Skip to main content
Log in

Wave and wind retrieval from sar images of the ocean

Estimation du Vent et des Vagues à Partir D’images rso de la Surface de L’océan

  • Published:
Annales Des Télécommunications Aims and scope Submit manuscript

Abstract

Over the past few years, recognition of the importance of the coastal zone has led to the establishment of international programmes for monitoring the coastal zone environment and its change. The European programme marsais is part of this effort. One important component of such actions aims to better predict the sea surface wind and wave dynamics in these vulnerable regions where most economic marine activity is taking place.

Indeed, ocean surface wind and wave observations serves both oceanographic and meteorological communities and have direct applications for driving ocean circulation models, numerical predictions and short term forecasts, but also for advancing in the physical understanding of the complex interactions that take place at the ocean-atmosphere interface. As now well recognised, satellite data and particularly the weather independent radar remote sensing data present potential advantages and applications to achieve these requirements. Nowadays, sea surface remote sensing techniques are rapidly developing throughout the world and need some kind of assessment. Altimetry and scatterometry are well proven techniques, which result in recognised operational applications. Synthetic Aperture Radar (sar) missions have not enjoyed such successes. However numerous space borne radar images of the ocean surface have revealed a wealth of information on different dynamical processes and sar images of the ocean surface very often reveal a remarkable range of signatures on the uppermost layers of the sea. These data have resulted in numerous quantitative scientific findings and theoretical advances in upper-layer and lower atmosphere dynamics. In this review, the main different techniques developed to retrieve surface wave and wind information are recalled. Illustrations are given for envisat wave mode products.

Résumé

Depuis quelques années la reconnaissance de l’importance de la zone côtière a conduit à l’établissement de programmes internationaux pour la surveillance de l’environnement et ses changements. Le programme européen marsais fait partie de cet effort. Une composante importante de telles actions a pour but de mieux prédire la dynamique du vent et des vagues à la surface des océans dans ces régions vulnérables où la plus grande partie de l’activité marine a lieu.

En effet, les observations du vent et des vagues à la surface de l’océan servent aussi bien les communautés d’océanographie que de météorologie et ont des applications directes pour forcer les modèles de circulation des océans, dans les modèles de prédiction numériques et les prévisions à court terme, mais aussi pour aider à comprendre les interactions complexes qui prennent place à l’interface océan-atmosphère. Ainsi qu’il est actuellement bien admis, les données satellitaires, et particulièrement celles provenant d’acquisitions par radar non affectées par les conditions météorologiques, présentent un potentiel d’avantages et d’applications pour répondre à ces besoins. De nos jours, les techniques de télédétection de la surface des océans se développent rapidement dans le monde et il est nécessaire de les évaluer. L’altimétrie et la diffusiométrie sont des techniques bien établies qui donnent des résultats en applications opérationnelles reconnues. Les missions Radars à Synthèse d’Ouverture (rso) n’ont pas eu un tel succès. Cependant de nombreuses images de l’océan par radars satellitaires ont révélé une grande richesse d’information sur différents processus dynamiques et ont très souvent montré une remarquable étendue de signatures des couches les plus proches de la surface. Ces données ont permis des découvertes scientifiques quantitatives et des avancées théoriques sur la dynamique des couches supérieures de l’océan et de la basse atmosphère. Dans ce papier, les principales techniques développées pour retrouver les informations de vents et vagues de surface sont rappelées. Des illustrations sont données pour les produits « vagues » du prochain satellite envisat.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Alpers (W.R.), Brüning (C), On the relative importance of motion-related contributions to the sar imaging mechanism of ocean surface waves,ieee Trans. Geosci. and Remote Sens., GE-24 (6), 873–885, 1986.

    Article  Google Scholar 

  2. Alpers (W.R.), Ruffenach (C.L.), The effect of orbital motions on synthetic aperture radar imagery of ocean waves,IEEE Trans. Antennas Propag.,AP-27(5), 685–690, 1979.

    Article  Google Scholar 

  3. Bao (M.), Brüning (C), Alpers (W.)., A generalized nonlinear ocean wave sar spectral integral transform and its application to ERS-1 SAR ocean wave imaging., inProceedings Second ers-1 Symposium, 219–224, esa Publications Division, estec, Noordwijk, The Netherlands, 1994.

