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An environment-driven basin scale tropical cyclone model

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

This paper presents an environment-driven tropical cyclone (TC) model for the Western North Pacific basin, which comprises a revised Poisson regression genesis model, a tailored beta-advection track model, and a fast intensity model. The TC model reproduces the temporal and spatial distributions of genesis events, the motion pattern of tracks, as well as the intensity evolutions along tracks. Risk analyses for Hong Kong and along the southeast coastline of mainland China demonstrate that this model can simulate extreme TC events with high fidelity. And the Gaussian mixture model outperforms the Frank Copula on approximating the joint distributions of the annual maximum wind speeds and the corresponding wind directions. This model is driven by a set of environmental variables including relative vorticity, relative humidity, sea surface temperature, vertical wind shear, potential intensity, sub mixed layer depth stratification, mixture layer depth and so on. This enables the model to not only reproduce historical records, but also make predictions for future TC behaviors under climate change with combination of global climate models. Besides, the computational efficiency of the TC model is comparable to traditional purely statistical models. The proposed model can also be coupled with other natural hazard models to conduct multi-hazard analysis. © 2024 Elsevier Ltd. All rights reserved.
Original languageEnglish
Article number102480
JournalStructural Safety
Volume109
Online published1 May 2024
DOIs
Publication statusPublished - Jul 2024

Funding

This work was supported by grants from the Research Grants Council of Hong Kong ( Project No: CityU 11206922, R1006-23), and the Science, Technology and Innovation Commission of Shenzhen Municipality, China (Project No: SGDX2020110309300301, JCYJ20220818101201003).

Research Keywords

  • Tropical cyclone
  • Natural hazard
  • Risk analysis
  • Joint distribution

RGC Funding Information

  • RGC-funded

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