A parametric Markov renewal model for predicting tropical cyclones in Bangladesh

Md. Asaduzzaman () and A. Latif ()

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2014, vol. 73, issue 2, 597-612

Abstract: In this paper, we consider a Markov renewal process (MRP) to model tropical cyclones occurred in Bangladesh during 1877–2009. The model takes into account both the occurrence history and some physical constraints to capture the main physical characteristics of the storm surge process. We assume that the sequence of cyclones constitutes a Markov chain, and sojourn times follow a Weibull distribution. The parameters of the Weibull MRP jointly with transition probabilities are estimated using the maximum likelihood method. The model shows a good fit with the real events, and probabilities of occurrence of different types of cyclones are calculated for various lengths of time interval using the model. Stationary probabilities and mean recurrence times are also calculated. A brief comparison with a Poisson model and a marked Poisson model has also been demonstrated. Copyright Springer Science+Business Media Dordrecht 2014

Keywords: Cyclone prediction; Marked Poisson process; Poisson process; Semi-Markov process; Statistical estimation of Markov renewal process (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:73:y:2014:i:2:p:597-612

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DOI: 10.1007/s11069-014-1101-z

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