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Stochastic modelling of tropical cyclone tracks

Author

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  • Jonas Rumpf
  • Helga Weindl
  • Peter Höppe
  • Ernst Rauch
  • Volker Schmidt

Abstract

A stochastic model for the tracks of tropical cyclones that allows for the computerised generation of a large number of synthetic cyclone tracks is introduced. This will provide a larger dataset than previously available for the assessment of risks in areas affected by tropical cyclones. To improve homogeneity, the historical tracks are first split into six classes. The points of cyclone genesis are modelled as a spatial Poisson point process, the intensity of which is estimated using a generalised version of a kernel estimator. For these points, initial values of direction, translation speed, and wind speed are drawn from histograms of the historical values of these variables observed in the neighbourhood of the respective points, thereby generating a first 6-h segment of a track. The subsequent segments are then generated by drawing changes in theses variables from histograms of the historical data available near the cyclone’s current location. A termination probability for the track is determined after each segment as a function of wind speed and location. In the present paper, the model is applied to historical cyclone data from the western North Pacific, but it is general enough to be transferred to other ocean basins with only minor adjustments. A version for the North Atlantic is currently under preparation. Copyright Springer-Verlag 2007

Suggested Citation

  • Jonas Rumpf & Helga Weindl & Peter Höppe & Ernst Rauch & Volker Schmidt, 2007. "Stochastic modelling of tropical cyclone tracks," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 66(3), pages 475-490, December.
    • Handle: RePEc:spr:mathme:v:66:y:2007:i:3:p:475-490
    DOI: 10.1007/s00186-007-0168-7
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    Citations

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    Cited by:

    1. Socorro Margarita T. Rodrigo & Cesar L. Villanoy & Jeric C. Briones & Princess Hope T. Bilgera & Olivia C. Cabrera & Gemma Teresa T. Narisma, 2018. "The mapping of storm surge-prone areas and characterizing surge-producing cyclones in Leyte Gulf, Philippines," 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. 92(3), pages 1305-1320, July.
    2. Ashley C. Freeman & Walker S. Ashley, 2017. "Changes in the US hurricane disaster landscape: the relationship between risk and exposure," 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. 88(2), pages 659-682, September.
    3. Björn Kriesche & Helga Weindl & Anselm Smolka & Volker Schmidt, 2014. "Stochastic simulation model for tropical cyclone tracks, with special emphasis on landfall behavior," 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. 73(2), pages 335-353, September.
    4. Jonas Rumpf & Helga Weindl & Peter Höppe & Ernst Rauch & Volker Schmidt, 2009. "Tropical cyclone hazard assessment using model-based track simulation," 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. 48(3), pages 383-398, March.
    5. Md. Asaduzzaman & A. Latif, 2014. "A parametric Markov renewal model for predicting tropical cyclones in Bangladesh," 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. 73(2), pages 597-612, September.

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