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.

物理上的考虑和先前的研究表明，在两个位置的海洋风暴严重性之间的极端依赖关系在较短的位置距离上表现出接近渐近的依赖关系，从而导致渐近独立性和随着距离的增加而变得完全独立。我们提出了风暴严重性的空间条件极端（SCE）模型，通过距离和方向来表征严重风暴的极端空间依赖性。该模型是Shooter等人的扩展。2019（环境计量学30，e2562，2019）和Wadsworth and Tawn（2019），并结合了具有距离和方向的SCE模型参数的分段线性表示; 还考虑了模型变体，包括一些SCE模型参数的参数表示。假定SCE残差过程略微遵循delta-Laplace形式，并具有与距离有关的参数。给定调节位置对远程位置的剩余依赖性的特征在于，条件高斯协方差取决于远程位置之间的距离以及远程位置到调节位置的距离。我们使用贝叶斯推论应用该模型来估计北海150个覆盖200,000 km ²的区域附近风暴峰有效波高的极值空间依赖性。