This research aims to discuss and validate the presence of internal wave signatures in sea surface radar backscatter images using a dataset collected by a shipboard X-Band radar and a vessel-mounted ADCP in equatorial waters. The internal wave event occurred on 19th May 2022 between 10:38-11:00 UTC when the research vessel Meteor (M181 TRATLEQ II cruise) was moving towards Brazilian waters reaching latitudes of about 0°0′ S and longitudes from 42°20.73′ W to 42°26.06′ W. The nautical radar onboard also reported this event and we identify some backscatter features from internal waves even in the individual raw-radar images. The internal waves are also detected in composite images of sea surface radar backscatter images and near-surface wave current maps. The radar-derived wave current vectors are computed through an iterative procedure based on filtering the energy of the dispersion relationship to enhance the signal-to-noise ratio of predictions. We observe variations in wave current vectors when interacting with internal wave signatures. Finally, in-situ velocity data from a vessel-mounted ADCP validates the presence of internal waves during the analysis period, where vertical displacements occur in zonal and meridional velocities between 100-600 m water depth. Hence, results suggest shipboard X-Band radars are able to detect internal wave features at sea surface under special conditions.

Sargassum seaweed is a macroalgae that drifts in the Atlantic and massively washes ashore under the influence of winds, ocean currents and waves. Despite its benefits to open ocean ecology, invasive coastal Sargassum influxes affect negatively coastal communities. Thus, more observations are needed to monitor Sargassum motion from sea to shore. This work highlights the capacity of X-band radars to detect free-floating Sargassum in the open-ocean, a completely novel use of this technology. Radar data was collected during M181 Transatlantic Equatorial Cruise on 21st May 2022 (13:40-17:25 UTC). Results show shipboard X-band radars are able to detect local Sargassum rafts, while measuring waves and near-surface wave currents in near real-time. A qualitative comparison of radar images to in-situ photographs and satellite data shows concordance between radar-detected Sargassum and in-situ observations. Thus, X-band radars are potential monitoring tools to provide data for Sargas-sum motion forecasting and local biomass calculation, which can support Sargassum sinking initiatives for climate change mitigation. This paper is thereby a step further to develop solutions for trying to turn the crisis into an opportunity.

Significant wave height retrieval from X-band marine radars operating at grazing incidence is typically achieved by empirical algorithms that require extensive calibrations, which ideally are performed for every individual setup. Within this novel physics based approach coherent X-band marine radar data are being utilized to retrieve significant wave heights. In contrast to previously published methods, where the antenna had to be pointed into the main wave direction, this approach is utilized with a continuously rotating antenna. Radial velocities of surface scatterers are retrieved from the coherent radar data and converted under consideration of linear wave theory to surface elevations, which in turn are utilized to retrieve the significant wave height. The method was tested and applied to an extensive data set collected over a period of 29.5 days, covering four storms, at the offshore research platformForschungsplattform in Nord und Ostsee 3(FINO-3) in the southern North Sea. Comparison of radar retrieved significant wave heights to data obtained by a wave buoy in vicinity of FINO-3 resulted in a correlation of 0.99, a root mean square error of 0.31 m, and a bias of 0.09 m. In addition, sensitivity studies were carried out with respect to the quality of the signal, width of the dispersion filter and amount of data considered for calculations, to study the robustness of the method.

The study analyzes the microwave imaging of shoaling nearshore surface gravity waves during the process of steepening and breaking over two beaches for a wide range of environmental conditions. Data are sourced from two coherent X–band radars, operating under low grazing angle conditions. Using automatic wave tracking on the radar images, the evolution of individual waves is followed over hundreds of meters. The extracted backscatter intensity and Doppler speed form distinct patterns that reveal a non-negligible dependence on environmental conditions. Statistical representations of the backscattered signal are presented by conditional Doppler speed–Intensity histograms. These are composed of ensembles extracted at the radar-facing fronts. This technique helps to focus on the steepening of the wave and minimizes the impact of extremely low-grazing angle imaging mechanisms which are still not well understood. The combination of wind speed and direction as well as initial wave steepness, local depth, and degree of non-linearity contribute to the shapes and centroid positions of the histograms. The backscatter signature exhibited by breaking waves remained consistent and similar throughout all datasets. The results are consistent across radars. Before consolidating the findings, it is imperative to conduct a further investigation of radar imaging of non-linear wave dynamics in shallow water to eliminate any possible influence of imaging mechanisms.

This research applies a calibration-free method to estimate the significant wave height$(H_{s})$using the amplitude of the electromagnetic signal acquired by a coherent on receive X-Band radar that operates in horizontal polarization. The ex-periments were conducted from 8th to 11 th November 2015 at the research platform FINO-3 located in the German Bight of the southern North Sea. Unlike the traditional wave disper-sion based procedure, the proposed method uses other filtering and signal processing techniques to invert the sea surface elevation from the sea clutter radar images. The compari-son of radar-derived$H_{s}$to in-situ measurements collected by a waver rider buoy resulted in a root mean square error of 0.33 m with a bias of 0.09 m and a correlation coefficient of$r=0.92$. Validation of$H_{s}$estimates considering the AWAC measurements shows a RMSE of 0.24 m with a bias of 0.18 m and$r=0.96$. Therefore, this calibration free methodol-ogy is very well suited to be applied to X-Band marine radars operated from offshore platforms as well as ships.

Observations of microwave backscatter from shoaling and breaking surface waves acquired with a shore-based, coherent-on-receive X-band marine radar are presented. The radar was located at the dune cliff of a sandy beach with two breaker bars. Waves were approximately shore-normal (inclination$\approx 10$dB compared to nonbreaking) with Doppler velocities close to the wave phase velocity in shallow water. The strong backscatter from active breakers can cause a significant amount of signal artifacts due to the leakage of pulse energy into adjacent range cells, in particular behind the breaking crests. In the near range, the backscatter from the undisturbed surface and such pulse smearing artifacts appear as distinct peaks inside the Doppler spectra. Thus, the velocity of both sources of scatterering can be retrieved using a dedicated peak separation algorithm. In the far range ($r > 500$m), the artifacts dominate the Doppler signal behind breaking wave crests. Therefore, when investigating the spatio-temporal evolution of breaking wave-induced Doppler velocities with marine radar, the analysis should be restricted to the wave crests and the well-illuminated front faces of the waves. The evolution of Doppler spectra tracked along the crest of an exemplary individual breaking wave is extracted during the steepening, active- and post-breaking stage.

