Statistical wave forecasting through Kalman filtering combined with principal component analysis

Noriaki Hashimoto, Toshihiko Nagai, Masanobu Kudaka

Research output: Contribution to journalConference article

2 Citations (Scopus)


Statistical wave forecasting methods have been applied because of their convenience. Most of them, however, include some drawbacks from the statistical or numerical viewpoints. In this paper, these drawbacks are discussed and a new statistical wave forecasting method utilizing the Kalman filter technique combined with Principal Component Analysis (PCA) is proposed in order to mitigate the drawbacks. The applicability and reliability of the proposed method is examined for five wave observation stations around Japan through simulations based on 5-years of wave data and weather charts.

Original languageEnglish
Pages (from-to)1364-1377
Number of pages14
JournalProceedings of the Coastal Engineering Conference
Publication statusPublished - Dec 1 1998
Externally publishedYes
EventProceedings of the 1998 26th International Conference on Coastal Engineering, ICCE-98 - Copenhagen, Denmark
Duration: Jun 22 1998Jun 26 1998


All Science Journal Classification (ASJC) codes

  • Ocean Engineering

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