An Environment‐Dependent Probabilistic Tropical Cyclone Model
An Environment‐Dependent Probabilistic Tropical Cyclone Model
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DOI：
10.1029/2019ms001975
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发表时间：
2018-12
影响因子：
6.8
通讯作者：
R. Jing;N. Lin
中科院分区：
文献类型：
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作者：
R. Jing;N. Lin
普林斯顿环境依赖概率热带气旋（PepC）模式是为生成合成热带气旋（TC）以支持TC风险评估而开发的。PepC由三个部分组成：分层泊松成因模型，模拟风跟踪模型和马尔可夫强度模型。这三个模型组件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海盆开发的。使用样本外检验，根据观察结果对三个模型组件和集成模型进行验证。该模式能较好地反映热带气旋的气候特征，重现热带气旋的生成、移动、快速增强、最大强度、登陆频率和强度等统计数据。它可以与气候模型和TC危害模型相结合，以量化各种气候条件下与TC相关的风、浪涌和降雨风险。当更多相关的环境变量被确定并在气候模型输出中可用时，可以进一步改进建模框架。
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.