DEVELOPMENT OF WAVE PREDICTION MODEL ASSIMILATED OBSERVATIONAL DATA FROM SHIPS USING ENSEMBLE KALMAN FILTER

Abstract

 It has been reported that the optimal route can be used to CO₂ during ship navigation, and it is important to predictthe wave field around the ship up to several hours ahead. In order to improve the avvuracy of local and short-term predictions such as the around field around ships, it is necessary to develop a mechanism to correct the prediction using ship observational data. Therefore, in this study, we constructed a data assimilation system that applies EnKF to a wave prediction model SWAN, in order to make wave predictions using real-time observational data obtained from ships. As a result, improving the accuracy of the ship position and usefulness of EnKF were shown by performing data assimilation using ship observational data. Moreover, in order to improve the accuracy in coastal area and the accuracy of the whole sea by increasing the number of observation points, we investigated the accuracy using NOWPHAS wave observational data. Compared with the estimation accuracy before data assimilation, the accuracy was improved about 27 % at the maximum.