The Princeton environment‐dependent probabilistic tropical cyclone (PepC) model is developed for generating synthetic tropical cyclones (TCs) to support TC risk assessment. PepC consists of three components: a hierarchical Poisson genesis model, an analog‐wind track model, and a Markov intensity model. The three model components are dependent on environmental variables that vary with the climate, including potential intensity, advection flow, vertical wind shear, relative humidity, and ocean‐cooling parameters. The present model is developed for the North Atlantic Basin. The three model components and the integrated model are verified against observations using out‐of‐sample testing. The model can generally capture the TC climatology and reproduce statistics of TC genesis, movement, rapid intensification, and lifetime maximum intensity, as well as local landfall frequency and intensity. It can be coupled with climate models and TC hazard models to quantify TC‐related wind, surge, and rainfall risks under various climate conditions. The modeling framework can be further improved when more relevant environmental variables are identified and become available in climate model outputs.

中文翻译：

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环境相关的概率热带气旋模型

开发了普林斯顿依赖环境的概率热带气旋（PepC）模型来生成合成热带气旋（TC）以支持TC风险评估。PepC由三部分组成：分层泊松发生模型，模拟风迹模型和马尔可夫强度模型。这三个模型成分取决于随气候变化的环境变量，包括潜在强度，平流，垂直风切变，相对湿度和海洋冷却参数。本模型是为北大西洋盆地开发的。使用样本外测试针对观察结果验证了三个模型组件和集成模型。该模型通常可以捕获TC气候，并复制TC发生，移动，快速增强和终生最大强度的统计信息，以及当地登陆频率和强度。它可以与气候模型和TC危害模型结合使用，以量化各种气候条件下与TC相关的风，潮和降雨风险。当确定更多相关的环境变量并在气候模型输出中可用时，可以进一步改善建模框架。