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In 2001 the European Space Agency ESA will launch the earth observation satellite ENVISAT. It will carry several instruments that provide new opportunities to measure oceanographic variables. Together, they represent the main measurement techniques of satellite oceanography, and complement each other in an ideal manner. These instruments are to be used in synergy to: • Improve the analysis of measured wind and ocean wave fields, and thereby improve weather forecasting at weather centers; • Determine the extent and variables of sea ice and develop a five-day sea ice prediction model, to support maritime shipping and offshore activities; • Monitor and map sediment and suspended matter transport in coastal regions, especially in areas with large river estuaries, which greatly affects shipping lanes, harbors, and dredging activities; • Monitor hydrobiological and bio-geochemical variables related to water quality in coastal regions and large inland waters, which affects ecology, coastal development, aquaculture, drinking water supplies, and tourism. To prepare the oceanographic community to make best use of the ENVISAT sensors in the pre-launch phase, existing algorithms to derive marine parameters are used and validated using data from the ERS SAR, the ERS RA, SeaWiFS and IRS MOS sensors now in operation. Derived products are used to address problems that can best be tackled using the synergy of radar and optical data, such as the effect of surface slicks on radar wind measurements, of sea state on ocean color, of wind and waves on the resuspension of suspended matter, and of wind and waves on sea ice variables.

An across track interferometric synthetic aperture radar (InSAR) is used to image ocean waves. Across track InSAR data were acquired during the SAR INnterferometry Experiment for validation of ocean Wave imaging models (SINEWAVE) in the North Sea using an airborne X-band radar with horizontal polarization. A wind sea system was imaged at different flight levels and with different flight directions with respect to the ocean wave propagation direction. Simultaneously, ocean wave spectra were measured by a directional wave rider buoy. Thus, the experiment data comprises synthetic aperture radar (SAR) intensity, coherence, and phase images together with in situ measurements. As shown in a recent theoretical study by Schulz-Stellenfleth and Lehner (2001), across track InSAR provides distorted (bunched) digital elevation models (DEMs) of the sea surface. Using SINEWAVE data the DEM bunching mechanism is verified with in situ ocean wave measurements available for the first time. It is shown that significant waveheight as well as one-dimensional (1D) wavenumber spectra derived from bunched DEMs and buoy data are in good agreement for small nonlinearities. Peak wave directions and peak wavelength detected in bunched DEMs and SAR intensity images are compared with the buoy spectrum. Peak rotations of up to 30/spl deg/ with respect to the buoy spectrum are found depending on flight direction and flight level. Two-dimensional (2D) spectra of bunched DEMs, corresponding coherency maps, and SAR intensity images are intercompared. The signal-to-noise ratio (SNR) of bunched DEM spectra is shown to be about 5 to 10 dB higher than the SNR of SAR intensity image spectra.

Since the launch of the ERS-1/2 Satellites in 1991 and 1995 respectively, synthetic aperture radar (SAR) images of coastal regions have been acquired and processed at the receiving station of the German Aerospace Center at Neustrelitz on an operational basis in near real time. These data are used to monitor large river estuaries of the German Bight which are morphodynamically very active, i.e. the bottom topography underlies a continuous change due to sediment transport, with strong impact on the main waterways of the river. Because of their all weather, day and night capability radar images are ideally suited to investigate these morphodynamics by monitoring the land-water boundary of the mud flats. Edge detection is a demanding task for radar images as they are contaminated by speckle noise. The water-line is extracted using edge detection methods based on a combination of blocktracing, wavelet-edge detection, and a snake algorithm resulting in the final coastline. The detected shorelines are transformed into isolines of bottom topography by combining them with available tide gauge information. Longer time series of such water lines are used for monitoring changes of topography over the years by comparing images taken at a similar tidal situation. The examples given, range from coastline monitoring, bottom topography control to sediment transport measurements. The areas investigated are the large estuaries of the German rivers at the North Sea (i.e. Ems, Weser, Elbe and Eider) and the Canadian Mackenzie delta.

Causal connections between mesoscale wind patterns and moisture distribution in the lower boundary layer can be studied using satellite synthetic aperture radar (SAR) observations. Wind information is retrieved from radar backscatter intensity over water areas, whereas the moisture distribution is reflected in the radar signal delay. The latter can only be observed over land areas, using the interferometric combination of two radar images. This paper reports on the relation between wind and moisture associated with boundary layer rolls and with a cold-frontal rain band. The combination of both signals, originating from one sensor, is used to infer a quantitative description of the underlying dynamical processes.

