Examination of generation mechanisms for an English Channel meteotsunami: combining observations and modeling

Williams, David A; Horsburgh, Kevin J; Schultz, David M; Hughes, Chris W. 2018 Examination of generation mechanisms for an English Channel meteotsunami: combining observations and modeling. Journal of Physical Oceanography, 49 (1). 103-120.

Before downloading, please read NORA policies.
[img] Text
Restricted to NORA staff only until 7 November 2019.

Download (8MB)


On the morning of 23 June 2016, a 0.70 m meteotsunami was observed in the English Channel between the UK and France. This wave was measured by several tide gages and coincided with a heavily precipitating convective system producing 10 m s−1 wind speeds at the 10-m level and 1–2.5 hPa surface pressure anomalies. A combination of precipitation rate crosscorrelations and NCEP/NCAR Reanalysis 1 data showed that the convective system moved northeastward at 19 ± 2 m s−1. To model the meteotsunami, the finite element model Telemac was forced with an ensemble of prescribed pressure forcings, covering observational uncertainty. Ensembles simulated the observed wave period and arrival times within minutes, and wave heights within tens of centimeters. A directly forced wave and a secondary coastal wave were simulated, and these amplified as they propagated. Proudman resonance was responsible for the wave amplification, and the coastal wave resulted from strong refraction of the primary wave. The main generating mechanism was the atmospheric pressure anomaly with wind stress playing a secondary role, increasing the first wave peak by 16% on average. Certain tidal conditions reduced modeled wave heights by up to 56%, by shifting the location where Proudman resonance occurred. This shift was mainly from tidal currents, rather than tidal elevation directly affecting shallow water wave speed. An improved understanding of meteotsunami return periods and generation mechanisms would be aided by tide gage measurements sampled at less than 15-minute intervals.

Item Type: Publication - Article
Digital Object Identifier (DOI):
ISSN: 0022-3670
Date made live: 14 Nov 2018 13:50 +0 (UTC)

Actions (login required)

View Item View Item

Document Downloads

Downloads for past 30 days

Downloads per month over past year

More statistics for this item...