Using Satellite Spectral Wave Data for Wave Energy Resource Characterization

Transcription

1 Using Satellite Spectral Wave Data for Wave Energy Resource Characterization M. T. ontes 1,2, M. Bruck 3, S. Lehener 3, A. Kabuth 1,4 1 LNEG Estrada do aço do Lumiar Lisboa, ortugal teresa.pontes@lneg.pt 2 IDMEC Av. Rovisco ais 1049 Lisboa, ortugal 3 DLR Oberpfaffenhofen Münchner Strasse Germany miguel.bruck@dlr.de susanne.lehner@dlr.de 4 IST Av. Rovisco ais, 1049 Lisboa, ortugal alina.kabuth@lneg.pt alina.kabuth@ist.utl.pt Abstract The German satellite Terra SAR-X () provides high resolution images, which can image ocean waves with an accuracy superior to former SAR satellites down to wave lengths of around 20 meters. This is useful for the retrieval of two dimensional wave spectra in highly variable sea states, especially in complex coastal areas or near islands. Using the three different SAR scanning modes it is possible to image the same location every 2 days. An inter-comparison between sea state parameters and spectral distributions retrieved from, and wind-wave models is presented for the Azores Archipelago in the area where the first wave energy power plant to be grid connected was built and continues in operation. A verification of the spectral parameters significant wave height, peak period, energy (mean) period and wave power in addition to wave spectral shape obtained from SAR against data and wind-wave model analysis is included, which shows the good accuracy of these remote sensed data. In addition, the strong spatial variability of wave conditions in complex coastal areas (in the channel between São Jorge and ico islands) is highlighted through the comparison of a series of (partially overlapping) SAR Spotlight image spectra. Keywords: Remote sensed wave data, wave spectra, energy resource Nomenclature DWD German Meteorological Office ESA European Space Agency ENVISAT ESA satellite SAR (ASAR) (Advanced) Synthetic Aperture Radar WAM - 3 rd generation wind-wave model OWC ower lant Oscillating Water-Column wave energy power plant 1. Introduction Investigation of the usefulness of satellite-based wave measurements for wave energy resource assessment has been pursued for several years. Altimeters on board of satellites Topex/oseidon ( ) followed by Jason (2002- ) provide quite accurate significant wave height data. Accurate mean period values can be obtained from simple analytical models (e.g.[1]). However, in addition to and period parameters, wave spectral information is required for the detailed development of wave energy converters (WECs). Remote sensed measurements by SAR (Synthetic Aperture Radar) systems on board of satellites and wind-wave models provide 2D wave spectra. The wave spectra obtained from SAR measurements (level 2 product) of the ESA ENVISAT satellite have been compared to data [1]. It was found that the accuracy of various wave climate and power parameters in the tropical area is good, and a preliminary verification of spectral shape was carried out for a small number of cases. The new German X-band SAR onboard the satellite TerraSAR-X () was launched on June 15, Since then it has provided operationally a significant amount of high quality data over land and ocean. In this paper we start by presenting the various types of wave information used herein and the respective sources. After, a verification of SAR data against data and results of the wind-wave model in the Azores archipelago is presented, which showed a quite god accuracy of the SAR data. This is 1

