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Operational tropical cyclone intensity prediction—an empirical technique

Author

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  • S. Roy Bhowmik
  • S. Kotal
  • S. Kalsi

Abstract

One very specific operational requirement of the Tropical Cyclone (TC) Programme of the Regional Specialized Meteorological Centre, New Delhi is to provide 12-hourly forecasts valid up to 48 h (preferably 72 h) on the intensity of cyclones over the southern Indian Seas. In this paper, a simple empirical model for predicting the intensity of TCs occurring in the Bay of Bengal is proposed. The model parameter has been determined from a database assembled on 30 recent cyclones, and the model itself is based on the assumption that a TC intensifies exponentially. A method for correcting the forecast during subsequent observation hours (6- or 12-h intervals) is also presented. The results show that the forecast skill for forecasts of up to 48 h is reasonably good. The absolute mean errors are less than 12 knots for 48-h forecasts, with the forecast skill decreasing with time. With the incorporation of a correction procedure based on the latest observations, some improvement in the forecast skill can be obtained. The model is expected to be useful to operational forecasters. Copyright Springer Science+Business Media, Inc. 2007

Suggested Citation

  • S. Roy Bhowmik & S. Kotal & S. Kalsi, 2007. "Operational tropical cyclone intensity prediction—an empirical technique," 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. 41(3), pages 447-455, June.
  • Handle: RePEc:spr:nathaz:v:41:y:2007:i:3:p:447-455
    DOI: 10.1007/s11069-006-9053-6
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    Cited by:

    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.

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