Dedicated science marine X-band radar (MR) systems onboard research vessels can complement the navigation radars by providing routine time series of surface wave parameters and near-surface currents as well as surface wave frequency-direction spectra. This study demonstrates how shipboard MR measurements can also be used to routinely retrieve near-surface current maps with high spatio-temporal resolution. The current maps are based on backscatter intensity image sequences acquired by a coherent-on-receive MR developed at Helmholtz Zentrum Geesthacht, Germany. Example results from two recent research cruises in the Pacific Ocean near Taiwan and off the coast of California are presented, showing energetic submesoscale upper ocean flow dynamics. The MR near-surface current maps are presented in conjunction with backscatter intensity images, which allow an indirect validation of the observed near-surface processes.

During a 2016 cruise to Palau, an X-Band, VV polarization Doppler Marine Radar (DMR) was installed on the R/V Roger Revelle. The DMR's capabilities to receive Doppler velocity information is utilized in order to find surface currents. An algorithm was developed to extract full Doppler velocity vectors from radially averaged data on a rotating antenna every 1.5 minutes for all 10 days of the cruise. This algorithm can also produce fully 2-D Doppler velocity vector maps for locations seen from a variety of look directions as the ship moves. Statistical analysis is done to show that the time series of Doppler velocity has dependence on three crucial variables: ship motion, wind speed, and surface current. A functional relationship is determined from this. The overall validity of this functional relationship is analyzed.

At the Helmholtz Zentrum Geesthacht (HZG), Germany an oceanic monitoring system, based on a Dopplerized microwave radar was developed. The focus of this paper is on the wave measurement methodology and applicability of this system. In addition, to the spectral wave properties such as peak wave period, peak wave direction and significant wave height, the system is capable of measuring, wave breaking, wind fields, near-surface currents, and bathymetry in shallow water. Due to the diversity of measurements that can be obtained with the system it is very well suited to be used to better understand hydrographic and oceanographic process studies in particular in the coastal zone.

Within this paper we describe a methodology to retrieve ocean surface currents from video data of ocean surface waves. The video sequences were acquired at nadir by an off the shelf quadcopter in the range of visible light. The quadcopter is equipped with an actively controlled gimbal for stabilization of the video camera and records all the information needed to geocode the video data. The geocoded video sequences are used to measure surface wave properties such as wave direction, length and phase velocity. These properties enable to measure the surface current, which results from the difference of the observed phase velocity to that given by the linear dispersion relation of surface waves. The method was applied to video data collected over the Elbe River in vicinity of a weir, showing the overall applicability.

Video imagery of surface waves recorded from a small off-the-shelf quadcopter with a self-stabilizing camera gimbal is analyzed to estimate the surface current field. The nadir looking camera acquires a short image sequence, which is geocoded to Universal Transverse Mercator coordinates. The resulting image sequence is used to quantify characteristic parameters (wavelength, period, and direction) of short (0.1–1 m) surface waves in space and time. This opens the opportunity to fit the linear dispersion relation to the data and thus monitor the frequency shift induced by an ambient current. The fitting is performed by applying a spectral energy-based maximization technique in the wavenumber–frequency domain. The current field is compared with measurements acquired by an acoustic Doppler current profiler mounted on a small boat, showing an overall good agreement. The root-mean-square error in current velocity is 0.09 m/s with no bias.

Significant wave height is one of the most important parameters for characterizing ocean waves and essential for coastal protection, shipping, as well as off shore industry operations. Within this paper, a robust method is introduced for retrieving significant wave heights from Doppler speed measurements acquired with a coherent-on-receive marine radar. The Doppler velocity is caused by the surface scattering in the line of site of the radar. To a huge extent its periodic component is induced by the orbital motions associated with surface waves. The proposed methodology is based on linear wave theory, accounts for projection effects caused by the fixed antenna look direction, and was applied to a coherent-on-receive radar operating at X-band with vertical polarization in transmit and receive. To show the overall performance of the method, a data set consisting of approximately 100 days of radar measurements was analyzed and used to retrieve significant wave heights. Comparisons to wave measurements collected by a wave rider buoy resulted in a root-mean-square (rms) error of 0.21 m and a bias of 0 m without any calibration parameters needed. To further improve the accuracy of significant wave height, a calibration factor needs to be accounted for, which improves the rms error to 0.15 m with a negligible bias of -0.01 m.

In this paper, the retrieval of sea surface current velocity from vertically polarized (V-pol) X-band marine radar data is presented. Three different methods, including the iterative least square approach, the normalized scalar product method, and the polar current shell algorithm, that have been used for horizontally polarized data are employed here. A comprehensive comparison of the performance of the three methods is conducted using the radar images collected by the V-pol radar deployed on the Forschungsplattformen in Nord- und Ostsee No. 3 (FINO3) offshore research platform and the acoustic Doppler current profiler (ADCP) data in the North Sea. The results indicate that all three methods are capable of providing reliable current speed and direction measurements from V-pol data, with similar performance. Based on the experimental data for which the current magnitude is less than 0.5 m/s, the radar-derived results agree best with the ADCP data at a depth of 6-8 m, with the root mean square difference for current velocity x- and y-components being 7.2-8.9 cm/s. The correlation coefficients between the radar-derived and ADCP-measured current velocity components are as high as 0.87-0.93.

In recent years, low-power high-frequency surface-wave radars have received significant attention thanks to their over-the-horizon coverage capability and the continuous-time operation mode. These radars have become effective long-range early-warning tools for maritime situational awareness applications. In this paper a knowledge-based multi-target tracking algorithm is described. The advantages in using a prior information on ship traffic are assessed exploiting real data acquired by two high-frequency surface-wave radars. The outcomes confirm the ability of the proposed approach to better follow targets with a time-on-target increment up to 30% with respect to existing methods. A reduction of the track fragmentation up to 20% is also observed.

