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Spaceborne synthetic aperture radar (SAR) is a powerful tool for monitoring marine environmental parameters of the seas. The ability to work independently of sun illumination, cloud coverage and atmospheric conditions, as well as the capability of delivering spatial information, makes SAR one of the most perceptive instruments. The newest methods for processing SAR data with increased precision allow sea state fields to be estimated with local variabilities. For large areas in oceans where no in-situ measurements and only forecast predictions are available, this information is indispensable for global shipping and over human activity. Due to newest developments, the derived meteo-marine parameters can be transferred to weather services and to a ship’s bridge several minutes after acquisition, where the ship route can be optimized. The study presents a method and application for estimating series of integrated sea state parameters from satellite-borne SAR, allow processing of data from different satellites and modes in near real time (NRT). The developed Sea State Processor (SSP) estimates total significant wave height Hs, dominant and secondary swell and windsea wave heights, first, and second moment wave periods, mean wave period and period of wind sea. The algorithm was applied for the Sentinel-1 (S1) C-band Interferometric Wide Swath Mode (IW), Extra Wide (EW) and Wave Mode (WM) Level-1 (L1) products and also extended to the X-band TerraSAR-X (TSX) StripMap (SM) mode. The scenes are processed in raster and result in continuous sea state fields with the exception of S1 WV. Each 20 km × 20 km WV imagette, acquired every 100 km along the orbit, presents averaged values for each sea state parameter. The SSP was tuned and validated using two independent global wave models WAVEWATCH-3 (NOAA) and CMEMS (Copernicus) and NDBC buoys. The accuracy of Hs reaches an RMSE of 0.25 m by comparison with models (S1 WV); comparisons to NDBC worldwide buoys result into an RMSE of 0.31 m. Due to implemented parallelization, a fine rater step for scene processing can be practical applied: for example, S1 IW scene with coverage of 200 km × 250 km can be processed using raster step of 1 km (corresponds to ~50.000 subscenes) during minutes. The DLR Ground Station “Neustrelitz” applies SSP as part of a near real-time demonstrator service that involves a fully automated daily provision of surface wind and sea state parameters estimates from S1 IW for the North and Baltic Sea. All results and the presented methods are novel and provide a wide field for applications and implementations in prediction systems.

Innovative algorithms for Sentinel-1 (S1) satellite allow daily observations of meteo-marine parameters, tracking of storm propagation, study of local sea state variability and coastal processes. Several minutes after acquisition, the produced data with geo-coded information on wind speed and wave height can be transferred to the weather services for validation of the forecasting models worldwide. The different kind of data like coastline, wave height, surface wind speed, ice coverage, oil spills etc. can be processed in parallel for the same satellite image and combined with other information (e.g. model results, ship traffic) for supporting Maritime Situation Awareness (MSA). The algorithms currently developed for this purpose are integrated into a prototype processor for Sentinel-1 imagery. The DLR Ground Station Neustrelitz applies this prototype as part of a near real-time demonstrator MSA service. The presented scientific service involves daily provision of surface wind and sea state fields estimated fully automatically from S1 Wide Swath Mode (IW) Synthetic Aperture Radar (SAR) images of North and Baltic Sea. S1 IW covers area-strips of thousand kilometres of earth and ocean surface with a resolution of ~10m by sequences of multiple individual IW images with an approximate size of 200km×250km. The NRT processing has been also applied by supporting a research ship cruise in the Antarctic Sea.

From Synthetic Aperture Radar (SAR) imagery various types of maritime information are extractable, including surface winds, waves, oil slicks, waterline changes, changes of seabed morphology in shallow waters, wakes of ships, etc. The algorithms recently developed for this purpose are integrated into a prototype processor for Sentinel-1 (S-1) imagery. The DLR Ground Station Neustrelitz applies this prototype as part of a near real-time demonstrator service for support of Maritime Situation Awareness. The presented scientific service involves daily provision of surface wind and sea state parameters estimated fully automatic from S-1 Interferometric Wide Swath (IW) images for North and Baltic Sea.

