Tsunami Detection by High-Frequency Radar Beyond the Continental Shelf

Abstract

International audienceWhere coastal tsunami hazard is governed by near-field sources, such as submarine mass failures or meteo-tsunamis, tsunami propagation times may be too small for a detection based on deep or shallow water buoys. To offer sufficient warning time, it has been proposed to implement early warning systems relying on high-frequency (HF) radar remote sensing, that can provide a dense spatial coverage as far offshore as 200-300 km (e.g., for Diginext Ltd.'s Stradivarius radar). Shore-based HF radars have been used to measure nearshore currents (e.g., CODAR SeaSonde(A (R)) system;), by inverting the Doppler spectral shifts, these cause on ocean waves at the Bragg frequency. Both modeling work and an analysis of radar data following the Tohoku 2011 tsunami, have shown that, given proper detection algorithms, such radars could be used to detect tsunami-induced currents and issue a warning. However, long wave physics is such that tsunami currents will only rise above noise and background currents (i.e., be at least 10-15 cm/s), and become detectable, in fairly shallow water which would limit the direct detection of tsunami currents by HF radar to nearshore areas, unless there is a very wide shallow shelf. Here, we use numerical simulations of both HF radar remote sensing and tsunami propagation to develop and validate a new type of tsunami detection algorithm that does not have these limitations. To simulate the radar backscattered signal, we develop a numerical model including second-order effects in both wind waves and radar signal, with the wave angular frequency being modulated by a time-varying surface current, combining tsunami and background currents. In each ``radar cell'', the model represents wind waves with random phases and amplitudes extracted from a specified (wind speed dependent) energy density frequency spectrum, and includes effects of random environmental noise and background current; phases, noise, and background current are extracted from independent Gaussian distributions. The principle of the new algorithm is to compute correlations of HF radar signals measured/simulated in many pairs of distant ``cells'' located along the same tsunami wave ray, shifted in time by the tsunami propagation time between these cell locations; both rays and travel time are easily obtained as a function of long wave phase speed and local bathymetry. It is expected that, in the presence of a tsunami current, correlations computed as a function of range and an additional time lag will show a narrow elevated peak near the zero time lag, whereas no pattern in correlation will be observed in the absence of a tsunami current; this is because surface waves and background current are uncorrelated between pair of cells, particularly when time-shifted by the long-wave propagation time. This change in correlation pattern can be used as a threshold for tsunami detection. To validate the algorithm, we first identify key features of tsunami propagation in the Western Mediterranean Basin, where Stradivarius is deploye...

HF Radar Activity in European Coastal Seas: Next Steps toward a Pan-European HF Radar Network

“…The spectra (frequency on the left and directional on the right) show strong swell (also evident in the peak wave directions on the map) with wind waves increasing in amplitude and peak frequency further offshore. Other products that can be obtained by means of advanced signal processing include: winds (Heron and Rose, 1986;Shen et al, 2012), and tsunami (Lipa et al, 2006;Gurgel et al, 2011;Grilli et al, 2015). In addition, several works have proven the potential use of HFRs for ship detection (Ponsford et al, 2001;Dzvonkovskaya et al, 2008) and tracking (Maresca et al, 2014).…”

Real-Time Tsunami Detection with Oceanographic Radar Based on Virtual Tsunami Observation Experiments

“…The Japan tsunami was detected 15-19 min before its arrival at the coast. Grilii et al [14] and Guérin et al [15] proposed a detection method using cross-correlation of the signals received at two points along a tsunami wave ray calculated beforehand and reported detection beyond the continental shelf, based on numerical experiments for far-and near-field tsunamis. The usage of band-averaged velocities is effective for detecting an incoming tsunami by reducing the observed errors in radial velocities and extracting the coherent motions of surface waters.…”

“…Figure 7a shows a timedistance diagram of the extracted ′ (04, , ) superimposed with the detection results from Equation (14). The green circles represent the time, (04, ), when the tsunami was detected ( ( , ) = 1), and the black line represents the arrival time of the first leading wavefront of the tsunami, ( (04, )), empirically defined as the time when the sea surface slope along the beam calculated from the simulated tsunami heights first exceeds 0.0001.…”

Introduction to “Global Tsunami Science: Past and Future, Volume II”

“…Grilli et al (2017) presented the second part of their two-part study of tsunami detection algorithms (TDA) based on analysing tsunami currents inverted from high-frequency (HF) radar Doppler spectra. In Part I of this work (Grilli et al 2016), the authors proposed a method, referred to as time correlation (TC) TDA that does not require inverting currents, but instead detects changes in correlations between radar signal time series. In Part II (Grilli et al 2017), the TC-TDA is applied for realistic tsunami case studies for the area West of Vancouver Island, British Columbia.…”