This paper presents a geophysical model function (GMF) that has been developed to describe the relation of the ocean surface wind with the normalized radar cross section (NRCS) at C-band cross polarization (cross-pol). Synthetic aperture radar (SAR) images have been simultaneously collected at copolarization (co-pol) and cross-pol at moderate to high wind speeds. Using the SAR co-pol retrieved wind fields and an uncertainty estimate of the retrieved wind speeds, the cross-pol dependencies of the NRCS are investigated with respect to wind, incidence angle, and polarization pairs. For wind speeds above 10 m/s, there is a significant dependence of the NRCS on wind speed. However, the SAR cross-pol data are also significantly affected by the noise floor and crosstalk between the channels. Estimates of the noise floor are determined and removed from the NRCS. Three GMFs are developed: the first is for transmission at horizontal (H) polarization and the second at vertical (V) polarization. A third GMF accounts for wind direction dependence. Validation of the GMFs is conducted by comparison with collocated Stepped Frequency Microwave Radiometer (SFMR) data. The resulting bias of -0.7 m/s and standard deviation of 3.7 m/s demonstrate the excellent performance for these GMFs for wind speed retrieval between 10 and 35 m/s. Furthermore, comparisons show that SAR cross-pol retrieved wind speeds are of similar quality as those of SFMR and are significantly better in the moderate to high wind speed regime than SAR co-pol retrieved winds.

These last decades spawned a great interest toward low-power high-frequency (HF) surface-wave (SW) radars for ocean remote sensing. By virtue of their over-the-horizon coverage capability and continuous-time mode of operation, these sensors are also effective long-range early warning tools in maritime situational awareness applications providing an additional source of information for target detection and tracking. Unfortunately, they also exhibit many shortcomings that need to be taken into account, and proper algorithms need to be exploited to overcome their limitations. In this paper, we develop a knowledge-based (KB) multitarget tracking methodology that takes advantage of a priori information on the ship traffic. This a priori information is given by the ship sea lanes and by their related motion models, which together constitute the basic building blocks of a variable structure interactive multiple model procedure. False alarms and missed detections are dealt with using a joint probabilistic data association rule and nonlinearities are handled by means of the unscented Kalman filter. The KB-tracking procedure is validated using real data acquired during an HF-radar experiment in the Ligurian Sea (Mediterranean Sea). Two HFSW radar systems were operated to develop and test target detection and tracking algorithms. The overall performance is defined in terms of time-on-target, false-alarm rate (FAR), track fragmentation (TF), and accuracy. A full statistical characterization is provided using one month of data. A significant improvement of the KB-tracking procedure, in terms of system performance, is demonstrated in comparison with a standard joint probabilistic data association tracker recently proposed in the literature to track HFSW radar data. The main improvement of our approach is the better capability of following targets without increasing the FAR. This increment is much more evident in the region of low FAR, where it can be over the 30% for both the HFSW radar systems. The KB-tracking exhibits on average a reduction of the TF of about the 20% and the 13% of the utilized HFSW-radar systems.

In the context of maritime surveillance, low-power HF surface-wave (HFSW) radars have demonstrated to be a cost-effective long-range early-warning sensor for ship detection and tracking. In this work, multi-target tracking and data fusion techniques are applied to live-recorded data from a network of oceanographic HFSW radars installed in the German Bight (North Sea). This experimentation closely follows the one conducted in the Ligurian Sea (Mediterranean Sea) by NATO Science and Technology Organization (STO) Centre for Maritime Research and Experimentation (CMRE) during the Battlespace Preparation 2009 (BP09) campaign. Ship reports from the Automatic Identification System (AIS), recorded from both coastal and satellite-based stations, are exploited as ground truth information and a methodology is applied to classify the fused tracks and to estimate system performances. Preliminary results are presented and discussed, together with an outline for future works.

In the last decades, great interest has been directed toward low-power high-frequency (HF) surface-wave radars as long-range early warning tools in maritime-situational-awareness applications. These sensors, developed for ocean remote sensing, provide an additional source of information for ship detection and tracking, by virtue of their over-the-horizon coverage capability and continuous-time mode of operation. Unfortunately, they exhibit many shortcomings that need to be taken into account, such as poor range and azimuth resolution, high nonlinearity, and significant presence of clutter. In this paper, radar detection, multitarget tracking, and data fusion (DF) techniques are applied to experimental data collected during an HF-radar experiment, which took place between May and December 2009 on the Ligurian coast of the Mediterranean Sea. The system performance is defined in terms of time on target (ToT), false alarm rate (FAR), track fragmentation, and accuracy. A full statistical characterization is provided using one month of data. The effectiveness of the tracking and DF procedures is shown in comparison to the radar detection algorithm. In particular, the detector's FAR is reduced by one order of magnitude. Improvements, using the DF of the two radars, are also reported in terms of ToT as well as accuracy.

Several algorithms have been proposed to retrieve near-surface wind fields from C-band synthetic aperture radar (SAR) images acquired over the ocean. They mainly differ in the way how to retrieve wind direction. Conventionally, the wind direction is taken from an atmospheric model or extracted from linear features visible on SAR images. Recently a new wind retrieval algorithm has been proposed by Mouche et al. (2012), which includes also the Doppler shift induced by motions of the sea surface. We have tested this algorithm on complex wind fields encountered over the Black Sea. It is shown that the new algorithm yields better near-surface wind fields than conventional wind retrieval algorithms.

Low-power HF surface-wave radars fit well the role of long-range early-warning tools in maritime situational awareness applications, by virtue of their over-the-horizon coverage capability and continuous-time mode of operation. In fact, these sensors, developed for ocean remote sensing, can represent also a further low-cost source of information for ship detection and tracking. Unfortunately, many shortcomings, like poor range and azimuth resolution, high non-linearity and significant presence of clutter, may degrade their performance. In this paper, multi-target tracking and data fusion techniques are applied to experimental data collected during the NATO Battlespace Preparation 2009 HF-radar campaign, which took place between May and December 2009 in the Mediterranean Sea. The system performance is defined in terms of time-on-target, false alarm rate and accuracy. Experimental results are presented and discussed.

