The Typhoon Wind Hazard Assessment Considering the Correlation among the Key Random Variables Using the Copula Method
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 9, Issue 2
Abstract
The probability distribution of typhoon key parameters is commonly incorporated into typhoon models to estimate the typhoon-induced wind speeds associated with certain return periods in typhoon-prone regions. In most studies that focus on the typhoon wind hazards of the southeast coastline of China, the typhoon key parameters are assumed to be independent. This paper develops a copula-based joint probability distribution for the typhoon key parameters to investigate its potential influence on the typhoon wind hazard on the southeast coastline of China. To this end, the best track typhoon data from the China meteorological administration are used to extract the key parameters of the typhoon. The analyses show that the observed correlation coefficients among the parameters could be larger than 0.4 at some locations on the considered coastline. The C-vine copula is then employed to establish the joint probabilistic model of these key parameters. Comparison between the observed and modeled joint probability distributions suggests the adequacy of the copula method–based probability distribution model. Then, a local track model and a typhoon wind field model are assembled to simulate the history of the typhoon-induced surface wind given the typhoon key parameters. Finally, Monte Carlo simulation is adopted to estimate the wind speed associated with 50- and 100-year return periods. Results show that neglecting the correlation among the typhoon key parameters could cause a relative difference of up to 7% at some locations on the coastline.
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Data Availability Statement
All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The financial support from the Fundamental Research Funds for the Central Universities of China (Nos. JZ2022HGQA0168 and PA2022GDSK0063), the Natural Science Foundation of Jiangsu Province (Grant No. BK20220357), and the Natural Science Foundation of the Jiangsu Higher Education Institutions (Grant No. 22KJB560005) are highly appreciated.
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Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 9 • Issue 2 • June 2023
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© 2023 American Society of Civil Engineers.
History
Received: Oct 12, 2022
Accepted: Feb 6, 2023
Published online: Mar 28, 2023
Published in print: Jun 1, 2023
Discussion open until: Aug 28, 2023
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