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On October 14th, 2016, the station of Tofino (British Columbia, Canada)issued the first ever real-time tsunami alert triggered by a coastalHigh-Frequency Radar system, based on the identification of abnormal surfacecurrent patterns. The detection occurred in the absence of any reported seismicevent but coincided with a strong atmospheric perturbation, which qualified theevent as meteo-tsunami. We re-analyze this case in the light of a new radarsignal processing method which was designed recently for inverting fast-varyingsea surface currents from the complex voltage time series received on theantennas. This method, based on an Auto-regressive modeling combined with aMaximum Entropy Method, yields a dramatic improvement in both theSignal-to-Noise Ratio and the quality of the surface current estimation forvery short integration time. This makes it possible to evidence the propagationof a sharp wave front of surface current during the event and to map itsmagnitude and arrival time over the radar coverage. We show that the amplitudeand speed of the inferred residual current do not comply with a Proudmanresonance mechanism but are consistent with the propagation of a low-pressureatmospheric front and wind vectors as revealed by satellite imagery. Thisindicates that the event that triggered a tsunami alert is more likely a stormsurge than a true meteo-tsunami. Beyond this specific case, another outcome ofthe analysis is the promising use of oceanographic radars as proxy's for thecharacterization of atmospheric fronts.

A Reanalysis of the October 2016 "Meteotsunami" in British Columbia with Help of High-Frequency Radars and Autoregressive Modeling