%0 Journal Article %1 Shooter2021 %A Shooter, Rob %A Tawn, Jonathan %A Ross, Emma %A Jonathan, Philip %D 2021 %J Extremes %K extremalDependence waves %N 2 %P 241--265 %R 10.1007/s10687-020-00389-w %T Basin-wide spatial conditional extremes for severe ocean storms %U https://doi.org/10.1007/s10687-020-00389-w %V 24 %X Physical considerations and previous studies suggest that extremal dependence between ocean storm severity at two locations exhibits near asymptotic dependence at short inter-location distances, leading to asymptotic independence and perfect independence with increasing distance. We present a spatial conditional extremes (SCE) model for storm severity, characterising extremal spatial dependence of severe storms by distance and direction. The model is an extension of Shooter et al. 2019 (Environmetrics 30, e2562, 2019) and Wadsworth and Tawn (2019), incorporating piecewise linear representations for SCE model parameters with distance and direction; model variants including parametric representations of some SCE model parameters are also considered. The SCE residual process is assumed to follow the delta-Laplace form marginally, with distance-dependent parameter. Residual dependence of remote locations given conditioning location is characterised by a conditional Gaussian covariance dependent on the distances between remote locations, and distances of remote locations to the conditioning location. We apply the model using Bayesian inference to estimates extremal spatial dependence of storm peak significant wave height on a neighbourhood of 150 locations covering over 200,000 km2 in the North Sea.

@article{Shooter2021, abstract = {Physical considerations and previous studies suggest that extremal dependence between ocean storm severity at two locations exhibits near asymptotic dependence at short inter-location distances, leading to asymptotic independence and perfect independence with increasing distance. We present a spatial conditional extremes (SCE) model for storm severity, characterising extremal spatial dependence of severe storms by distance and direction. The model is an extension of Shooter et al. 2019 (Environmetrics 30, e2562, 2019) and Wadsworth and Tawn (2019), incorporating piecewise linear representations for SCE model parameters with distance and direction; model variants including parametric representations of some SCE model parameters are also considered. The SCE residual process is assumed to follow the delta-Laplace form marginally, with distance-dependent parameter. Residual dependence of remote locations given conditioning location is characterised by a conditional Gaussian covariance dependent on the distances between remote locations, and distances of remote locations to the conditioning location. We apply the model using Bayesian inference to estimates extremal spatial dependence of storm peak significant wave height on a neighbourhood of 150 locations covering over 200,000 km2 in the North Sea.}, added-at = {2022-04-05T18:14:03.000+0200}, author = {Shooter, Rob and Tawn, Jonathan and Ross, Emma and Jonathan, Philip}, biburl = {https://www.bibsonomy.org/bibtex/20c7760a7508530d76bd2cb49c3be6c42/simon.brown}, day = 01, description = {Basin-wide spatial conditional extremes for severe ocean storms | SpringerLink}, doi = {10.1007/s10687-020-00389-w}, interhash = {df666624f84a6e5ac084e874b26e4dd9}, intrahash = {0c7760a7508530d76bd2cb49c3be6c42}, issn = {1572-915X}, journal = {Extremes}, keywords = {extremalDependence waves}, month = jun, number = 2, pages = {241--265}, timestamp = {2022-04-05T18:14:03.000+0200}, title = {Basin-wide spatial conditional extremes for severe ocean storms}, url = {https://doi.org/10.1007/s10687-020-00389-w}, volume = 24, year = 2021 }