In this study, we assess the performance of the three state-of-the-art ice drift retrieval algorithms for Synthetic aperture radar (SAR) images. The algorithms were selected by their difference in underlying technique to reveal their advantages and limitations based on C- and X-band data in the Arctic. The results suggest that area-based algorithms are applicable in most cases, while feature-tracking algorithm demonstrates better precision but with fewer produced drift vectors. The hybrid algorithm provides the best data density compared to the other two algorithms but suffers from generating artificial vectors in the case of strong ice speed gradients such as at the edge between fast and drift ice.

A known and challenging effect in the retrieval of ocean surface currents from synthetic aperture radar (SAR), is the so called wave-induced velocity bias. This effect is due to the correlation between the normalized radar cross section (NRCS) and Doppler shift modulations, which are generated by the long modulating waves. This paper analyses two collocated NRCS and Doppler frequency shift images acquired by the along-track interferometric SAR TanDEM-X at two polarizations VV and HH. These images capture a swell traveling nearly in the range direction. First, it is shown that the NRCS and Doppler shift modulations, due to the modulating swell wave, are highly correlated. Second, it is shown that this correlation affects the mean Doppler shift. Consequently, the ocean current estimation can be biased by approximately 0.2 m/s, which can be significant at low current magnitudes and when high-accuracy current retrievals are required.

One of the challenges in ocean surface current retrieval from synthetic aperture radar (SAR) data is the estimation and removal of the wave-induced Doppler centroid (DC). This article demonstrates empirically the relationship between the dc derived from spaceborne X-band InSAR data and the ocean surface wind and waves. In this study, we analyzed over 300 TanDEM-X image pairs. It is found that the general characteristics of the estimated dc follow the theoretically expected variation with incidence angle, wind speed, and wind direction. An empirical geophysical model function (GMF) is fit to the estimated dc and compared to existing models and previous experiments. Our GMF is in good agreement (within 0.2 m/s) with other models and data sets. It is found that the wind-induced Doppler velocity contributes to the total Doppler velocity with about 15% of the radial wind speed. This is much larger than the sum of the contributions from the Bragg waves (~0.2 m/s) and the wind-induced drift current (~3% of wind speed). This indicates a significant (dominant) contribution of the long wind waves to the SAR dc. Moreover, analysis of dual-polarized data shows that the backscatter polarization ratio ($PR=\sigma ^{0}_{VV}/\sigma ^{0}_{HH}$) and the dc polarization difference ($PD={|dc_{VV}|-|dc_{HH}|}$) are systematically larger than 1 and smaller than 0 Hz, respectively, and both increase in magnitude with incidence angle. The estimated PR and PD are compared to other theoretical and empirical models. The Bragg scattering theory-based (pure Bragg and composite surface) models overestimate both PR and PD, suggesting that other scattering mechanisms, e.g., wave breaking, are involved. In general, it is found that empirical models are more consistent with both backscatter and Doppler data than theory-based models. This motivates a further improvement of SAR dc GMFs.

This paper presents a direct comparison of the sea surface radial velocity (RVL) derived from the two satellite SAR systems Sentinel-1 and TanDEM-X, operating at different frequencies and imaging modes. The RVL is derived from the Doppler centroid (Dc) provided in the Sentinel-1 OCN product and from the along-track interferometric phase of the TanDEM-X, respectively. The comparison is performed using an opportunistic collocated acquisition over the Pentland Firth strait, known for its strong tidal stream. This comparison shows that the two SAR systems observe similar sea surface circulation patterns with high spatial correlation coefficient (r ~10.8). It is also shown that, provided a common calibration reference is available, the two independently derived RVL are quantitatively in good agreement with a negligible bias and reasonable RMSE (~10.3 m/s). This encourages use of the synergy between different C- and X-band SAR systems, measuring sea surface velocity.

In this paper, the capability of Sentinel-1 data to map ocean surface currents in the Skagerrak Sea, with a focus on the Norwegian Coastal Current (NCC), is investigated. Post-processing methods for removing artefacts in the data and improving of the geophysical interpretation are suggested. Scalloping is one major artefact, which significantly degrades the quality of the velocity maps. Two methods, in spatial and spectral domain, for correcting this effect are proposed. It is also found that the radial velocity provided in the Sentinel-1 ocean data is biased, hence land is used as a reference to correct for the absolute and inter-beam bias. Finally, the retrieved (corrected) velocity is compared to a regional ocean circulation model (ROMS). It is shown that there is a good agreement between the ocean model and the retrieved velocity with values of ≈ 0.8 m/s in the core of the NCC.

