Statistical Forecasting of Long Period Waves Based on Weather Data for the Purpose of Judgment of Executing Cargo Loading

Noriaki Hashimoto; Koji Kawaguchi

Statistical Forecasting of Long Period Waves Based on Weather Data for the Purpose of Judgment of Executing Cargo Loading

Noriaki Hashimoto, Koji Kawaguchi

Research output: Contribution to conference › Paper › peer-review

Abstract

Statistical wave forecasting methods are sometimes applied because of their simplicity and convenience. Most of them, however, include some drawbacks from statistical and numerical viewpoints. In this paper, these drawbacks are discussed and a statistical forecasting method utilizing the Kalman filter technique combined with the Principal Component Analysis (Kalman-PCA model) is applied for the prediction of long period waves having the period of tens of seconds or longer, which was proposed to mitigate the drawbacks of the conventional statistical wave forecasting methods. Applicability and reliability of the method is examined for observed wave data at Shibushi port in Japan based on wave data and weather data for 5-years.

Original language	English
Pages	2042-2049
Number of pages	8
Publication status	Published - 2003
Externally published	Yes
Event	Proceedings of the Thirteenth (2003) International Offshore and Polar Engineering Conference - Honolulu, HI, United States Duration: May 25 2002 → May 30 2003

Other

Other	Proceedings of the Thirteenth (2003) International Offshore and Polar Engineering Conference
Country/Territory	United States
City	Honolulu, HI
Period	5/25/02 → 5/30/03

All Science Journal Classification (ASJC) codes

Energy Engineering and Power Technology
Ocean Engineering
Mechanical Engineering

Cite this

Statistical Forecasting of Long Period Waves Based on Weather Data for the Purpose of Judgment of Executing Cargo Loading. / Hashimoto, Noriaki; Kawaguchi, Koji.
2003. 2042-2049 Paper presented at Proceedings of the Thirteenth (2003) International Offshore and Polar Engineering Conference, Honolulu, HI, United States.

Research output: Contribution to conference › Paper › peer-review

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AB - Statistical wave forecasting methods are sometimes applied because of their simplicity and convenience. Most of them, however, include some drawbacks from statistical and numerical viewpoints. In this paper, these drawbacks are discussed and a statistical forecasting method utilizing the Kalman filter technique combined with the Principal Component Analysis (Kalman-PCA model) is applied for the prediction of long period waves having the period of tens of seconds or longer, which was proposed to mitigate the drawbacks of the conventional statistical wave forecasting methods. Applicability and reliability of the method is examined for observed wave data at Shibushi port in Japan based on wave data and weather data for 5-years.

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Statistical Forecasting of Long Period Waves Based on Weather Data for the Purpose of Judgment of Executing Cargo Loading

Abstract

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All Science Journal Classification (ASJC) codes

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