High-frequency surface wave radar (HFSWR) is used in oceanography to monitor surface wind waves and currents and, more recently, to detect ships in maritime surveillance. The radar accuracy is affected by range-Doppler coupling, which yields a displacement in the measured range proportional to the target radial velocity, i.e., the Doppler shift in the returned pulse. Although in oceanography this effect is usually not accounted for, its relevance grows in ship detection. In this letter, we present the results of two experimental data sets showing displacements in the HFSWR range measurements of up to 300 m and confirming the theoretical analysis. Furthermore, we show that the correction based on theoretical arguments, achieved by the statistical correlation between the range and Doppler measurements, provides remarkable improvement in the radar accuracy.

Due to its specific way of recording signals from multiple adjacent swaths in an alternating manner, a scanning synthetic aperture radar (SAR) (ScanSAR) cannot sample Doppler histories continuously like a SAR in stripmap mode. This can cause an effect known as azimuth scalloping, a wavelike modulation of the image intensity in near-azimuth direction. In theory, azimuth scalloping can be straightened out by using appropriate beam pattern corrections and multilooking techniques in the SAR processor. This works well over land, but lower signal-to-noise ratios and less accurate Doppler centroid estimates over water cause significant residual scalloping in many ScanSAR images of ocean scenes. The scalloping patterns hamper a correct interpretation of signatures of wind streaks, waves, and other phenomena. To overcome this problem once and for all, we have developed an algorithm that can eliminate scalloping patterns from existing ScanSAR images by postprocessing. Our algorithm detects the dominant scalloping pattern in an image automatically and eliminates most of it with very small side effects. We treat the scalloping pattern as a multiplicative effect, i.e., the amplitude spectrum of an affected image is assumed to be the convolution of the amplitude spectra of the unscalloped image and of the scalloping pattern. The proposed descalloping technique works partly in the spatial and partly in the spectral domain to approximate an exact deconvolution. We give a detailed technical description, show example results, and perform a quality analysis. We demonstrate the positive effects of the proposed descalloping treatment with a wind field retrieval example.

Low-power High-Frequency Surface-Wave (HFSW) radars, designed for oceanic applications, are promising tools also for long-range surveillance in open-water Multi-Target Tracking (MTT) applications. This paper focuses on the fusion of multiple aspects over single-perspective systems. The single-sensor tracking steps, made up by the Joint Probabilistic Data Association (JPDA) rule and the Unscented Kalman Filter (UKF), are followed by a Track-to-Track association and Fusion (T2TF) strategy. Tracking performance improvements are investigated using real data collected by two simultaneously operated HFSW-radars.

In this paper we evaluate different methods to retrieve wind information from marine radar data. In contrast to traditional in-situ sensors, marine radar wind data cover a large area and therefore are much less susceptible to air flow distortion by the platform. Unlike previous studies that have been limited to fixed-platform data, this study includes data from a quasi-stationary and moving platform. Images collected with a standard marine HH-polarized X-band radar operating at grazing incidence angle exhibit a single intensity peak in the upwind direction. Marine radar images that are averaged over about 1 min may also show wind streaks, which are usually well-aligned with the mean surface wind direction. Here, we use both phenomena to retrieve wind directional information and compare results to determine the best approach under the given conditions. To retrieve wind speeds, an empirical model function which relates average backscatter intensity to wind speed is developed.

Due to its specific way of scanning over multiple sub-swaths of a radar image, a ScanSAR (scanning synthetic aperture radar) cannot sample Doppler histories continuously like a regular SAR in stripmap mode. This can cause an artifact known as azimuthal scalloping, a wave-like modulation of the image intensity in azimuth direction. Although the problem is theoretically understood, many ScanSAR images of ocean scenes continue to exhibit scalloping. This hampers their use for applications such as wave and wind retrievals. We have developed an efficient descalloping algorithm that can be applied to such images as a post-processing tool. We describe how it works and show examples.

This paper describes a procedure to evaluate the performance of ship detection algorithms for Synthetic Aperture Radar (SAR) using real SAR images and Automatic Identification System (AIS) data as ground truth. Accurate AIS-SAR data association is achieved by correcting the AIS data for the SAR induced position errors by exploiting SAR acquisition parameters and vessel state information (speed and course) provided by AIS tracks. The methodology has been tested on a ship detection algorithm based on mathematical morphology which is described in this paper. The evaluation has been carried out on a RADARSAT-2 data set including images at different acquisition modes which was collected in the Mediterranean Sea. Estimates for the detection and the false alarm probability, and the contact position error are provided.

Bora events over the Adriatic Sea and Black Sea are investigated by using synthetic aperture radar (SAR) images acquired by the Advanced Synthetic Aperture Radar (ASAR) onboard the Envisat satellite, optical and infrared images acquired by the MODIS sensor onboard the Terra satellite, and sea surface wind data acquired by the scatterometer onboard the Quikscat satellite. Quantitative information on the sea surface wind field is extracted from the ASAR images by using the CMOD4 wind scatterometer model. It is shown that SAR images yield information of the spatial structure of bora events over coastal waters with high spatial resolution that cannot be obtained by other spaceborne instruments. Furthermore, by using ASAR data in combination with MODIS data we are able to detect cyclonic atmospheric eddies, which are often generated by lateral wind shear associated with bora events.

