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For the design of ships as well as for the investigation of ship accidents it is important to have knowledge about both the two dimensional spectral wave properties as well as extreme value statistics of ocean waves. Although numerical wave models have reached a high level of accuracy, they still have weaknesses with respect to the details of the 2-D wave spectrum. Furthermore standard models like WAM provide estimates of the 2-D wave spectrum, i.e., second order sea state statistics and therefore lack information on individual wave properties and the occurrence of extreme events. In this study the potential of global Synthetic Aperture Radar (SAR) wave mode data acquired by the European satellites ERS-2 and ENVISAT to investigate ship accidents is discussed and compared to altimeter data and ECMWF model results. These data are acquired independent of light and weather conditions on a global scale. A historic data set of ERS-2 wave mode data acquired between 1998 and 2000 is co-located with accidents which occurred during that time. ENVISAT ASAR wave mode data acquired since 2002 are considered, too. Different ocean wave parameters like significant wave height and wave periods are derived from the SAR data. The potential role of the respective wave conditions for some recent accident is discussed in detail. This includes in particular the analysis of cross sea conditions, groupiness and extreme events.

[1] In this study a new empirical approach to retrieve integral ocean wave parameters from synthetic aperture radar (SAR) data is presented. The idea behind this computationally efficient technique is to estimate integral ocean wave parameters without the intermediate step of retrieving the two-dimensional ocean wave spectrum. The method has the radiometrically calibrated SAR image as the only source of information and is based on a quadratic model function with 22 input parameters. These parameters include the radar cross section, the image variance, and 20 parameters computed from the SAR image variance spectrum using a set of orthonormal functions. The coefficients of the quadratic function were fitted for the estimation of Hs, the mean periods Tm01, Tm02, T−10, the wave power, and the wave heights associated with different spectral bands. The fit procedure is based on a stepwise regression method. A data set of 12,000 globally distributed ERS-2 wave mode image spectra and colocated WAM ocean wave spectra was available for the study. Two separate subsets of 6000 collocation pairs each were used to fit the model and to carry out comparisons of the retrieved wave parameters with numerical model results. Additional comparisons were performed using NDBC buoy measurements. Scatterplots and global maps with the derived parameters are presented. It is shown that the rms of the SAR derived Hs with respect to the WAM Hs is about 0.5 m. For the mean period Tm−10 an rms of 0.72 s with a high-frequency cutoff period of about 6 s is achieved.

Both atmospheric and oceanic processes play an important role in the dynamics of tropical cyclones. Due to the relatively small amount of in situ data available for extreme events like hurricanes or typhoons remote sensing techniques play an important role in the measurement of the relevant geophysical parameters. In this paper some recent results on SAR observation of extreme wind conditions are summarized. The study is based on the use of ENVISAT ASAR wide swath images. The objective of this study is to investigate the performance of SAR to improve the existing model for the retrieval of information on wind field under extreme wind and wave conditions using information from a parametric Holland type model.

Space borne radar systems are capable of providing wind field information over the ocean. Radar instruments are of high value for operational applications because of their all weather and daylight capabilities. Synthetic aperture radar (SAR) instruments as flown on the European satellites ERS-2, ENVISAT or the Canadian platform RADARSAT are of particular interest for applications where high resolution two- dimensional information on the near surface wind field is needed. All these operate in C-band. The respective wind field algorithm CMOD was tuned to this wavelength. New research focussed on high speed cases to be able to measure wind speeds above 20 m/sec and on the W to HH polarisation ratio. For future missions like TerraSAR-X, to be launched in May 2007 new wind field algorithms tuned to X-band are needed. The TerraSAR-X instrument has a spatial resolution of up to 1 m and additional features like multi polarisation which make it a very interesting tool for oceanographic applications. In this paper a new X band wind field algorithm, XMOD1.0 is introduced. The algorithm is based on the detection of wind streaks in the SAR images and scatterometer measurements of [1]. Data from the SRTM mission flown on the shuttle in February 2000 and SIR C/X SAR in 1994 are used to test the algorithm. Results are validated against in situ data and model data from ECMWF. The potential of SAR measurements to support the optimal siting, the design, as well as the operation of offshore wind parks is shown. Applications for offshore wind farming of the TerraSAR-X mission will be discussed. The platform FINO 1 was chosen as a primary test site to calibrate and validate wind fields for X band satellite images. For the development, optimisation and validation of the retrieval algorithms comparisons with in situ data, e.g., acquired at the FINO platform will be carried out. The respective calibration and validations strategies will be summarized.

Currently the European satellites ERS-2 and ENVISAT are flying on the same orbit with a time separation of 30 minutes. In this presentation pairs of the respective synthetic aperture radar data are analyzed with respect to different atmospheric and oceanic processes. The presented results were obtained in the framework of the ESA AO project COTAR. The tandem configuration exists since the launch of ENVISAT in 2002. In the presentation an overview will be given of the available image pairs acquired over the ocean on a global scale. Combinations of ERS-2 SAR data with both image mode and wide swath mode scenes provided by the ENVISAT ASAR are considered. The two SAR images enable the analysis of the change of radar cross section within half an hour. This temporal separation is very interesting for oceanographic applications because there are many processes like atmospheric fronts, convective cells, ocean tides, etc., which are detectable on this time scale. In the presentation tandem pairs acquired over the research platform FINO west of the island Borkum in the North Sea will be presented. The area is of high practical interest because of the planned Offshore Windpark Borkum West. The platform provides wind measurements at different heights and additional oceanic information to support the planning activities for this windpark. The dynamics of atmospheric structures is analysed. It is well known that the near surface wind field is a dominating factor for the normalized radar cross section of the sea surface. For this reason SAR scenes are well suited to study atmospheric effects with high spatial resolution. It is shown that the use of tandem pairs enables the study of processes like the propagation of an atmospheric fronts or the evolution of convective cells. Both effects are illustrated with different examples using additional information from in situ measurements. Furthermore existing techniques for the estimation of the wind field in 10 m height from SAR data are applied to both images. The evolution of the spatial structure of both wind speed and wind direction is analysed. The observations are related to some theoretical issues like, e.g., the Taylor hypothesis. Particular emphasize is put on the connection between the spatial and the temporal structure of the wind field. This topic is of high practical relevance, e.g., in the context of offshore windenergy exploitation. Additional applications like ship tracking, oil spill detection and the study of ocean wave field dynamics are briefly discussed as well.

