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SMOS+SOS Ocean Salinity Science and Salinity Remote Sensing Workshop, 26-28 november 2014, Exeter, United Kingdom.-- 2 pages, Remote sensing imagery of the ocean surface provides a synoptic view of mesoscale signatures from different ocean scalars advected by the oceanic flow. The most probable origin of the observed structures is the turbulent character of the oceanic flow as they slowly evolve and are very persistent over time scales compatible with ocean mesoscale dynamics. At spatial scales of kilometers, turbulence is mainly 2D, and a complex geometry, full of filaments and eddies of different sizes, emerges in remote sensing images of surface chlorophyll-a concentration (Chl-a) and sea surface salinity (SSS), as well as in the better resolved sea surface temperature (SST) and sea surface height (SSH). A fusion technique has been recently proposed to exploit these common turbulent signatures between variables. This technique is theoretically based on the geometrical properties of advected tracers [Turiel et al., 2005b]. Coherent vortices in a turbulent flow strongly interact, leading to permanently stretch and fold small-scale filaments ejected from vortex cores, and generate small-scale tracer gradients between eddies. Therefore the spatial structure of a tracer inherits some properties of the underlying flow. This geometrical arrangement of the flow is intimately linked to the energy cascade. A key point in this approach is the assumption of a multifractal structure in ocean images [Lovejoy et al., 2001]. It is assumed that singularity lines of ocean variables coincide [Umbert et al., 2014]. In turn, the gradient of both variables can be related by a smooth function. As a first and simple approach, the relating function is expressed as the identity, leading to a local regression scheme. This simple approach allows reducing the error and improving the coverage of the resulting Level 4 product of one variable using another variable as a template. Moreover, information about the statistical relationship between the two fields can also be obtained. This methodology is been applied to Aquarius SSS using SSH from AVISO as template in the Gulf Stream. Resulting SSS Level 4 product contain the mesoscale structures seen by SSH and a significant reduction of the uncertainty

IV Congress of Marine Sciences, Encuentro de la Oceanografía Física Española (EOF 2014), 11-13 June 2014, Las Palmas de Gran Canaria.-- 1 page, Remote sensing imagery of the ocean surface provides a synoptic view of mesoscale signatures from different ocean scalars advected by the oceanic flow. The most probable origin of the observed structures is the turbulent character of the oceanic flow as they slowly evolve and are very persistent over time scales compatible with ocean mesoscale dynamics. At spatial scales of kilometers, turbulence is regarded as a two-dimensional phenomenon, with a complex geometry. Such complexity emerges in remote sensing images as filaments and eddies of different sizes. This is seen in images of surface chlorophyll-a concentration (Chl-a) and sea surface salinity (SSS), as well as the better-resolved sea surface temperature (SST) and sea surface height (SSH). A fusion technique has been recently proposed to exploit these common turbulent signatures between variables. This technique is theoretically based on the geometrical properties of advected tracers [Turiel et al., 2005b]. Coherent vortices in a turbulent flow strongly interact, leading to permanently stretch and fold small-scale filaments ejected from vortex cores, and generate small-scale tracer gradients between eddies. Therefore the spatial structure of a tracer inherits some properties of the underlying flow. This leads to an organized geometry of the flow as a hierarchy of fractal sets, called singularity manifolds, each one of them associated to a singularity exponent; this is the so-called multifractal formalism for fully developed turbulence. This geometrical arrangement of the flow is intimately linked to the energy cascade. A key point in this approach is the assumption of a multifractal structure in ocean images [Lovejoy et al., 2001]. It is assumed that singularity lines of ocean variables coincide [Umbert et al., 2013]. In turn, the gradient of both variables can be related by a smooth function. As a first and simple approach, the relating function is expressed as the identity, leading to a local regression scheme. This simple approach allows reducing the error and improving the coverage of the resulting Level 4 product of one variable using another variable as a template. Moreover, information about the statistical relationship between the two fields can also be obtained. This methodology is been applied to daily Aqua MODIS Level-3 chlorophyll maps using MODIS SST maps as template, to SMOS SSS using OSTIA SST as template, and to Aquarius SSS using SSH from AVISO as template. Resulting SSS and Chl-a Level 4 products contain the mesoscale structures seen in SST and SSH maps, exhibit a significant reduction of the uncertainty, and allow extrapolation to cloud-affected areas

