The impact of several devastating hurricanes revealed the vulnerability of large areas of the U.S.A. to this catastrophic natural hazard. Therefore, especially considering the uncertainties in future climate and demographic conditions, exposure and vulnerability, there is a strong need to include storm surge predictions in hurricane risk analyses. In general, the models used for storm surge are unsuited for probabilistic studies that require a large number of simulations. This article presents a probabilistic formulation for storm surge predictions that are developed using the combination of a logistic model and a non-stationary random field. The proposed fully probabilistic formulation (i) provides the probability that a location is being flooded, (ii) considers the spatial correlation among the storm surge at different locations and (iii) predicts storm surge at locations that are different from those of the observations used for the model calibration and are not restricted to be alongshore. Such formulation can include the effects of climate change by calibrating the models with high-fidelity simulations that account for the effect of climate change performed using a realistic set of hurricanes. The proposed formulation is used to predict the storm surge in a specific geographic region near the Pamlico River in North Carolina.

几场破坏性飓风的影响揭示了美国大片地区对这种灾难性自然灾害的脆弱性。因此，特别是考虑到未来气候和人口状况，暴露和脆弱性的不确定性，强烈需要在风暴风险分析中包括风暴潮预测。通常，用于风暴潮的模型不适合需要大量模拟的概率研究。本文介绍了使用逻辑模型和非平稳随机域的组合开发的风暴潮预报的概率公式。拟议的完全概率公式（i）提供了某个位置被淹没的可能性，（ii）考虑不同地点的风暴潮之间的空间相关性，（iii）预测与模型校准所用观测值不同且不限于沿岸的地点的风暴潮。这样的表述可以通过使用高保真度模拟对模型进行校准来包括气候变化的影响，这些模拟考虑了使用现实飓风造成的气候变化的影响。拟议的公式用于预测北卡罗来纳州帕姆利科河附近特定地理区域的风暴潮。这样的表述可以通过使用高保真度模拟对模型进行校准来包括气候变化的影响，这些模拟考虑了使用现实飓风造成的气候变化的影响。拟议的公式用于预测北卡罗来纳州帕姆利科河附近特定地理区域的风暴潮。这样的表述可以通过使用高保真度模拟对模型进行校准来包括气候变化的影响，这些模拟考虑了使用现实飓风造成的气候变化的影响。拟议的公式用于预测北卡罗来纳州帕姆利科河附近特定地理区域的风暴潮。