Ocean waves play an important role in the dynamics of extreme events like hurricanes or typhoons by conditioning the air/sea fluxes of momentum, heat and moisture. In this study a data set of ENVISAT ASAR Scan SAR images (400 times 400 km coverage) are used to observe the structure of tropical cyclones and typhoons at the sea surface. The following features of hurricanes were determined: wavelength and direction of boundary layer rolls for information of mixed boundary layer depth, radius of maximum wind speed, sea state in terms of wavelength, and direction. These image parameters are related to parametric models of hurricanes and validated by aircraft measurements from the National Hurricane Center (NHC). The work aims at the improvement of prediction of the cyclone track, intensity and sea state at these high wind speed conditions. The paper focuses on two illustrative case studies from August 2005, e.g., images of Hurricane Katrina acquired over the Gulf of Mexico and of Typhoon Talim acquired over the NW Pacific.

Spacebore Synthetic Aperture radar (SAR) is still the only instrument providing continuous two-dimensional (2-D) ocean wave measurements on a global basis. For more than a decade the European satellites ERS-1 and ERS-2 have acquired SAR data over the open ocean operating in wave mode. The ERS acquisitions are currently continued by the ENVISAT ASAR wave mode. It is well known that the derivation of ocean wave parameters from SAR data is not straightforward and different approaches have been proposed. It this study we present a new technique, which is based on an empirical SAR imaging model. The method has the calibrated SAR image as the only input. A data set of 6000 globally distributed ERS-2 wave mode image spectra and collocated ocean wave spectra computed with the numerical model WAM are used to fit a linear model, which relates the SAR spectrum to integral wave parameters like, e.g., the significant wave height. This model is then used for ocean wave parameter retrieval. The radar cross section and the azimuthal cut-off wavelength estimated from the wave mode images are used as additional input variables. The method takes into account the coupling of the different parameters and is based on a least-square minimisation approach. The resulting coupled linear system of equations is solved using a singular value decomposition technique. Disjunct subsets of the collocated data set are used for fitting the model and retrieving ocean wave parameters. Scatterplots and global maps with the derived parameters are presented. It is shown that the standard deviation of the retrieved significant waveheight with respect to the WAM waveheight is in the order of 0.62 m. Other wave parameters, which are of practical relevance like mean wave periods are investigated as well.

It is well known that along track interferometric SAR systems (ATI) are able to provide information on ocean surface currents. For example interferograms acquired during the Shuttle radar topography mission (SRTM) were used at DLR to measure currents in the river Elbe. The ocean current information is important for many practical applications like, e.g., monitoring of sediment transport in coastal areas, optimal siting of current turbines, or forecast of oil slick drift. It has been shown that the TerraSAR-X split antenna mode can be expected to provide current information comparable to SRTM data, i.e., the ocean current component in the antenna look direction on a kilometre scale. This is already valuable information and complements the traditional in situ current measurements very well. However, there is still demand for two-dimensional (2- D) ocean current vectors to get a more complete picture of the 2-D spatial structure of the current field in particular in areas with strong spatial dynamics of the current direction. The presentation will give an overview of a proposal to carry out an experiment in the framework of the Tandem-X mission with the objective to retrieve additional 2-D information on currents and ocean waves. The idea is to operate both SAR instruments in split antenna mode with large squints of one or both satellites. Using this flight configuration it is expected that it will be possible to gain information on 2-D ocean current vectors. Due to the lack of suitable instruments this technique has never been applied using spaceborne platforms before. First experiments with airborne systems demonstrating the potential of the approach have been conducted. Apart from new current field information the proposed configuration enables the derivation of 2-D information on near surface wind fields applying the standard scatterometer approach. Furthermore it is expected that the approach will provide new information on the so called modulation transfer function (MTF) for ocean waves, which is one of the key factors in SAR ocean wave spectra retrieval schemes. The presentation will give a summary of the main technical issues including simulation studies showing the impact of different key parameters, e.g., the squint angle. The potential as well as limitations of the approach will be discussed.

Due to the relatively small amount of in situ data available for the open oceans, particularly during extreme events, under such conditions remote sensing techniques take an important role in the retrieval of geophysical information. Up to now the only remote sensing system capable of providing information on two dimensional sea state on a global and continuous scale and under all weather conditions is the Synthetic Aperture Radar (SAR). In the scope of the project Wave Atlas, ESA provided a two years wave-mode dataset of ERS-2 SAR raw data, mainly collected during 1999 and 2000, which was reprocessed to single-look- complex imagettes at DLR using the BSAR processor. In this study the data were used for a statistical evaluation resulting in global ocean maps of different basic image parameters and oceanic parameters like wind speed, significant wave height, mean period and their respective regional and temporal variability during the seasons of the year using the empirical algorithms CWIND1.0 and CWAVE1.0. Global statistics are given for the time frame of 1998 to 2000 and examples of severe storms are analysed in detail. In future, the reprocessing of wavemode data is planned to be extended to the full lifetime of ERS-1 and ERS-2, which is at least 1991-2006. As wave mode data are also available from the ENVISAT mission, there is the possibility for future expansion.

