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Since its launch in 2009, the European Space Agency mission Soil Moisture and Ocean Salinity (SMOS) has provided valuable information on soil moisture, sea surface salinity data, and other geophysical variables. Due to its innovative instrument, an L-band 2-D synthetic aperture interferometric radiometer, SMOS is able to provide high-resolution L2 data (as compared with other L-band missions). However, SMOS processing is complex, giving rise to the emergence of some unexpected biases. In this paper, we have analyzed the spatial structure of two-point correlations owing to the SMOS synthetic antenna, finding that they are not negligible. Those correlations can be characterized by means of effective point spread functions (PSFs). This paper indicates that the SMOS PSF matrix can be computed in a fast way from measured data without the need for any model or auxiliary data. Furthermore, this matrix can be described in terms of a convolution kernel. The knowledge of that convolution kernel can be used to improve the quality of the SMOS image and to assess the effect of changes of processing procedures, including calibration methods. [ABSTRACT FROM PUBLISHER]

Abstract Sea surface salinity (SSS) retrieved from SMAP radiometer measurements are validated against in situ salinity from Argo floats, tropical moored buoys and ship-based thermosalinograph (TSG) data. SMAP SSS achieved an accuracy of 0.2 PSU on a monthly basis in comparison with Argo gridded data in the tropics and mid-latitudes. In the tropical oceans, time series comparison of salinity measured at 1 m by moored buoys indicates that SMAP can track large salinity changes occurred within a month. Synergetic analysis of SMAP, SMOS and Argo data allows us to identify and exclude erroneous jumps or drift in some real-time buoy data from the assessment of the satellite data. The resulting SMAP-buoy matchup analysis gives an average standard deviation of 0.22 PSU and correlation coefficient of 0.73 on weekly scale. On monthly time scales, the average standard deviation reduced to 0.17 PSU and the correlation coefficient improved to 0.8. SMAP L3 daily maps reveals salty water intrusions from the Arabian Sea into the Bay of Bengal during the Indian summer monsoon, consistent with the daily measurements collected from Argo floats deployed during the Bay of Bengal Boundary Layer Experiment (BoBBLE) project field campaign. In the Mediterranean Sea, the spatial pattern of SSS from SMAP is confirmed by the ship-based TSG. Comparison with individual Argo floats suggests the SMAP retrieval algorithm performs better in the Western Mediterranean region, but suffers from radio-frequency interference (RFI) and land contamination in the Eastern Mediterranean region and Adriatic Sea. [ABSTRACT FROM AUTHOR]