SMOS & Aquarius Science Workshop, 15-17 April 2013, Brest, France, The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission has provided nearly continuous global record of fully polarimetric brightness temperatures at L-band (1.4135 GHz) since November 2009. The single payload of the SMOS satellite, MIRAS, is a two-dimensional aperture synthesis radiometer that measures the cross-correlations between the signals from many L-band antennas distributed in a Y-shape array. These cross-correlations are transformed by ground processing into brightness temperature images that extend over a swath several hundred kilometers across. Over the ocean, these brightness temperature images are used, together with a forward model of the L-band scene brightness, to derive maps of surface salinity over the global oceans, with full earth coverage approximately every five days. Over the global oceans the surface salinity varies between about 32 and 38 on the practical salinity scale, with the strongest variations in the vicinity of river outflows and heavy rainfall. The sensitivity of the brightness temperature at L-band to a change in salinity depends somewhat upon polarization and sea surface temperature but, in tropical latitudes, is about +1 K in the first Stokes parameter per unit decrease of salinity on the pratical salinity scale. Thus, the dynamic range of L-band brightness temperatures over the open ocean is only several kelvin. As one goal of the mission is to produce global maps of salinity with an accuracy of 0.1 after averaging over 10-30 days, strict requirements must be placed upon the accuracy and stability of the brightness temperatures. Efforts to reach this goal continue, but challenges related to interannual, seasonal, and orbital stability of the retrieved salinity remain. These challenges stem from difficulties in the instrument calibration, image reconstruction, and modeling of the scene brightness over the ocean. On the one hand, the instrument calibration and image reconstruction are plagued by the sun which impacts the accuracy of the brightness temperatures indirectly, through variations in the thermal characteristics of the instrument, and directly, through its impact on the visibilities. On the other hand, the scene modeling is plagued by emission from the rough ocean surface, emission from foam, and galactic radiation scattered towards the instrument by the wind-roughened ocean surface. Moreover, the sun-synchronous orbit of the SMOS satellite is such that both the solar (direct and indirect) and galactic impacts exhibit orbital and seasonal cycles that, if not properly accounted for, will contribute to bias in the salinity. A key factor complicating progress is the fact that the aforementioned problems can produce similar bias evolutions, and so disentangling the various sources of bias is difficult. Using open-ocean model solutions for the brightness temperature images as well as the antenna temperatures (which provide the mean brightness temperature level for the images), this paper will examine the spatial and temporal structures observed in the biases over the nearly four years of continuous data. An attempt will be made to exploit the recent oscillatory character of the sun L-band brightness in order to separate the impacts of the sun and scattered galactic radiation. In parallel, improvements in the modeling of the scattering of galactic radiation will be presented, and a comparison will be made with the impact on the brightness temperatures and salinity maps from the Aquarius mission. Finally, recognizing that adequate calibration and forward scene modeling may not be achieved in the near future, the paper will examine practical alternatives to bias correction, with an emphasis on finding an approach that minimizes impact on the range of applications of the SMOS salinity maps

European Space Agency (ESA) Living Planet Symposium, 9-13 September 2013, Edinburgh, Due to their relatively rapid motion and low dynamic viscosity, geophysical fluids such as the atmosphere and the oceans are turbulent, although the particular regime of turbulence depends on the scale at which the fluid is studied. In the case of oceans, at scales of meters and below turbulence is mainly 3D with strong vertical displacements across the mixed layer, while at scales of kilometers and above turbulence is mainly 2D - except at some specific areas such as upwelling zones- and shows up as a complicated pattern of filaments, meanders and eddies. The fingerprint of those structures can be recognized in remote sensing images of different types, such as chlorophyll concentration (CC), sea surface temperature (SST), sea surface salinity (SSS) or sea surface height (SSH). The observed spatial redundancy among the different scalars suggests that a synergistic approach could be used to study and analyze ocean variables. In particular, synergy could be used to improve the signal-to-noise ratio of corrupted variables by using information from other variables or to infer missing values. However, it is very complicated to give a mathematical formalism leading to practical algorithms. In the last years a new formalism has arisen to systematize the concept of scalar synergy: that of Microcanonical Multifractal Formalism (MMF). According to MMF, any scalar variable submitted to the action of a turbulent flow develops a structure of singular fronts, reminiscent of the streamlines of the flow, that can be extracted from any ocean scalar as a field of dimensionless variables, the singularity exponents. The validity of MMF has been verified on remote sensing images of different types, included ocean leaving radiances, SST, CC or SSH. As singularity exponents have no dimensions, singularity exponents coming from variables of different type can be directly compared, and in fact must coincide for the reasons exposed above. Not only that: an algorithm for merging the information of variables of different type has been devised using this common information. With this algorithm, a noisy variable can be improved by merging it with a higher-quality variable of a different type. In this work we show the application of this algorithm for a different goal: the extrapolation of chlorophyll maps to missing areas by using SST as a template. This extrapolation provides significant results in open ocean without assuming any parametrization and warrants that the extrapolated field is consistent with the observed ocean structures