IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i21p13969-d954999.html
   My bibliography  Save this article

High-Resolution Hazard Assessment for Tropical Cyclone-Induced Wind and Precipitation: An Analytical Framework and Application

Author

Listed:
  • Jiting Tang

    (Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China
    State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
    Academy of Disaster Reduction and Emergency Management, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Fuyu Hu

    (School of International Affairs and Public Administration, Ocean University of China, Qingdao 266100, China)

  • Yimeng Liu

    (Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China
    State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
    Academy of Disaster Reduction and Emergency Management, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Weiping Wang

    (School of National Safety and Emergency Management, Beijing Normal University, Beijing 100875, China)

  • Saini Yang

    (Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China
    State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
    Academy of Disaster Reduction and Emergency Management, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
    School of National Safety and Emergency Management, Beijing Normal University, Beijing 100875, China)

Abstract

Intensified tropical cyclones (TCs) threaten the socioeconomic development of coastal cities. The coupling of strong wind and precipitation with the TC process usually amplifies the destructive effects of storms. Currently, an integrated analytical framework for TC hazard assessment at the city level that combines the joint statistical characteristics of multiple TC-induced hazards and local environmental features does not exist. In this study, we developed a novel hazard assessment framework with a high spatiotemporal resolution that includes a fine-tuned K-means algorithm for clustering TC tracks and a Copula model to depict the wind–precipitation joint probability distribution of different TC categories. High-resolution wind and precipitation data were used to conduct an empirical study in Shenzhen, a coastal megacity in Guangdong Province, China. The results show that the probabilities of TC-induced wind speed and precipitation exhibit significant spatial heterogeneity in Shenzhen, which can be explained by the characteristics of TC tracks and terrain environment factors. In general, the hazard intensity of TCs landing from the west side is higher than that from the east side, and the greatest TC intensity appears on the southeast coast of Shenzhen, implying that more disaster prevention efforts are needed. The proposed TC hazard assessment method provides a solid base for highly precise risk assessment at the city level.

