TY - JOUR

T1 - Statistical estimation of extreme ocean environments

T2 - The requirement for modelling directionality and other covariate effects

AU - Jonathan, P.

AU - Ewans, K.

AU - Forristall, G.

PY - 2008

Y1 - 2008

N2 - With increasing availability of good directional data, provision of directional estimates of extreme significant wave heights, in addition to the omni-directional estimates, is more common. However, interpretation of directional together with omni-directional design criteria is subject to inconsistency, even in design guidelines. In particular, omni-directional criteria are usually estimated ignoring directional effects. In this article, for data which exhibit directional effects, we show that a directional extreme value model generally explains the observed variation significantly better than a model which ignores directionality, and that omni-directional criteria developed from a directional model are different from those generated when directionality is not accounted for. We also show that omni-directional criteria derived from a directional model are more accurate and should be preferred in general over those based on models which ignore directional effects. We recommend use of directional extreme value models for estimation of both directional and omni-directional design criteria in future, when good directional data are available. If effects of other covariates (e.g. time or space) are suspected, we similarly recommend use of extreme value models which adequately capture sources of covariate variability for all design analysis. © 2008 Elsevier Ltd. All rights reserved.

AB - With increasing availability of good directional data, provision of directional estimates of extreme significant wave heights, in addition to the omni-directional estimates, is more common. However, interpretation of directional together with omni-directional design criteria is subject to inconsistency, even in design guidelines. In particular, omni-directional criteria are usually estimated ignoring directional effects. In this article, for data which exhibit directional effects, we show that a directional extreme value model generally explains the observed variation significantly better than a model which ignores directionality, and that omni-directional criteria developed from a directional model are different from those generated when directionality is not accounted for. We also show that omni-directional criteria derived from a directional model are more accurate and should be preferred in general over those based on models which ignore directional effects. We recommend use of directional extreme value models for estimation of both directional and omni-directional design criteria in future, when good directional data are available. If effects of other covariates (e.g. time or space) are suspected, we similarly recommend use of extreme value models which adequately capture sources of covariate variability for all design analysis. © 2008 Elsevier Ltd. All rights reserved.

KW - Design criteria

KW - Directional models

KW - Extremes

KW - Generalised Pareto

KW - Architectural design

KW - Estimation

KW - Modal analysis

KW - Photoacoustic effect

KW - Covariate

KW - Covariates

KW - Design criterion

KW - design guidelines

KW - Design/analysis

KW - Directional data

KW - Directional effects

KW - Elsevier (CO)

KW - extreme values

KW - General (CO)

KW - Omni directional

KW - Significant wave height (SWH)

KW - Statistical estimation

KW - Mathematical models

KW - design method

KW - estimation method

KW - statistical analysis

KW - wave height

U2 - 10.1016/j.oceaneng.2008.04.002

DO - 10.1016/j.oceaneng.2008.04.002

M3 - Journal article

VL - 35

SP - 1211

EP - 1225

JO - Ocean Engineering

JF - Ocean Engineering

SN - 0029-8018

IS - 11-12

ER -