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11 th International Symposium for GIS and Computer Cartography for Coastal Zones ManagementTable 1. Frequency bands and bandwidths allocated for ocean RADAR applications (general values, minor variations may applyfor different regions). The given typical ranges are valid for array type WERA systems.Frequency Bands Typical Range (currents / wave) Typical Resolution4.438 - 4.488 MHz 400 km / 180 km 3,000 m5.250 - 5.275 MHz 350 km / 150 km 6,000 m9.305 - 9.355 MHz* 170 km / 80 km 3,000 m13.450 - 13.550 MHz 100 km / 45 km 1,500 m16.1 - 16.2 MHz 80 km / 35 km 1,500 m24.450 - 24.600 MHz 45 km / 20 km 1,000 m26.200 - 26.350 MHz 40 km / 15 km 1,000 m39 - 39.500 MHz 25 km / 10 km 300 m42 - 42.500 MHz 20 km / 8 km 300 m*Not for the US.ValidationWithin the last decades numerous validation studies demonstrated the accuracy and reliability of these systems(Wyatt et al., 2003). Samples for various applications clearly show the value of these instruments for monitoring ofocean surface currents and wave analysis for an entire area.With these land-based sensors, ocean currents and wave parameters can be measured and analysed over largeareas, not only at selected points.Figure 1B shows an ocean current map derived from a pair of WERA (12 MHz, 16 antennas) at the FrenchAtlantic coast near Brest. At about 30 km distance from the coast, an ADCP delivered data for comparison (Figure1C) which show good agreement with the RADAR data, proving their reliability (Helzel et al., 2009). Thesevalidation tests were carried out in 2005 by Actimar for the French institute SHOM.Similar tests were carried out for wave data. For reliable wave height measurements with the ocean RADAR, thewaves need to be at least 1.2 m high and therefore are displayed from this height onward. This lower threshold forwave measurements depends on the operating frequency of the RADAR and will increase with decreasing frequency(Wyatt, 2009). The accordance with the buoy measurement is very good (correlation factor 0.885).ApplicationThe provided ocean current data can be used to improve the predictions of actual positions of drifting objects incase of an accident. This improved quality of the drift prediction can be very useful for Search and Rescue (SAR)applications. Presently, search and rescue tools are based on hydro-dynamical and atmospheric models to providehindcast and forecast situations. Even if these oceanic numerical models are efficient to produce instantaneous mapsof currents, the accuracy of derived Lagrangian trajectories is often not sufficient for search and rescue purposes.Experimental results show the significant improvement of the drift simulation when using real-time current dataprovided by RADAR systems instead of using results from numerical models. To test this technique for SARapplications, surface drifters were launched and tracked. The drift prediction for this simulated “man-overboard”situation was carried out by means of a 2D tidal model typically used for the SAR operations and by a driftprediction based on the ocean currents measured by the WERA systems (Cochin et al., 2006). The results clearlyshow that the drift prediction based on the measured current data keeps closer to the real drift trajectory much longerthan the model-based drift prediction. The improved prediction would significantly increase the chance to find a lostperson or drifting objects and can save lives.In combination with a stochastic estimation, the drift of oil after an accident can be predicted as well. The driftprediction method can be used in hindcast mode as well to perform a backward computation. In case of a smaller oilpollution (e.g. caused by illegal tank flushing), an observed oil slick can be “backtracked”. This helps the coastguard to identify the polluter (Taillandier et al., 2011).105