So far spaceborne SAR are the only all weather systems to provide directional ocean wave information on a continuos and global basis. However some care must be taken using SAR data to derive 2D ocean wave spectra; basic SAR principles cause unrecoverable information loss in the imaging process, and incomplete understanding of ocean wave imaging mechanisms leads to unsatisfactory exploitation of SAR data. The common approach to deal with the problem of information loss in the SAR image spectrum, is the use of an inversion algorithm taking some a priori knowledge, e.g. from wave models, S. Hasselmann et al. (1996). One goal of the present study is to address the second problem and to improve the understanding of SAR ocean wave imaging. In the following the authors investigate the ocean wave imaging mechanisms of a cross track InSAR system, which uses two SAR antennas with baseline perpendicular to the flight direction. In contrast to along track InSAR systems, which have been used, for example, to measure ocean currents, a cross track InSAR is able to measure topography. This is done by using the phase difference, of the radar signals, which are transmitted and received by the two antennas in turn. As the system yields simultaneous measurements of the sea surface elevation and the corresponding radar cross section, it is an ideal tool to investigate the ocean wave imaging by conventional SAR.

ERS SAR (synthetic aperture radar) wave mode raw data are focussed to complex imagettes of 5x10 km size approximately. For the processing DLR's research SAR processor BSAR is used. The raw data imagettes are acquired globally every 200 km along the orbit over the ocean and over sea ice, usually acquisition is switched off over land, although a few scenes are available. Up to now the detected imagettes were further processed by ESA to so called UWA spectra, a dataset from which ocean wave spectra could be calculated using SAR inversion methods. Chapron and Kerbaol used some datasets of real valued imagettes to derive wind speed. The new complex imagettes give the opportunity to derive two looks separated in time by approximately half a second. Using these multilook techniques newly developed algorithms are taken to infer propagation direction of the waves, to calculate wind speed and to derive ocean wave spectra. The results are compared to buoy measurements, the WAM model and the Hasselmann algorithm, which is presently state of the art at the ECMWF. The cross correlation algorithm is used to derive wind speed. The algorithm relates the width of the cross correlation of two separate complex looks, which is a measure of the energy contained in the high frequency part of the ocean wave spectrum, to wind speed. Complex imagettes will be available from the ASAR on ENVISAT therefore these investigations are an ideal preparation for the planned operational use of ENVISAT imagette data at meteorological centers like ECMWF. Using the imagettes instead of spectra additionally yields the opportunity to study ocean surface features.

Wind over sea can be determined with sufficient accuracy by SAR in global scale. Wind profiles can be measured by Doppler lidar. A first comparison in a few levels was performed.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The intention of DLR's remote sensing activities is to provide the user community with geophysical information both on land and ocean surfaces in near real time with highest possible reliability on the thermatic quality. Towards this end, the German Remote Sensing Data Centre (DFD) as part of the Germany's aerospace research establishment (DLR) operates a High Resolution Picture Transmission (HRPT) Station for the operational acquisition of Advanced Very High Resolution Radiometer (AVHRR) data. Additionally, DFD functions as a national Processing and Archiving Facility (PAF) for ERS-1/2 data on behalf of ESA. Also, high resolution SAR data from ERS missions can be captured in near-real time by DLR's X-band facilities at the DFD in Neustrelitz, enabling operational derivation of maritime and climatological parameters. This paper describes the value adding processes for the operational derivation of Multichannel Sea Surface Temperatures (MCSST) from NOAA AVHRR data in order to generate daily, weekly and monthly temperature maps of the Mediterranean including the Black Sea, the northeastern Atlantic including the Baltic and North Seas, and the region around Madeira and the Canary Islands. Emphasis is given to special sensor processing steps such as calibration, navigation and cloud-screening for the available products. The ERS SAR is used to derive parameters such as mesoscale wind fields, currents and water levels for the needs of coastal management. Since the SAR works with the same wavelength as the scatterometer, the signal can be evaluated by the same algorithm used for the scayterometer signal (CMOD4 Algorithm from ESA). The wind direction is determined by a method that uses the average direction of wind rows visible on SAR images. Comparisons of wind measurements using recalibrated ERS SAR images to ground truth data are given. Finally, the application potential is outlined and network data distribution, including public access to all products via DLR's Intelligent Satellite Information System (ISIS), are described.

