SKIM is an ESA Earth Explorer-9 candidate mission designed to measure directly and simultaneously, for the first time, directional ocean surface current vector (OSCV) and ocean wave spectra. SKIM will measure at 6° and 12° incidence angle using the pulse-pair radar Doppler technique to observe the sea surface Doppler signal and then derive the ocean surface current.
The concept has been first demonstrated using opportunity data from the Ka-band AirSWOT instrument showing unambiguous estimations of the wave spectrum and surface current [Nouguier et al., 2016, IEEE TGRSL].
The DRIFT4SKIM campaign is a dedicated airborne campaign to validate the SKIM concept. In order to assess this capability, airborne Doppler measurement will be compared with a wide range of observations that cover all instruments generally used as reference for the measurement of both currents and the driving forces of currents (wind, temperature gradient, waves).
The DRIFT4SKIM campaign, takes place in the Iroise sea (4 to 6°W, 48 to 49°N) end of November 2018 (after the deadline for the abstract).
Observations will be performed in two 4-km side squares located in the field-of-view of a shore-based HF radar system (measuring surface current vectors):one where currents are spatially homogeneous; and one where strong horizontal current gradients are present.
Two microwave radars will observed the sea surface:
KuROS is a near nadir Ku-band conical scanning fan-beam real aperture pulse-coherent radar (Caudal et al., 2014, JAOT)
KaRADOC is a near nadir Ka-band narrow-beam real aperture pulse-coherent radar.
Additional observations will be carried out from optical cameras with an additional airborne platform in order to confirm the homogeneity of the experiment based on the sea surface temperature, and provide additional observations of wave spectrum and current.
Ocean surface processes will be characterized using in situ instrumentation with a large number (100) of surface drifters (current in the top meter); drogue drifters (10 for each drogue depth) at 15, 5, 2 and 1 m; 10 drifting wave measuring buoys; wind measurement and a buoy carrying current profiler.
The paper will present a first analysis of the microwave radar Doppler measurements and assessed these measurements against the geophysical conditions which will be well monitored during the campaign with comparison with in situ measurements.

Sea state information are needed for many applications, ranging from safety at sea and on the coast, for which real time data is essential, to planning and design needs for infrastructure that require long time series. The definition of the wave climate and its possible evolutions requires high resolution data, and knowledge on possible drift in the observing system. Sea states are also an important climate variable that enters in air-sea fluxes parameterizations. Finally, sea state patterns can reveal the intensity of storms and associated climate patterns at large scales, and the intensity of currents at small scales.

Here we review user requirements collected as part of the Sea State Climate Change Initiative, and sketch a path for how these requirements could be met by combining satellite and in situ data with numerical models.

As today's models are far from perfect, observations are critical in providing forcing data, namely winds, currents and ice, and validation data, in particular for frequency and direction information, and extreme wave heights. In situ and satellite observations are particularly critical for the correction and calibration of significant wave heights to ensure the stability of model time series. A number of developments are underway for extending the capabilities of satellites and in situ observing systems. These include the generalization of directional measurements, an easier exchange of moored buoy data, the measurement of waves on drifting buoys, the evolution of satellite altimeter technology, and the measurement of directional wave spectra from satellite radar instruments. For each of these observing systems, the stability of the data is a very important issue. The combination of the different data sources, including numerical models, can help better fulfill the needs of users.

Offshore wind farms are increasingly common in coastal waters. They experience gradients in the wind resources across the wind farm that need to be quantified before construction. In operation, they extract energy from the wind reducing the downstream wind speed (wake) and thus affect surrounding wind farms. Both effects can be modelled but lack large scale high resolution reference data to check and validate the models. SAR based wind retrievals offer such measurements.

Large archives from past missions like Envisat or Radarsat-1 are available from a time before most offshore wind farms have been built. These can serve as a baseline of wind conditions before wind farms are present for most cases. New data from the current satellites Sentinel-1A/B let the archives grow fast. Wind maps from these sensors are processed using the Geophysical Model Function CMOD5.N and are publically available under https://satwinds.windenergy.dtu.dk/.

Offshore wind farm development is emerging at the US East Coast and wind resource atlases from models have been created. We inter-calibrated wind maps from the above mentioned SAR sensors and created a SAR satellite based wind atlas. Comparison with the modelled data revealed differences in mean wind speed gradients in the coastal zone. Sites for future wind farms are close to shore, mostly between 10 and 50 km. Wind resources within these potential sites vary by less than 0.1 m/s from models but around 0.3 m/s from SAR. Spatial variation of wind resources are important for correctly estimating the yield from a wind farm and optimize its placement. Due to a higher resolution, SAR derived wind atlases are sensitive to smaller scale variations that are not present in the model.

