remote sensing system to monitor ocean surface currents, waves and wind .... balance of all receive channels as well as free disk space or power supply (UPS) ...
Preprint from the IEEE Oceans Conference Proceedings, Bremen, 2009
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Accuracy and Reliability of Ocean Current and Wave Monitoring with the Coastal Radar “WERA” Thomas Helzel1, Leif Petersen1, Vincent Mariette2,, Nicolas Thomas2 1
Helzel Messtechnik GmbH, Carl-Benz-Str. 9, 24568 Kaltenkirchen, Germany 2 Actimar S.A., 36 Quai de la Douane, 29200 Brest, France
Abstract- The WERA system (WavE RAdar) is a shore based remote sensing system to monitor ocean surface currents, waves and wind direction. WERA is using the lowest noise FMcw technique to provide highest temporal and fine spatial resolution for time critical applications. The vertical polarised electromagnetic wave is coupled to the conductive ocean surface and will follow the curvature of the earth. This over the horizon oceanography radar can pick up back-scattered signals (Bragg effect) up to ranges of more than 200 km. Publications about the results from systems installed all over the world have proved the accuracy of the WERA system. The reliability of these ocean data was studied for more than 2 years at a permanent WERA installation at the French coast near Brest.
I.
The data are provided for the “Vigicote” project with a pair of 16 channel medium range WERA systems [1] owned by SHOM (Oceanographical and Hydrographical Service of the French Navy). The radar operates at a center frequency of 12.38 MHz with a bandwidth of 100 kHz (range cell size of 1.5 km) at 30 Watts rf-power. Over a period of more than 12 months a study was carried out to validate the quality of the provided data by means of a comparison with buoy data [2]. Furthermore the reliability was qualified by comparing the users demands for data availability with the resulting data.
INTRODUCTION
A pair of over the horizon radar systems for ocean monitoring is being operated continuously since September 2006 to measure ocean currents and waves off the west coast of France near Brest.
Figure 2. Surface current map, averaging time: 12 min
Figure 1. Location of the instruments for ground truthing
Preprint from the IEEE Oceans Conference Proceedings, Bremen, 2009 II.
ACCURACY
Current measurements The accuracy was tested prior to the reliability study in a 2 months experiment. The coastal area and the location of the instruments are displayed in figure 1. The distance of the buoys from the radar locations is between 23 and 34 km. Figure 2 shows a typical current map.
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Wave measurements The comparison between the data measurement with a “Wave Rider” buoy and the WERA system shows figure. Under extreme weather conditions the signal to noise of the radar echo is getting worse. This results in a reduced range in particular for the second order return that is used to derive the wave information. As a result, there are no wave data available at the required grid point for wave heights >5.5 m.
The comparison between the measurement data of the ADCP and the WERA system at the Garchine site from August to October 2005 is displayed in figure 3. The influence of the tides on the radial current in this area is clearly visible.
Figure 5. Comparison of significant wave height measured with WERA and a swell buoy
Plotting the correlation figure 6 is obtained. The correlation factor is 0.88, also a very good agreement. Figure 3. Comparison of radial current velocity measured with WERA and an ADCP
The corresponding correlation between the ADCP and WERA data, displayed in figure, shows a correlation factor of 0.947. This excellent agreement proves the accuracy of the WERA system to measure ocean surface currents.
Figure 6. Comparison of significant wave height measured with WERA and Wave Rider Buoy: Correlation = 0.885
Figure 4. Comparison of radial current velocity measured with WERA and ADCP: Correlation = 0.947
Summary The experiment showed that with the WERA systems it is possible to measure very accurate near real-time data of ocean surface currents and waves with excellent agreement to traditional sensors.
Preprint from the IEEE Oceans Conference Proceedings, Bremen, 2009 III.
TABLE II DEMANDS AND ACHIEVED SPATIAL COVERAGE OF DATA
RELIABILITY
Temporal coverage The customers demands for temporal availability of WERA measurement data and the achieved results are presented in Table I.
Wanted percentage of the time
TABLE I DEMANDS AND ACHIEVED TEMPORAL AVAILABILITY OF DATA
Parameter
Archived raw data Near real-time, processed current, wave and wind data
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Achieved Demand in % from 01/2007 of time to 02/2008 98 %
98.6 %
95 %
87.1 %
The demand to acquire the data for archiving was fulfilled, but the availability of data in real-time was missed by about 8 %. The reason for this was a non stable data link that almost always failed during thunder storms. The resulting near realtime data gaps were always recovered with post processed raw data after restoring the data link. Spatial coverage The customers definitions and demands for spatial coverage of WERA measurement data and the achieved results in September 2007 are presented in Table II and figure 7.
