Algorithms for tsunami detection by High Frequency Radar : development and case studies for tsunami impact in British Columbia, Canada

A shore-based High-Frequency (HF) WERA radar was recently installed by Ocean Networks Canada (ONC) near Tofino, British Columbia (Canada), to mitigate the elevated tsunami hazard along the shores of Vancouver Island, from both farand near-field seismic sources and, in particular, from the Cascadia Subduction Zone (CSZ). With this HF radar, ocean currents can be measured up to a 70-85 km range, depending on atmospheric conditions, based on the Doppler shift they cause in ocean waves at the radar Bragg frequency. In earlier work, the authors (and others) have shown that tsunami currents need to be at least 0.15-0.20 m/s to be reliably detectable by HF radar, when considering environmental noise and background currents (from tide and mesoscale circulation). This would limit the direct detection of tsunami-induced currents to shallow water areas where they are sufficiently strong due to wave shoaling and, hence, to the continental shelf. It follows that, in locations with a narrow shelf, warning times based on such a tsunami detection method may be small. To detect tsunamis in deeper water, beyond the shelf, the authors have proposed a new algorithm that does not require “inverting” currents, but instead is based on spatial correlations of the raw radar signal at two distant locations/cells located along the same wave ray, time shifted by the tsunami propagation time along the ray. A pattern change in these correlations indicates the presence of a tsunami. They validated this algorithm for idealized tsunami wave trains propagating over a simple seafloor geometry in a direction normally incident to shore. Here, this algorithm is further developed, extended, and validated for realistic case studies conducted for seismic tsunami sources and using the bathymetry, offshore of Vancouver Island, BC. Tsunami currents, computed with a state-ofthe-art long wave model, are spatially averaged over cells aligned along individual wave rays, within the radar sweep area, obtained by solving the wave geometric optic equation. A model simulating ONC radar’s backscattered signal in space and time, as a function of the simulated tsunami currents, is applied on the Pacific Ocean side of Vancouver Island. Numerical experiments are performed, showing that the proposed algorithm works for detecting a realistic tsunami. Correlation thresholds relevant for tsunami detection can be inferred from the results. INTRODUCTION Major tsunamis can be enormously destructive and cause large numbers of fatalities along the world’s increasingly populated and developed coastlines (Ioualalen et al., 2007; Grilli et al., 2013). While the brunt of tsunami impact cannot be easily attenuated, loss of life, however, can be mitigated or even eliminated by providing early warning to coastal populations. Such warnings can be issued based on early detection and assessment of the mechanisms of tsunami generation (e.g., seismicity) as well as detection of the tsunami itself as soon as possible after its generation. The latter is particularly important when the tsunami source is located close to the nearest coastal areas, and thus both energy spreading is low and propagation time is short. This is the case, for instance for co-seismic tsunamis generated in nearshore subduction zones (SZ) (e.g., Japan Trench, Puerto Rico Trench, Cascadia SZ,...), or for submarine mass failures (SMFs), that can be triggered on or near the continental shelf slope by moderate seismic activity (Fine et al., 2005; Tappin et al., 2008; Grilli et al., 2015b); meteotsunamis, also, may be generated on continental shelves by fast moving elongated low pressure systems (e.g., derechos) (Thomson et al., 2009). The detection of offshore propagating tsunamis from a nearshore generation area is usually made in deep water, at bottom-mounted pressure sensors (so-called DART buoys), based on which a warning is issued for far-field locations. The detection of onshore propagating tsunamis in shallow water, over the continental shelf, is typically made by bottom pressure sensors and tide gauges that may not survive the impact of large tsunamis; additionally such detection is local (i.e., point-based) and often takes place too late (i.e., too close to shore) to be used in early warning systems. Hence, with the current detection technology used in tsunami warning systems, there may not be enough time to issue a warning for near-shore seismic or SMF tsunami sources, based on actual tsunami data. When the earthquake is the tsunami triggering mechanism, a warning can be issued based on detecting seismic waves and from these estimating the earthquake parameters and the likelihood for tsunami generation. For non-seismically induced nearshore SMF tsunamis or for meteotsunamis, a warning can only be issued based on detecting the tsunami at nearshore sensors and, hence, there may not even be enough time to issue it before the tsunami impacts the coast; this is particularly more so in the case of a narrow shelf. 