| Summary: | European Geosciences Union General Assembly 2017, 23-28 April 2017, Vienna, Austria.-- 1 page The Arctic Ocean is under profound transformation. Observations and model predictions show dramatic declinein sea ice extent and volume [1]. A retreating Arctic ice cover has a marked impact on regional and global cli-mate, and vice versa, through a large number of feedback mechanisms and interactions with the climate system [2].The launch of the Soil Moisture and Ocean Salinity (SMOS) mission, in 2009, marked the dawn of a newtype of space-based microwave observations. Although the mission was originally conceived for hydrological andoceanographic studies [3,4], SMOS is also making inroads in the cryospheric sciences by measuring the thin icethickness [5,6]. SMOS carries an L-band (1.4 GHz), passive interferometric radiometer (the so-called MIRAS)that measures the electromagnetic radiation emitted by the Earth’s surface, at about 50 km spatial resolution,continuous multi-angle viewing, large wide swath (1200-km), and with a 3-day revisit time at the equator, butmore frequently at the poles.A novel radiometric method to determine sea ice concentration (SIC) from SMOS is presented. The method usesthe Bayesian-based Maximum Likelihood Estimation (MLE) approach to retrieve SIC. The advantage of thisapproach with respect to the classical linear inversion is that the former takes into account the uncertainty of thetie-point measured data in addition to the mean value, while the latter only uses a mean value of the tie-point data.When thin ice is present, the SMOS algorithm underestimates the SIC due to the low opacity of the ice at thisfrequency. However, using a synergistic approach with data from other satellite sensors, it is possible to obtainaccurate thin ice thickness estimations with the Bayesian-based method.Despite its lower spatial resolution relative to SSMI or AMSR-E, SMOS-derived SIC products are little af-fected by the atmosphere and the snow (almost transparent at L-band). Moreover L-band measurements are ...
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