A method, called WiRAR, is developed to measure the wind vector using a marine X-band radar as sensor. WiRAR extracts local wind directions from wind induced streaks, which are visible in radar images at scales above 50 m. It is shown that the streaks are very well aligned with the mean surface wind directions. Wind speeds are derived with WiRAR from the normalized radar cross section (NRCS), by parametrization of its dependency on the wind vector, which was performed by training of a Neural Network. The dependency of the NRCS on sea state and atmospheric parameters, such as air-sea temperatures and humidity, were studied with respect to further improvement of WiRAR. Therefore, sea state parameters are extracted from radar-image sequences by derivation of the Signal-to-Noise Ratio (SNR) and wave phase speed at the spectral peak cp. The SNR is directly related to the significant wave height Hs- Recently, the research platform FINO-I has been set-up in the German Bight. This platform provides various environmental data, such as wind measurements at different heights of up to 100 m for studying the atmospheric boundary layer, as well as air-sea temperatures, humidity, and other meteorological and oceanographical parameters. WiRAR is applied to radar-image sequences acquired by a marine X-band radar aboard FINO-I. The derived wind vectors are compared to wind measurements at the platform. The comparison of wind directions resulted in a correlation coefficient of 0.99 with a standard deviation of 12.8deg and for wind speeds with a correlation coefficient of 0.99 with a standard deviation of 0.41 ms-1, respectively. In contrast to traditional offshore wind sensors, the retrieval of the wind vector from the backscatter of the ocean surface makes the system independent of the sensors motion and installation height and reduces the effects due to platform induced blockage and turbulence effects.

Since 1999 several synthetic aperture radar (SAR) images of hurricanes have been acquired by the Canadian satellite RADARSAT-1 as well as the European satellite ENVISAT. Several of these SAR images have captured hurricanes of category 4 and 5. These SAR images provide a unique opportunity to investigate the utility of SAR data for estimation of hurricane winds as well as for the improvement of hurricane forecasting. Using the SAR wind retrieval algorithm WiSAR, we have obtained good accuracies (root mean square error of 18' circ and 1.5 ms-1) for low to moderate wind speed conditions. The algorithm enables one to retrieve wind fields with a resolution of up to 300 m over a swath width of up to 500 km. WiSAR is an algorithm, which has shown to give good results under low and moderate wind conditions. The algorithm extracts wind directions from wind induced streaks imaged by the SAR at scales above 200 m. Wind speeds are extracted from the SAR measured normalized radar cross section (NRCS) utilizing the C-band model CMOD5, which describes the dependency of the NRCS on wind. It will be shown that the algorithm enables to measure wind directions as well as wind speeds of over 50 m s-1. The SAR-retrieved wind fields are compared to results of a high resolution numerical hurricane model.

The friction velocity is estimated from image sequences of a marine Radar, which operates at grazing incidence with X-band at horizontal polarization in transmit and receive. Therefore, radar image sequences are analyzed in space and time. The direction of the friction velocity is extracted from streak like features visible in the image resulting from the temporal integrated radar image sequence. The orientation of these streaks are determined by derivation of local gradients of the radar images. The magnitude of the friction velocity is derived from the measured normalized radar cross section by a geophysical model function (GMF), which is parameterized by training of a Neural Network. For further improvement of the GMF the radar retrieved signal to noise ratio, which is strongly related to the significant wave height, is taken into account. The methodology is validated at FINO-I, a research platform in the North Sea, were various meteorological and oceanographical parameters are measured on an operational basis. The radar retrieved friction velocities are compared to in-situ wind directions as well as to the friction velocities estimated from in situ measurements using the TOGA COARE formulation. The comparison resulted in a standard deviation of 13deg for wind direction and 0.41 ms-1for the magnitude of the friction velocity. In contrast to traditional measurements the retrieval of friction velocity from marine radars is free of platform induced effects, e.g., turbulence, and can be used from moving platforms.

A new method for wind-field retrieval with spatially and temporally high-resolution using marine radar-image sequences is presented. The method is based on analyzing the movement of wind gusts, which become visible in radar image sequences after filtering. In contrast to previous methods, this new technique requires no calibration phase of the radar system. The retrieved wind directions are compared to wind directions of the recently developed method, were wind directions are extracted from wind induced streaks that are orientated in wind direction. Wind speeds are derived from the backscatter of temporal integrated radar-image sequences using a empirical model function, which was parameterized by training a Neural Network. The different methods are applied to radar image sequences acquired by a marine X-band radar mounted aboard an offshore platform in the North Sea. The radar derived winds from more than 1300 radar-image sequences are compared to in-situ wind data measured at the platform. In contrast to traditional offshore wind sensors, the retrieval of the wind field from the backscatter of the ocean surface makes the system independent of the sensors motion and installation height and reduces the effects due to platform induced blockage and turbulence effects

The operational algorithm WiSAR is introduced, which enables to extract high-resolution ocean surface wind fields from satellite borne synthetic aperture radars (SARs) on a fully operational basis. WiSAR can be applied to SAR data acquired in C-band at either vertical (VV) or horizontal (HH) polarization in transmit and receive from the European satellites ERS-1/2 and ENVISAT as well as the Canadian satellite RADARSAT-1. SAR wind field retrieval is a two step process. In the first step wind directions are extracted from wind induced streaks that are visible in the SAR images at scales above 200 m and that are assumed to be approximately in line with the mean surface wind direction. The orientations of these streaks are derived by a method based on investigation of local gradients of the SAR intensity image. The SAR retrieved wind directions are used in the second step, where wind speeds are derived from the normalized radar cross sections of the SAR data under consideration of the wind direction and local SAR imaging geometry. Therefore, the empirical model CMOD4, is used, which was developed for the C-band VV polarized scatterometer aboard ERS-1/2. CMOD4 has been extended to HH polarization considering the polarization ratio and its dependency on incidence angle. To show WiSARs applicability it is applied to a set of 32 ENVISAT ASAR data from the North Sea. The resulting wind fields are compared to the results of the operational numerical model of the German Weather Service.

TerraSAR-X is a new generation, high resolution radar satellite, which is planned for launch in 2006. The mission is setup to produce operational remote sensing products for commercial and scientific use from a spaceborne X-Band synthetic aperture radar (SAR) system. After a 5 month in-orbit commissioning phase TerraSAR-X will be operational for an active lifetime of 5 years. TerraSAR-X is Germany's first Earth Observation space project based on public-private partnership of the German Aerospace Center and the ASTRJUM GmbH. The TerraSAR-X mission was designed to serve two main objectives: 1) provide the scientific community with high-quality, X-band SAR-data for research and application purposes; 2) support the establishment of an Earth Observation market; and 3) and develop a sustainable Earth Observation service in Europe, based on TerraSAR-X derived products. The broad spectrum of TerraSAR-X applications, include: Hydrology, Geology, Climatology, Oceanography, Environmental- and Disaster Monitoring as well as Cartography. The scientific potential of TerraSAR-X is based on a combination of unprecedented features of the SAR instrument, which will for the first time be operational in space. The features of TerraSAR-X offer new and promising applications for oceanography. In this work some promising applications concerning wind, wave and current measurements as well as monitoring of morphodynamic changes are introduced.