Satellite data prove: Not only the extension, but also the thickness of sea ice in the Arctic is shrinking. One of the major side effects of this is that northern sea routes such as the Northeast Passage will be easier to navigate for ships. An increase in shipping traffic in Arctic waters is widely predicted. Nevertheless, navigation in ice-infested waters is and remains difficult because sea ice is constantly changing. Within hours, winds and ocean currents can shove floating sea ice floes together and close areas of open water. Even more: If the pressure process continues, ice floes are piled over and under each other, forming a thick, uneven sea ice cover which is difficult or impossible to pass even for icebreakers. Spaceborne Synthetic Aperture Radar (SAR) images reveal the condition of oceans and frozen waters - due to their active radar antenna in all weathers, though clouds and darkness. National Ice Services use SAR to generate ice maps, which are taken into account when planning the route of polar operating ships. However, the actuality and resolution of these maps is limited. In several polar expeditions, we acquired high-resolution SAR images from the satellite mission TerraSAR-X/TanDEM-X over the planned course, and provided those to navigators on board the ship in near real-time. It has been shown that these "exclusive" acquisitions help to avoid dangerous situations, but also to avoid unnecessary detours. SAR, however, can do more. The satellite data contains information that cannot be visually extracted from a single acquisition, e.g. information about the local sea ice drift. Here, we present a new processor that is designed to derive high resolution sea ice drift fields along with information on local ice coverage from TerraSAR-X/TanDEM-X images with a resolution ranging from 3 m to 17 m. The extraction of sea ice coverage is based on texture analysis. The core of the subsequent sea ice drift estimation is the well-known phase correlation technique, executed within a hierarchical motion estimation framework. The output is a vector field indicating the sea ice motion. It shows converging and diverging ice sheets, and sheering zones. The vector field, delivered on board the ship in near real-time, will further improve navigation in ice-infested waters. The presented processor is intended to be part of the operational data processing chain at DLR Ground Station Network sites.

The automatic processing of bathymetry in shelf oceans as well as the creation of topography for tidal flat areas from Sentinel-1 Synthetic Aperture Radar (SAR) satellite data was developed. SAR bathymetry processing is applicable in oceans with water depths of about 10 m to 100 m. This is a crucial depth range for many offshore construction areas like wind parks. The high costs of bathymetry generation with conventional ship surveys are a major reason for the lack of accurate bathymetry data worldwide. Using radar satellites like Sentinel-1 and automated algorithms, the effort of generating bathymetry data on suitable coasts worldwide is strongly reduced. The algorithm tracks changes of the lengths of long swell waves interacting with the seafloor, shortening the wave length due to the shoaling effect when waves reach shallower waters. In tidal flat areas like the Wadden Sea at the Danish, German and Dutch North Sea coast, the morphodynamics of seabed structures are significant; the soft seabed can change within days during severe storms. Data from past measurement campaigns, which are very expensive using ship soundings and airborne LIDAR scanning, deprecates quickly as the positions of islands, sandbanks or tidal inlets change. We have developed automated algorithms to retrieve the waterline from SAR images. In the tidal flat areas of the Wadden Sea, analyzing time series of acquisitions at similar tidal states allows estimating rates of change and sediment transport; a combination of several images acquired within a short time frame at different tidal states allows estimating the topography. Acquisitions from the Sentinel-1 (S1) Synthetic Aperture Radar (SAR) satellites cover most coasts worldwide. With two satellites currently in orbit, the acquisition interval is at most 6 days at the equator and almost daily in our latitudes. The Interferometric Wide Swath (IW) mode covers lands and coastal oceans with a swath width of 250km and an image resolution of 10m. In contrast to optical satellites, SAR acquisitions are independent of illumination and cloud cover; hence, they deliver new images very reliably. The DLR satellite ground station in Neustrelitz receives these data and processes and delivers the value-added products in Near Real Time (NRT), usually within 20 minutes after acquisition.

