Tsunami Detection by High Frequency Radar Using a Time-Correlation Algorithm: Performance Analysis Based on Data From a HF Radar in British Columbia

Guérin, Charles-Antoine (Université de Toulon) | Grilli, Stéphan T. (University of Rhode Island) | Moran, Patrick (University of Rhode Island) | Grilli, Annette (University of Rhode Island) | Insua, Tania (Ocean Networks Canada (ONC))

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ABSTRACT

A High-Frequency (HF) radar was installed by Ocean Networks Canada in Tofino, BC, to detect tsunamis from far- and near-field sources on the Pacific Ocean side of Vancouver Island; in particular, from seismic sources in the Cascadia Subduction Zone. Based on a classical analysis of the Doppler spectrum, this HF radar can measure ocean surface currents up to a 85-110 km range depending on sea state. However, an inherent limitation of detection of small and short-lived tsunami currents is the conflicting requirement for short integration time and sufficient accuracy (resolution) of the Doppler spectra. This limits a direct tsunami detection typically to shallow water areas over the continental shelf where tsunami currents have become sufficiently strong due to wave shoaling.

To overcome this limitation, the authors have recently proposed a new detection method, referred to as “Time-Correlation Algorithm (TCA)”, that does not require inverting Doppler spectra for the tsunami currents and can thus potentially detect an approaching tsunami in deeper water, beyond the continental shelf. This algorithm is based on computing space-time correlation of the raw radar signal in different radar cells aligned along precomputed tsunami wave rays, and time-shifted by the precomputed tsunami propagation time between cells. A change in pattern of such correlations indicates the presence of a tsunami. They validated the TCA with numerical simulations for both idealized (Grilli et al., 2016a) and realistic (Grilli et al., 2016b, 2017) tsunami wave trains and seafloor bathymetry, using data simulated with a radar simulator.

Here, the TCA is for the first time applied to actual radar data measured with the ONC WERA HF radar and numerically modified by a synthetic tsunami current. Using a state-of-the-art long wave model we perform tsunami simulations with realistic source and bathymetry, and combine the resulting currents with the background currents and radar backscattered signal measured by the HF radar system. This combination makes it possible to evaluate the performance of the proposed TCA detection algorithm, based on an experimental rather than numerically simulated, data set of radar signal. Our findings confirm that an actual detection can be achieved beyond the continental shelf, where tsunami currents are small (as low as 5 cm/s), in deeper water than when using an algorithm based on a direct inversion of currents from the measured radar Doppler spectra.