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The local oscillators (LOs) of the Soil Moisture and Ocean Salinity mission payload are used to shift the operating frequency of the 72 receivers to an optimal intermediate frequency needed for the signal processing. The LO temperature variations produce phase errors in the visibility, which result in a blurring of the reconstructed brightness temperature (Tb) image. At the end of the commissioning phase, it was decided to calibrate the LO every 10 min while waiting for a more in-depth analysis. During short periods of time, the LO calibration has been performed every 2 min to assess the impact of a higher calibration rate on the quality of the data. In this paper, by means of a decimation experiment, the relative errors of 6- and 10-min calibration interval data sets are estimated using the 2 min as a reference. A noticeable systematic across- and along-track pattern of amplitude \pm0.3 K is observed for Tb differences between 10 and 2 min, whereas this is reduced between 6 and 2 min. A simulation experiment confirms that the nature of such systematic pattern is due to the visibility phase errors induced by the LO calibration rate. Such pattern is propagated into the sea surface salinity (SSS) retrievals. Overall, the SSS error increase (relative to the 2 min SSS data) is about 0.39 and 0.14 psu for the 10- and 6-min data sets, respectively. This paper shows that a LO calibration rate of at least 6 min would noticeably improve the SSS retrievals. [ABSTRACT FROM AUTHOR]

The Baltic Sea is one of the most challenging regions for the satellite Sea Surface Salinity (SSS) retrieval. Nowadays, the availability of SMOS SSS products is quite limited over this region (temporal and spatially) due to several technical limitations related to the low sensitivity of L-band TB at SSS changes in cold waters, land-sea and ice-sea contamination, and high contamination by Radio-Frequency Interferences (RFI) sources. The assessment of the quality of the SMOS SSS products in the Baltic Sea is also an issue. On one hand, the basin is strongly stratified and therefore, differences between the first centimetres (SMOS measurements) and the few meters (measurements provided by in situ) can be noticeable. On the other hand, the basin is very shallow and then, the near surface vertical salinity gradient must be estimated from different sources. There are also seasonal salinity variations in the surface, which are caused by melting of ice and spring floods from rivers. Thus, the representativeness of satellite salinity must be assessed. Besides, some parts of the Baltic Sea such as the Gulf of Finland have estuarine regimes and therefore exhibit relatively strong horizontal salinity gradients.In the recent years, the Barcelona Expert Center (BEC) team has developed innovative algorithms for improving the quality of brightness temperatures and sea surface salinities dealing with the main processing issues: (i) Nodal Sampling [1] to mitigate the RFI contamination, (ii) Debiased non-Bayesian SSS retrieval [2] to empirically mitigate systematic biases and improve the spatial coverage of SSS maps, and (iii) Multifractal Fusion technique [3] to improve the temporal and spatial resolution to better describe the salinity dynamics. The application of these techniques has led to the generation of regional SMOS SSS products over some critical areas such as the Mediterranean Sea (http://bec.icm.csic.es/ocean-experimental-dataset-mediterranean/). The Baltic+ Salinity Dynamics project is a recent European Space Agency funded initiative, which aims at advancing research and consolidating existing developments towards the generation of a dedicated SSS product suited for Baltic Earth research (https://www.baltic-earth.eu/organisation/bewg%5fsalinity/index.html). The project started in December 2018. We will present at the conference the up-to-date Baltic+ SSS products generated in this project. We will provide a quality assessment of the SMOS SSS dataset in the Baltic Sea and we will present the potential scientific applications of this product. [1] V. González-Gambau, E. Olmedo, A. Turiel, J. Martínez, J. Ballabrera-Poy, M. Portabella, and M. Piles, "Enhancing SMOS brightness temperatures over the ocean using the nodal sampling image reconstruction technique," Remote Sensing of Environment, vol. 180, pp. 205 – 220, 2016, special Issue: ESA's Soil Moisture and Ocean Salinity Mission - Achievements and Applications. [2] E. Olmedo, J. Martínez, A. Turiel, J. Ballabrera-Poy, M. Portabella, "Debiased non-Bayesian retrieval: A novel approach to SMOS Sea Surface Salinity", Remote Sensing of Environment, vol. 193, no. Supplement C, Pages 103-126, 2017.[3] Olmedo, E., Martínez, J., Umbert, M., Hoare au, N., Portabella, M., Ballabrera-Poy, J., Turiel, A., 2016. "Improving time and space resolution of SMOS salinity maps using multifractal fusion". Remote Sens. Environ. 180, 246–263. [ABSTRACT FROM AUTHOR]

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]