A Statistical Model for Post‐Tropical Cyclone Hazard Assessment

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Abstract
Post‐tropical cyclones (PTCs) induce significant hazards in the mid‐latitudes, yet are often misrepresented in storm hazard models. This study introduces a new statistical model for assessing PTC hazard in the North Atlantic (NA). The model comprises three components: a logistic regression model for PTC identification, an auto‐regressive model for PTC intensity prediction, and a probability‐based PTC lysis model. The PTC identification component is adapted from a statistical model developed earlier by Bieli et al. (2020), https://doi.org/10.1175/waf‐d‐19‐0045.1 , while the PTC intensity and lysis components are newly developed. These components are coupled with synthetic tropical cyclone (TC) tracks and intensities generated by the Columbia Hazard Model (CHAZ) to simulate the full life cycle of PTCs, with flexibility for integration with other TC hazard models. The model reproduces key features of Atlantic PTC climatology, including timing of extratropical transition completion, intensity distributions, and spatial track density, and enables robust estimation of PTC return periods. It reveals lower risks of intense PTCs and higher risks of weak PTCs along the western NA near North America relative to the eastern NA near Europe. In some cases, the return periods of landfalling intense PTCs along the western side can be up to 4.4 times the eastern side, when PTCs stronger than 942 hPa are considered. Notably, comparable return periods between PTC‐only and storms at all phases near Europe and Canada underscore the importance of explicitly representing PTCs in hazard assessments for these regions. The framework is designed to support assessments of future Atlantic PTC hazard and risk.
Funding Information
  • National Science Foundation (AGS2244917)
  • National Science Foundation (AGS‐2244918)
  • National Science Foundation (AGS‐2244919)
  • U.S. Department of Energy (DE‐SC0016605)

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