    Google Scholar 

  4. Beal (R.C.), Tilley (D.G.), Monaldo (F.M.), Large and small-scale spatial evolution of digitally processed ocean wave spectra from Seasat synthetic aperture radar,J. Geophys. Res.,88 (C3), 1761–1778, 1983.

    Article  Google Scholar 

  5. Brillinger (D.R.), Distributions of particle displacements via higher-order moment functions,Proc. ieee, Part. F,140 (6), 390–394, 1993.

    Google Scholar 

  6. Brüning, (C), Hasselmann (S.), Hasselmann (K.), First evaluation of ers- 1 synthetic aperture radar wave mode data,Global Atmos. Ocean Syst.,2, 61–98, 1994.

    Google Scholar 

  7. Chapron (B.), Garello (R.), Kerbaol (V.), Lefevre (J.M.), Nonlinear theory of ocean-SAR transformation and statistical analysis of ers-1 sar wave mode imagettes, inProceedings Second ers-1 Symposium, 247–250, esa Publications Division, estec, Noordwijk, The Netherlands, 1994.

    Google Scholar 

  8. Chapron (B.), Elfouhaily (T.), Kerbaol (V.), Calibration and validation of ers wave mode products,Tech. Rep. DRO/OS 95-02, Inst. Fr. de Rech, pour l’Exploit, de la Mer, Brest, France, 1995.

    Google Scholar 

  9. Engen (G.), Johnsen (H.), Analysis and inversion of ers-1 image cross-spectra, inigarss’95, 1863-1865, ieee Press, Piscataway, N.J., 1995.

    Google Scholar 

  10. Engen (G.),Hogda (K.A.),Johnsen (H.), A new method for wind field retrieval from sar data,in Proceedings ceos sar Workshop, estec, wpp-138, 47–51, 1998.

  11. Engen (G.), Johnsen (H.), Krogstad (H.E.), Barstow (S.F.), Directional wave spectra by inversion of ers-1 Synthetic Aperture Radar ocean imagery,ieee Trans. Geo. Rem. Sens.,32, 2, 340–352, 1994.

    Article  Google Scholar 

  12. Engen (G.), Johnsen (H.), SAR-Ocean wave inversion using image cross spectra,IEEE Trans. Geo. Rent. Sens.,33, 4, 1995.

    Google Scholar 

  13. Engen (G.), Imaging ocean waves with synthetic aperture radar,Ph. D, University of Tromsö, 1997.

  14. Fay (F.S.), Clarke (J.), Peters (R.S.), Weibull distribution applied to sea clutter,iee Conf. Publ,105, 101–104, 1977.

    Google Scholar 

  15. Goldfinger (A.D.), Estimation of spectra from speckled images,IEEE Trans. Aerosp. Electron. Syst.,AES-18 (5), 675–681, 1982.

    Article  Google Scholar 

  16. Hasselmann (K.), Hasselmann (S.), On the nonlinear mapping of an ocean wave spectrum into a synthetic aperture radar image spectrum and its inversion,J. Geophys. Res.,96 (C6), 10713–10729, 1991.

    Article  Google Scholar 

  17. Hasselmann (K.), Raney (R.K.), Plant (W.J.), Alpers (W.), Shuchman (R.A.), Lyzenga (D.R.), Rufenach (C.L.), Tucker (M.J.), Theory of synthetic aperture radar ocean imaging: a marsen view,J. Geophys. Res.,90 (C3), 4659–4686, 1985.

    Article  Google Scholar 

  18. Hasselmann (S.), Brüning (C), Hasselmann (K.), Heimbach (P.), An improved algorithm for the retrieval of ocean wave spectra from SAR image spectra,J. Geophys. Res.,101, 16615–16629, 1996.

    Article  Google Scholar 

  19. Häuser (D.),Caudal (G.),Podvin (T.),Laurent (G.),Valentin (R.),Chapron (B.), Airborne polarimetric radar measurements in the context of the geophysical validation of the ENVI-SAT AS AR,Proceedings of the ers-envisat Symposium, 16–20 Oct 2000, Gothenburg, Sweden, CD-ROM, ESA pulications , SP-461,2000

  20. Heimbach (P.), Hasselmann (S.), Hasselmann (K.), Statistical analysis and intercomparison of wam model data with global ERS-1 sar Wave Mode spectral retrievals over three years,J. Geophys. Res.,103, 7931–1978, 1998.

