We describe theoretical and experimental work for evaluating the suitability of coastal High Frequency (HF) radar sites for tsunami detection. A method is outlined which involves superimposing simulated tsunami velocities on typical radial current velocities measured at the radar site. This leads to an estimate of the minimum detectable tsunami height at the site. Results are presented from application of these methods to data measured over a day by a radar located at Brant Beach, New Jersey.

We describe the evolution of coastal HF radar observations of tsunamis, first proposed in 1979 and developed after the 2004 Indonesia and 2011 Japan tsunamis to allow routine monitoring to detect an approaching tsunami. Oceanographic tsunami theory is summarized, both for the fundamental equations of motion and in the ray optics and Green's Law approximations; the latter can be applied when water depths are slowly varying. Observations of the current velocities caused by the 2011 Japan tsunami off the Japanese, the US West, and Chilean coasts are described and examples are shown. These observations led to the development of an empirical tsunami detection method, which is outlined. Examples of offline tsunami detections are given and detection times are compared with arrival times at neighboring tide gauges. We describe the observation and offline detection of the June 2013 meteotsunami off the New Jersey coast using coastal radar systems and tide gauges. Methods to model and simulate tsunami velocities are described and videos of the resulting velocity/height maps are given. We describe preliminary methods for evaluating the suitability of radar sites for tsunami detection using simulated tsunami velocities. Factors affecting tsunami detectability are discussed and methods are described for the alleviation of false alarms.

Rutgers University has begun to use their SeaSonde HF Radar coastal ocean current and wave-monitoring network for vessel detection purposes. This project aims to evaluate the effectiveness of using the HF Radar network for vessel detection in the New York Harbor. Two separate HF Radar sites were analyzed. The sites, Sea Bright and Seaside Park, are located along the New Jersey coast and are separated by approximately 48 km. The data from each of these sites was analyzed and compared to Automatic Identification System (AIS) data provided by ships entering and leaving the New York Harbor. This was done for a week (Sunday, October 21st through Sunday, October 28th) on a daily basis to determine the number of ships that were accurately detected by the HF Radar network. Sea Bright had an average detection rate of 72% for the week and Seaside Park had an average rate of 78%. Overall the HF radar network proved to be a quite accurate vessel detection resource during this one week case. At Sea Bright and Seaside Park, the radar detected an average of 6.375 and 5.75 vessels that were not reporting to the AIS network, respectively. The HF radar network's ability to detect vessels that do not report to the AIS network will be a great contribution to matters of homeland security.

Since 2011, Rutgers has been operating an over-the-horizon vessel detection software called `PeakPicker' at two 13 MHz CODAR SeaSonde sites located in Sea Bright, NJ and Belmar, NJ. The challenge of vessel detection using High Frequency (HF) radar is dealing with false detection peaks and then associating multiple peaks derived from different coherent integration times and background filters at a single time step into one peak representing the best estimate. Association of distinct signal peaks derived from the CODAR SeaSonde high frequency (HF) radar PeakPicker software provides a challenge. Association of peaks occurs in two distinct phases. Level 1 Association will associate multiple detection peaks derived from different coherent integration times and background filters at a single time step into one `best' peak while Level 2 Association will combine data from multiple sites representing different viewing angles. A Matlab script, plot_all_matches, finds matches target data in range and range rate (radial velocity) with AIS data providing a ground truth of our ship detection progress. Utilizing the output of the matching data from plot_all_matches, we present techniques that increase the accuracy and decrease the error of detections.

vessel detection software called 'PeakPicker' at two 13 MHz CODAR SeaSonde sites located in Sea Bright, NJ and Belmar, NJ. The challenge of vessel detection using High Frequency (HF) radar is dealing with false detection peaks and then associating multiple peaks derived from different coherent integration times and background filters at a single time step into one peak representing the best estimate. Association of distinct signal peaks derived from the CODAR SeaSonde high frequency (HF) radar PeakPicker software provides a challenge. Association of peaks occurs in two distinct phases. Level 1 Association will associate multiple detection peaks derived from different coherent integration times and background filters at a single time step into one ` best' peak while Level 2 Association will combine data from multiple sites representing different viewing angles. A Matlab script, plot_ all_ matches, finds matches target data in range and range rate (radial velocity) with AIS data providing a ground truth of our ship detection progress. Utilizing the output of the matching data from plot_ all_ matches, we present techniques that increase the accuracy and decrease the error of detections.