The main highlights of TerraSAR-X (TS-X) synthetic aperture radar (SAR) imagery are a higher resolution of up to 1 m, when compared to conventional C-band SAR data, and a reduction of nonlinear imaging effects of a moving target by lower platform altitude. Thus, ocean waves with wavelength

The precision images (PRI) of the synthetic aperture radars (SAR) on board the European Remote Sensing Satellites ERS-1 and ERS-2 are used to derive mesoscale wind fields over the ocean. For calculation of the wind speed the C-band model (CMOD4) is used, which was originally developed by Stoffelen and Anderson [1993] for the European Space Agency (ESA) to derive wind fields from measurements of the wind scatterometer (SCAT). In the case of the ERS-1/2 SAR the CMOD4 is used to compute the wind speed from the normalized radar backscatter cross section (NRCS) and the incidence angle of the radar beam, both computed from the SAR.PRI data. The third input variable is the wind direction, which is estimated from the wind streaks in the images or from ground truth measurements. The SAR data are affected by a power loss, caused by saturation of the analog to digital converter (ADC) of the SAR. Therefore the images have to be recalibrated. Errors in the derived wind speed are mainly due to ADC saturation and uncertainties of the input wind direction. These errors are estimated for various wind conditions. Mesoscale wind fields computed from ERS-1/2 SAR.PRI images taken between the Shetland Islands and the west coast of Norway are compared to ground truth measurements and modeled wind fields from the German weather service (DWD). Wind fields of the nonhydrostatic mesoscale model Geesthacht simulation model of the atmosphere (GESIMA) are compared to the derived wind field of the ERS-1 SAR.PRI image at the island Rugen in the Baltic Sea.

To calibrate synthetic aperture radar (SAR) images to normalized radar cross sections (NRCS) a calibration constant is required. Usually the calibration constant is determined by analyzing measurements of corner reflectors. However, due to the high costs there are only a very limited number of corner reflectors available. In this paper a new method for estimating the calibration constant on the basis of a few days of SAR data is introduced. The method is based on knowledge of the dependency of the NRCS on the ocean surface wind, which is described by well-tested empirical C-band models, e.g., CMOD4 and CMOD IFR2. Given the mean wind vector at each SAR wave mode image both models enable to derive the mean NRCS of the image. Application of the method is demonstrated and validated utilizing a total of 34000 SAR imagettes and co-located winds from the European Centre for Medium range Weather Forecast and the ERS-2 scatterometer. The SAR imagettes were processed to ENVISAT ASAR-like single look complex SAR images using three weeks of SAR wave mode data. It is shown that the method is an ideal tool for retrieving the SAR calibration constant and is capable to monitor and estimate variations of the calibration constant, e.g., due to saturation of the SAR analogue to digital convertor or gain drifts.

In the framework of the EuroROSE project high resolution ocean wave, wind and current fields were measured at the North Coast of Spain by simultaneous data acquisitions of spaceborne, airborne, and in situ instruments. The objective of the project was to provide a guidance system for ships entering the harbour of Gijon, by monitoring and forecasting wind, waves and currents. This paper presents first results of a new airborne three antenna interferometric synthetic aperture radar (InSAR) system which provides information on both sea surface elevation and motion. The system transmits and receives signals with a combination of three antennas, whereby two are placed along flight direction and the third in across flight direction. This configuration allows, for the first time, to acquire along and across track InSAR data simultaneously. The system was flown in different flight patterns with simultaneous measurements of directional wave spectra, wind and currents fields taken by the HF-radar WERA, the radar based wave monitoring system WaMoSII, the ERS-2 SAR and a waverider buoy.

In this paper an algorithm is presented which enables high-resolution ocean surface wind fields to be retrieved from the advanced synthetic aperture radar (ASAR) data acquired by the European remote sensing satellite ENVISAT. Wind directions are extracted from wind-induced streaks that are visible in ASAR images at scales above 200 m and that are approximately in line with the mean surface wind direction. Wind speeds are derived from the normalized radar cross section (NRCS) and image geometry of the calibrated ASAR images, together with the local ASAR-retrieved wind direction. Therefore the empirical C-band model CMOD4, which describes the dependency of the NRCS on wind and image geometry, is used. CMOD4 is a semi-empirical model, which was originally developed for the scatterometer of the European remote sensing satellites ERS-1 and 2 operating at C-band with vertical polarization. Consequently, CMOD4 requires modification when applied to ASAR images that were acquired with horizontal polarization in transmitting and receiving. This is performed by considering the polarization ratio of the NRCS. To demonstrate the applicability of the algorithm, wind fields were computed from several ENVISAT ASAR images of the North Sea and compared to atmospheric model results of the German weather service.