For more than one decade, the scientific developments carried out with spaceborne synthetic aperture radar (SAR) have demonstrated that SAR is a reliable remote sensing technique to analyze wave fields on the open ocean. In their so-called image mode, these SAR systems, such the Advanced SAR (ASAR) ENVISAT, are able to scan ocean areas of 100 x 100 km 2 and more with spatial resolutions about 20 x 20 m 2 . Those SAR images are able to provide information about the spatial variability of 2D wave fields. This work investigates the potential of ENVISAT ASAR capability to scan the ocean surface with dual polarizations. The relevance of these investigations for different practical applications concerning the analysis of ocean waves is discussed.

Wind farming has grown rapidly in Europe over the last decade. All European countries with shallow coastal waters and strong mean coastal wind speeds are planning or already constructing offshore wind farms. Large parts of the North Sea and Baltic Sea are being investigated to see whether they are suitable for offshore wind parks. In this study we show how satellite images taken by space-borne radar sensors can be used to determine mesoscale wind fields and thus help in the task of planning offshore wind farms. High-resolution synthetic aperture radar (SAR) images acquired by the European remote sensing satellite ERS-2 showing single wind turbines are investigated. The methods for retrieving high-resolution wind fields from SAR images are explained and statistical comparisons of wind speed and wind direction at the two offshore wind park sites in the North Sea, Horns Rev and Butendiek, are given.

[1] A parametric inversion scheme for the retrieval of two-dimensional (2-D) ocean wave spectra from look cross spectra acquired by spaceborne synthetic aperture radar (SAR) is presented. The scheme uses SAR observations to adjust numerical wave model spectra. The Partition Rescaling and Shift Algorithm (PARSA) is based on a maximum a posteriori approach in which an optimal estimate of a 2-D wave spectrum is calculated given a measured SAR look cross spectrum (SLCS) and additional prior knowledge. The method is based on explicit models for measurement errors as well as on uncertainties in the SAR imaging model and the model wave spectra used as prior information. Parameters of the SAR imaging model are estimated as part of the retrieval. Uncertainties in the prior wave spectrum are expressed in terms of transformation variables, which are defined for each wave system in the spectrum, describing rotations and rescaling of wave numbers and energy as well as changes of directional spreading. Technically, the PARSA wave spectra retrieval is based on the minimization of a cost function. A Levenberg-Marquardt method is used to find a numerical solution. The scheme is tested using both simulated SLCS and ERS-2 SAR data. It is demonstrated that the algorithm makes use of the phase information contained in SLCS, which is of particular importance for multimodal sea states. Statistics are presented for a global data set of 11,000 ERS-2 SAR wave mode SLCS acquired in southern winter 1996.

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.

Spaceborne synthetic aperture radar (SAR) is still the only instrument providing directional ocean wave information on a global and continuous basis. Operating in ASAR wave mode, ENVISAT provides imagettes every 100 km along the orbit. These SAR data continue and expand the era of the two European Remote Sensing satellites ERS-1 and ERS-2. Algorithms for ENVISAT ASAR wave mode data are developed using a reprocessed dataset of ERS-2 SAR imagettes. The focus of this study is the generation of global maps giving an overview of the wave systems contained in SAR wave mode cross spectra. In this approach no prior information is used, i.e. the analysis concentrates on swell systems and long wind seas, present in strong wind cases of tropical cyclones, which are detected by the SAR. In order to analyze wind sea and swell systems separately, a new classification method based on the calibrated normalized radar cross section (NRCS) provided by the imagette data is presented. The method is based on known relationships between wind speed, NRCS, and wind sea wavelength (CMOD4 algorithm).

So far mainly one dimensional wave measurements (e.g. buoy time series) have been collected and analyzed. Using new measurement techniques, like Synthetic Aperture Radar (SAR) based ones (e.g. using ERS-1/2 and ENVISAT SAR Imagettes), it is now possible to retrieve two dimensional sea surface elevations. New analysis techniques have been found to examine these data. As in time series wave crests and troughs follow each other simply as alternating maximum and minimum points, in two dimensions the situation is more complicated. A so-called 'Spider' algorithm has been developed creating an assignment of corresponding crest and trough points on a two dimensional sea surface. This allows examination of individual wave parameters like individual wave height or steepness to be compared with global and statistical ones on the surface itself, like significant wave height and sea surface gradient. In addition, grouping parameters can be generalized in the spatial domain. Image analysis also allows parameters not available in one dimension like the crest/trough lengths. For statistical examinations, these parameters have been calculated on some 34,000 SAR imagettes, globally distributed in a 3 week period in the southern winter.

An algorithm is introduced, which is designed to retrieve high-resolution wind fields from C-band synthetic aperture radars (SAR) operating at both vertical and horizontal polarization. The wind directions are extracted from wind-induced streaks, which are approximately in line with the mean wind direction near to the ocean surface. The 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 retrieved from the image. Therefore the semi empirical C-band model CMOD4, which describes the dependency of the NRCS on wind and image geometry, is used. The CMOD4 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 for horizontal polarization, which is performed by considering the polarization ratio. To verify the algorithm, wind fields were computed from the European satellites ERS-1/2 and ENVISAT SAR as well as the Canadian satellite RADARSAT-1 and compared to results from numerical models and a scatterometer.