Synthetic Aperture Radar (SAR) data from the Sentinel-1 A/B satellites are used to monitor tidal flats in the Elbe River estuary in the German Bight. While the Elbe fairway is frequently sounded, the surrounding tidal flats are only surveyed every 6 years using airborne laser scanning. However, the high rate of erosion and sedimentation causes major changes in the topography like opening of new channels in much shorter timescales. A more frequent monitoring is necessary to ensure the safety of ships and also to be able to determine the effects of new underwater constructions and dredging for the planned deepening of the Elbe River. While Earth Observation satellites frequently acquire images of the Wadden Sea area, only those acquired at low tide can be used to identify changes in tidal flats, since these are underwater during high tide. With Sentinel-1 A/B offering a 6-day repeat frequency and almost daily coverage in the German Bight, a low tide situation is captured approximately every two weeks, which is a sufficiently small interval for monitoring this area. As additional benefit, Sentinel-1 data are offered free of charge. An automatic waterline detection algorithm was developed to delineate the land-water-line for an individual SAR image. It uses contrast-based edge detection and iterative thresholding for identification of edge pixels, yielding edges that match the visually identified edge. Automatic error corrections are applied to filter out smaller ships and buoys; however, some errors need to be corrected manually. The pixel spacing in Sentinel-1 Interferometric Wide swath (IW) images usually acquired over the German Bight is 10 m, allowing for a 1 px offset this results in an accuracy of 20 m for the automatically derived waterlines. While this is lower than the resolution of an airborne laser scanning survey, the satellite data is available much more frequently and created with low effort for large areas. Its resolution and accuracy are sufficient to identify areas of major change in the tidal flats which is very helpful for local authorities.

A close inspection of the Sentinel-1 (S-1) Interferometric Wide Swath (IW) mode data over the ocean reveals antenna beam patterns remaining in the calibrated and noise-corrected data, resulting in discontinuous wind speed values across the beam boundaries. We present an analysis of the impact of this effect on estimated wind fields based on more than 8000 Sentinel acquisitions with level-2 OCN data available and compare to high resolution ECMWF model data. We propose a correction scheme to minimize the beam pattern impact. The method can be applied to both, level-2 OCN da-ta products and level-1 original IW image data.

Wind information retrieval over the sea surface from microwave sensor data has a long and successful history. The accuracy of geophysical model functions (GMFs) applied to relate the microwave backscatter to wind speed and direction in 10m height has been continuously improved from early scatterometer missions to contemporary spaceborne SAR sensors like the current Sentinel-1 (S-1) pair. The statistical accuracy of SAR-based wind speeds is nowadays better than 2m/s (e.g. [1], [2], [3]) and therefore the data is appreciated by met-ocean modellers to validate and improve their models. State of the art high resolution SAR systems can provide wind fields with a resolution of less than 100 m which have been successfully validated against co-located LiDAR data [4]. SAR-based data is particularly interesting for the offshore wind industry as it combines a resolution near to LiDAR capabilities and a large cross-track coverage of up to 250km for e.g. the two S-1 satellites. The S-1 systems work in TOPS SAR imaging mode, which has been designed to reduce the scalloping effect in burst mode SAR imaging, e.g. ScanSAR. The large spatial coverage of these systems allows wind park operators to get regular snapshots of entire marine regions such as the German Bight and cross-validate model data especially with focus on the impact of wind shadows of adjacent turbine clusters. A close inspection of the Sentinel-1 Interferometric Wide Swath (IW) mode data over the ocean reveals antenna beam patterns remaining in the calibrated and noise-corrected data, resulting in discontinuous wind speed values across the beam boundaries. While of minor importance when calculating coarse wind fields of several kilometres resolution, high resolution wind fields as desired by offshore wind operators suffer from this uncertainty. A compensation for these errors contained in S-1 IW wind fields is believed to further increase the acceptance of SAR-bases wind data in both, industrial users of the data and the Numerical Weather Prediction (NWP) community for assimilation in met-ocean models. We present an analysis of the impact of this effect on estimated wind fields based on more than 8000 Sentinel acquisitions with level-2 OCN data available and compare to high resolution ECMWF model data. We propose a correction scheme to minimize the beam pattern impact. The method can be applied to both, level-2 OCN data products and level-1 original IW image data.