    Article  Google Scholar 

  21. Heimbach (P.), Use of ocean wave spectra retrieved from ers-1 sar Wave Mode data for global wave modelling,Ph. D., University of Hamburg, 1998.

  22. Horstmann (J.), Koch (W.), Lehner (S.), Tonboe (R.), Wind Retrieval over the Ocean using Synthetic Aperture Radar with C-Band HH-Polarization,ieee, tgarss,38 (5), 2000.

  23. Horstmann (J.), Lehner (S.), Koch (W.), Tonboe (R.), Computation of wind vectors over the ocean using spaceborne synthetic aperture radar,John Hopkins APL Technical Digest, 21(1), 100–107, 2000

    Google Scholar 

  24. Jackson (EC), Peng (C.Y.), Comment on «Imaging radar observations of directional properties of ocean waves» by Mc Leish and D. B. Ross,J. Geophys. Res.,90 (C4), 7367–7370, 1985.

    Article  Google Scholar 

  25. Jakeman (E.), Pusey (P.N.), A model for non-Rayleigh sea echo,ieee Trans. Antennas Propag.,AP-2 (6), 806–814, 1976.

    Article  Google Scholar 

  26. Jakeman (E.), Tough (R.J.A.), Non-gaussian models for the statistics of scattered waves,Adv. Phys.,37 (5), 471–529, 1988.

    Article  Google Scholar 

  27. Johnsen (H.), The envisat asar Wave Mode cross spectra algorithm,in Proceedings ceos sar Workshop, estec, wpp-138, 159–166, 1998.

  28. Johnsen (H.), Multi-look versus single-look processing of sar images with respect to ocean wave spectra estimation,Int. J. Rem. Sens.,13, 1627–1643, 1992.

    Article  Google Scholar 

  29. Johnson (N.L.), Kotz (S.), Distribution in Statistics: Continuous Univariate Distributions, vol. I, John Wiley, New York, 1969.

    Google Scholar 

  30. Kanevsky (M.B.), On the theory of sar ocean wave imaging,ieee Trans. Geosci. and Remote Sens.,31 (5), 1031–1035, 1993.

    Article  Google Scholar 

  31. Kerbaol (V),Chapron (B.), Calibration and validation of ers-1/2 wave mode products,Eur. Space Agency Rep. PO no 160709,Inst. Fr. de Rech, pour l’Exploit. de la Mer, Brest, France, October 1996.

  32. Kerbaol (V), Chapron (B.), Elfouhaily (T.), Garello (R.), Fetch and wind dependence of sar azimuth cut-off and higher order statistics in a mistral wind case,in igarss’96, 621–624, IEEE Press, Piscataway, N.J., 1996.

    Google Scholar 

  33. Kerbaol (V.), Chapron (B.), Vachon (P.W.), Analysis of ERS-1/2 synthetic aperture radar Wave Mode imagettes,J. Geophys. Res.,103, 7833–7846, 1998.

    Article  Google Scholar 

  34. Kerbaol (V.), Analyse spectrale et statistique vent-vague des images radar à ouverture synthétique,Ph. D., University of Rennes, 1997.

  35. Korsbakken (E.), Quantitative wind field retrievals from ers- sar images,Tech. Rep., Eur. Space Agency (estec), 1996.

  36. Korsbakken (E.), Johannessen (J.A.), Johannessen (O.M.), Coastal wind field retrievals from ers synthetic aperture radar images,J. Geophys. Res.,103, 7857–7874, 1998.

    Article  Google Scholar 

  37. Krogstad (H.E.), A simple derivation of hasselmann ’s nonlinear ocean-synthetic aperture radar transform,J. Geophys. Res.,97 (C2), 2421–2425, 1992.

    Article  Google Scholar 

  38. Krogstad (H.E.), Vachon (P.W.), Generalizations of the non-linear ocean-SAR transform and a simplified sar inversion algo- rithm,Atmos. Ocean,32 (1), 61–82, 1994.

    Google Scholar 

  39. Krogstad (H.E.), Some comments about the processing of ers-1/2 imagettes and the wave mode product,Tech. Rep. stf10 A94008, SINTEF Industrial Mathematics, Trondheim, Norway, 1994.

