PROBABILISTIC HURRICANE TRACK GENERATION FOR STORM SURGE PREDICTION

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Last Modified
  • March 21, 2019
Creator
  • Smith, Jessica
    • Affiliation: College of Arts and Sciences, Department of Marine Sciences
Abstract
  • Storm surge is a major source of devastation from hurricane events, and as such it is important to understand the uncertainty associated with storm surge forecasting. Uncertainty in predicted storm surge can be quantified by synthesizing a suite of probable storm tracks that are based on errors in predictions of previous hurricanes and computing storm surge with a suitable model. Davis et al. (2010) developed an approach to track generation based on cross-track errors in the official National Hurricane Center (NHC) forecast tracks. In this work their methods are extended to include along-track and maximum wind speed errors. Errors in the NHC forecasts are used to compute probability distributions that are sampled to generate synthetic tracks on either side of the official forecast track, with each track having an equal likelihood of occurrence. Storm surge for each track is then computed with the ADCIRC model (Westerink et al., 2008) to generate probability of exceedance maps and worst-case potential storm surge (maximum of maximums). The ideal error distribution sampling number for the forecast experiments used in this study for each dimension are 27 in the cross-track dimension, 9 in the along-track dimension, and 9 in the intensity dimension.
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Rights statement
  • In Copyright
Advisor
  • Blanton, Brian
  • Luettich, Richard A.
  • Bane, John
Degree
  • Master of Science
Degree granting institution
  • University of North Carolina at Chapel Hill Graduate School
Graduation year
  • 2017
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