Estimating the parameters of ocean wave spectra
File(s)
Published version
Author(s)
Grainger, Jake P
Sykulski, Adam M
Jonathan, Philip
Ewans, Kevin
Type
Journal Article
Abstract
Wind-generated waves are often treated as stochastic processes. There is particular interest in their spectral density functions, which are often expressed in some parametric form. Such spectral density functions are used as inputs when modelling structural response or other engineering concerns. Therefore, accurate and precise recovery of the parameters of such a form, from observed wave records, is important. Current techniques are known to struggle with recovering certain parameters, especially the peak enhancement factor and spectral tail decay. We introduce an approach from the statistical literature, known as the de-biased Whittle likelihood, and address some practical concerns regarding its implementation in the context of wind-generated waves. We demonstrate, through numerical simulation, that the de-biased Whittle likelihood outperforms current techniques, such as least squares fitting, both in terms of accuracy and precision of the recovered parameters. We also provide a method for estimating the uncertainty of parameter estimates. We perform an example analysis on a data-set recorded off the coast of New Zealand, to illustrate some of the extra practical concerns that arise when estimating the parameters of spectra from observed data.
Date Issued
2021-04-13
Date Acceptance
2021-03-21
Citation
Ocean Engineering, 2021, 229
ISSN
0029-8018
Publisher
Elsevier
Journal / Book Title
Ocean Engineering
Volume
229
Copyright Statement
© 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Sponsor
Engineering and Physical Sciences Research Council
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000648525500021&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
EP/R01860X/1
Subjects
Science & Technology
Technology
Physical Sciences
Engineering, Marine
Engineering, Civil
Engineering, Ocean
Oceanography
Engineering
Wave spectrum
Parameter estimation
JONSWAP
Spectral-likelihood
De-biased Whittle likelihood
Parameter uncertainty
FREQUENCY-DOMAIN
EQUILIBRIUM RANGE
EXACT SIMULATION
TIME
LIKELIHOOD
MODEL
Publication Status
Published
Article Number
ARTN 108934