  40. Kudryavtsev (V.N.), Mastenbroek (C), Makin (V.K.), Modulation of wind ripples by long surface waves via the air flow: a feedback mechanism,Bound. Layer. Meteo.,83, 99–116, 1997.

    Article  Google Scholar 

  41. Kudryavtsev (V.N.),Hauser (D.),Caudal (G.),Chapron (B.): Radar backscatter from the sea surface: a semi-empirical model including non-Bragg scattering, Part I: Surface model and background radar cross-section, submitted toJ. Geophys. Res.,2001.

  42. Kudryavtsev (V.N.),Hauser (D.),Caudal (G.),Chapron (B.): Radar backscatter from the sea surface: A semi-empirical model including non-Bragg scattering- Part II: Modulations due to long waves, submitted toJ. Geophys. Res., 2001

  43. Laur (H.),Meadows (P.J.),Sanchez (J.I.),Dwyer (E.), ers-1-sar radiometric calibration, inProceedings of the ceos sar Cali-bration Workshop, 257–281, estec, Noordwijk, The Netherlands, ESA wpp-048, 1993.

  44. Laur (H.),Bally (P.),Meadows (P.J.),Sanchez (J.I.),Schaettler (B.),Lopinto (E.), ers sar calibration - Derivation of backs-cattering coefficient in esa ers sar pri products,Tech. Note es-TN-RS-PM-HL09,Eur. Space Agency — Eur. Space Res. Inst., Frascaty, Italy, 1996.

  45. Le Caillec (J.M.), Garello (R.), Chapron (B.), Two dimensional bispectrum from ocean sar images,Nonlin. Proc. Geophys.,3, 196–215, 1996.

    Article  Google Scholar 

  46. Lehner (S.), Horstmann (J.), Koch (W.), Rosenthal (W), Mesoscale wind measurements using recalibrated ers sar images,J. Geophys. Res.,103, 7847–7856, 1998.

    Article  Google Scholar 

  47. Lehner (S.), Schättler (B.), Schulz-Stellenfleth (J.), Breit (H.), Processing and Calibration of ers sar single look complex imagettes: Extraction of wind and sea state parameters,in Proceedings ceos sar Workshop, estec,wpp-138, 9–15, 1998.

    Google Scholar 

  48. Lehner (S.), Schultz-Stellenfleth (J.), Schättler (B.), Breit (H.), Horstmann (J.), Wind and wave measurements using complex ers-2 sar wave mode data,ieee Trans, on Geoscience and Remote Sensing,38(5), 2246–2257, 2000

    Article  Google Scholar 

  49. Lehner (S.),Schulz-Stellenfleth (J.),Horstmann (J.), Global Distribution of Sea Surface Features from ers-2 sar Wave Mode Data,in Surface Slicks and Remote Sensing of Air-Sea Interac- tion, editor M.Gade, Kluwer Verlag, under review, 2001.

  50. Lyzenga (D.R.), Numerical simulation of synthetic aperture radar image spectra for ocean waves, ieee Trans.Geosci. and Remote Sens.,GE-24 (6), 863–872, 1986.

    Article  Google Scholar 

  51. Mastenbroek (C), De Valk (CF.), A semi-parametric algorithm to retrieve ocean wave spectra from sar,to appear in J. Geophys. Res.,105, (C2), 3497–3516, 2000.

    Article  Google Scholar 

  52. Mastenbroek (C), Spectral wave climate data from space-borne sar,in Proceedings ceos sar Workshop, estec,wpp-138, 17–25, 1998.

    Google Scholar 

  53. Ouchi (K.), Cordey (R.A.), Statistical analysis of azimuth streaks observed in digitally processed cassie imagery of sea surface,ieee Trans. Geosci. and Remote Sens.,29 (5), 727–735, 1991.

    Article  Google Scholar 

  54. Portabella (M.), ERS-2 sar wind retrievals versus hirlam outputs: a two-way validation-by-comparison,Tech. Rep., Eur. Space Agency (estec),ewp-190, 1998.

  55. Quilfen (Y.), ers-1 off-line wind scatterometer products,Tech. Rep. ifremer-scat/ioaJdos-01 , Inst. Fr. de Rech, pour l’Exploit,de la Mer, Brest, France, 1993.