Innovative algorithms for Sentinel-1 (S1) satellite allow daily observations of meteo-marine parameters, tracking of storm propagation, study of local sea state variability and coastal processes. In order to investigate geophysical processes, the sea state and wind fields estimated simultaneously from S1 scenes acquired twice daily are combined with numerical forecast model results and in-situ measurements. The focus of the investigations are the evolution and propagation of storm peaks/centres, storm front movement, and arrival of swell. An example of efficient storm tracking in the Black Sea in April 2017 over three days is analysed. The HZG forecast spectral wave model running for the Black Sea reproduces the storm peak propagation near to the S1 observations. In detail, the storm peak observed by S1 is shifted ~80km towards the south in comparison to the model simulations. During this storm, the ship “Geroi Arsenala” of river-sea class licensed for inland waterways with access to the coastal seas was capsized about 40 kilometres to the south of the Kerch Strait in the open Black Sea, according to the associated press. The cargo ship was carrying grain from Russia to Turkey. Obviously, the course was taken too far from the coast to shorten the way across the sea with unexpected high sea state. Only one of the 12 people aboard was rescued. This is a tragic incident that proves the importance of Maritime Safety and Security. With the Sentinel satellites and the processing framework demonstrated in this work, we have appropriate tools to raise Maritime Situation Awareness (MSA) to unprecedented levels, which helps avoiding such accidents. The rapid development of satellite techniques, information extraction algorithms and ground infrastructures during the last years enabled a series of oceanographic applications with near-real-time (NRT) capabilities. Several minutes after acquisition, the produced data with geo-coded information on wind speed and wave height can be transferred to the weather services for validation of the forecasting models. The different kind of data like coastline, wave height, surface wind speed, ice coverage, oil spills etc. can be processed in parallel for the same image and combined with other information (e.g. model results, ship traffic) for supporting MSA. The algorithms currently developed for this purpose are integrated into a prototype processor for Sentinel-1 imagery. The DLR Ground Station Neustrelitz applies this prototype as part of a near real-time demonstrator MSA service. The presented scientific service involves daily provision of surface wind and sea state parameters estimated fully automatically from S1 Wide Swath Mode (IW) Synthetic Aperture Radar (SAR) images of North and Baltic Sea. S1 IW covers area-strips of thousand kilometres of earth and ocean surface with a resolution of ~10m by sequences of multiple individual IW images with an approximate size of 200km×250km. The data are free to use and provide unprecedented observation possibilities of ocean processes and natural phenomena worldwide at a high repetition rate. Due to the independence of sunlight and cloud coverage, SAR data are an indispensable source of 2D information of the ocean surface for open sea and for coastal applications.

The automatic daily processing of coastlines from Sentinel-1 satellite data for updating the bathymetry to support modelling as part of a Near Real Time chain is being developed. In shallow waters, the physical processes caused by the interaction between waves, currents and the sea bottom become important and are crucial for modelling, requiring current and accurate bathymetry data. The spatial properties of sea state and currents change strongly in coastal areas and especially in the Wadden Sea at the Danish, German and Dutch North Sea coast with large areas of intertidal flats. The morphodynamics of seabed structures are significant in such littoral zones; the soft seabed can change within days during severe storms. Data from past measurement campaigns, which are very expensive using ship soundings and airborne LIDAR scanning, deprecates quickly as the positions of islands, sandbanks or tidal inlets change. Acquisitions from the Sentinel-1 (S1) Synthetic Aperture Radar (SAR) satellites cover most coasts worldwide. With two satellites currently in orbit, the acquisition interval is at most 6 days at the equator and almost daily in our latitudes. The Interferometric Wide Swath (IW) mode covers lands and coastal waters with a swath width of 250km and an image resolution of 10m. In contrast to optical satellites, SAR acquisitions are independent of illumination and cloud cover; hence, they deliver new images very reliably. The DLR satellite ground station in Neustrelitz receives these data and processes and delivers them in Near Real Time (NRT), usually within 20 minutes after acquisition. We have developed automated algorithms to retrieve the waterline from SAR images. In the tidal flat areas of the Wadden Sea, analyzing time series of acquisitions at similar tidal states allows estimating rates of change and sediment transport; a combination of several images acquired within a short time frame at different tidal states allows estimating the topography. Our algorithms for Sentinel-1 SAR images offer a quick and cheap way to spot ongoing processes, verify modelling results and identify regions of major change for future measurement campaigns.