong winds are necessary. Therefore, in this study, the types and representative cases of windstorms that were observed to have been higher than 14 m/s, which is the criterion for strong-wind warnings from the Korea Meteorological Administration, were selected from among those windstorm cases that occurred on the Korean Peninsula for 10 years to conduct a statistical analysis of them and determine their synoptic meteorological characteristics. The cases of windstorms occurring on the Korean Peninsula were divided into six weather patterns according to the locations of the anticyclones/cyclones. Among these types, the SH type, which occurs when Siberian Highs expand into the Korean Peninsula, showed the highest occurrence frequency, accounting for at least the majority of the entire occurrence frequency of windstorms together with that of the EC type, which occurs when cyclones develop on the East Sea, and there was no clear yearly trend of the occurrence frequencies of windstorms. The monthly occurrence frequencies of windstorms were formed mainly by typhoons in the summer and the Siberian Highs in the winter, and the months with the highest windstorm occurrence frequencies were December and January, in which mainly the SH and EC type windstorms occurred. March showed the next highest occurrence frequency with10 times, and SH windstorms occurred the most frequently in March, followed by the CC, SC, and EC types of windstorms, in order of precedence. Therefore, attention to these types of windstorms is required. Countermeasures against storm and flood damage in Korea targeting the summer should be re-reviewed together with pre-disaster prevention plans, because cases of storm and flood damage due to windstorms occur more frequently than those due to typhoons, and they occur throughout the year.

The forecasting of container volume which is the basis of port logistics facilities expansion has a great influence on development of an port. Based on this importance, various previous studies have presented methodology on container volume forecasting. The results of many previous studies pointed out the limitations of future forecasting based on past container volume and emphasized that more various factors should be considered to compensate this. Taking notice of this point, this study forecasted future container volume by using ARIMA model, time series analysis and System Dynamics (SD) method, a dynamic analysis technique and performed the comparative review with the forecast of the Ministry of Land, Transport and Maritime affairs. Recently with rapid changes in economic and social environment, the non-linear change tendency for forecasting container traffic is presented as a new alternative to the country.