Sentinel-1 images show the presence of wind farm wakes downstream of offshore wind turbines. Derived wind maps show a wind speed reduction in this area. For the first time, the wake detected in SAR imagery was compared to wind fields from Doppler radars around the wind farm Westermost Rough in the UK. We could confirm that the structure of the wake can be observed from SAR on scales of 150 m. At the Anholt wind farm in Denmark, wakes were characterized by comparing wind conditions in SAR images before and after construction of the wind farm. Evidence of wind farm wakes was found even for conditions where strong wind speed gradients are present.

With an increasing archive of SAR data that becomes increasingly open for wind energy purposes, the data are becoming more reliable and cheaper. SAR derived wind atlases can be useful, especially in areas where offshore wind farms are emerging. Applications of wake detection are also becoming more useful as Sentinel-1 data is free to use and available all over Europe.

This work received funding from the EU H2020 program under grant agreement no. 730030 (CEASELESS project). Thanks to Ørsted for providing access to data from the Anholt wind farm and the BEACon experiment.

As shown at previous conferences, we have developed a novel ocean wave retrieval technique based on spotlight-mode SAR data, which takes advantage of the long SAR integration time to identify moving wave patterns. In the first step, a complex spotlight-mode image is reprocessed into a series of subaperture images, which makes motions during a time interval of a few seconds visible. Then individual Fourier transforms of parts of the subaperture images are computed and combined into three-dimensional wavenumber-frequency spectra, in which most of the spectral energy is found near a dispersion shell given by the theoretical dispersion relation of ocean waves. This enables us to remove other contributions to obtain a very clean spectrum of moving sinusoidal ocean wave signatures. The inversion of this filtered image spectrum into a surface slope or wave height spectrum is much more straightforward than traditional wave retrieval techniques for SAR. Furthermore, our technique is phase preserving, i.e. the retrieved wave spectrum can be transformed back into the space-time domain to show the actual ocean wave field and its evolution during the SAR overpass.

In this presentation we discuss how the extracted spatially varying wave field can be analyzed further to derive water depths and surface current vectors. It is well known that wave refraction patterns in SAR images can be used for bathymetry retrievals. Our method is based on the same basic principles, but the availability of frequency-wavenumber spectra with phase information for each component allows us to identify coherent wave patterns more accurately and should theoretically lead to more accurate and more robust retrieval results. Furthermore, we can retrieve current vectors together with the depths. This makes the technique attractive for a variety of applications in coastal regions, river estuaries, and the open ocean. We think that wave, current, and depth retrievals from spotlight-mode SAR data can be an interesting alternative to the use of proposed future instruments on satellites, such as along-track InSARs, Doppler scatterometers, and advanced wave scanners such as the Sea Surface Kinematics Multiscale Monitoring Mission (SKIM), while these are still under development.

Nowadays, wind speed retrieval is a topic of great interest. Most of the remote-sensing satellite radar systems are able to provide sea-surface wind field information, and they can be considered the main near sea surface wind information source. Within this context, active microwave remote sensing, in particular the scatterometer and the Synthetic Aperture Radar (SAR), is worldwide recognized as one of the best suitable tools to perform a reliable sea-surface wind speed retrieval. Radar backscatter intensity and its statistical properties contain quantitative information about sea surface roughness and, therefore, can be used to derive sea-surface wind information. Empirically derived Geophysical Model Functions (GMF) are used to relate the calibrated radar return to the wind speed at a height of 10m. GMFs usually relate the radar backscatter to wind speed and wind direction. An alternative method to retrieve wind speed from SAR is represented by the spectral based approaches, i.e.; the azimuth cut-off procedure. When dealing with SAR microwave sensors, Doppler misregistration along the azimuth is induced by gravity wave orbital motion. This issue is the major responsible of a distortion of the imaged wave spectrum and of a strong cut-off in the azimuthal direction: this is the azimuth cut-off. Originally, this technique was proposed in [1] to retrieve significant wave height (SWH), without the knowledge of any a priori wind direction information.
The theory that is at the basis of the azimuth cut-off method is related to the effect of the orbital motion related to the surface waves in the SAR imaging of the ocean surface. This orbital motion results in additional Doppler shifts that distort the phase history of the backscattered signal used to synthetize the resolution in azimuth. The result is a low-pass filtered SAR image in the azimuth direction. The azimuth cut-off well correlates to the SWH because of its sensitivity to the long waves.
In this study, the ACF-based λc approach is extended to high wind speed regimes, e.g.; extreme weather conditions. The key issues that need to be tackled concern the tuning with respect to pixel spacing, box size and the homogeneity of the SAR imagery. Preliminary results obtained processing a large data set of Sentinle-1 SAR imagery collected under a broad range of wind conditions show that the box size and the median filter window should be set at 1 km × 1 km and 90-120 m, respectively. Then, tailored experiments have been undertaken an actual Sentinel-1 dataset collected under high wind regimes, i.e.; tropical cyclones. The obtained λc values are compared both with the ECMWF forecasted information and with wind speed maps provided by Ifremer. Preliminary results show that there is a good agreement between λc and wind speed in some areas of the cyclone, i.e.; further enough from the cyclone eye.

