Evaluation of the CODAR Tsunami Detection Algorithm and Software

Hugh Roarty, Rutgers University New Brunswick, New Brunswick, NJ, United States and Chad W Whelan, CODAR Ocean Sensors, Mountain View, CA, United States
Abstract:
Coastal hazards pose a threat to human life and property around the globe. Tsunami waves and storm surge are some examples of coastal hazards we must try to mitigate over the coming decades. High Frequency radars have emerged as possible technology capable of mitigating the destruction from these hazards by providing early detection of these disturbances out at sea. Rutgers University has worked with CODAR Ocean Sensors by collecting and analyzing data from four HF radar stations for potential tsunami signals from October 2016 to June 2019. CODAR has developed a pattern recognition process to detect the presence of tsunami waves. The output of the process is quantified as an alongshore and cross shore q-factor. If there is a spike in the q-factor measurement then arrival of a tsunami could be imminent. The statistics of the q-factor measurements at the four stations were calculated and compared against the radio noise spectrum and other environmental data like nearby water level and atmospheric pressure. Recently, on May 30, 2019 a weather system moved through the region that generated a small meteotsunami (amplitude 15-30 cm) that was detected by a DART buoy, water level gauges and one of the HF radar stations. The data from all three system covered a large spatial area which allowed us to study the propagation of the wave through the region. The different detection schemes with each technology also allowed us to study the characteristics of the tsunami signal.