The main challenging problems in ocean current retrieval from along-track interferometric (ATI)-synthetic aperture radar (SAR) are phase calibration and wave bias removal. In this paper, a method based on differential InSAR (DInSAR) technique for correcting the phase offset and its variation is proposed. The wave bias removal is assessed using two different Doppler models and two different wind sources. In addition to the wind provided by an atmospheric model, the wind speed used for wave correction in this work is extracted from the calibrated SAR backscatter. This demonstrates that current retrieval from ATI-SAR can be completed independently of atmospheric models. The retrieved currents, from four TanDEM-X (TDX) acquisitions over the Öresund channel in the Baltic Sea, are compared to a regional ocean circulation model. It is shown that by applying the proposed phase correction and wave bias removal, a good agreement in spatial variation and current direction is achieved. The residual bias, between the ocean model and the current retrievals, varies between 0.013 and 0.3 m/s depending on the Doppler model and wind source used for wave correction. This paper shows that using SAR as a source of wind speed reduces the bias and root-mean-squared-error (RMSE) of the retrieved currents by 20% and 15%, respectively. Finally, the sensitivity of the sea current retrieval to Doppler model and wind errors are discussed.

The main problem in wind retrieval using SAR imagery is the lack of the wind direction information. A few methods have been proposed to extract the wind direction from SAR images. The main limitation of these methods is the 180°ambiguity in the direction. Usually, an external source of wind direction is used to remove this ambiguity. This study exploits the Along-track Interferometric SAR (ATI-SAR) phase to demonstrate its usefulness to tackle this problem. A method is proposed to remove the wind direction ambiguity using the ATI-SAR phase information. This is based on the fact that the interferometric phase is related to the sea surface motion direction. Depending on the sign convention, the phase is positive/negative for advancing/receding target respectively. This effect is used to assist the wind extraction algorithm to select the most plausible direction. The results show a very good agreement with atmospheric model and visual investigation.

It has been demonstrated that Along Track Interferometric (ATI) SAR is a useful tool to retrieve ocean surface currents. The ATI SAR provides an interferometric phase (hereafter called phase) which is directly related to the Line-Of-Sight (LOS) component of the surface velocity. The accuracy of ocean currents retrieval is highly dependent on the phase processing. For instance, a properly processed phase must equal zero over static targets. The measured TanDEM-X phase rarely (if ever) satisfies this condition which indicates a phase offset independent of the surface properties. The offset can be either due to a phase synchronization issue or to using inaccurate orbital and attitude information in the processing. The objective of phase calibration is the estimation and the removal of the offset and possible trends from the measured phase. In this paper, the topographic phase is simulated using a Digital Elevation Model (DEM) and baseline information. The calibration is carried out by estimating the average of the phase over land, after topography correction, and subtracting the estimated value from the measured phase. Finally, the residual phase trend is removed using a second order polynomial fitting.

Along-Track Interferometric (ATI) SAR has demonstrated through several studies a capability to detect ocean surface currents. One of the most challenging problems in ocean surface current retrieval using SAR is the removal of the wind-wave contribution. The phase difference provided by ATI-SAR technique is directly related to the radial velocity of the moving ocean surface. In order to infer the current-only velocity from the total phase the wind-wave contribution need to be removed. This is achieved by simulation of SAR Doppler spectra from given wind fields. This paper investigates the effect of the local wind on ATI-SAR phase. A study case, where the backscatter modulation is dominated by the wind variation, is illustrated using TanDEM-X data over the Baltic Sea. It is shown that retrieving high resolution winds from SAR data using an empirical wind model and using the retrieved winds as input to the SAR imaging model improves the simulated SAR signatures.