We report here on the observation and offline detection of the weak tsunamis generated by earthquakes near Indonesia on 11 April 2012 using radar systems and tide gauges on the coasts of Sumatra and the Andaman Islands. This work extends the previous observations of the much stronger 2011 Japan tsunami. The distance offshore at which the tsunami can be detected, and hence the warning time provided, depends primarily on the bathymetry: the wider the shallow continental shelf, the greater this time. The weak Indonesia tsunamis were detected successfully in spite of the narrow shallow-water shelf offshore from the radar systems. Larger tsunamis could obviously be detected further from the coast. This paper provides further confirmation that radar is an important tool to aid in tsunami observation and warning.

Quantitative real-time observations of a tsunami have been limited to deep-water, pressure-sensor observations of changes in the sea surface elevation and observations of sea level fluctuations at the coast, which are essentially point measurements. Constrained by these data, models have been used for predictions and warning of the arrival of a tsunami, but to date no system exists for local detection of an actual incoming wave with a significant warning capability. Networks of coastal high frequency (HF)-radars are now routinely observing surface currents in many countries. We report here on an empirical method for the detection of the initial arrival of a tsunami, and demonstrate its use with results from data measured by fourteen HF radar sites in Japan and USA following the magnitude 9.0 earthquake off Sendai, Japan, on 11 March 2011. The distance offshore at which the tsunami can be detected, and hence the warning time provided, depends on the bathymetry: the wider the shallow continental shelf, the greater this time. We compare arrival times at the radars with those measured by neighboring tide gauges. Arrival times measured by the radars preceded those at neighboring tide gauges by an average of 19 min (Japan) and 15 min (USA) The initial water-height increase due to the tsunami as measured by the tide gauges was moderate, ranging from 0.3 to 2 m. Thus it appears possible to detect even moderate tsunamis using this method. Larger tsunamis could obviously be detected further from the coast. We find that tsunami arrival within the radar coverage area can be announced 8 min (i.e., twice the radar spectral time resolution) after its first appearance. This can provide advance warning of the tsunami approach to the coastline locations.

We neglected to state that the radar data from Tokushima and Anan is owned by the Ministry of Land, Infrastructure, Transport and Tourism, Shikoku Regional Development Bureau, Komatsushima port and airport office, Japan. Lipa et al. [1] describe results on tsunami detection using data measured by two radars located at Tokushima and Anan on the Kii channel. This data is owned by the Ministry of Land, Infrastructure, Transport and Tourism, Shikoku Regional Development Bureau, Komatsushima port and airport office, Japan. Locations of the radars are shown in Figure 4(a,c) [1]. Results of the data analysis are given in Section 3.1.2, plotted in Figure 6 and listed in Table 1 [1].

High-frequency (HF) surface wave radar has been identified to be a gap-filling technology for Maritime Domain Awareness. Present SeaSonde HF radars have been designed to map surface currents but are able to track surface vessels in a dual-use mode. Rutgers and CODAR Ocean Sensors, Ltd., have collaborated on the development of vessel detection and tracking capabilities from compact HF radars, demonstrating that ships can be detected and tracked by multistatic HF radar in a multiship environment while simultaneously mapping ocean currents. Furthermore, the same vessel is seen simultaneously by the radar based on different processing parameters, mitigating the need to preselect a fixed set and thereby improving detection performance.