From raw ERS wavemode data, complex SAR images of size 5 km x 10 km - so called imagettes - are computed using DLR's BSAR processor. Being collected over oceans every 200 km along the orbit, imagettes provide a patchy daily global coverage of the world's oceans. This paper presents DLR's processing chain and results for a three week testing period covering the detection of ocean slicks and sea ice, the use of cross spectra to derive wave spectra over open ocean, the detection of one or several ocean wave systems together with its wave length and its propagation direction, and the estimation of single wave heights. In sea ice covered areas, statistical parameters derived from the SAR are well correlated to physical measures such as the ice deformation energy and ridge frequency. Over ice free areas, comparisons between the SAR results and the ECMWF analysis as well as model results show good agreement in most cases. Observed deviations between SAR measurements and model results are discussed. As a new application of wave mode data statistics are presented on the occurence of extreme waves. As soon as ESA will make available the daily global raw wavemode data for the whole lifetime of ERS-1 and ERS-2, it will be possible to DLR to derive unique statistics on sea ice and wave parameters for a period of at least 10 years, which may be even extended by the use of ENVISAT data in future. Together with near surface wind fields which are also derivable from the imagettes, this work will be of extreme use for climate research applications.

[1] In recent years a number of remote sensing techniques capable to provide two-dimensional information of the sea surface have been applied to describe sea states. This information is obtained from the estimation of the directional wave number spectrum. However, the wave number spectrum is not sufficient for a complete description of sea states. The analysis of some phenomena such as wave grouping, detection of individual waves, maximum wave heights, etc., needs a complementary study, which has been carried out historically in the temporal domain from buoy records. In two dimensions (e.g., the spatial domain), the complementary analysis of those phenomena can be carried out in the spatial domain rather than the temporal domain. In this work, two methods to analyze wave groupiness in the spatial domain from sea surface images are presented: The first method is based on the two-dimensional generalization of the Smoothed Instantaneous Wave Energy History (SIWEH) function, which had been originally developed to analyze wave groupiness for wave elevation time series. The second method uses the estimation of the wave envelope in two dimensions to extract wave grouping parameters. Assuming that the wave fields are Gaussian stochastic processes, both methods are applied to ERS-2 synthetic aperture radar (SAR) and ENVISAT advanced SAR (ASAR) images of the sea surface, where only cases with almost range traveling waves are considered in order to avoid strong nonlinearities in the SAR imaging mechanisms. The obtained results shown that spaceborne SAR can be used to extract wave grouping information on global scale.

Since 1991, the ERS satellites have collected high resolution SAR data over the oceans on a global and continuous basis. Operating in wave mode the ERS SAR yields a patchy coverage of the oceans with about 1500 images of 10 by 5 km size each day. These data have recently been shown to be able to deliver wind speed and wave spectra as well as information on individual waves. In the scope of the ESA AO WaveAtlas, the ERS-2 raw data acquired in 1999 and 2000 are reprocessed to single look complex imagettes. This paper describes the necessary steps for the reprocessing of historic wave mode data including an assessment of the effort required to reprocess all available ERS wave mode raw data archived at ESA. Furthermore the paper demonstrates the potential of these data for different oceanographic applications. Special emphasize is put on wind, wave and sea ice measurements. In addition atmospheric features can be analyzed. The data in particular enable the estimation of two-dimensional sea surface elevation fields which are of high practical relevance for ship design or offshore operations. Mean wave parameters like the mean period derived from SAR wave mode data can be used for the assimilation of numerical wave models thus helping to improve wave forecast. Global maps of mean and individual wave parameters are presented. The reprocessing of wave mode data is planned to be extended to the full lifetime of ERS-1 and ERS-2, which is at least 1991-2004. This allows the derivation of wave climatologies on a decadal basis in particular enabling the analysis of climate trends. As wave mode data are also available from the ENVISAT mission a consistent update of these climatologies is possible

Spaceborne Synthetic Aperture Radar (SAR) is able to provide sea state information on a global scale by means of the directional wave spectrum. Recent developed algorithms have been developed to obtain additional information in the spatial domain rather than the spectral domain. These methods permit to detect of individual wave heights, wave groupiness in open sea areas, as well as surface wind fields. This work shows the capabilities of spaceborne SAR to extract offshore information about individual waves and wave grouping for areas of about 100 × 100 square kilometers. The methods are applied to ERS-2 SAR images of the North Sea over areas close to the location of some oil platforms. Results obtained in the vicinity of the Ekofisk platform are shown. In addition, ERS-2 SAR images taken on January 1, 1995 over the Draupner platform in the North Sea are analyzed. These SAR images were taken at the approximate time when the wave record known as “new year wave” was measured.Copyright © 2004 by ASME

One of the major goals of the European Remote Sensing Satellites ERS-1 and ERS-2 were applications in ocean wave research and wave forecasting. For the first time, two-dimensional spectral information on the sea state globally, continuously, and in quasi real time are provided in the so-called SAR wave mode. To use not only the spectral but also the image information of these data, a global set of single look complex (SLC) synthetic aperture radar (SAR) images (imagettes) was processed from ERS-2 wave mode raw data, using the BSAR processor developed at DLR. SAR imagettes are used to analyze recently developed algorithms for wind and wave measurements. As the new European Satellite ENVISAT will provide cross spectra on a global and continuous basis, interest in the described techniques is growing. Two-dimensional ocean wave spectra are derived from SAR imagettes by quasi-linear inversion of the SAR imaging mechanism. Individual wave systems are detected by a so-called partitioning algorithm. The resulting wave parameters are analyzed and compared to model data. To take into account the complete nonlinear SAR imaging mechanisms, wave model spectra are simulated forward into cross spectra and compared to observations. Using this approach cases of significant inconsistencies between SAR and model data can be detected. With our 3 week data base in 1996 (about 30,000 imagettes) statistics are calculated. Finally, we derive daily maps showing areas with significant deviations between simulated and observed cross spectra.

