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Salinity observing satellites have the potential to monitor river fresh-water plumes mesoscale spatio-temporal variations better than any other observing system. In the case of the Soil Moisture and Ocean Salinity (SMOS) satellite mission, this capacity was hampered due to the contamination of SMOS data processing by strong land-sea emissivity contrasts. Kolodziejczyk et al. (2016) (hereafter K2016) developed a methodology to mitigate SMOS systematic errors in the vicinity of continents, that greatly improved the quality of the SMOS Sea Surface Salinity (SSS). Here, we find that SSS variability, however, often remained underestimated, such as near major river mouths. We revise the K2016 methodology with: a) a less stringent filtering of measurements in regions with high SSS natural variability (inferred from SMOS measurements) and b) a correction for seasonally-varying latitudinal systematic errors. With this new mitigation, SMOS SSS becomes more consistent with the independent SMAP SSS close to land, for instance capturing consistent spatio-temporal variations of low salinity waters in the Bay of Bengal and Gulf of Mexico. The standard deviation of the differences between SMOS and SMAP weekly SSS is <0.3 pss in most of the open ocean. The standard deviation of the differences between 18-day SMOS SSS and 100-km averaged ship SSS is 0.20 pss (0.24 pss before correction) in the open ocean. Even if this standard deviation of the differences increases closer to land, the larger SSS variability yields a more favorable signal-to-noise ratio, with r 2 between SMOS and SMAP SSS larger than 0.8. The correction also reduces systematic biases associated with man-made Radio Frequency Interferences (RFI), although SMOS SSS remains more impacted by RFI than SMAP SSS. This newly-processed dataset will allow the analysis of SSS variability over a larger than 8 years period in regions previously heavily influenced by land-sea contamination, such as the Bay of Bengal or the Gulf of Mexico. [ABSTRACT FROM AUTHOR]

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Sea Surface Salinity, SSS, retrieved from measurements of Soil Moisture and Ocean Salinity, SMOS, satellite mission using the European Space Agency version 5 processors displays systematic errors, in particular in the vicinity of large land masses and in the open ocean as a function of latitude and season. The main goal of this paper is to quantify the contribution of systematic errors close to and away from land by examining the statistics of SMOS minus interpolated fields of in situ SSS before and after removal of climatological mean fields. Using interpolated fields of in situ SSS as reference, we find that the precision of monthly SMOS SSS anomalies, SSS ANO , relative to a SMOS SSS monthly climatology computed over four years between 45°N and 45°S is 30% better than the one of SSS when considering pixels further than 1000 km from the coast. This improvement reaches 40% when all pixels are included. At 1600 km from the coast, the standard deviation of the difference between SMOS SSS and in situ interpolated fields is 0.15. These very encouraging results show that it is possible to correct part of the systematic errors in SMOS SSS from the SMOS SSS themselves, pending improvements in SMOS reconstructed brightness temperatures resulting from improved calibration and image reconstruction processes. The largest SSS anomalies are observed in the tropical Indian Ocean as related to Indian Ocean Dipole and in the tropical Pacific Ocean where latitudinal migration of the SSS minimum in the South Pacific Convergence Zone is related to El Niño Southern Oscillation phases and where strong SSS anomalies are observed in the Intertropical Convergence Zone during positive phases of ENSO in early 2010 and in late 2014, early 2015. [ABSTRACT FROM AUTHOR]

The North Brazil Current (NBC) flows offshore of the mouth of the Amazon River and seasonally sheds anticyclonic rings (NBC rings) that propagate northwestward and interact with the Amazon River plume (ARP). Mesoscale features have a high temporal variability that is hard to monitor from current weekly and monthly sea surface salinity (SSS) satellite fields. Novel SSS fields with a higher temporal resolution analyzed together with satellite geostrophic currents, chlorophyll-a, and wind speed and in-situ data from the "Microbiomes cruise" on the SV Tara in August–September 2021 revealed a late summer freshwater pathway, which was not well documented in earlier studies. By combining these datasets, we improved the characterization of summer ARP pathways. In 2021, the ARP was a succession of freshwater patches cut off from the main plume by the NBC rings. A patch of about 200.000 km2 with salinity <33.5 pss was observed in September 2021, bringing 0.5 Sv of Amazon water northwestward in a period where the mean ocean currents lead to eastward transport. This patch was shallow, very stratified, and it created a surface steric-height anomaly that was identified as an anticyclonic feature in altimetric sea level products. Once separated from the NBC retroflection, it was mainly driven by Ekman currents. Other similar patches were observed during the 2021 summer, leading to a strong intermittency of the ARP transport. They strongly contributed to make 2021 the year with the largest northwestward freshwater transport in late summer within the 2010–2021 time-period investigated. This freshwater transport pathway is important for all plume-related phenomena, and show the ability of combined SMOS and SMAP data to accurately represent the day-to-day SSS variability. • New high-resolution satellite fields monitor mesoscale SSS day-to-day variability. • Satellite and in-situ data reveal freshwater patches detached from the Amazon plume. • The pathways of freshwater patches are northwestward and eastward. • Eddies, geostrophic and Ekman currents drive the fresh patches pathways. • Sept. 2021 mesoscale freshwater transport to the north is the largest since 2010. [ABSTRACT FROM AUTHOR]