A methodology of intercalibration of C-band spaceborne scatterometers is developed and applied to European Remote Sensing satellite-1 (ERS-1), European Remote Sensing satellite-2 (ERS-2), and Meteorological Operational satellite (METOP) scatterometer data. Assuming that the differences between the instruments can be represented by an incidence-angle-dependent bias, this paper presents and discusses four methods, providing an estimate of that bias and of its standard deviation. Model-based methods performed more accurately than a direct comparison of σ0. The latter provides a systematic larger positive bias. The methodology is applied to ERS-1 and ERS-2 data acquired during the tandem mission in 1996. The same methodology is applied to ERS-2 and Advanced Scatterometer (ASCAT) data acquired in December 2008. Generally, the bias between the ERS-1 and ERS-2 scatterometers is smaller than 0.2 dB over most incidence angles, and the four methods provide relatively consistent results. The bias between ERS-2 and ASCAT is slightly higher, reaching 0.4 dB at certain incidence angles. These results suggest that these scatterometers need to be intercalibrated to achieve a consistent backscatter data.

The importance of long-term, continuous, and homogenous time-series of satellite data is widely accepted and strongly fostered by the international scientific community. The various global projects and initiatives undertaken in the last few years are evidences of that effort. Among those are: the Long Term Data Preservation Working Group [1], the Permanent Access to the Records of Science in Europe (PARSE) [2], or the Global Climate Observing System (GCOS) [3]. One of the examples of long-term monitored variable is the wind vector. Since the European Remote-sensing Satellite (ERS)-1 launch in July 1991 and until ERS-2 decommissioning in July 2011, a continuous and consistent database of backscattering signal from the Earth surface has been built, and is now available. The Active Microwave Instrument (AMI) [4], which was one of the ERS-1 and ERS-2 payloads, provided radar backscattering coefficient measurements during the last 20 years by using its three nominal operational acquisition modes: Synthetic Aperture mode (SAR mode), Scatterometer mode (wind mode) and a special combination of the two over ocean where SAR and Scatterometer mode are interleaved (wind/wave mode). The main applications for data acquired in Scatterometer mode is related to the estimation of the wind vector over the sea surface. In that field the ERS-2 Scatterometer measurements give a very valuable contribution to the accuracy of the numerical weather forecast models, being assimilated in several meteorological weather forecast centers since the beginning of the mission. After the decommissioning of ERS-2, effort has been devoted to achieve a complete reprocessed database, including both ERS-1 and ERS-2 acquisitions [5]. The cross-calibration between these two satellites is a crucial task to obtain the homogeneousness of the wind vector database, and allow its long-term characterization. The approach followed by ESA in term of team organization, cross-calibration strategy and validation methodology towards this goal is presented in this paper as well as the preliminary results of the long-term characterization of the wind vector.

This paper presents an overview of the evolution of the European Remote-sensing Satellite (ERS)-2 scatterometer mission during the last 16 years, highlighting the changes in both satellite configuration and on-ground data processing algorithm. Instrument and on-ground data processor performances and evolutions are analyzed and commented; finally, future developments are emphasized. ERS-2 was launched in 1995 by the European Space Agency (ESA). Since then, the active microwave instrument, which is one of the ERS-2 payloads, is providing radar backscattering coefficient measurements by using its three nominal operational acquisition mode: synthetic aperture mode (SAR mode), scatterometer mode (wind mode), and a special combination of the two over ocean where SAR and scatterometer mode are interleaved (wind/wave mode). The main applications for data acquired in scatterometer mode are related to the estimation of the wind vector over the sea surface. In that field, the ERS-2 scatterometer measurements give a very valuable contribution to the accuracy of the numerical weather forecast models, being assimilated in several meteorological weather forecast centers since the beginning of the mission. Other applications of the ERS-2 scatterometer data are over land to retrieve information about the soil water content and over the sea-ice. A constant monitoring of the scatterometer performances is carried out since the beginning of the mission by ESA engineering teams located in ESTEC and ESRIN and the instrument manufacture (Dornier at launch time), in collaboration with several European research institutions, as the European Centre for Medium-range Weather Forecasts for product geophysical validation, the Belgian Royal Military Academy for data processing and calibration during the zero-gyro phase, and industrial partners, as Serco SpA for the routine data quality control activities since the beginning of operational phase. Results show outstanding performances even after the failure of several hardware components that has been properly compensated on-ground with evolution of the processor, and many years of operation, which permits the creation of a homogeneous database of wind vectors for the last 16 years (20 years if the ERS-1 mission is considered), in accordance with Global Climate Observing System recommendations.