A parametric inversion scheme for the retrieval of two dimensional ocean wave spectra from look cross spectra (LCS) acquired by spaceborne synthetic aperture radar (SAR) is presented. The scheme takes information about the spectral shape of different wave systems from a prior wave spectrum, while estimates for wavelength, waveheight and wave propagation direction are extracted from SAR cross spectra. The Partition Rescaling and Shift Algorithm (PARSA) is based on a partioning of a prior wave spectrum, e.g. taken from ocean wave models. For each ocean wave system a stochastic model is set up, which defines the probability that the propagation direction, the wavelength or the energy of the different wave systems deviate from the prior knowledge. The prescribed probabilities thereby quantify the confidence into the prior wave spectrum. Based on the probability models for the prior wave spectrum and the measured cross spectrum an optimal ocean wave spectrum is estimated using a maximum a posteriori approach. To solve the corresponding minimization problem the prior model is approximated with a multivariate Gaussian model. The optimization problem is solved with a Gauss-Newton method. The scheme is tested using both simulated cross spectra and reprocessed wave mode data acquired by the ERS-2 SAR. The reprocessed data are similar to the products, which will be available from the ENVISAT satellite launched in March 2002.

Within the last years a considerable number of large ships have been lost due to severe sea state conditions. The cause of accidents are in many cases believed to be rogue waves, which are individual waves of exceptional wave height or abnormal shape. In particular steep breaking waves can be fatal for smaller ships. Damage is sometimes can also be caused by unusual grouping of waves, which can lead to dangerous ship motion. In situ measurements of extreme waves are sparse with most observations reported by ship masters after the encounter. In this paper a global data set of 5 /spl times/ 10 km sized synthetic aperture radar (SAR) images acquired by the European Remote Sensing satellite ERS-2 every 200 km along the track is used to analyse extreme ocean wave events. As the European Space Agency (ESA) does not provide this dataset as a standard product wave mode raw data were reprocessed to complex SAR images using the processor BSAR developed at the German Aerospace Center (DLR). About 1000 globally distributed SAR wave mode images are available every day. Two dimensional ocean wave fields are derived from SAR images by inversion of the SAR imaging mechanism. Individual high waves are detected in the derived wave fields using a matched filter technique. The inhomogeneity of ocean wave fields is analysed using a parameter, which describes the shift invariance of the wave spectrum.

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.

From raw ERS wavemode data, complex SAR images of size 5 km /spl times/ 10 km - so called imagettes - were computed using the BSAR processor at the German Aerospace Center (DLR). Being collected every 200 km along the orbit, imagettes provide a relatively dense coverage especially over polar oceans up to 84 degrees North. Several statistical measures have been introduced for analysis of imagettes classifying ice free and ice contaminated imagettes as well as deriving sea ice parameters such as ice concentration, deformation energy, and ridge frequency. The results are compared to SSM/I data and sea ice model results. In addition, a wavelet-based edge detector is used to examine the ice surface structure. Using the imagettes in an automatic extraction system can provide global statistics of sea state and sea ice parameters from both upcoming ENVISAT and historic ERS data providing a 10 year dataset.

A noise model for synthetic aperture radar (SAR) look cross spectra (LCS) acquired over the ocean is proposed. The study is meant to contribute to the improvement of algorithms for retrieval of two dimensional ocean wave spectra from LCS. Error bars for the LCS phase, which contains information on the ocean wave phase speed and propagation direction are derived. The error estimates depend on the respective LCS coherence and the amount of smoothing applied in the LCS estimation process. A model for the LCS coherence is introduced. The first part of the model describes the dependence of the coherence on system parameters like spatial resolution. The second part is associated with the motion of the imaged ocean wave field. Decorrelation is shown to be caused by the coupling of dispersive ocean wave components in the SAR image formation process. Forward simulations for the cross spectrum coherence are carried out using parameterized swell and wind sea spectra. Coherence is estimated from a global data set of reprocessed ERS-2 wave mode data and compared to theory.

Since launch of the ERS-2 Satellite in 1995, more than 40 SAR images of the intertidal areas of the River Elbe estuary have been received at Neustrelitz antenna station and processed at DFD in near real time. This area is morphodynamical very active, i.e. the bottom topography underlies a continuous change due to sediment transport, with strong impact on the main waterways of the Elbe. To investigate these morphodynamics, the ERS-2 SAR images are very useful, because of their all weather, day and night capability and because the land-water boundary-the shoreline-can be extracted using edge detection methods. The detected shorelines are transformed into isolines of bottom topography by combining them with available tide gauge information. Due to the speckle noise of the SAR image, edge detection from SAR is a demanding task. In this paper a new approach is used combining wavelet methods and active contour models. In a first step this approach takes advantage of Mallats (1992) wavelet algorithm acting as a full resolution noise filter and edge detector. The Mallat algorithm leads to a first guess full resolution land water segmentation. Based on this segmentation an active contour model starting from the wafer side is used as a second step, similar to the approach used by Mason and Davenport (1996). After the active contour model has mapped a connected shoreline, the derived line is combined with height, information from tide gauges and compared to bottom topography provided by the German Federal Waterway Engineering and Research Institute (BAW) to show changes due to morphodynamics.

The synthetic aperture radar (SAR) aboard the European remote sensing satellite ERS-2 acquires so called imagettes when operating in wave mode. These are high resolution 10 km x 6 km SAR images taken every 200 km along the orbit over the ocean. These data are operationally processed by the European Space Agency (ESA) to image power spectra (SWA.UWA). In this study the data are processed using the SAR research processor (BSAR) of the German Aerospace Center (DLR) to uncalibrated single look complex (SLC) imagettes. SLC imagettes give the opportunity to derive two looks separated in time by approximately half a second. Using these multilook techniques, newly developed algorithms are applied to derive directional wave spectra, ice parameters, and wind speed with global coverage. The results are compared to buoy measurements, results of the wave model WAM, and the Hasselmann algorithm for SAR wave spectra retrieval. Furthermore the SLC imagettes allow one to study surface features on a global scale ,e.g., statistical distribution of natural slicks, that can effect SAR and scatterometer (SCAT) derived parameters, especially wind. Complex imagettes will be available for the advanced SAR aboard the European satellite ENVISAT and therefore these investigations are an ideal preparation for the planned operational use of ENVISAT imagettes at meteorological centers.