807 Proceedings of the Twenty-sixth (2016) International Ocean and Polar Engineering Conference Rhodes, Greece, June 26-July 1, 2016 Copyright © 2016 by the International Society of Offshore and Polar Engineers (ISOPE) ISBN 978-1-880653-88-3; ISSN 1098-6189 www.isope.org Grid SW corner Nx x Ny Resolution Resolution (Lat/Lon) grid cells (actual) (∼ m) G0 (10.00,-180.00) 1950 x 1560 0.6 min (S) 3,600 G1 (44.00,-129.01) 700 x 600 2 min (S) 1,089 G2 (46.99, -127.52) 766 x 900 270 m (C) 270 G3 (48.25, -126.90) 1800 x 1200 90 m (C) 90 Table 1: Parameters of nested grids in FUNWAVE-TVD simulations, in which G0 is a spherical (S) grid with 100 km thick sponge layers on the outside boundary, and G1, G2 and G3 are spherical (S) or Cartesian (C) grids centered on the WERA radar sweep area in Tofino, BC (Figs. 1a and 2a). G1-G3 simulations are performed by one-way coupling. The use of shore-based High Frequency (HF) radars to detect incoming tsunami waves has been proposed almost 40 years ago by Barrick (1979) and, more recently, was supported by numerical simulations (see, e.g., Lipa et al. (2006), Heron et al. (2008), Dzvonkovskaya et al. (2009), Gurgel et al. (2011)), and by HF radar measurements made during the Tohoku 2011 tsunami in Japan (Hinata et al., 2011; Lipa et al., 2011, 2012), in Chile (Dzvonkovskaya, 2012), and in Hawaii (Benjamin et al., 2016). No realtime tsunami detection algorithms were in place, but an a posteriori analysis of the radar data identified the tsunami current in the measurements. As for other nearshore currents, this works by measuring the Doppler shift tsunami currents induce on the radar signal and from this estimating time series of radial surface currents (i.e., projected on the radar line-of-sight) over a grid of radar cells covering the radar sweep area (typical cell size is one to a few km in each direction, with10th to 100th of km in the radial direction, depending on radar frequency and power). This dense spatial coverage is another advantage of HF radar detection over standard instrument methods. Tsunami detection and warning algorithms were proposed in some of these earlier studies, based on both a sufficient magnitude of the tsunami current inferred from the radar Doppler spectrum, combined with identifying its oscillatory nature in space and time. In earlier work based on a 4.5 MHz HF radar (Stradivarius) with a 200 km range, Grilli et al. (2015a) showed that such algorithms reliably work when tsunami currents are at least Ut ∼ 0.15−0.20 m/s, and thus raise above background noise and currents. Hence, this limits a direct detection of tsunami currents to fairly shallow water and thus nearshore locations, and also means short warning times, unless there is a very wide shelf. To detect a tsunami in deeper water, beyond the continental shelf, the authors proposed a new detection algorithm that does not require “inverting” currents, but instead is based on computing spatial correlations of the raw radar signal at pairs of radar cells located along the same wave ray, shifted in time by the tsunami propagation time along the ray. A change in pattern of these correlations indicates an approaching tsunami, since no other geophysical phenomenon can be responsible. They validated this algorithm only for idealized tsunami wave trains, propagating over a simple seafloor geometry in a direction normally incident to shore (Grilli et al., 2015a). Here, this algorithm is extended and validated for the area offshore of Vancouver Island, in British Columbia (Canada), based on realistic tsunami case studies conducted for seismic sources. To mitigate tsunami hazard in this area from both farand near-field seismic sources, in particular, from the Cascadia Subduction Zone (CSZ), Ocean Networks Canada (ONC) recently installed a shore-based WERA HF radar near Tofino (TF), BC. This HF radar can remotely sense ocean currents up to a 70-85 km range, depending on ocean/atmospheric conditions (Fig. 1b). In this paper, we perform numerical experiments to confirm that the proposed algorithm also works for a site with complex bathymetry and for realistic tsunami data; results will allow defining correlation thresholds relevant for tsunami detection. In the numerical experiments, tsunami currents are computed with the state-of-the-art long wave model FUNWAVE-TVD (Shi et al., 2012; Kirby et al., 2013a) and spatially averaged over a series of radar cells aligned along individual wave rays, obtained by solving the geometric optic equation. Here, we only detail results for a Mw 9.1 far-field seismic source located in the Semidi Subduction zone (SSZ; Fig. 1a), but simulations were also performed for large seismic sources in the CSZ (Insua et al., 2015). The radar signal is simulated in each cell based on the computed time series of tsunami radial currents using a backscattering model (Grilli et al., 2015a), which is applied for the characteristics of the WERA radar installed in TF (carrier electromagnetic wave (EMW) frequency fEM = 13.5 MHz). This is detailed in the following sections.