An effective methodology using satellite high-resolution polarized information to interpret and quantitatively assess various surface ocean phenomena is suggested. Using a sample RADARSAT-2 quad-polarization ocean synthetic aperture radar (SAR) scene, the dual co-polarization (VV and HH) radar data are combined into polarization difference, polarization ratio, and nonpolarized components. As demonstrated, these field quantities provide means to distinguish Bragg scattering mechanism and radar returns from breaking waves. As shown, quantitative characteristics of the surface manifestation of ocean currents, slicks, and wind field features in these dual co-polarization properties are very different and may be effectively used in the development of new SAR detection and discrimination algorithms.

[1] A synergetic approach for quantitative analysis of high-resolution ocean synthetic aperture radar (SAR) and imaging spectrometer data, including the infrared (IR) channels, is suggested. This approach first clearly demonstrates that sea surface roughness anomalies derived from Sun glitter imagery compare very well to SAR roughness anomalies. As further revealed using these fine-resolution ($1 km) observations, the derived roughness anomaly fields are spatially correlated with sharp gradients of the sea surface temperature (SST) field. To quantitatively interpret SAR and optical (in visible and IR ranges) images, equations are derived to relate the "surface roughness" signatures to the upper ocean flow characteristics. As developed, a direct link between surface observations and divergence of the sea surface current field is anticipated. From these satellite observations, intense cross-frontal dynamics and vertical motions are then found to occur near sharp horizontal gradients of the SST field. As a plausible mechanism, it is suggested that interactions of the wind-driven upper layer with the quasi-geostrophic current field (via Ekman advective and mixing mechanisms) result in the generation of secondary ageostrophic circulation, producing convergence and divergence of the surface currents. The proposed synergetic approach combining SST, Sun glitter brightness, and radar backscatter anomalies, possibly augmented by other satellite data (e.g., altimetry, scatterometry, ocean color), can thus provide consistent and quantitative determination of the location and intensity of the surface current convergence/divergence (upwelling/downwelling). This, in turn, establishes an important step toward advances in the quantitative interpretation of the upper ocean dynamics from their two-dimensional satellite surface expressions.Citation: Kudryavtsev, V., A. Myasoedov, B. Chapron, J. A. Johannessen, and F. Collard (2012), Imaging mesoscale upper ocean dynamics using synthetic aperture radar and optical data,

A method is proposed to retrieve and interpret fine spatial variations of the sea surface roughness in sun glitter imagery. Observed sun glitter brightness anomalies are converted using a transfer function determined from the smoothed shape of sun glitter brightness. The method is applied to MODIS and MERIS sun glitter imagery of natural oil seeps and the catastrophic Deepwater Horizon oil spill in the Gulf of Mexico. The short-scale roughness variations in the presence of mineral oils slicks are consistently extracted and compared to variations associated with the biogenic slicks. In doing so, the wind speed dependency on the roughness anomalies is also considered. A comparison to normalized radar cross section (NRCS) anomalies taken from the corresponding high resolution ASAR images is performed, and similarities as well as differences are investigated. The results document significant benefit from the synergetic use of sun glitter and radar imagery for detection and monitoring of surface slicks. Highlights► Estimation of the spatial anomalies in the mean square slope of the sea surface. ► Distinct relationship between sun-glitter and radar backscatter contrasts. ► Collocated MODIS, MERIS and ASAR images. ► Film elasticity coefficient. ► Consistent optical and radar imaging model.

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