An Environment‐Dependent Probabilistic Tropical Cyclone Model
Abstract 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 inte...
| Published in: | Journal of Advances in Modeling Earth Systems |
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| Main Authors: | , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
American Geophysical Union (AGU)
2020
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| Subjects: | |
| Online Access: | https://doi.org/10.1029/2019MS001975 https://doaj.org/article/132f7e1e5e1646828d9671603b1681e8 |
| Summary: | Abstract 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. |
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