Tropical cyclone probability estimation in data-sparse regions: a subtropical high based approach

Jingyi Lu, Jiazi Li, Zhenguo Wang, Xiaochao Li, Chenlu Wang, Xiaopeng Yang, Zhiguo Gao, Shaohua Wang and Hua Zhang ()
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Jingyi Lu: Beijing Normal University at Zhuhai
Jiazi Li: Beijing Normal University at Zhuhai
Zhenguo Wang: State Grid Zhejiang Electric Power Research Institute
Xiaochao Li: PowerChina Beijing Engineering Corporation Limited
Chenlu Wang: Beijing Normal University at Zhuhai
Xiaopeng Yang: Beijing Normal University at Zhuhai
Zhiguo Gao: Beijing Normal University at Zhuhai
Shaohua Wang: State Grid Zhejiang Electric Power Research Institute
Hua Zhang: Beijing Normal University at Zhuhai

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2025, vol. 121, issue 12, No 42, 15007-15023

Abstract: Abstract The occurrence of tropical cyclones (TCs) in rare-event zones, such as mid-latitudes and inland regions, poses a significant challenge to disaster preparedness due to the limitations of traditional probabilistic forecasting methods based on historical events or random events set. This study addresses this challenge by developing a novel approach for estimating TC track probabilities in data-sparse areas. Focusing on the Northwest Pacific, we leverage the mechanistic link between TC genesis and movement and the subtropical high-pressure system. We find that the distance between the TC track and the edge of subtropical high exhibits a distinct spatial pattern. By quantifying the spatial correlation between historical TC tracks and subtropical highs distribution, we construct a probabilistic model for TC track prediction. Model simulations accurately reproduce the characteristics of historical high-frequency TC tracks and effectively estimate TC probabilities in rare-occurrence zones, surpassing the limitations of historical data reliance and random event set approaches. This methodology offers a promising framework for enhancing TC risk assessment and preparedness in understudied regions.

Keywords: Tropical cyclone; Subtropical high; Disaster reduction; Risk assessment (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11069-025-07378-x

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