用二元布朗-雷斯尼克过程预报极值的统计后处理及其在阵风中的应用
Statistical Post-Processing of Forecasts for Extremes Using Bivariate Brown-Resnick Processes with an Application to Wind Gusts
摘要：
为了提高极端天气的预测，我们提出了一个联合空间模型的观测和预测，基于一个双变量布朗-雷斯尼克过程。由于类的平稳二元布朗-Resnick过程的充分特点是类的伪交叉变差函数，我们有助于伪交叉变差函数的理论理解，完善其所有组件的渐近行为的知识，并引入一个简约的，但灵活的参数模型。这两个发现都是经典地质统计学本身的兴趣。该模型适用于实际观测和预测数据的极端阵风在德国北部的119个站。
英文摘要：
To improve the forecasts of weather extremes, we propose a joint spatial model for the observations and the forecasts, based on a bivariate Brown-Resnick process. As the class of stationary bivariate Brown-Resnick processes is fully characterized by the class of pseudo cross-variograms, we contribute to the theorical understanding of pseudo cross-variograms refining the knowledge of the asymptotic behaviour of all their components and introducing a parsimonious, but flexible parametric model. Both findings are of interest in classical geostatistics on their own. The proposed model is applied to real observation and forecast data for extreme wind gusts at 119 stations in Northern Germany.
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