Multivariate spatial conditional extremes for extreme ocean environments

Rob Shooter,Emma Ross,Agustinus Ribal,Ian R Young,Philip Jonathan

doi:10.1016/j.oceaneng.2022.110647

Abstract

The joint extremal spatial dependence of wind speed and significant wave height in the North East Atlantic is quantified using Metop satellite scatterometer and hindcast observations for the period 2007–2018, and a multivariate spatial conditional extremes (MSCE) model, ultimately motivated by the work of Heffernan and Tawn (2004). The analysis involves (a) registering individual satellite swaths and corresponding hindcast data onto a template transect (running approximately north-east to south-west, between the British Isles and Iceland), (b) non-stationary directional-seasonal marginal extreme value analysis at a set of registration locations on the transect, (c) transformation from physical to standard Laplace scale using the fitted marginal model, (d) estimation of the MSCE model on the set of registration locations, and assessment of quality of model fit. A joint model is estimated for three spatial quantities: Metop wind speed, hindcast wind speed and hindcast significant wave height. Results suggest that, when conditioning on extreme Metop wind speed, extremal spatial dependence for all three quantities decays over approximately 600–800 km.

Highlights

Severe ocean events at a location often involve extreme values for more than one oceanographic variable, leading to interest in the development and tailoring of statistical methods for multivariate and conditional extremes in a met-ocean context; for example, extreme loads on an offshore structure often arise from a combination of wind, wave and current
The objective of the analysis is to evaluate our ability to quantify the joint structure of spatial fields corresponding to significant wave height and wind speed, based on hindcast and satellite data, conditional on the occurrence of an extreme wind speed or significant wave height event
Results of applying the multivariate spatial conditional extremes (MSCE) model to the Laplace-scale sample illustrated in Figure 4 are discussed

Summary

Introduction

Severe ocean events at a location often involve extreme values for more than one oceanographic variable, leading to interest in the development and tailoring of statistical methods for multivariate and conditional extremes in a met-ocean context; for example, extreme loads on an offshore structure often arise from a combination of wind, wave and current. Design and maintenance of a wind farms requires characterisation of the joint spatial field for metocean variables over a spatial neighbourhood. This leads to interest in the development of statistical models for the joint characteristics of multiple spatial fields of variables such as wind speed and significant wave height. The main use of the MSCE model is to provide a principled approach to characterising the joint structure of spatial fields, to be applied in any situation where environmental hazard results from extreme values of at least one metocean variable

Objectives

Methods

Results

Conclusion