Monsoon rain and rivers bring large freshwater input to the Northern Bay of Bengal (BoB), yielding low Sea Surface Salinity (SSS) after the monsoon. The resulting sharp upper-ocean salinity stratification is thought to influence tropical cyclones intensity and biological productivity by inhibiting vertical mixing. Despite recent progresses, the density of in situ data is far from sufficient to monitor the BoB SSS variability, even at the seasonal timescale. The advent of satellite remotely-sensed SSS (SMOS, Aquarius, SMAP) offers a unique opportunity to provide synoptic maps of the BoB SSS every ~8 days. Previous SMOS SSS retrievals did not perform well in the BoB. Here, we show that improved systematic error corrections and quality control procedures yield a much better performance of the new "debiased v4" CATDS level-3 SSS from SMOS (~0.8 correlation, 0.04 bias and 0.64 root-mean-square difference to more than 28,000 collocated in situ data points over 2010–2019). The SMOS product now performs equivalently to Aquarius, and is slightly inferior to SMAP over the BoB. In particular, SMAP and SMOS are able to capture salinity variations close to the east coast of India (r > 0.8 within 75–150 km of the coast). They thus capture the seasonal freshening there, associated with equatorward advection of the Northern BoB low-salinity water by the East Indian Coastal Current (EICC) after the summer monsoon. The 10-year long SMOS record further allows to describe the BoB interannual SSS variability, which is strongest in boreal fall in relation with the Indian Ocean Dipole (IOD). Positive IOD events induce a weakening of the southward export of freshwater by the EICC, and hence negative SSS anomalies in the Northern BoB and positive ones along the East Indian coast. This confirms results from earlier studies based on modelling, sparse in situ data, or shorter satellite records, but this time from a 10-year long SSS record. Overall, our study indicates that the new SMOS retrieval can be confidently used to monitor the BoB SSS and to study its mechanisms. We end by a brief description of the BoB SSS anomalies associated with the extreme 2019 IOD event and highlight the very good performance over the BoB of a new multi-satellite product developed by the European Space Agency merging SMOS, Aquarius and SMAP data. • The new debiased CATDS SMOS SSS product resolves major issues in the Bay of Bengal. • New SMOS has a comparable quality with SMAP and Aquarius, but over a full decade. • Confirms the post-monsoon southward transport of low saline water by the EICC. • Confirms that this transport is interannually modulated by the Indian Ocean Dipole. [ABSTRACT FROM AUTHOR]

Operated since the end of 2009, the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite mission is the first orbiting radiometer that collects regular and global observations from space of two Essential Climate Variables of the Global Climate Observing System: Sea Surface Salinity (SSS) and Soil Moisture. The National Aeronautics and Space Administration (NASA) Aquarius mission, with the primary objective to provide global SSS measurements from space operated from mid-2011 to mid-2015. NASA's Soil Moisture Active-Passive (SMAP) mission, primarily dedicated to soil moisture measurements, but also monitoring SSS, has been operating since early 2015. The primary sensors onboard these three missions are passive microwave radiometers operating at 1.4 GHz (L-band). SSS is retrieved from radiometer measurements of the sea surface brightness temperature (T B). In this paper, we first provide a historical review of SSS remote sensing with passive L-band radiometry beginning with the discussions of measurement principles, technology, sensing characteristics and complementarities of the three aforementioned missions. The assessment of satellite SSS products is then presented in terms of individual mission characteristics, common algorithms, and measurement uncertainties, including the validation versus in situ data, and, the consideration of sampling differences between satellite SSS and in situ salinity measurements. We next review the major scientific achievements of the combined first 10 years of satellite SSS data, including the insights enabled by these measurements regarding the linkages of SSS with the global water cycle, climate variability, and ocean biochemistry. We also highlight the new ability provided by satellites to monitor mesoscale and synoptic-scale SSS features and to advance our understanding of SSS' role in air-sea interactions, constraining ocean models, and improving seasonal predictions. An overview of satellite SSS observation highlights during this first decade and upcoming challenges are then presented. • Historical review of sea surface salinity estimates with passive L-band radiometry • SMOS, Aquarius, and SMAP sensor characteristics and algorithms are presented. • Quality assessment of latest satellite SSS products is provided. • The major scientific achievements of the first decade of satellite SSS are reviewed. [ABSTRACT FROM AUTHOR]