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The limitations of statistical low runs prediction in rough seas: a study based on real wave data

The limitations of statistical low runs prediction in rough seas: a study based on real wave data
The limitations of statistical low runs prediction in rough seas: a study based on real wave data
This work aims to estimate the feasibility of wave runs statistical prediction in rough seas, with a specific application of Kimura’s theory (Kimura, A.,1980). According to Kimura, the probability of a low run of waves of assigned length is a function of the correlation between consecutive waves in a group. Time series from wave buoy measurements (located at Bideford Bay, England and data downloaded from the Channel Coast website) have been tested. The spectral analysis showed that higher values of the significant wave height correspond to broader bandwidth spectra. The Kimura’s low runs prediction is noticeably affected by this aspect: by plotting the low runs probability against the number of incoming waves, narrow spectra show a steeper behaviour of the low runs probability curve, whereas broader spectra correspond to flat probability curves settled on lower values. Therefore, it appears that broader spectra are characterised by more grouping phenomena. Moreover, the Kimura’s estimation has been calculated in an adaptive frame applied to the signal, in order to test the sensitivity to the length of the data; a minimum length of 6 to 8 hours has been found to have a stable prediction of the low runs probability.
Quiescent Period Prediction;, wave runs prediction, signal processing.
0029-8018
25-32
Caiazzo, Giuseppe
37f9766e-73e5-4c47-8f08-3140ed38e9e8
Wilson, Philip
8307fa11-5d5e-47f6-9961-9d43767afa00
Taunton, Dominic
10bfbe83-c4c2-49c6-94c0-2de8098c648c
Caiazzo, Giuseppe
37f9766e-73e5-4c47-8f08-3140ed38e9e8
Wilson, Philip
8307fa11-5d5e-47f6-9961-9d43767afa00
Taunton, Dominic
10bfbe83-c4c2-49c6-94c0-2de8098c648c

Caiazzo, Giuseppe, Wilson, Philip and Taunton, Dominic (2019) The limitations of statistical low runs prediction in rough seas: a study based on real wave data. Ocean Engineering, 175, 25-32. (doi:10.1016/j.oceaneng.2019.02.022).

Record type: Article

Abstract

This work aims to estimate the feasibility of wave runs statistical prediction in rough seas, with a specific application of Kimura’s theory (Kimura, A.,1980). According to Kimura, the probability of a low run of waves of assigned length is a function of the correlation between consecutive waves in a group. Time series from wave buoy measurements (located at Bideford Bay, England and data downloaded from the Channel Coast website) have been tested. The spectral analysis showed that higher values of the significant wave height correspond to broader bandwidth spectra. The Kimura’s low runs prediction is noticeably affected by this aspect: by plotting the low runs probability against the number of incoming waves, narrow spectra show a steeper behaviour of the low runs probability curve, whereas broader spectra correspond to flat probability curves settled on lower values. Therefore, it appears that broader spectra are characterised by more grouping phenomena. Moreover, the Kimura’s estimation has been calculated in an adaptive frame applied to the signal, in order to test the sensitivity to the length of the data; a minimum length of 6 to 8 hours has been found to have a stable prediction of the low runs probability.

Text
THE LIMITATIONS OF STATISTICAL LOW RUNS PREDICTION IN ROUGH SEAS - Accepted Manuscript
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More information

Submitted date: 11 September 2018
Accepted/In Press date: 3 February 2019
e-pub ahead of print date: 10 February 2019
Published date: 1 March 2019
Keywords: Quiescent Period Prediction;, wave runs prediction, signal processing.

Identifiers

Local EPrints ID: 426362
URI: http://eprints.soton.ac.uk/id/eprint/426362
ISSN: 0029-8018
PURE UUID: 2f26b256-6bd4-4bc7-a8c6-dd269dabd920
ORCID for Giuseppe Caiazzo: ORCID iD orcid.org/0000-0002-1500-4341
ORCID for Philip Wilson: ORCID iD orcid.org/0000-0002-6939-682X
ORCID for Dominic Taunton: ORCID iD orcid.org/0000-0002-6865-089X

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Date deposited: 26 Nov 2018 17:30
Last modified: 08 Oct 2020 04:17

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