On the suitability of the Generalised Pareto to model extreme waves
File Type:
PDFItem Type:
Journal ArticleDate:
2018Access:
openAccessCitation:
Teixeira, R., Nogal, M. & O'Connor, A., On the suitability of the Generalised Pareto to model extreme waves, Journal of Hydraulic Research, 56-6, 2018, 755-770Download Item:
Abstract:
Dealing with extreme events implies working with events that have low probability of occurrence. To characterize these, the peak-over-threshold method alongside the generalized Pareto distribution is commonly applied. However, when it comes to significant wave heights, this approach is not recommended. Here, the generalized Pareto distribution is discussed based on data collected around the coast of Ireland. A careful choice of threshold takes place, and a new methodology to establish the threshold level is introduced. Five indicators to evaluate the fitting are considered to compare the different statistical models. No evidence was identified to justify the rejection of the generalized Pareto distribution to model exceedances. Results show that it may be statistically less, equally or more adequate, depending on the peak-over-threshold implementation. Nevertheless, the generalized Pareto bounded character is of elementary interest for wave statistics. In some circumstances not considering it might lead to unrealistic significant wave return levels.
URI:
https://www.tandfonline.com/doi/abs/10.1080/00221686.2017.1402829http://hdl.handle.net/2262/91194
Sponsor
Grant Number
European Union (EU)
642453
Author's Homepage:
http://people.tcd.ie/teixeirrDescription:
PUBLISHEDSponsor:
European Union (EU)Type of material:
Journal ArticleURI:
https://www.tandfonline.com/doi/abs/10.1080/00221686.2017.1402829http://hdl.handle.net/2262/91194
Series/Report no:
Journal of Hydraulic Research;56-6;
Availability:
Full text availableKeywords:
Ocean engineering, Hydraulics of renewable energy systems, Extremes, Statistical theories and models, Peak-over-threshold, Significant wave heightSubject (TCD):
Marine Engineering , Probability theoryDOI:
https://doi.org/10.1080/00221686.2017.1402829Metadata
Show full item recordLicences: