Ramos-Santiago, Efrain

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    Stochastic simulation of tropical cyclones for quantification of uncertainty associated with storm recurrence and intensity
    (2019-07-10) Ramos-Santiago, Efrain; Pagán-Trinidad, Ismael; College of Engineering; Nadal-Caraballo, Norberto C.; Zapata-López, Raúl E.; Department of Civil Engineering; Ramírez-Durand, Lillian
    Current practice for the design and assessment of coastal infrastructure requires the use of stochastic methods for the evaluation of the risk associated with coastal hazards such as storm surge and flooding induced by tropical cyclones (TCs). The joint probability method (JPM) has become the standard probabilistic model used to quantify coastal storm hazard in hurricane-prone areas. The storm recurrence rate (SRR) is an integral component of the JPM. Estimation of SRR is necessary at multiple locations throughout a study area. A TC stochastic track model (STM) was developed for the North Atlantic basin capable of generating a large number of synthetic TCs that complement the historical record and improve the reliability of TC frequency and intensity statistics. Each synthetic TC is initiated by a non-homogeneous Poisson point process and propagated through a Markov process at 6-hour intervals. Characteristic TC parameters are populated along the track by sampling from spatially-varying probability distributions and statistical regression models derived from the historical record. Results from a 10,000-year run under stationary climate conditions demonstrate the capability of the STM to replicate the general trends of historical SRR and minimum central pressure statistics along the U.S. coastlines, including the Virgin Islands and Puerto Rico.