The high resolution together with the large coverage of satellite based synthetic aperture radars (SAR) offer an unique opportunity to derive mesoscale wind fields over the ocean surface. In this paper different methods for deriving wind fields from SAR data are introduced and compared to each other. Wind directions are extracted from wind induced streaks visible in most SAR images. Wind speeds are computed with C-band models for both VV- and HH-polarization from the calibrated normalized radar cross section (NRCS). Another method is based on sea surface movements due to the local wind which allows the width of the peak of the autocorrelation function (ACF) to be a measure of wind speed. The algorithms are applied to ScanSAR wide swath images acquired by RADARSAT and to SAR images from the European remote sensing satellites (ERS-1 and ERS-2). Comparisons to in situ measurements and results of an atmospheric model emphasize the benefits of each method. Sources of errors in wind retrieval are discussed for different algorithms. Errors in wind speed due to speckle, uncertainty in wind direction, and accuracy of NRCS are estimated for different wind speeds, wind directions and polarization. ERS SAR derived ocean surface winds are applied to investigate the spatial variation of the wind on different scales resulting in a decrease of spectral density according to the power law k/sup 5/3/ predicted by two dimensional isotropic turbulence.

New techniques have been developed to study single wave events and wave groupiness from space borne SAR images of the sea surface. These techniques are based on the determination of wave groupiness features from the local wave envelope, estimated by using a two dimensional Hilbert transform, and the analysis of the local variability of the wave height within SAR images. This analysis is carried out on a global scale by using 34,310 SAR images, taken by the European satellite ERS-2. The obtained results are used to generate global maps of maximum wave heights, and other parameters of describing wave events, which are able to inform about potentially dangerous situations for navigation and offshore structures.Copyright © 2003 by ASME

Recent techniques to derive sea state parameters in the spatial domain from radar images of the sea surface have been derived. This work describes these techniques in order to derive wave elevation maps from space borne SAR and nautical radar images of the sea surface. These wave elevation maps permits to extract additional sea state information in the spatial domain derived from the statistical analysis of the wave elevation, as well as wave height, spatial distribution.

In all European countries with shallow coastal waters and strong mean wind speed at the coast the planning and construction of offshore wind farms is on the way and large parts of the North Sea and the Baltic are under investigation as to whether they are suitable for offshore parks. In this paper it is demonstrated how satellite images taken by spaceborne radar sensors can be used to determine mesoscale wind fields and thus help in the task of planning offshore wind farms. High resolution SAR images acquired by the European remote sensing satellite ERS 2 are presented which show single wind turbines (Fig. 1). The derivation of high resolution wind fields from SAR images is explained and comparisons with numerical models are presented.Copyright © 2003 by ASME

All European countries with shallow coastal waters and strong mean wind speed at the coast have begun planning and construction of offshore wind farms, and large parts of the North Sea and the Baltic are under investigation as to whether they are suitable for offshore parks. This paper demonstrates how satellite images taken by spaceborne radar sensors can be used to determine mesoscale wind fields and thus help in the task of planning offshore wind farms. High resolution SAR (Synthetic Aperture Radar) images acquired by the European remote sensing satellite ERS-2 are presented which show single wind turbines. The derivation of high resolution wind fields from SAR images is explained and comparisons with numerical models are presented.

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.

In the above titled paper (ibid., vol. 52, no. 5, pp. 2928-2939, May 2014), there is a typo in equation (A3) in the Appendix. The correct equation is presented here.

Within the framework of the current cooperation between the Federal Waterway Engineering and Research Institute (BAW) and the German Aerospace Center (DLR) in the Project TIDE, a possible improvement of the boundary conditions of the hydrodynamic tide model TRIM-2D in the Elbe estuary using satellite data is investigated. The model currently uses a bottom topography boundary condition determined by conventional vessel mounted echo sounder measurements, which is difficult and expensive to update. With the aid of Synthetic Aperture Radar (SAR) data of the European Remote Sensing Satellites (ERS-1/2) it can be shown that this intertidal Elbe estuary region underlies a continual change. This is essential for the model performance and has to be taken into account. The major goal of the TIDE project is the operational extraction of shorelines from the SAR data. The shorelines are transformed to isolines of bottom topography which then can be used as model boundary. The transformation is done either by combining the SAR data with conventional tide gauges or with satellite based ERS-2 altimeter data. To derive topography by satellite is much cheaper and less time consuming than conventional methods, but ifs accuracy has still to be validated against them.

The paper is a short summary on measurements of directional wave spectra during the Shuttle Radar Topography Mission (SRTM) in Feb. 2000 and mainly demonstrates the possibility to retrieve information on significant wave height and direction of ocean waves. Further information will be available after the data are phase calibrated and delivered to users.

An algorithm is presented for retrieving high resolution wind fields from the scanning synthetic aperture radar (ScanSAR) data acquired aboard the Canadian satellite RADARSAT-1. The wind directions are extracted from wind induced streaks, e.g. from boundary layer rolls, Langmuir cells, or wind shadowing, which are approximately in line with the mean wind direction. The wind speeds are derived from the normalized radar cross section (NRCS) and image geometry of the calibrated ScanSAR images, together with the local wind direction. Therefore the semi-empirical C-band model CMOD4, which describes the dependency of the NRCS on wind and image geometry, is inverted. CMOD4 was originally developed for the scatterometer operating at C-band with vertical polarization and has to be modified for horizontal polarization, which is performed by considering the polarization ratio according to Kirchhoff scattering. To verify the algorithm, wind fields were computed from several RADARSAT-1 ScanSAR images and compared to collocated results from the Danish high resolution limited area model. To estimate relative errors of wind speed due to uncertainties in wind direction and NRCS, sensitivity studies were performed.

