Presented at the 2014 Ocean Sciences MeetingThanks to new remote sensing platforms SMOS and Aquarius we have access to synoptic maps of Sea Surface Salinity (SSS). Much effort is still under way to bring both missions to meet pre-launch requirements on the quality of SSS. In this work we explain a new technique to improve the quality of SSS maps at Level 4, by combining SMOS/Aquarius data with high quality maps of Sea Surface Temperature (SST). We use singularity analysis for the assessment of the structure of ocean flows at submesoscale and larger scales. Visual correspondence of eddies and fronts in images of different variables can be expressed as the correspondence of singularity exponents associated to each variable. Scalars having the same singularity exponents have a local functional dependence that is approximated by local linear regressions around each point. This simple algorithm to reduce noise and increase the resolution has been applied to SMOS and Aquarius data. Redundancy between ocean scalars opens the use of remote sensed sea surface salinity data for new applications, including the instant identification of ocean fronts, rain lenses, hurricane tracks, etc.