Spatial modeling of extreme snow depth
Spatial modeling of extreme snow depth
复制标题
极端积雪深度的空间建模
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
A. Davison
中科院分区：
文献类型：
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作者：
J. Blanchet;A. Davison
极端降雪的空间建模对于阿尔卑斯山和高海拔国家的充分风险管理非常重要。这种建模的一种自然方法是通过最大稳定过程理论，这是多元极值理论的无限维扩展。在本文中，我们描述了这样的过程中建模的空间依赖性的极端积雪深度在瑞士，1966年至2008年的冬天在101站的数据的基础上的应用。我们提出的模型依赖于气候转换，使我们能够考虑到气候区域的存在和方向性影响，导致天气模式。通过成对似然推断进行估计，并使用惩罚似然准则对模型进行比较。最大稳定模型提供了一个更好的适合联合行为的极端比独立或完全依赖模型。
The spatial modeling of extreme snow is important for adequate risk management in Alpine and high altitude countries. A natural approach to such modeling is through the theory of max-stable processes, an infinite-dimensional extension of multivariate extreme value theory. In this paper we describe the application of such processes in modeling the spatial dependence of extreme snow depth in Switzerland, based on data for the winters 1966--2008 at 101 stations. The models we propose rely on a climate transformation that allows us to account for the presence of climate regions and for directional effects, resulting from synoptic weather patterns. Estimation is performed through pairwise likelihood inference and the models are compared using penalized likelihood criteria. The max-stable models provide a much better fit to the joint behavior of the extremes than do independence or full dependence models.