The availability of cloud- and light-independent synthetic aperture radar (SAR) data provides a perspective of the ocean surface that is unique in satellite remote sensing. The high spatial resolution and large coverage of satellite-based SAR offer the opportunity to derive mesoscale wind fields over the ocean surface with spatial resolution nearly 2 orders of magnitude higher (500 m) than conventional scatterometers (45 km). This enhanced resolution gives new opportunities for quantitative analyzes of marine atmospheric boundary layer and oceanographic processes especially in coastal areas. In this paper an algorithm is developed and tested to retrieve mesoscale wind fields from the ScanSAR aboard the Canadian satellite RADARSAT-1, which operates at C-band with horizontal polarization in transmit and receive. Wind directions are extracted from wind induced streaks visible on most SAR images by visual inspection and spectral filtering of the image power spectra. Wind speeds are derived from the normalized radar cross section (NRCS), image geometry of the images, and wind direction by inversion of semi empirical C-band models which describe the dependency of the NRCS on wind. The models were specially developed for the scatterometer aboard the European remote sensing satellites ERS-1 and ERS-2, which operates at C-band with vertical polarization in transmit and receive. To apply these models to ScanSAR data they have to be modified for horizontal polarization, which was performed considering several C-band polarization ratios including theoretical and empirical forms.

It is well known that typhoons are hard to forecast because of their complicated dynamical behaviour. In this study a new global data set of reprocessed ERS-2 wave mode data is used to study typhoons assessing the potential of these data for improving typhoon forecast. Operating in wave mode the ERS SAR acquires high resolution images of 10 by 5 km size every 200 km along the track yielding a patchy coverage of the global oceans with about 1500 scenes taken each day. The images contain information on both ocean waves and near surface wind. The typhoon TRINING in November 1999 is analyzed. Local wind speeds are estimated from the SAR image intensity. Results are compared with collocated ERS-2 altimeter measurements of wave height and wind speed as well QuikScat wind vectors. The potential of the high resolution SAR information with regard to the analysis of rain cells and atmospheric turbulence is discussed. SST measurements obtained from spaceborne radiometers are used as complementary information. The combined use of altimeter wind speeds and radar cross sections obtained from SAR to estimate wind vectors is investigated

In this study a global data set of reprocessed synthetic aperture radar (SAR) data acquired by the European Remote Sensing satellite ERS-2 is used to study ocean wave grouping using wavelet based methods. For more than a decade the ERS-1/2 satellites have continuously recorded SAR images of the ocean surface. Operating in wave mode both instruments have acquired about 1400 imagettes of 10/spl times/5 km. size (every 200 km along the orbit) each day, which allows to study ocean waves on a global basis. Only coarsely gridded SAR image spectra are available as official wave mode products from the European Space Agency (ESA). As the full image information is required for the present study about 3 weeks of ERS-2 SAR wave mode raw data were reprocessed to 34000 complex SAR images using the BSAR processor from the German Aerospace Center (DLR). ENVISAT satellite, which was successfully launched on February 28, 2002, will provide almost 3000 imagettes a day due to its higher sampling rate (every 100 km). Applying a wavelet edge detection method on the SAR-amplitude-density image and using a region growing approach for the edgefree areas allows examinations of the wave groupiness on a single image. These examinations include group size and number of large groups. The wavelet coefficient as a measure for edge strength is correlated to both wave height and steepness. The wavelet method is compared with an alternative approach, which is based on the classical Hilbert-transform technique. For the latter method the actual sea surface elevation field has to be known. Therefore a quasilinear inversion scheme is used which estimates the surface elevation from complex SAR data.

