 brightness temperatures (Tb). The measurements are affected by strong radiometric noise. However, during a satellite overpass, numerous measurements are acquired at various incidence angles at the same location on the Earth’s surface. The sea surface salinity (SSS) retrieval algorithm implemented in the Level 2 Salinity Prototype Processor (L2SPP) is based on an iterative inversion method that minimizes the differences between Tb measured at different incidence angles and Tb simulated by a full forward model. The iterative method is initialized with a first-guess surface salinity that is iteratively modified until an optimal fit between the forward model and the measurements is obtained. The forward model takes into account atmospheric emission and absorption, ionospheric effects (Faraday rotation), scattering of celestial radiation by the rough ocean surface, and rough sea surface emission as approximated by one of three models. Potential degradation of the retrieval results is indicated through a flagging strategy. We present results of tests of the L2SPP involving horizontally The L2OS processor generates SSS maps from the SMOS MIRAS instrument. ARGANS develops and maintains the L2OS processor in collaboration with Expert Support Laboratories (ESLs): LOCEAN-IPSL, ICM, IFREMER and ACRI-ST. Level 1 & Level 2 processors are used in the ESA SMOS ground station (DPGS) to generate data products; data and processors are also available for the scientific community. The L2SM Processor from ARRAY generates SMOS Level 2 Soil Moisture products. Over the ocean Stokes vector brightness temperatures (TB) are a function of the sea surface dielectric constant, with a low sensitivity to salinity and water temperature. MIRAS takes overlapping large area snapshots every 1.2 seconds, so TBs for each ISEA surface grid point are available for a large number (100-200) of incidence angles (60 degrees to nadir and beyond). SMOS Level 1c (L1c) products for each half-orbit map MIRAS measurements onto grid points. The L2OS processor uses surface emission models to predict TB measurements and an iterative convergence scheme to refine predictions, deriving salinity from L1c TBs. Readers are refered to the ARGANS web site for additional information on the SMOS level 2 algorithm and processors for ocean salinity. |