[1] V. Kerbaol, B. Chapron, and P.W. Vachon, “Analysis of ERS-1/2 synthetic aperture radar wave mode imagettes”, Journal of Geophysical Reserarch, vol. 103, no. C4, pp. 7833-7846, 1998.

Ocean dynamics at smaller spatial and temporal scales is not yet fully understood. For that reason, several space missions, such as SEASTAR, SKIM or STEREOID, have been proposed in the last years to improve the observational capabilities that may enable improved understanding of ocean currents. From these three missions the latter two are under consideration and are being currently studied and evaluated by ESA. These three mission concepts have in common that they measure the surface Doppler velocity in order to obtain information about the ocean currents, while previous missions used only the altimetric signature of ocean currents imprinted on the ocean's surface to derive the currents. This latter approach had the limitation that only the current in geostrophic equilibrium could be monitored from space. For instance, this left significant parts of the ocean near the equator with insufficient space-borne observations.

In parallel to these scientific needs, a general trend in global remote sensing is to require cost-effective space-borne solutions that permit a sustained launch and replacement of missions to provide mid and long term continuity of global observations. The PARIS concept, which consists in a passive space-borne GNSS receiver that acquires GNSS signals reflected off the ocean's surface to obtain altimetric and/or scatterometric observations of the surface, is in line with this need. The PARIS concept has been successfully implemented in two recent missions, UK's TDS-1 and NASA's CYGNSS mission. The advantage of this measurement concept is that it achieves an improvement in the spatial and temporal densification of the measurements, thanks to the large number of transmitters, and to the use of a relatively cost-effective instrument as it is an only-receiving one.

In addition to GNSS transmitters the Earth is illuminated in the microwave frequency range by many other satellites, in particular at X and Ku bands (~10.7 - 12.7 GHz). These are digital TV signals broadcast by geostationary satellites. The current number of transmitters is above 300, the total bandwidth spans up to 2 GHz, and the available power is two orders of magnitude stronger than that of GNSS signals. This makes them suitable to be used in passive bi-static radar configurations using non-forward scattering geometries. In such configurations the horizontal velocity component (of ocean currents) does imprint a Doppler signature onto the reflected signals, which can be measured. This Doppler signature is stronger than that of GNSS signals, as the wavelength of X-band signals is in the order of 3 cm, seven times shorter that that of GNSS signals.

We have implemented an new instrument that uses digital satellite TV signals at X-band, and have successfully tested the bi-static PARIS concept in non-forward scattering geometries in a proof of concept experiment at the Ebro river, where we have been able to measure the river's Doppler velocity.

In Figure 1 we present a delay Doppler map computed from the digital satellite TV signals reflected off the river, that shows three clear distinct echoes. The two of them with a zero Doppler frequency correspond to the echoes of the nearby and distant shores, respectively. The echo with a Doppler frequency around 30 Hz corresponds to the signals reflected off the stream.

In the presentation we will provide details about the measurement concept, the experimental campaign and its results, as well as over the potentialities of this technique to provide and complement future space-borne Doppler velocity observations.


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Caption of Figure 1:
Delay-Doppler map of the digital satellite TV signals reflected off the Ebro river. The echoes with zero Doppler frequency correspond to the signal reflected off the shores, while the reflection off the flowing stream has a non-zero Doppler frequency.