A global set of single look complex (SLC) synthetic aperture radar (SAR) images is processed, from wave mode raw data using the B-SAR processor developed at Deutsches Zentrum fur Luft und Raumfahrt (DLR). Multilook methods are used to reduce speckle or to analyze the time evolution of the ocean surface cross section during SAR Integration time. Using imagettes instead of image power spectra allows to study ocean surface features caused by natural slicks, sea ice or atmospheric processes. Different automatic image analysis methods are used to detect and classify these features. About 200 imagettes are acquired over the Arctic every day, from these data sea ice parameters are derived.

Radar interferometry is known to be a useful technique for mapping terrain heights and surface currents. Several studies on along track or cross track interferometry provided highly accurate results. In the case of coastal applications a simultaneous measurement of topography and surface currents is beneficial. Therefore an approach for airborne interferometric measurements with a baseline consisting of an along and cross track component is presented. Analysis of experimental airborne interferometric data shows good results. The final accuracy is highly dependent on the accuracy of the navigation data of the aircraft.

Coastal regions like the intertidal area of the German Bight are continuously changing their topography due to morphodynamic processes. This fact has serious impact on the German waterways, requiring a huge amount of dragging with costs of about 8/spl times/10/sup 7/ DM per year. To investigate these morphodynamics and to reduce the costs, an up to date digital elevation model (DEM) is needed. The DEM currently used is determined by conventional vessel-mounted echo sounder measurements, which is difficult and expensive to update, especially in very shallow areas that are navigable only during extreme tides. In order to monitor morphodynamic changes and to continuously update the changes in the bottom topography, shoreline information extracted from synthetic aperture radar (SAR) images of the European remote sensing satellites (ERS-1/2) at different tidal levels are interpolated into a DEM. Therefore, the shorelines are extracted with a new developed method using a combination of wavelet and active contours. The corresponding height information is interpolated from tide gauge data. In a final step, from this height information a DEM is generated using a weighted mean interpolation in space and time. For validation purpose, the extracted shorelines and the interpolated DEM are compared to an independent. Generated DEM based on airborne crosstrack interferometric SAR images as well as on ground truth measurements. In total some 100 ERS SAR scenes from 1992 to 2000 are used to identify morphodynamical active areas in the German Bight.

The high spatial resolution and large coverage of satellite-based synthetic aperture radars (SAR) offer an unique opportunity to derive mesoscale wind fields over the ocean surface especially in coastal areas. For this purpose an algorithm was developed and tested using the C-band SAR images from the European remote sensing satellite ERS-2 and from the Canadian satellite RADARSAT-1. Wind speeds are derived from the normalized radar cross sections (NRCS) using a semi empirical model. The model was originally developed for a C-band scatterometer with vertical polarization and therefore has to be modified for horizontal polarization of the RADARSAT-1 SAR. Several C-band polarization ratios were considered including theoretical and empirical forms. To improve and verify the algorithm, wind speeds were computed from several RADARSAT-1 ScanSAR images and compared to results of the Danish high resolution limited area model (HIRLAM). Furthermore the main error sources in SAR wind field extraction are studied with respect to both polarizations.

This paper discusses an algorithm designed to retrieve high-resolution wind fields from scanning synthetic aperture radar (ScanSAR) data acquired on board the Canadian satellite RADARSAT-1. The ScanSAR operates at C-band with horizontal polarization. The wind directions are extracted from wind-induced streaks, e.g., from atmospheric boundary layer rolls or wind shadowing, which are approximately in line with the mean wind direction near the ocean surface. The wind speeds are derived from the normalized radar cross section (NRCS) and image geometry of the calibrated ScanSAR images, together with the local wind direction retrieved from the image. Therefore the semi-empirical C-band model CMOD4, which describes the dependency of the NRCS on wind and image geometry, is used. The CMOD4 was originally developed for the scatterometer of the European remote sensing satellites ERS-l and ERS-2 operating at C-band with vertical polarization. Consequently, the CMOD4 required modification for horizontal polarization, ...

Proceedings of the second international Conference on EuroGOOS, Rome, Italy, 11–13 March 1999; International audience; Surface wind fields over the ocean can be retrieved from synthetic aperture radar (SAR) measurements using empirical models. These models are based on the relation between the measured normalised radar cross section, wind speed and wind direction. In this study the applicability of these models to SAR images in a fetch limited situation is investigated. The mesoscale wind field is retrieved from one ERS-2 SAR image using the empirical C-band model CMOD_IFR2. The image was acquired on April 7, 1998 over the Gulf of Lion in the Mediterranean Sea during the Flux, Etat de la Mer et Télédétection en Condition de Fetch Variable (FETCH) experiment, which was performed to study wind and waves under fetch-limited situations. In addition, wind vectors were derived from an airborne real aperture radar (RAR) using the same empirical model as for the SAR. For comparison of the SAR and RAR retrieved results, in situ measurements were taken from a research vessel and a buoy, which were positioned in the area investigated.