The global availability of synthetic aperture radar (SAR) wave mode data from the European remote sensing satellite ERS-2 allows to investigate the wind field over the ocean on a global and continuous basis. For this purpose 27 days of ERS-2 SAR wave mode data were processed to single look complex SAR images, representing a total of 34310 images of size 5 km/spl times/10 km, available every 200 km along the satellite track. In this paper two methods for retrieving wind speeds from SAR images are presented and validated, showing the applicability of both methods for global ocean wind retrieval. The first method is based on the well tested empirical C-band scatterometer (SCAT) models which describe the dependency of the normalized radar cross section (NRCS) on wind speed and direction. To apply C-band models to SAR data the NRCS has to be accurately calibrated. This is achieved by a new simple but effective method using a subset of collocated ERS-2 SCAT and model winds from the European Center for Medium Range Weather Forecast (ECMWF). SAR derived wind speeds are compared to the entire set of collocated ERS-2 SCAT and ECMWF model data. Comparison to ERS-2 SCAT results in a correlation of 0.94 with a bias of -0.45 m s/sup -1/ and a root mean square error of 1.21 m s/sup -1/. The second approach is based on neural network algorithms allowing one to retrieve wind speeds from uncalibrated SAR images. For this purpose a neural network is trained using ERS-2 SAR data and collocated wind data from ERS-2 SCAT and the ECMWF atmospheric model. Validation of the neural network retrieved SAR wind speeds to ERS-2 SCAT and ECMWF model wind data is performed. A correlation of 0.95 with a bias of -0.1 m s/sup -1/ and a root mean square error of 1.03 m s/sup -1/ is achieved in comparison to ERS-2 SCAT.

This paper represents a consensus on the state-of-the-art in wind retrieval using synthetic aperture radar (SAR), after the SEASAR 2012 workshop “Advances in SAR Oceanography” hosted by the European Space Agency (ESA) and the Norwegian Space Centre in Tromsø, Norway 18–22 June 2012. We document the recent advances of the methodologies, which are capitalizing on the improved capabilities of the modern generation of SAR sensors providing Doppler grid and multi-polarizations. The many applications of SAR wind retrieval have also benefitted from on the improved availability of wide swath modes (~500 km) with excellent coverage, giving much better overview of regional and mesoscale wind features. The accuracy of offshore wind retrieval is robust and generally in the order of 1.5 m/s in speed and 20° in direction, whereas the new methodologies steadily improve the performance for the more challenging conditions near cyclones and complex coastal topography.

Due to the shortage of suitable sites on land offshore wind farming has grown rapidly in Europe over the last decade. For the optimal siting, building and operation of these wind parks, remote sensing techniques can help in many different ways. In this study a special application of the well known wind field measurement technique based on synthetic aperture radar (SAR) data is presented. SAR scenes as acquired by the European satellites ERS-2 or ENVISAT permit the estimation of 2D wind fields with a resolution of less than 1 km and a coverage of up to 500 km. With this capability SAR is an efficient instrument to obtain wind information on spatial scales relevant for offshore wind farming. In the analysis the two wind parks sites "Horns Rev" and "Butendiek" in the North Sea are compared. While "Horns Rev" is already in operation "Butendiek" is still in the planning stage. The objective is to assess the expected power yield in the new wind park in comparison to the existing wind farm. For the investigation ERS-2 image mode scenes of 100 by 100 km size were used, which are ideally suited for this application, because both wind farm sites are covered by a single scene. Scatterplots of SAR derived wind speed and wind direction obtained for both wind farms are presented and discussed

In this paper some recent results on SAR observation of extreme surface wind conditions are summarized. Particular emphasis is put on the investigation of typhoons occurring in the North West Pacific. The study is based on the use of ENVISAT ASAR wide swath images (400 km×400 km), which allow synoptic measurements of the complete mesoscale system at high resolution (150 m). Surface wind speed for typhoon cases is determined from SAR measurements using the geophysical model function CMOD5. Further structures observed in the image like streaks indicating wind direction and the ring of maximum wind speed are additionally taken into account to reconstruct the typhoon wind field. The influence of heavy rain on the radar cross section is estimated from an existing radiative transfer model and compared to the SAR measurements. A new technique for the estimation of typhoon intensity from SAR data is presented, which makes use of a parametric type model. The main goal of the paper is the improvement of the estimation of maximum typhoon intensity using SAR data.