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

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

A new method for retrieving wind speeds and directions using nautical radar-image sequences is presented. The method consists of two parts, one for wind direction and another for wind speed retrieval. Wind directions are locally extracted from wind induced streaks, which are approximately in line with the mean wind direction. The algorithm assumes wind direction as normal to the local gradients of the amplitude image. Wind speeds are derived from the radar cross section, by parameterization of its dependency on the wind vector, which is performed by training of a neural network. For verification of the method the wind direction and speed from nearly 1400 radar-image sequences are compared to in situ data from a wind sensor. The accuracy and limitations of the method are discussed. A second new method is introduced, which enables to retrieve spatial and temporal wind fields from radar-image sequences. Thereby the wind streaks are available in space and time. The local velocity and direction of the wind pattern of each point in the investigated area is determined using tensor-based techniques. This method has the advantage that no calibration of the radar images or training of a neural network is necessary.

In the last years several algorithms for high-resolution ocean surface wind field retrieval from space borne synthetic aperture radar (SAR) have been developed. These algorithms were specially designed for the C-band SARs aboard the European satellites ERS-1 and ERS-2 operating at vertical (VV) polarization in transmit and receive and the Canadian satellite RADARSAT-1 operating at horizontal (HH) polarization. This paper shows the application of the algorithms to data of the advanced SAR (ASAR) from the European satellite ENVISAT. The wind retrieval algorithm consist of two parts. In the first wind directions are extracted from wind-induced streaks visible in most SAR images at scales between 200 and 1600 m using two different methods. In the second part wind speeds are derived from the normalized radar cross section (NRCS) and image geometry of the calibrated SAR images, together with the local wind direction resulting from the first step. For the wind speed retrieval the semi empirical. C-band scatterometer model CMOD5 is used. CMOD5 was originally developed for the scatterometer aboard ERS-1 and 2 operating at VV polarization and consequently requires modification if applied to HH-polarized SAR data. In case of HH-polarization the CMOD5 model is extended by considering the polarization ratio. It is shown that the quality of ENVISAT ASAR data is very well suited for measuring high-resolution ocean wind fields, which are especially important in coastal zones.

An algorithm is introduced and verified, which is designed to retrieve high-resolution wind fields from C-band synthetic aperture radar (SAR) operating at both vertical and horizontal polarization. SAR wind retrieval is a two-step process: In the first, step wind directions are ex- tracted from wind-induced streaks, which have a typical spacing of 200 to 1600 m and are normally aligned with the mean surface wind direction. In the second step, wind speeds are derived from the normalized radar cross section (NRCS) and image geometry of the calibrated SAR images, to- gether with the local wind direction retrieved in the first step. Several semi empirical C-band models are available, which describe the dependency of the NRCS on wind speed, wind direction and image geometry. To ver- ify the algorithm, wind fields were computed from 84 RADARSAT-1 SAR and ScanSAR scenes of the east coast of North America and compared to co-located results from the high resolution numerical model MM5. I. INTRODUCTION Synthetic aperture radars (SARs) are flown on several satellites, e.g., European satellites ESR-1, ERS-2 and EN- VISAT, Japanese satellite JERS and the Canadian satellite RADARSAT-1. Their independence of daylight and cloudi- ness together with their high resolution and large spatial cov- erage make them a valuable tool especially in coastal areas for measuring and observing geophysical parameters, e.g. ocean waves (1) and surface winds (2), (3). The SARaboard the Canadian satellite RADARSAT-1 operates in the C-band at moderate incidence angles. For this wavelength and range of incidence angles the backscatter from the ocean surface is primarily caused by the small-scale surface roughness, which is strongly influenced by the local wind field. Therefore, the backscatter can be empirically related to the wind. In the past few years much effort has been undertaken to develop algorithms for derivation of wind vectors from SAR images. The wind direction can be retrieved from the direction of wind-induced streaks, which are visible in most SARim- ages and are related to the mean wind direction. The direction of these streaks can either be retrieved by using spectral meth- ods or in the spatial domain by a method based on derivation of local gradients. The wind speed is derived from the normal- ized radar cross section (NRCS), which is retrieved from the SARdata, using semi empirical C-band models which were especially developed for vertical (VV) polarization. In case of HH polarization these models have been extended for the polarization ratio. The main objective of this paper is to introduce a recently developed algorithm for wind field retrieval from SAR, oper- ating at C-band with either VV or HH-polarization (2), and demonstrate its application utilizing RADARSAT-1 data. In contrast to the previously used wind direction retrieval algo- rithms based on filtering in the spectral domain (4) here they are retrieved in the spatial domain (2), (5). The spatial domain is an important improvement, because it enables us to exclude individual areas from the wind retrieval, e.g., areas covered by surface slicks, land or sea ice. Therefore, wind fields can be retrieved in coastal areas or areas partly covered by slicks or ice. II. INVESTIGATED DATA The Canadian satellite RADARSAT-1 is positioned on a near-circular, polar and sun-synchronous orbit at a mean al- titude of 790 km. It has a repeat cycle of 24 days with an orbital period of ∼ 100 min. The satellite operates a SAR with a frequency of 5.3 GHz (C-band) and transmits and re- ceives with linear horizontal (HH) polarization in transmit and receive. In this study different RADARSAT-1 SAR modes were used, which offer a possible range of incidence angles, between 20 ◦ and 49 ◦ perpendicular to flight direction. In the ScanSARmode an area of up to 500 km is covered with a reso- lution of ∼ 100 m and in the SARmodes enable a resolution of ∼ 30 m. All utilized RADARSAT-1 ScanSAR data were pro- cessed by the Alaska SARFacility (ASF) into calibrated SAR data.