This study presents methods for sea ice analysis which make use of SAR wave mode data products, so-called imagettes, to be provided by the European satellite ENVISAT every 100 km along the track, thus forming a particulary dense coverage of the polar regions. Prior to ENVISAT a reprocessed ERS-2 wave mode data set is used to derive sea ice variables like deformation energy. The results are compared to sea ice model runs and SSM/I data. Furthermore, ENVISAT data are of particular interest for observation of the damping of ocean waves by sea ice as pairs of high resolution images with different polarizations will be available. It is e.g. shown that ENVISAT data allow a better distinction between effects due to ocean wave motion and mechanisms. The basic principles of extracting parameters describing sea ice damping characteristics are demonstrated using ERS-2 SAR data.Copyright © 2002 by ASME

Publisher Summary This chapter describes the different aspects of the complex ERS-2 synthetic aperture radar (SAR) wave mode. Flying over the ocean, the synthetic aperture radar (SAR) aboard the European remote sensing satellite ERS-2 acquires SAR images of 10 km × 6 km size every 200 km along the orbit. Imagettes are operationally processed to image power spectra (SWA.UWA) by the European space agency (ESA). As compared to conventional SAR intensity images used, SLC imagettes are better suited for wind and wave measurements because they contain a lot of additional information on sea surface motion. The multilook techniques are applied to derive directional wave spectra, ice parameters, and wind speed on a global scale. The first method is based on converting grey levels of SAR images into normalized calibrated radar cross-section (NCRS) using the ESA calibration algorithm. Wind speed is derived using the semi empirical CMOD4 algorithm and some additional information on wind direction. The complex imagettes processed with the SAR research processor (BSAR) are an important test data set to develop and validate ENVISAT ocean wave retrieval algorithms, which will be used by different meteorological institutes, such as the European Centre for Medium-Range Weather Forecast.

[1] Damping of ocean waves by sea ice is studied using spaceborne synthetic aperture radar (SAR) images of the marginal ice zone (MIZ) acquired by the European Remote sensing satellite ERS-2. SAR imaging of waves damped by sea ice is analyzed theoretically. The impact of sea ice on the azimuthal cutoff is studied by simulation of the azimuthal SAR image autocorrelation function as well as the two- dimensional SAR image spectrum. Typical imaging artifacts like spiky wave crests and wave refraction seen on SAR scenes of the MIZ are reproduced by simulation. Sensitivity studies are performed using models for wind sea and swell systems. It is shown that the degradation of the azimuthal SAR image resolution is dominated by the orbital velocity variance of the waves, while the coherence time of the complex radar reflectivity has a minor impact. A first-order analysis of wave damping observed on SAR scenes is carried out using a technique that was originally developed for wind estimation by Kerbaol et al. [1998]. The method does not require a priori information and is insensitive to real aperture modulation. The azimuthal SAR image cutoff wavelength is estimated and related to the orbital velocity variance of the sea surface by regression. The model is fitted on the basis of a global set of model ocean wave spectra. The technique is applied within the sea ice and in the open water in front of the ice boundary. On the basis of simple models for wind sea and swell, ocean wave attenuation rates are obtained from the observed orbital velocity decrease of waves entering the ice. The required wind information is derived from calibrated SAR data using the CMOD method. Two case studies showing examples from the Greenland and the Weddell Seas are given. It is shown that the estimated wave damping is consistent with damping parameters found in earlier field campaigns carried out in the Weddell Sea and the Bering Sea. An inversion technique providing estimates for the two-dimensional wave spectra behind and in front of the ice boundary as well as a two-dimensional filter function characterizing the sea ice impact is introduced. The technique is based on simultaneous inversion of the two-dimensional image spectra in the open water and within the ice using a priori information from an ocean wave model. It is shown that the technique gives results consistent with the first-order analysis based on the cutoff estimation.

This paper introduces a recently developed algorithm to retrieve high-resolution wind fields over the ocean surface from spaceborne synthetic aperture radar (SAR) data. The algorithm consists of two parts, the first for determining wind direction and the second for wind speed retrieval. Wind directions are extracted from wind induced streaks e.g. from boundary layer rolls, Langmuir cells, or wind shadowing, which are approximately in line with the mean wind direction. Wind speed is derived from the normalized radar cross section (NRCS) and image geometry of the SAR image, together with the local retrieved wind direction. The application of SAR-wind retrieval in coastal regions is demonstrated using data acquired aboard the European satellites ERS-1 and ERS-2 and the Canadian satellite RADARSAT-1. These data allow to measure wind fields of an area of up to 500 km × 500 km with a resolution of up to 200 m. To improve and validate the set-up of numerical high-resolution models in coastal regions SAR-retrieved wind fields offer an unique opportunity. This is shown by comparisons of wind fields measured by SAR to results of the numerical model REMO, HIRLAM and GESIMA.Copyright © 2002 by ASME

Within the last 20 years at least 200 supercarriers have been lost, due to severe weather conditions. In many cases the cause of accidents is believed to be ‘rouge waves’, which are individual waves of exceptional wave height or abnormal shape. I situ measurements of extreme waves are scarce and most observations are reported by ship masters after the encounter. In this paper a global set of synthetic aperture radar (SAR) images is used to detect extreme ocean wave events. The data were acquired aboard the European remote sensing satellite ERS-2 every 200 km along the track. As the data are not available as a standard product of the Europea Space Agency (ESA), the radar raw data were focused to complex SAR images using the processor BSAR developed by the German Aerospace Center. The entire SAR data set covers 27 days representing 34000 SAR imagettes with a size of 5km×10km. Complex SAR data contain information on ocean wave height, propagation direction and grouping as well as on ocean surface winds. Combining all of this information allows to extract and locate extreme waves from complex SAR images on a global basis. Special algorithms have been developed to retrieve the following parameters from the SAR data: Wind speed and direction, significant wave height, wave direction, wave groups and their individual heights. The satellite ENVISAT launched in March 2002 acquires SAR data with an even higher sampling rate (every 100 km). It is expected that a long-term analysis of ERS and ENVISAT data will give new insight into the physical processes responsible for rogue wave generation. Furthermore, the identification of hot spots will contribute to the optimization of ship routes.