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Long-term distributions of individual wave and crest heights.

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Title: Long-term distributions of individual wave and crest heights.
Authors: Mackay, Ed1 e.mackay@exeter.ac.uk, Johanning, Lars1
Source: Ocean Engineering. Oct2018, Vol. 165, p164-183. 20p.
Subjects: Ocean waves, Ocean conditions (Weather), Ocean bottom, Ocean currents, Time series analysis
Abstract: This paper considers three types of method for calculating return periods of individual wave and crest heights. The methods considered differ in the assumptions made about serial correlation in wave conditions. The long-term distribution of individual waves is formed under the assumption that either (1) individual waves, (2) the maximum wave height in each sea state or (3) the maximum wave height in each storm are independent events. The three types of method are compared using long time series of synthesised storms, where the return periods of individual wave heights are known. The methods which neglect serial correlation in sea states are shown to produce a positive bias in predicted return values of wave heights. The size of the bias is dependent on the shape of the tail of the distribution of storm peak significant wave height, with longer-tailed distributions resulting in larger biases. It is shown that storm-based methods give accurate predictions of return periods of individual wave heights. In particular, a Monte Carlo storm-based method is recommend for calculating return periods of individual wave and crest heights. Of all the models considered, the Monte Carlo method requires the fewest assumptions about the data, the fewest subjective judgements from the user and is simplest to implement. [ABSTRACT FROM AUTHOR]
Copyright of Ocean Engineering is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 131295542
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Long-term distributions of individual wave and crest heights.
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  Data: <searchLink fieldCode="JN" term="%22Ocean+Engineering%22">Ocean Engineering</searchLink>. Oct2018, Vol. 165, p164-183. 20p.
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  Data: <searchLink fieldCode="DE" term="%22Ocean+waves%22">Ocean waves</searchLink><br /><searchLink fieldCode="DE" term="%22Ocean+conditions+%28Weather%29%22">Ocean conditions (Weather)</searchLink><br /><searchLink fieldCode="DE" term="%22Ocean+bottom%22">Ocean bottom</searchLink><br /><searchLink fieldCode="DE" term="%22Ocean+currents%22">Ocean currents</searchLink><br /><searchLink fieldCode="DE" term="%22Time+series+analysis%22">Time series analysis</searchLink>
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  Label: Abstract
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  Data: This paper considers three types of method for calculating return periods of individual wave and crest heights. The methods considered differ in the assumptions made about serial correlation in wave conditions. The long-term distribution of individual waves is formed under the assumption that either (1) individual waves, (2) the maximum wave height in each sea state or (3) the maximum wave height in each storm are independent events. The three types of method are compared using long time series of synthesised storms, where the return periods of individual wave heights are known. The methods which neglect serial correlation in sea states are shown to produce a positive bias in predicted return values of wave heights. The size of the bias is dependent on the shape of the tail of the distribution of storm peak significant wave height, with longer-tailed distributions resulting in larger biases. It is shown that storm-based methods give accurate predictions of return periods of individual wave heights. In particular, a Monte Carlo storm-based method is recommend for calculating return periods of individual wave and crest heights. Of all the models considered, the Monte Carlo method requires the fewest assumptions about the data, the fewest subjective judgements from the user and is simplest to implement. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Group: Ab
  Data: <i>Copyright of Ocean Engineering is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.oceaneng.2018.07.047
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 20
        StartPage: 164
    Subjects:
      – SubjectFull: Ocean waves
        Type: general
      – SubjectFull: Ocean conditions (Weather)
        Type: general
      – SubjectFull: Ocean bottom
        Type: general
      – SubjectFull: Ocean currents
        Type: general
      – SubjectFull: Time series analysis
        Type: general
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      – TitleFull: Long-term distributions of individual wave and crest heights.
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            NameFull: Mackay, Ed
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            – D: 01
              M: 10
              Text: Oct2018
              Type: published
              Y: 2018
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              Value: 165
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            – TitleFull: Ocean Engineering
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