Spaceborne synthetic aperture radar (SAR) is still the only instrument providing directional information on surface wind and ocean waves on a global and continuous basis. From RADARSAT-1, many SAR images have been collected over the past years, which cover several hurricanes and allow investigation of the wind and wave fields under these extreme situations. A time-frame of 27 days of ERS-2 SAR wave mode data was processed, which covers several tropical cyclones in the Atlantic Ocean, of which Hurricane Edouard has been investigated in detail together with additional data available from scatterometers, buoys and weather centers. The wind fields and wave parameters are extracted from SAR imagery and compared to results of the numerical model output provided by the European Centre for Medium-Range Weather Forecast (ECMWF) and co-located ERS-2 scatterometer measurements. For each wave system, spectral parameters such as wavelength, wave propagation direction and wave age are calculated and compared to the numerical model output provided by ECMWF.

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.

The new satellite ENVISAT, launched in march 2002, provides 10 x 5 km Synthetic Aperture Radar images (SAR imagettes) every 100 km along the track. This data set continues the data acquisition of the two European Remote Sensing satel- lites ERS-1 and ERS- 2, that have acquired similar SAR data for more than 10 years. In contrast to the ERS satellites, calibrated intensity images as well as lookcross spectra are provided as standard products from ENVISAT. The new data, e.g. enable the extraction of information on wind fields on a global scale. In this study the problem of wind direction estimation is addressed. The idea is to use the spectral information contained in lookcross spectra to estimate the propagation direction of the wind sea, which is strongly correlated with wind direction. The normalised radar cross section (NRCS) provided by calibrated imagettes then allows to estimate the wind speed using the CMOD4 model. A new classification method is applied to distinguish between swell and wind sea systems. The method is tested using a reprocessed data set of ENVISAT-like ERS-2 data, which are collocated with scatterometer data (SCAT). The analysis comprises case studies of hurricanes. The data set includes several hurricanes in the Atlantic Ocean and single events will be investigated. In addition comparison with ECMWF model data will be presented. The benefit the extracted directional information on wind speed estimation is analyzed. In particular it is shown that the method leads to better results than obtained assuming a constant wind direction.

In this paper we are concerned with automated approaches for generating wind vectors, an in particular with comparing approaches that differ in the spatial scales of the features used to estimate wind direction from the SAR imagery. One group (Veridian Systems Division) has focused on using larger scales (3 to 16 km) and estimating directions from either a spectrum of the image or from a projection of the imagery in different directions. The other group (GKSS Research Center) has focused on much smaller spatial scales (0.4 to 1.6 km), which extract directions either in the spectrum of the image or from local gradients derived from the image.

The properties of individual wave groups in space and time utilizing synthetic aperture radar (SAR) images and nautical radar image sequences are studied. This is possible by the quantitative measurement and analysis of wave groups both spatially and spatio-temporally. The SAR, with its high spatial resolution and large coverage, offers a unique opportunity to study and derive wave groups. In addition to SAR images, nautical radar image sequences allow the investigation of wave groups in space and time and, therefore, the measurement of parameters such as the group velocity. The detection of wave groups is based on the determination of the envelope function, which was first adopted for one-dimensional (1-D) time series by Longuet-Higgins. The method is extended from 1-D to spatial and spatio-temporal dimensions to derive wave groups in images and image sequences. To test the algorithm, wave groups are derived from SAR images and two radar image sequences, recorded at locations in deep and shallow water. It is demonstrated that the algorithm can be employed for the determination of both location and size of wave groups from radar images. Investigating the detected wave groups in radar image sequences additionally allows the measurement of the spatial and temporal development of wave groups and their extension and phase velocities. Comparison of measured wave group velocities in shallow and deep water gives a deviation of the average value from the group velocities resulting from linear wave theory and shows a clear oscillation of the group velocities in two dimensions.

The global availability of synthetic aperture radar (SAR) wave mode data from the European Remote Sensing (ERS) satellites ERS-1 and ERS-2, as well as ENVISAT, allows for the investigation of 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, representing a total of 34310 imagettes of size 10 km /spl times/5 km, available every 200 km along the satellite track. In this paper, two methods for retrieving wind speeds from SAR imagettes are presented and validated, showing the applicability of ENVISAT alike SAR wave mode data 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 needs to be accurately calibrated. This is performed by a new efficient method utilizing a subset of colocated measurements from ERS-2 SCAT and model winds from the European Centre for Medium-Range Weather Forecast (ECMWF). SAR wind speeds are computed from the calibrated imagettes and compared to the entire set of colocated ERS-2 SCAT and ECMWF model data. Comparison to ERS-2 SCAT winds result in a correlation of 0.95 with a bias of -0.01 m s/sup -1/ and an rms error of 1.0 m s/sup -1/. The second approach is based on neural networks (NNs), which allow the retrieval of wind speeds from uncalibrated SAR imagettes. NNs are trained using the mean intensity of ERS-2 SAR imagettes and colocated wind data from the ERS-2 SCAT and ECMWF model data. Validation of the NN-retrieved SAR wind speeds to ERS-2 SCAT and ECMWF model wind data result in a correlation of 0.96 with a bias of -0.04 m s/sup -1/ and an rms error of 0.93 m s/sup -1/.

An algorithm is presented for retrieving wind vectors from radar-image sequences acquired by a standard nautical radar near at near grazing incidence. The radar operates at X-band (9.5 GHz) with horizontal and vertical polarization in transmit and receive. The algorithm consists of two parts, one for wind direction and another for wind speed retrieval. Wind directions are locally extracted from wind induced streaks, which are approximately in line with the mean wind direction. The algorithm assumes wind direction as normal to the gradient of the amplitude image, which is approximated by finite differences over an appropriate length. The resulting wind direction is taken as normal to the retrieved local gradients. Wind speeds are derived from the radar cross section, by parameterization of its dependency on the wind vector using a neural network. The algorithm was tested and validated using data from a radar mounted in the North Sea. The applicability of nautical radars for wind retrieval is shown for both tower based and ship borne (moving) instruments.

