DEVELOPMENT OF WAVE PREDICTION MODEL ASSIMILATED OBSERVATIONAL DATA FROM SHIPS USING ENSEMBLE KALMAN FILTER
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- FUJIWARA Kazuhiro
- 元 中央大学大学院 理工学研究科都市人間環境学専攻
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- SHIRAI Tomoki
- 中央大学 理工学部都市環境学科
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- OMIYA Tomoki
- 株式会社商船三井 技術革新本部 スマートシッピング推進部
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- ARIKAWA Taro
- 中央大学 理工学部都市環境学科
Bibliographic Information
- Other Title
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- アンサンブルカルマンフィルタによる船舶観測データを用いた波浪推算手法の開発
- アンサンブルカルマンフィルタ ニ ヨル センパク カンソク データ オ モチイタ ハロウ スイサン シュホウ ノ カイハツ
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Description
<p> 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.</p>
Journal
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- Journal of Japan Society of Civil Engineers, Ser. B2 (Coastal Engineering)
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Journal of Japan Society of Civil Engineers, Ser. B2 (Coastal Engineering) 76 (2), I_241-I_246, 2020
Japan Society of Civil Engineers