Long-term distributions of individual wave and crest heights. (1st October 2018)
- Record Type:
- Journal Article
- Title:
- Long-term distributions of individual wave and crest heights. (1st October 2018)
- Main Title:
- Long-term distributions of individual wave and crest heights
- Authors:
- Mackay, Ed
Johanning, Lars - Abstract:
- 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 : A new method for resampling time series to create random storms is proposed. Long-term distributions of individual wave heights are compared using 100,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 : A new method for resampling time series to create random storms is proposed. Long-term distributions of individual wave heights are compared using 100, 000-year simulated time series. Krogstad and Battjes methods are shown to produce positive bias in return values of individual wave heights. Storm-based methods are shown to give accurate estimates of return values. … (more)
- Is Part Of:
- Ocean engineering. Volume 165(2018)
- Journal:
- Ocean engineering
- Issue:
- Volume 165(2018)
- Issue Display:
- Volume 165, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 165
- Issue:
- 2018
- Issue Sort Value:
- 2018-0165-2018-0000
- Page Start:
- 164
- Page End:
- 183
- Publication Date:
- 2018-10-01
- Subjects:
- Wave height -- Crest height -- Long-term distribution -- Return period -- Serial correlation
Ocean engineering -- Periodicals
Ocean engineering
Periodicals
620.4162 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00298018 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.oceaneng.2018.07.047 ↗
- Languages:
- English
- ISSNs:
- 0029-8018
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6231.280000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 12877.xml