A method is presented to localize wave groups spatially and spatio-temporally utilizing synthetic aperture radar (SAR) images and nautical radar-image sequences of the ocean surface. Extreme waves can grow in space and time as a result of wave group evolution. These wave groups have to be taken into account for instance for the design of offshore platforms, breakwaters or ships, because they can cause severe damage on those structures. To detect extreme waves, dominant wave groups are selected from SAR images and radar-image sequences by considering the wave envelope. A radar-image sequence is transformed into the wave-number frequency domain using a 3D Fourier transform where the signal of the ocean gravity waves is filtered using a band pass filter based on the dispersion relation for linear surface gravity waves. Thereafter, a 3D Hilbert transform is applied to the filtered complex Fourier coefficients, which are then transformed back into the spatio-temporal domain applying an inverse 3D Fourier transform. The resulting spatio-temporal complex envelope of the wave field is investigated for the dominant wave groups, by considering the amplitude of the complex envelope. With slight changes the algorithm can also be applied to single radar images. To test and verify the algorithm, several radar image sequences were acquired with the wave monitoring system WaMoS-II, which is based on a nautical radar operating in the X-band (9.5 GHz) near grazing incidence. The instrument was operated on towers in the North Sea. All these data sets are exploited with respect to the localization of extreme waves and wave groups.

An algorithm is introduced, which is designed to retrieve high-resolution wind fields from C-band synthetic aperture radars (SARs) operating at vertical or horizontal polarization. Wind directions are extracted from wind-induced streaks, which are approximately in line with the mean wind direction near to the ocean surface. Wind speeds are derived from the normalized radar cross section (NRCS) and image geometry of the calibrated SAR data, together with the prior retrieved wind direction. Therefore the semi empirical C-band model CMOD4, which describes the dependency of the NRCS on wind and image geometry, is used. CMOD4 was originally developed for the scatterometer of the European remote sensing satellites ERS-1 and ERS-2 operating at C-band with vertical polarization. Consequently CMOD4 requires modification for horizontal polarization, which is performed by considering the polarization ratio. To verify the algorithm, wind fields were computed from 159 ERS SAR and 20 RADARSAT-1 ScanSAR images and compared to co-located results from the numerical models REMO and HIRLAM.

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.

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/.

Monitoring and modelling of suspended particulate matter (SPM) is an important task especially in coastal environments. SPM concentration is one of the major parameters that regulates the penetration of light into the ocean and hence the primary production. In the past several SPM models have been developed for the North Sea. However, due to waves in shallow water and strong tidal currents in the southern part of the North Sea, this is a challenging task. In general there is a lack of measurements to determine appropriate exchange coefficients. In many satellite borne ocean colour images of the North Sea a plume is visible, which is caused by the scattering at SPM in the upper ocean layer. The intensity and length of the plume depends on the wave and current climate. It is well known that the SPM plume is especially obvious shortly after strong storm events. In this paper a SPM transport model is presented using the synergy of satellite borne ocean colour data and numerical modeling to derive the vertical exchange coefficients due to currents and waves. This results in a model that for the first time is able to reproduce the temporal and spatial evolution of the plume intensity. The SPM model is a quasi-3D model which consists of 3 components: ocean dynamics, SPM vertical exchange and SPM exchange processes with the sea bed. The component for vertical exchange of SPM considers sedimentation and resuspension. The SPM exchange processes with the sea bed take into account erosion, bioturbation by benthos as well as diffusion in the bottom layers.

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.

The high spatial resolution and large coverage of satellite-based synthetic aperture radars (SAR) offers a unique opportunity to derive mesoscale wind fields over the ocean surface, providing high resolution wind fields near the shore. For this purpose, algorithms were developed and tested using the ScanSAR aboard the Canadian satellite RADARSAT-1, operating at C-band with horizontal polarization in transmit and receive. Wind directions are extracted from wind-induced streaks visible on most SAR images. Wind speeds are derived from normalized radar cross sections (NRCS) using empirical models. The models were developed for scatterometers (SCAT) operating at C-band with vertical polarization and must be modified for horizontal polarization. Several available C-band polarization ratios were considered, including theoretical and empirical forms. To verify and improve the algorithm, wind speeds were computed from several RADARSAT-1 ScanSAR images and compared to colocated measurements from the SCAT aboard the European remote sensing satellite ERS-2 and to the results of the Danish high resolution limited area model (HIRLAM). Using the colocated measurements, the polarization ratio was estimated and applied to improve the wind retrieval algorithm. In addition, the main error sources in SAR wind field extraction are discussed with respect to the RADARSAT-1 ScanSAR data. Sensitivity studies were performed under different atmospheric situations using the modified C-band model to compute the errors due to wind direction and inaccuracies in NRCS.

A global dataset of complex synthetic aperture (SAR) images is processed from wave mode raw data acquired by the ERS-2 satellite. Using these data, different algorithms for wind and wave measurements recently developed in view of future ENVISAT ASAR data are analyzed on a statistical basis. Different aspects of complex SAR wave mode processing with the DLR processor BSAR are discussed and global statistics of processing parameters are presented. Single-look complex (SLC) imagettes give the opportunity to apply multilook techniques in range as well as in azimuth. Such methods are used to reduce speckle noise or to analyze the time evolution of the ocean surface cross section during SAR integration time. A global analysis of different new algorithms for wind and ocean wave measurements, taking advantage of SLC data, is given. Wind speed is estimated with the azimuthal cross-correlation algorithm (CCA). As a modification of the existing CCA, range multilooking is used to deal with the speckle bias. Homogeneity of the imagettes is considered. Wind speed is derived from mean SAR image intensities taking into account wind direction (CMOD algorithm). Comparison with collocated ERS-2 scatterometer data shows reasonable agreement with the CCA and good agreement for the CMOD approach. Using imagettes instead of image power spectra allows the authors to study ocean surface features caused by natural slicks, sea ice, or atmospheric processes. The impact of these phenomena on SCAT measurements is considered. Cross spectral methods are used to derive the ocean wave propagation direction from complex imagettes on a global basis. Comparison with model data provided by the European Center for Medium Range Weather Forecast (ECMWF) shows good agreement.