On the use of discrete seasonal and directional models for the estimation of extreme wave conditions
On the use of discrete seasonal and directional models for the estimation of extreme wave conditions
Extreme value theory is commonly used in offshore engineering to estimate extreme significant wave height. To justify the use of extreme value models it is of critical importance either to verify that the assumptions made by the models are satisfied by the data or to examine the effect violating model assumptions. An important assumption made in the derivation of extreme value models is that the data come from a stationary distribution. The distribution of significant wave height varies with both the direction of origin of a storm and the season it occurs in, violating the assumption of a stationary distribution. Extreme value models can be applied to analyse the data in discrete seasons or directional sectors over which the distribution can be considered approximately stationary. Previous studies have suggested that models which ignore seasonality or directionality are less accurate and will underestimate extremes. This study shows that in fact the opposite is true. Using realistic case studies, it is shown that estimates of extremes from non-seasonal models have a lower bias and variance than estimates from discrete seasonal models and that estimates from discrete seasonal models tend to be biased high. The results are also applicable to discrete directional models.
425-442
Mackay, Edward B.L.
3a339ca6-23db-4084-8e28-8e6d32603331
Challenor, Peter G.
a7e71e56-8391-442c-b140-6e4b90c33547
Bahaj, AbuBakr S.
a64074cc-2b6e-43df-adac-a8437e7f1b37
April 2010
Mackay, Edward B.L.
3a339ca6-23db-4084-8e28-8e6d32603331
Challenor, Peter G.
a7e71e56-8391-442c-b140-6e4b90c33547
Bahaj, AbuBakr S.
a64074cc-2b6e-43df-adac-a8437e7f1b37
Mackay, Edward B.L., Challenor, Peter G. and Bahaj, AbuBakr S.
(2010)
On the use of discrete seasonal and directional models for the estimation of extreme wave conditions.
Ocean Engineering, 37 (5-6), .
(doi:10.1016/j.oceaneng.2010.01.017).
Abstract
Extreme value theory is commonly used in offshore engineering to estimate extreme significant wave height. To justify the use of extreme value models it is of critical importance either to verify that the assumptions made by the models are satisfied by the data or to examine the effect violating model assumptions. An important assumption made in the derivation of extreme value models is that the data come from a stationary distribution. The distribution of significant wave height varies with both the direction of origin of a storm and the season it occurs in, violating the assumption of a stationary distribution. Extreme value models can be applied to analyse the data in discrete seasons or directional sectors over which the distribution can be considered approximately stationary. Previous studies have suggested that models which ignore seasonality or directionality are less accurate and will underestimate extremes. This study shows that in fact the opposite is true. Using realistic case studies, it is shown that estimates of extremes from non-seasonal models have a lower bias and variance than estimates from discrete seasonal models and that estimates from discrete seasonal models tend to be biased high. The results are also applicable to discrete directional models.
This record has no associated files available for download.
More information
Published date: April 2010
Organisations:
Marine Systems Modelling
Identifiers
Local EPrints ID: 152137
URI: http://eprints.soton.ac.uk/id/eprint/152137
ISSN: 0029-8018
PURE UUID: b0a4d848-b716-49c0-a599-dca13e18f2d3
Catalogue record
Date deposited: 13 May 2010 15:38
Last modified: 14 Mar 2024 02:32
Export record
Altmetrics
Contributors
Author:
Edward B.L. Mackay
Author:
Peter G. Challenor
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics