Abstract. New possibilities for horizontal current retrieval in marginal ice zones (MIZs) from sequential Sentinel-1 synthetic aperture radar (SAR) images are demonstrated. Daily overlapping SAR acquisitions within 70–85∘ S/N at time intervals < 1 h enable estimation of high-resolution velocity fields, revealing MIZ dynamics down to submesoscales. An example taken from the Fram Strait MIZ reveals energetic eddies and filaments with Rossby numbers reaching O(1) magnitudes. The SAR-derived velocity estimations at such high spatial resolution can be critical for monitoring the evolving MIZ dynamics and model validation of submesoscale processes in polar oceans.

Two remote sensing methods, satellite altimetry and 4D-Var assimilation of satellite imagery, are used to compute surface velocity fields in the Black Sea region. Surface currents derived from the two methods are compared for several cases with intense mesoscale and large-scale dynamics during low wind conditions. Comparison shows that the obtained results coincide well quantitatively and qualitatively. However, satellite imagery provides more reasonable results on the spatial variability of coastal dynamics than altimetry data. In particular, this is related to the reconstruction of eddy coastal dynamics, such as Black Sea near-shore anticyclones. Current streamlines in these eddies are not closed near the coast in altimetry data, which we relate to the extrapolation during mapping procedure in the absence of coastal along-track measurements. On the other hand, in offshore areas, imagery-derived currents can be underestimated due to the absence of thermal contrasts and smoothing during the procedure of the 4D-Var assimilation. Wind drift currents are another source of inconsistency, as their impact is directly observed in satellite imagery but absent in altimetry data. The advantage of the 4D-Var method for reconstructing coastal dynamics is used to compute surface currents in the Marmara Sea on the base of 250 m resolution Modis optical data. The results reveal the very complex dynamics of the basin, with a large number of mesoscale and sub-mesoscale eddies. 4D-Var assimilation of Modis imagery is used to obtain information about dynamic characteristics of these small eddies with radiuses of 4-10 km.

The paper presents a motion estimation method based on data assimilation in a dynamic model, named Image Model, expressing the physical evolution of a quantity observed on the images. The application concerns the retrieval of apparent surface velocity from a sequence of satellite data, acquired over the ocean. The Image Model includes a shallow-water approximation for the dynamics of the velocity field (the evolution of the two components of motion are linked by the water layer thickness) and a transport equation for the image field. For retrieving the surface velocity, a sequence of Sea Surface Temperature (SST) acquisitions is assimilated in the Image Model with a 4D-Var method. This is based on the minimization of a cost function including the discrepancy between model outputs and SST data and a regularization term. Several types of regularization norms have been studied. Results are discussed to analyze the impact of the different components of the assimilation system.

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