IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v117y2023i1d10.1007_s11069-023-05860-y.html
   My bibliography  Save this article

Forecasting tropical cyclogenesis over ocean basins in the Northern Hemisphere

Author

Listed:
  • Ishita Sarkar

    (University of Calcutta)

  • Jayanti Pal

    (Central University of Rajasthan)

  • Tapajyoti Chakraborty

    (Indian Institute of Technology Bhubaneswar)

  • Sutapa Chaudhuri

    (University of Calcutta)

Abstract

Understanding the role of tropical cloud clusters (TCC) in the development of tropical cyclones involves various complexities and, thus, necessitates precise research. The study on TC development from the TCCs is still minimal. The present research is carried out to investigate the predictability of Tropical cyclogenesis (TCG) by examining the Rossby Radius Ratio (RRR) and Daily Genesis Potential (DGP) of different cloud clusters over the four ocean basins in the Northern Hemisphere, viz., North Indian Ocean (NIO), North Atlantic Ocean (NAO), West Pacific Ocean (WPO), and East Pacific Ocean (EPO). The analysis of the TCC data, taken for the period 1996–2005, shows that both the predictors are skilled at identifying the developed and non-developed TCCs. The method of cumulative distribution is implemented to identify the threshold ranges of RRR and DGP. In addition, the forecast skill scores are estimated for the selected predictors. The rough set theory based on different condition-decision support is implemented to estimate the certainty in the TCG prediction scheme with each predictor individually and in combination. The result shows that higher certainty in TCG prediction is observed when RRR ≤ 24 and DGP ≥ 1.21 × 10−5 for the NIO basin. However, it is to be noted that the combination of both RRR and DGP provides better confidence in the predictability of TCG over the NAO basin (RRR ≤ 38 and DGP ≥ 0.71 × 10−5) and EPO basin (RRR ≤ 28.7 and DGP ≥ 0.47 × 10−5). Furthermore, RRR (threshold value ≤ 28.2) individually gives better predictability for TCG over the WPO basin. The forecasts of TCG with RRR and DGP are validated with the observations from 2006 to 2009.

Suggested Citation

  • Ishita Sarkar & Jayanti Pal & Tapajyoti Chakraborty & Sutapa Chaudhuri, 2023. "Forecasting tropical cyclogenesis over ocean basins in the Northern Hemisphere," 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. 117(1), pages 293-311, May.
  • Handle: RePEc:spr:nathaz:v:117:y:2023:i:1:d:10.1007_s11069-023-05860-y
    DOI: 10.1007/s11069-023-05860-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-023-05860-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11069-023-05860-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sutapa Chaudhuri & Anirban Middey & Sayantika Goswami & Soumita Banerjee, 2012. "Appraisal of the prevalence of severe tropical storms over Indian Ocean by screening the features of tropical depressions," 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. 61(2), pages 745-756, March.
    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. Sutapa Chaudhuri & Arumita Roy Chowdhury & Payel Das, 2018. "Implementation of Sugeno: ANFIS for forecasting the seismic moment of large earthquakes over Indo-Himalayan region," 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. 90(1), pages 391-405, January.
    2. Sutapa Chaudhuri & Debashree Dutta & Sayantika Goswami & Anirban Middey, 2013. "Intensity forecast of tropical cyclones over North Indian Ocean using multilayer perceptron model: skill and performance verification," 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. 65(1), pages 97-113, January.
    3. S. Chaudhuri & D. Basu & D. Das & S. Goswami & S. Varshney, 2017. "Swarm intelligence and neural nets in forecasting the maximum sustained wind speed along the track of tropical cyclones over Bay of Bengal," 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. 87(3), pages 1413-1433, July.
    4. Sutapa Chaudhuri & Sayantika Goswami & Anirban Middey, 2014. "Medium-range forecast of cyclogenesis over North Indian Ocean with multilayer perceptron model using satellite data," 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. 70(1), pages 173-193, January.
    5. Sutapa Chaudhuri & Jayanti Pal & Anirban Middey & Sayantika Goswami, 2013. "Nowcasting Bordoichila with a composite stability index," 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. 66(2), pages 591-607, March.

    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:spr:nathaz:v:117:y:2023:i:1:d:10.1007_s11069-023-05860-y. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.