Space borne synthetic aperture radar are able to provide high resolution measurements of ocean waves on a global scale. The present study uses a reprocessed data set of complex SAR images acquired by the European Remote Sensing satellite ERS-2 to estimate different wave parameters relevant for ship security. In addition, a new method is presented to derive two dimensional sea surface elevation fields from complex SAR data. The method permits to analyze wave fields in more detail than conventional SAR wave measurement techniques, which only estimate the wave spectrum. The technique provides parameters like maximum to significant wave height ratios, wave steepness, or the probability of wave breaking. Global maps and statistics of the new parameters are presented.

A global dataset of complex synthetic aperture radar (SAR) images processed from wave mode raw data acquired by the European remote sensing satellite ERS-2 is used to measure ocean waves. Cross spectra of two looks extracted from the azimuth spectrum of wave mode imagettes are used to derive ocean wave propagation directions on a global basis. Energy and propagation direction derived from wave mode cross spectra are compared with ocean wave model data from the European center for medium range weather forecasts (ECMWF). A new inversion scheme for the retrieval of two dimensional wave spectra from SAR cross spectra is presented. The algorithm is based on a maximum a posteriori estimation which combines the information from SAR measurements with a priori knowledge on short ocean waves. A new regularization approach is used to impose smoothness constraints on the retrieved wave spectra.

Three weeks of ERS-2 SAR wave mode data, representing a total of 34000 SAR images of 5 km /spl times/ 10 km size, were utilized to verify wind retrieval algorithms on a global basis. Wind speeds are retrieved from calibrated SAR normalized radar cross section (NRCS) as well as uncalibrated SAR intensity images. In case of the calibrated NRCS the well-tested empirical C-band scatterometer (SCAT) model CMOD4 is used, which describes the dependency of the NRCS on wind. Therefore the SAR data are calibrated, which is performed by utilizing a subset of co-located ERS-2 SCAT data. SAR derived wind speeds are compared to co-located winds from the ERS-2 SCAT and model results of the European Centre for Medium-range Weather Forecast (ECMWF). The comparison to ERS-2 SCAT results in a correlation of 0.95 with a bias of -0.01 ms/sup -1/ and a root mean square error of 1.0 ms/sup -1/. In case of SAR intensities a Neural Network (NN) is used that allows to retrieve wind speeds from uncalibrated SAR images. Comparison of NN retrieved SAR wind speeds to ERS-2 SCAT wind speeds result in a correlation of 0.96 with a bias of -0.04 ms/sup -1/ and a root mean square error of 0.93 ms/sup -1/.

Safety of shipping is an ever growing concern. In a summary, Faulkner investigated the causes of shipping casualties (2002, “Shipping Safety: A Matter of Concern,” Ingenia, The Royal Academy of Engineering, Marine Matters, pp. 13–20) and concluded that the numbers of unexplained accidents are far too high in comparison to other means of transport. From various sources, including insurers data over 30% of the casualties are due to bad weather (a fact that ships should be able to cope with) and a further 25% remain completely unexplained. The European project MaxWave aimed at investigating ship and platform accidents due to severe weather conditions using different radars and in situ sensors and at suggesting improved design and new safety measures. Heavy sea states and severe weather conditions have caused the loss of more than 200 large cargo vessels within the 20years between 1981 and 2000 (Table 1 in Faulkner). In many cases, single “rogue waves” of abnormal height as well as groups of extreme waves have been reported by crew members of such ships. The European Project MaxWave deals with both theoretical aspects of extreme waves and new techniques to observe these waves using different remote sensing techniques. The final goal is to improve the understanding of the physical processes responsible for the generation of extreme waves and to identify geophysical conditions in which such waves are most likely to occur. Two-dimensional sea surface elevation fields are derived from marine radar and space borne synthetic aperture radar data. Individual wave parameters such as maximum to significant wave height ratios and wave steepness, are derived from the sea surface topography. Several ship and offshore platform accidents are analyzed and the impact on ship and offshore design is discussed. Tank experiments are performed to test the impact of designed extreme waves on ships and offshore structures. This article gives an overview of the different work packages on observation of rogue waves, explanations, and consequences for design.

Surface wind fields over the ocean can be estimated from synthetic aperture radars (SAR) data using an empirical model relating the radar cross section to the wind speed and a prescribed wind direction. Results are presented for a ERS SAR image acquired on April 7th, 1998 over the Gulf of Lion (Mediterranean Sea) during the FETCH experiment. A comparison with data collected during the campaign is presented.