2 followed by an example of the strong spatial variability of sea states in the channel between the islands of São Jorge and ico, off the ico OWC wave energy power plant. Finally, conclusions and plans for further work are presented. 2. Data The wave data used in this paper have been obtained from various sources thus being of different types. Directional Datawell Waverider spectra in the ortuguese Azores archipelago, namely at the channel between Faial and ico islands were provided by CLIMAAT roject. This is located at 38º N, 28º 32.6 W. The spectral wave information is composed by 1D frequency spectra E(f), mean direction ( f ) and standard deviation ( f ) per frequency band in the frequency range 0.025< f <0.58 Hz. Wave analysis spectral parameters produced by the MAR3G 3 rd generation wind-wave model [2] (further updated) were also used. In the coastal area this windwave model takes into account shelter by neighboring islands and/or the coast itself, in addition to wave shoaling, refraction and breaking. This model is operationally running at the ortuguese Instituto de Meteorologia (ortuguese Met Office). The good accuracy of results for the same location off the ico lant described in [3] had been verified against data. Scatter index for January, February, March and April 1989 were 22, 18, 21 and 29%, respectively [4]. Remote sensed data have been obtained from SAR on board of satellite. It provided image spectra from which significant wave height was derived in coastal areas through the XWAVE empirical algorithm [5]. This model is expressed by the following equation The image spectrum is retrieved by Fourier analysis over a sub-scene of the image. For ScanSAR mode, normally 512 pixels are enough corresponding to a 4.2 x 4.2 km area. For Spotlight data, normally 2048 pixels are used, which correspond for retrieval to a 1.5 x 1.5 km area. When using Spotlight data normally the purpose is to study the spatial variability of wave conditions. 3. Verification of SAR data SAR data measured over the central group of Azores archipelago is compared below against (i) directional Waverider data measured at the Faial-ico channel and (ii) wind-wave model analysis off the ico lant. The comparison focused spectral parameters namely significant wave height Hs Hm0 4 m0, energy m 1 n (mean) period T 10, with mn f E( f ) df m0 being the n-th order spectral moments. eak period is defined as T 1/ f where f p is the frequency p p corresponding to the maximum spectral energy density. In deep water, the flux of energy per unit wave front (wave power) can be computed by.4906hm T. Wave power is given in kw/m if Hm0 is expressed in meter and T 10 in second. For the data a comparison of 1D frequency spectrum is also included. a* 4.0 E(1.0 abs(cos ) b (1) where E is the total energy calculated from the SAR image wave number (k) spectrum F(k) via E F( k) dk. is the angle between peak wave direction (with 180º ambiguity) and SAR azimuth direction, which is determined from the image spectra. The two coefficients a and b were tuned by a linear fitting between E and the collocated significant wave height computed by the Deutcher Wetterdienst (DWD) wind-wave model. The wind-wave model run at DWD is the WAM model cycle 4 [6]. Three SAR images were taken on 11 February 2010, 25 March 2010 and 27 March The images taken on 11 February and on 27 March are of Spotlight mode. These cover a 10 x 10 km area with circa 1.8 m resolution. The image acquired on the 25 March is of the ScanSAR mode with an area of 100 x 100 km and resolution circa 18 m, which is approximately 10 times smaller than the one of the Spotlight mode. Figure 1: Overview of the SAR data over the central group of Azores archipelago. One ScanSAR image shows Faial, ico, São Jorge and Graciosa islands. Two overlaid Spotlights were acquired north of ico Island. The data products used are the Multi-Look Ground Range Detected (MGD), which is the standard product. When retrieving an image spectrum from a 2

3 MGD product, a peak ambiguity of 180 exists as can be observed on Figure 5. This means that the peak wave direction estimation presents two values differing 180. However in this case the direction ambiguity is easily solved since waves can come only from the sea. Figure 3: Zoom of the ScanSAR image overlaid on Google Earth map. Spotlight mode data are framed by red boxes: left over directional Waverider deployed at the Faial ico channel, right off the ico lant [6]. Figure 2: Zoom of the overview of the data acquired over the Azores archipelago. Two Spotlight images overlaid on the ScanSAR mode image shown in Figure 1. a) b) c) d) Figure 4: SAR 2D normalized wave number spectrum F (k) (left) and 512 pixel (4.2 x 4.2 km) subscenes (right). a) and b) over Faial-ico (left red square in Figure 3), c) and d) off ico lant (right red square in the same figure). 3

