A framework for the probabilistic analysis of meteotsunamis

  • Eric L. GeistEmail author
  • Uri S. ten Brink
  • Matthew Gove
Original Paper


A probabilistic technique is developed to assess the hazard from meteotsunamis. Meteotsunamis are unusual sea-level events, generated when the speed of an atmospheric pressure or wind disturbance is comparable to the phase speed of long waves in the ocean. A general aggregation equation is proposed for the probabilistic analysis, based on previous frameworks established for both tsunamis and storm surges, incorporating different sources and source parameters of meteotsunamis. Parameterization of atmospheric disturbances and numerical modeling is performed for the computation of maximum meteotsunami wave amplitudes near the coast. A historical record of pressure disturbances is used to establish a continuous analytic distribution of each parameter as well as the overall Poisson rate of occurrence. A demonstration study is presented for the northeast U.S. in which only isolated atmospheric pressure disturbances from squall lines and derechos are considered. For this study, Automated Surface Observing System stations are used to determine the historical parameters of squall lines from 2000 to 2013. The probabilistic equations are implemented using a Monte Carlo scheme, where a synthetic catalog of squall lines is compiled by sampling the parameter distributions. For each entry in the catalog, ocean wave amplitudes are computed using a numerical hydrodynamic model. Aggregation of the results from the Monte Carlo scheme results in a meteotsunami hazard curve that plots the annualized rate of exceedance with respect to maximum event amplitude for a particular location along the coast. Results from using multiple synthetic catalogs, resampled from the parent parameter distributions, yield mean and quantile hazard curves. Further refinements and improvements for probabilistic analysis of meteotsunamis are discussed.


Meteotsunami Probabilistic analysis Squall line Derecho Shallow-water wave Linear long wave 


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The authors appreciate the constructive comments during review of this paper by Alexander Rabinovich, Richard Signell, and an anonymous reviewer.


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Copyright information

© US Government 2014

Authors and Affiliations

  • Eric L. Geist
    • 1
    Email author
  • Uri S. ten Brink
    • 2
  • Matthew Gove
    • 3
  1. 1.U.S. Geological SurveyMenlo ParkUSA
  2. 2.U.S. Geological SurveyWoods HoleUSA
  3. 3.Oklahoma CityUSA

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