  56. Romeiser (R.), Schmidt (A.), Alpers (W), A three-scale composite surface model for the ocean wave-radar modulation transfer function,J. Geophys. Res.,99 (C5), 9785–9801, 1994.

    Article  Google Scholar 

  57. Romeiser (R.), Alpers (W.), An improved composite surface model for the radar backscattering cross-section of the ocean surface: model response to surface roughness variations andd the radar imagery of underwater bottom topography, J. Geophys. Res.,102, 25251–25267, 1997.

    Article  Google Scholar 

  58. Scoon (A.), Robinson (I.S.), Meadows (P.J.), Demonstration of an improved calibration scheme for ers-1 sar imagery using a scatterometer wind model,Int. J. Remote Sens.,17 (2), 413–418, 1996.

    Article  Google Scholar 

  59. Steinberg (H.), Schulteiss (P.M.), Wogrin (CA.), Zweig (F.), Short-time frequency measurements of narrow-band random signals by means of a zero-counting process,J. Appl. Phys.,26 (2), 195–201, 1955.

    Article  Google Scholar 

  60. Stoeffelen (A.), Anderson (D.L.T.), ers-1 scatterometer data characteristics and wind retrieval skill,Adv. Space Res.,13, 553–560, 1993.

    Google Scholar 

  61. Swift (CT.), Wilson (L.R.), Synthetic aperture radar imaging of moving ocean waves,ieee Trans. Antennas Propag.,AP-27 (6), 725–729, 1979.

    Article  Google Scholar 

  62. Tilley (D.G.), Sarma (Y.V.), A comparison of synthetic aperture radars applied for satellite remote sensing of the ocean surface,Trends Geophys. Res.,2, 467–486, 1993.

    Google Scholar 

  63. Trunk (G.V.), Radar properties of non-Rayleigh sea clutter,ieee Trans. Aerosp. Electron. Syst., aes-8 (2), 196–204, 1972.

    Article  MathSciNet  Google Scholar 

  64. Tucker (M.J.), The imaging of waves by satelliteborne synthetic aperture radar: the effect of sea-surface motion,Int. J. Remote Sens.,6 (7), 1059–1074, 1985.

    Article  Google Scholar 

  65. Vachon (P.W.), Dobson (F.W.), Validation of wind vector retrieval from ers-1 sar images over the ocean,Global Atmos. Ocean Syst.,5, 177–187, 1996.

    Google Scholar 

  66. Vachon (P.W.), Krogstad (H.E.), Scott Paterson (J.), Airborne and spaceborne synthetic aperture radar observations of ocean waves,Atmos. Ocean,32 (1), 83–112, 1994.

    Google Scholar 

  67. Vachon (P.W.), Raney (R.K.), Resolution of the ocean wave propagation direction in sar imagery,ieee Trans. Geo. Rem. Sens.,29, 105–112, 1991.

    Article  Google Scholar 

  68. Vandemark (D.), Mourad (P.D.), Bailey (S.A.), Crawu-ford (T.L.), Vogel (CA.), Sun (J.), Chapron (B.), Measured changes in ocean surface roughness due to atmospheric boun- dary layers,J. Geophys. Res.,106 (C3), 4639–4654, 2001.

    Article  Google Scholar 

  69. Vandemark (D.), Jackson (F.C), Walsh (E.J.), Chapron (B.), Airborne radar measurements of ocean wave spectra and wind speed during the Grand Banks ers-1 sar wave experiment,Atmos.-Ocean,32 (1), 143–178, 1994

    Google Scholar 

  70. Vesecky (J.F.), Stewart (R.H.), The observation of ocean surface phenomena using imagery from the Seasat synthetic aperture radar,J. Geophys. Res.,87 (C5), 3397–3430, 1982.

    Article  Google Scholar 

  71. Voorrips (A.C.),Mastenbroek (C),Hansen (B.), Validation of two algorithms to retrieve ocean wave spectra from ers-sar, sub- mitted toJ. Geophys. Res, 2001.

  72. Ward (K.D.), Compound representation of high resolution sea clutter,Electron. Lett.,17, 561–563, 1981.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chapron, B., Johnsen, H. & Garello, R. Wave and wind retrieval from sar images of the ocean. Ann. Télécommun. 56, 682–699 (2001). https://doi.org/10.1007/BF02995562

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02995562

Key words

Mots clés

Navigation