4 S* 3 rd International Conference on Ocean Energy, 6 October, Bilbao Hs = 5.0 m Hs = 4.6 m Tp = 12.1 s Tp = 11.8 s freq(hz) Figure 5: Comparison of 1D frequency normalized spectrum over the Faial-ico (blue) and normalized spectrum (red) at , 08:41h (stormy conditions). The figure above shows a fair agreement between the spectral shape for long waves (f <0.09 Hz, T>11s), while an important difference is found for shorter (higher frequency) wave components as it is known to occur with SAR data. The difference between the two measurements is of 0.4m (8.7%) for H m0 and 0.3 s (2.5%) for. Table 1 presents the comparison of,, and obtained from SAR images and measurements in the Faial-ico channel, and SAR data and analysis off the ico lant in the ico - São Jorge channel. Since the SAR measurements were made between the two measurements (made every 3h) both data were retained, but the two values are not significantly different. In this table we find generally a fair agreement between data and data for two cases (Faial- ico data) and the three cases off ico lant ( data and results). These sea states include two average conditions ( around 2m, around 11s, < 9.5s, < 30 kw/m) and one stormy condition ( > 4.5 m, > 11s, >10.5s and circa 100 kw/m). 4. Spatial Sea State Variability To illustrate the spatial variability that occurs in channels, a set of neighboring SAR measurements were carried out off the northern coast of ico island in the vicinity of ico lant. Figure 6 shows the Spotlights and Figure 7 compares the 2D wave image spectra F(k) showing clear differences for the lower energy components (shorter waves). Figure 6: SAR Spotlights off the northern coast of ico Island, acquired on (average wave conditions). 5. Conclusions and Further Work The verification of SAR wave data (including spectral parameters and 2D image spectra from which 1D spectra were obtained) against Waverider data and wind-wave model analysis shows the good accuracy of such SAR data, which are relevant for the usual applications including also wave energy resource characterization. This work will be further developed with an extended validation of SAR data focusing additional spectral parameters (namely spectral width parameters). On what regards SAR data, other tools will be developed that will enable to obtain more information, namely wave spectra with non-directional ambiguity. Acknowledgements The authors thank rof. Eduardo de Brito Azevedo from CLIMAAT roject (University of Azores) for providing the directional data measured by the Faial ico, and Instituto de Meteorologia (ortugal) for supplying analysis and forecasts for the ico lant area. The work of Alina Kabuth has been carried out within in the EC F7 programme The eople rogramme - Wavetrain2 contract nº ITN-GA

5 1) 2) 3) 4) 5) 6) 7) Figure 7: Variability of SAR 2D image spectra off the northern coast of ico Island on :41 UTC time (numbers refer to the positions shown in Figure 6) 5

6 At on Faial-ico Channel Off ico lant 1 Hs 2 ico : : : At Faial-ico Channel Off ico lant : : : At on Faial-ico Channel Off ico lant : : : At on Faial-ico Channel Off ico lant : : : Table 1. Comparison of,, and and data against (left) ico-faial Channel data and (right) wind-wave model results off ico lant. 6

7 References [1] M. T. ontes, M. Bruck, M. and S. Lehener (2009), Assessing the Wave Energy Resource Using Remote Sensed Data, roceedings of 8 th EWTEC, Uppsala, Sweden. [2] H. Oliveira-ires (1993) Numerical modeling of windgenerated ocean waves. h.d. Thesis, Lisbon Technical University. [3] A. F. de O. Falcão (2000) The shoreline OWC wave power plant at the Azores. roceedings 4 th EWTEC, paper B1, Aalborg, Denmark.. [4] H. Oliveira-ires, F. Carvalho and M. T. ontes (1997), Modelling the Effect of Shelter in the Modification from the Open Sea to Near-Shore, J. Offshore Mechs. and Arctic Engng, Vol. 119, Nº. 1, [5] X.-M. Li (2009), Ocean Surface Wave Measurements Using SAR Wave Mode Data. h. D. Thesis, University of Hamburg, 157 pp. [6] G. J. Komen, L. Cavaleri, M. Donelan, K. Hasselmann, S. Hasselman,.A.E.M. Jassen (1994) Dynamics and Modelling of Ocean Waves, Cambridge University ress. 7