Suggested Citation

  • Jiting Tang & Fuyu Hu & Yimeng Liu & Weiping Wang & Saini Yang, 2022. "High-Resolution Hazard Assessment for Tropical Cyclone-Induced Wind and Precipitation: An Analytical Framework and Application," Sustainability, MDPI, vol. 14(21), pages 1-18, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:13969-:d:954999
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/21/13969/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/21/13969/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tayyebeh Nadaf & Taher Lotfi & Stanford Shateyi, 2022. "Revisiting the Copula-Based Trading Method Using the Laplace Marginal Distribution Function," Mathematics, MDPI, vol. 10(5), pages 1-9, March.
    2. Dan Chavas & Jie Chen, 2020. "Tropical cyclones could last longer after landfall in a warming world," Nature, Nature, vol. 587(7833), pages 200-201, November.
    3. Weihua Fang & Haixia Zhang, 2021. "Zonation and scaling of tropical cyclone hazards based on spatial clustering for coastal China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 109(1), pages 1271-1295, October.
    4. Benjamin Bass & John N. Irza & Jennifer Proft & Philip Bedient & Clint Dawson, 2017. "Fidelity of the integrated kinetic energy factor as an indicator of storm surge impacts," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 85(1), pages 575-595, January.
    5. Wang, Haiying & Yuan, Ying & Li, Yiou & Wang, Xunhong, 2021. "Financial contagion and contagion channels in the forex market: A new approach via the dynamic mixture copula-extreme value theory," Economic Modelling, Elsevier, vol. 94(C), pages 401-414.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yuan, Ying & Du, Xinyu, 2023. "Dynamic spillovers across global stock markets during the COVID-19 pandemic: Evidence from jumps and higher moments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
    2. Adriana AnaMaria Davidescu & Eduard Mihai Manta & Razvan Gabriel Hapau & Mihaela Gruiescu & Oana Mihaela Vacaru (Boita), 2023. "Exploring the Contagion Effect from Developed to Emerging CEE Financial Markets," Mathematics, MDPI, vol. 11(3), pages 1-50, January.
    3. Ahmed, Shamima & Assaf, Rima & Rahman, Molla Ramizur & Tabassum, Fariha, 2023. "Is geopolitical risk interconnected? Evidence from Russian-Ukraine crisis," The Journal of Economic Asymmetries, Elsevier, vol. 28(C).
    4. Imen Bedoui-Belghith & Slaheddine Hallara & Faouzi Jilani, 2023. "Crisis transmission degree measurement under crisis propagation model," SN Business & Economics, Springer, vol. 3(1), pages 1-27, January.
    5. Cevik, Emrah Ismail & Caliskan Terzioglu, Hande & Kilic, Yunus & Bugan, Mehmet Fatih & Dibooglu, Sel, 2024. "Interconnectedness and systemic risk: Evidence from global stock markets," Research in International Business and Finance, Elsevier, vol. 69(C).
    6. Wei, Zhengyuan & He, Qingxia & Zhou, Qili & Wang, Ge, 2023. "Measuring dependence structure and extreme risk spillovers in stock markets: An APARCH-EVT-DMC approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    7. Zhao, Wandi & Gao, Yang, 2024. "Dynamic patterns and the latent community structure of sectoral volatility and jump risk contagion," Emerging Markets Review, Elsevier, vol. 59(C).
    8. Jang, Hyuna & Kim, Jong-Min & Noh, Hohsuk, 2022. "Vine copula Granger causality in mean," Economic Modelling, Elsevier, vol. 109(C).
    9. Yuan, Ying & Wang, Haiying & Jin, Xiu, 2022. "Pandemic-driven financial contagion and investor behavior: Evidence from the COVID-19," International Review of Financial Analysis, Elsevier, vol. 83(C).
    10. Ur Rehman, Mobeen & Al Rababa'a, Abdel Razzaq & El-Nader, Ghaith & Alkhataybeh, Ahmad & Vo, Xuan Vinh, 2022. "Modelling the quantile cross-coherence between exchange rates: Does the COVID-19 pandemic change the interlinkage structure?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    11. He, Fuli & Yarahmadi, Ali & Soleymani, Fazlollah, 2024. "Investigation of multivariate pairs trading under copula approach with mixture distribution," Applied Mathematics and Computation, Elsevier, vol. 472(C).
    12. Zheng, Yanting & Luan, Xin & Lu, Xin & Liu, Jiaming, 2023. "A new view of risk contagion by decomposition of dependence structure: Empirical analysis of Sino-US stock markets," International Review of Financial Analysis, Elsevier, vol. 90(C).
    13. Thai Hung, Ngo & Nguyen, Linh Thi My & Vinh Vo, Xuan, 2022. "Exchange rate volatility connectedness during Covid-19 outbreak: DECO-GARCH and Transfer Entropy approaches," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    14. Jiang, Kunliang & Ye, Wuyi, 2022. "Does the asymmetric dependence volatility affect risk spillovers between the crude oil market and BRICS stock markets?," Economic Modelling, Elsevier, vol. 117(C).
    15. Liu, Yuntong & Wei, Yu & Wang, Qian & Liu, Yi, 2022. "International stock market risk contagion during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 45(C).
    16. Benkraiem, Ramzi & Garfatta, Riadh & Lakhal, Faten & Zorgati, Imen, 2022. "Financial contagion intensity during the COVID-19 outbreak: A copula approach," International Review of Financial Analysis, Elsevier, vol. 81(C).
    17. Krzysztof Brania & Henryk Gurgul, 2021. "Contagion effects on capital and forex markets around GFC and COVID-19 crises. A comparative study," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(2), pages 59-92.
    18. Fernandes, Mário Correia & Dias, José Carlos & Nunes, João Pedro Vidal, 2021. "Modeling energy prices under energy transition: A novel stochastic-copula approach," Economic Modelling, Elsevier, vol. 105(C).
    19. Hu, Genhua & Fan, Gang-Zhi, 2022. "Empirical evidence of risk contagion across regional housing markets in China," Economic Modelling, Elsevier, vol. 115(C).
    20. Vera Wendler-Bosco & Charles Nicholson, 2022. "Modeling the economic impact of incoming tropical cyclones using machine learning," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(1), pages 487-518, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:13969-:d:954999. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.