Basin-wide spatial conditional extremes for severe ocean storms
Basin-wide spatial conditional extremes for severe ocean storms
复制标题
严重海洋风暴的全流域空间条件极端
作者：
R. Shooter;J. Tawn;E. Ross;P. Jonathan
物理的考虑和以前的研究表明，极端的依赖性在两个位置的海洋风暴的严重程度表现出近渐近的依赖性在短的位置间的距离，导致渐近独立性和完美的独立性随着距离的增加。我们提出了一个空间条件极值（SCE）模型的风暴强度，其特征极端的空间依赖性的强烈风暴的距离和方向。该模型是Shooter等人2019（Environmetrics 30，e2562，2019）以及沃兹沃斯和Tawn（2019）的扩展，将SCE模型参数的分段线性表示与距离和方向结合起来;还考虑了包括一些SCE模型参数的参数表示在内的模型变体。SCE残差过程被假定为遵循delta-Laplace形式的边缘，与距离相关的参数。给定调节位置的远程位置的残差依赖性的特征在于依赖于远程位置之间的距离以及远程位置到调节位置的距离的条件高斯协方差。我们应用贝叶斯推断模型，以估计极端的空间依赖性的风暴峰值显着波高在附近的150个地点，覆盖超过200,000平方公里的北海。
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.
DOI：
10.48550/arxiv.1912.06560
发表时间：
2019
期刊：
arXiv e-prints
影响因子：
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作者：
Wadsworth Jennifer L.
通讯作者：
Wadsworth Jennifer L.