STATISTICAL WAVE FORECASTING THROUGH KALMAN FILTERING COMBINED WITH PRINCIPAL COMPONENT ANALYSIS

Noriaki Hashimoto, Toshihiko Nagai, Masanobu Kudaka

Abstract


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.

Keywords


wave forecasting; Kalman filtering; principal component analysis

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