1. Demanded 2. Achieved number of grid number of grid At which cells with this cells with this range percentage of percentage of the time the time
2. / 1. (in %)
99 %
40 km
50
527
1054
80 %
60 km
343
1596
465
It is clearly visible that the resulting areas are much larger than requested. Just at the edges of the requested areas the limits of the achieved areas and the requested are almost identical. The requested number of grid cells with available data for more than 80 % of the time was 343 cells. At the sample displayed in figure 7 1596 grid cells were provided up to a range of 60 km. These are 4.65 times more cells than requested. The requested number of grid cells with available data for more than 99 % of the time was 50 cells. At the sample displayed in figure 5 527 grid cells were provided up to a range of 40 km. These are 10.54 times more cells than requested. Environmental influence on coverage Measurement range and thus grid cell coverage is also dependent on several environmental conditions. Figure 8 displays a typical time series of the covered grid cells for ocean surface current data for one day for this 12.4 MHz WERA system. 3900
Number of grid cells
3400
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Figure 8. Time series of grid cell coverage variation for one day 11/2007
Obviously at night time more grid cells are covered than during the day. Nevertheless, even during day time the covered grid cell count is always more than 1400 cells which is superior compared to other over the horizon radar systems. Figure 7. The required areas are marked with solid lines (availability 99 % = blue, 80 % = green) The achieved areas are marked with dashed lines.
Preprint from the IEEE Oceans Conference Proceedings, Bremen, 2009 6000
5000
Number of grid cells
This day- to night-time variation is caused by external noise within the radar frequency band. Figure 9 shows a typical time series of the measured external noise for one day, generated from periodical measurements. For the WERA radar system such a measurement can be performed 2 minutes before every data acquisition to find the optimum transmit frequency within the allocated frequency band. Additionally, if there is too much external noise in this band, the bandwidth can automatically be reduced for the next measurement, resulting in better quality data on coarser grid. Regularly noise patterns can be reduced by a sophisticated RFI (Radio Frequency Interference) software introduced by Gurgel et al [3]. These software features enhance spatial coverage and thus reliability of the measurement data. Figure 9 shows that at night time the signal to noise ratio is about 20 dB better than during day time resulting in longer ranges at night. At day time weak signal are covered by external noise resulting in a smaller number of covered grid cells.
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4000
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Figure 10. Variation of the number of cells per current map in December 2006 9
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Figure 11. Variation of the measured sea state in December 2006
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Beside the external noise there is another environmental condition influencing the measurement range and thus the amount of covered grid cells. Figure 10 displays a time series of the covered grid cells for ocean surface current data for December 2006. The clearly visible day- to night-time variations is superimposed by another effect, that modulated the day and night coverage. The comparison with the actual wave height shows that the observed range is correlated with the wave height. The higher the ocean waves, the less grid cells are covered. Plotting grid cell coverage against ocean wave height clearly shows this effect, displayed in figure 12. A linear regression results in a correlation of –0.87 between sea state and measurement range for ocean surface currents for December 2006.
Number of grid cells - (radial current)
Figure 9. Variation of external noise power within the radar frequency band measured before transmitting) according to the hour of day, 09/2007
December 2006 - Lon 5.106° W - Lat 48.451° N Correlation: -0.87 6000
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y = -485.15x + 5125.8 0 0
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Figure 12. Correlation between sea state (ocean wave height) and range (grid cell coverage)
So the amount of covered ocean surface current measurement grid points is directly related to ocean wave height and thus sea state.
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Preprint from the IEEE Oceans Conference Proceedings, Bremen, 2009 Long-term reliability Despite the high reliability of the hard- and software of the system, regular maintenance and use of the various monitoring features of the system is mandatory. As the system is designed to operate remotely, it has automatic functions to monitor all relevant system parameters like voltages and temperatures in all racks of the system as well as signal level, external noise, phase relation and I/Qbalance of all receive channels as well as free disk space or power supply (UPS) parameters. These monitoring functions can be configured to automatically send an email or SMS to the user if a certain threshold is reached.
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The monitoring data will also be displayed as a time series on a remotely accessible web page to enable the user to notice even tiny changes over time and to be able to replace a module before its parameters are out of tolerance. See figure 13. Additionally the user is able to manually execute all test procedures remotely if required. These features assure long-term availability, reliability and wide spatial coverage of measurement data as presented. CONCLUSIONS The shore based oceanographic radar system WERA provides a high accuracy, similar to the data quality of buoys, but with a much wider ocean surface coverage. The availability rate of the measurement data is very high, as long as all quality assurance tools are used and skilled personnel is available to carry out first line maintenance. The data link is the most critical part if near real-time data are required. Overall it was shown that a professionally installed and maintained coastal radar system can continuously provide accurate and reliable data. ACKNOWLEDGMENT We wish to thank the team of ACTIMAR (France) and the owner of these systems SHOM to provide the measurement data. REFERENCES [1] [2]
Figure 13. Time series of some of the monitoring functions of the system
[3]
Thomas Helzel et al., Over-the-Horizon-Radar, an Introduction to WavE Radar (WERA), MAST Conference, Cadiz, Spain, November 2008 V. Cochin, et al., SURLITOP experiment in West Brittany (France): Results and validation. 6th intern. Radiowave Oceanography Workshop (ROW-6), Hamburg, Germany, May 2006 Gurgel et al, Suppressing Radio Frequency Interference in HF Radars, Sea Technology, Compass Publications, pp. 39-42, March 2008
