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We identify and analyze tropical instability waves (TIWs) in the equatorial Atlantic Ocean during 2010–2018 using satellite derived observations of sea surface salinity (SSS), sea surface temperature (SST), sea level anomaly, and Argo profiles. In particular, the weekly 50‐km resolution SSS time series from the climate change initiative project provides an unprecedented opportunity to observe the salinity structure at a scale closer to the SST scale. We examine the relative contributions of SSS and SST to the horizontal surface density gradient on seasonal and interannual time scales and how they contribute to the TIW properties and energetics. For the central Atlantic TIWs, the maximum of the SST contribution to the density anomaly lags the SSS one by approximately one month. Argo vertical profiles indicate that temperature and salinity both significantly contribute to TIW‐related density anomalies. In May–June, salinity contributes to 50% of the perturbation potential energy in the top 60 m, and between 30% and 45% from July to September. While variations in SST appear to be related to dynamic processes, the interannual variability of SSS is also influenced by precipitations. However, the two leading modes of variability in the region (Atlantic Meridional and Zonal modes) do not well explain at 1°N these interannual variations. Plain Language Summary: Density is a key variable, influenced by both salinity and temperature and essential to understand the equatorial Atlantic dynamics. Each spring and summer, the horizontal density gradient generated by the equatorial upwelling is subject to undulations associated with tropical instability waves (TIWs). These waves are important features that influence both the ocean dynamics and air‐sea interactions. The scarcity of historical salinity observations has been a limiting factor in the study of the relative role of salinity and temperature (and therefore density) in the TIWs dynamics. To do so, we use here an unprecedented 9‐year satellite‐based dataset together with sea surface temperature and in situ Argo floats data. We show that the Atlantic TIWs seasonal and interannual variations are different in salinity and temperature. The TIWs surface salinity seasonal cycle leads the temperature one by one month. Concerning the wave energetics, salinity is responsible for almost half of the potential energy generated by the density gradient. Contributions of temperature and salinity are similar in May and June, while temperature dominates in July to September. Further characterization of the seasonal cycle, interannual variations, and energetics of TIWs will be necessary to better understand their role in climate. Key Points: Satellite and in situ data highlight large seasonal and interannual variability in the respective roles of salinity and temperature on tropical instability waves (TIWs)TIWs maximum surface salinity signal leads the temperature one by one monthIn the top 60‐m of the ocean, salinity and temperature each contribute to about 50% of the TIWs perturbation potential energy [ABSTRACT FROM AUTHOR]

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]

The Soil Moisture and Ocean Salinity (SMOS) mission carries the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument. It is the first time that an interferometric radiometer is in orbit. The objective of this paper is to assess the quality of the brightness temperatures (TBs) derived from this novel instrument, as processed with the SMOS operational chain at the end of the SMOS commissioning phase. Extensive comparisons have been conducted between reconstructed TBs derived from MIRAS measurements (MIRAS TB) and TBs simulated using the default radiative transfer model implemented in the European Space Agency SMOS ocean salinity processor and the European Centre for Medium-Range Weather Forecast forcings. At first order, the North-South variability of MIRAS TB due to geophysical variations of temperature, salinity, and wind speed over the ocean is consistent with the simulated L-band signal, and the standard deviation of the MIRAS TB minus the model simulations is close to the theoretical radiometric resolution. On the other hand, biases of several Kelvins, that depend on the location in the field of view, are observed between averaged MIRAS TB and simulations. After these biases are removed, the North-South gradient of sea surface salinity is well sensed by MIRAS except at high wind speed. [ABSTRACT FROM AUTHOR]

The Soil Moisture and Ocean Salinity (SMOS) satellite, launched in November 2009, carries the first interferometric radiometer at L-band (1.4 GHz) in orbit. Over the open ocean and for moderate wind speeds (WSs), the SMOS brightness temperatures (TB) are at first order consistent with simulated TB of theoretical prelaunch models implemented in the European Space Agency Level 2 Ocean Salinity processor. However, we found large discrepancies between measurements and model simulations when WS is above 12 ms-1. A new set of parameters for a sea wave spectrum and a foam coverage model that can be used for simulating L-band radiometer data over a large range of WS is proposed based on the deduced wind-induced components from the SMOS data. The quality of the SMOS retrieved sea surface salinity (SSS) with the new emissivity model is estimated by comparing it with the World Ocean Atlas 2005 climatological SSS and the Array for Real-Time Geostrophic Oceanography (ARGO) SSS. [ABSTRACT FROM AUTHOR]

We validate Soil Moisture and Ocean Salinity (SMOS) sea surface salinity (SSS) retrieved during August 2010 from the European Space Agency SMOS processing. Biases appear close to land and ice and between ascending and descending orbits; they are linked to image reconstruction issues and instrument calibration and remain under study. We validate the SMOS SSS in conditions where these biases appear to be small. We compare SMOS and ARGO SSS over four regions far from land and ice using only ascending orbits. Four modelings of the impact of the wind on the sea surface emissivity have been tested. Results suggest that the L-band brightness temperature is not linearly related to the wind speed at high winds as expected in the presence of emissive foam, but that the foam effect is less than previously modeled. Given the large noise on individual SMOS measurements, a precision suitable for oceanographic studies can only be achieved after averaging SMOS SSS. Over selected regions and after mean bias removal, the precision on SSS retrieved from ascending orbits and averaged over 100 km × 100 km and 10 days is between 0.3 and 0.5 pss far from land and sea ice borders. These results have been obtained with forward models not fitted to satellite L-band measurements, and image reconstruction and instrument calibration are expected to improve. Hence, we anticipate that deducing, from SMOS measurements, SSS maps at 200 km × 200 km, 10 days resolution with an accuracy of 0.2 pss at a global scale is not out of reach. [ABSTRACT FROM AUTHOR]

A renewal of interest for the radiometric L-band Sea Surface Salinity (SSS) remote sensing appeared in the 1990s and led to the Soil Moisture and Ocean Salinity (SMOS) satellite launched in November 2009 and to the Aquarius mission (launched in June 2011). However, due to low signal to noise ratio, retrieving SSS from L-band radiometry is very challenging. In order to validate and improve L-band radiative transfer model and salinity retrieval method used in SMOS data processing, the Cooperative Airborne Radiometer for Ocean and Land Studies (CAROLS) was developed. We analyze here a coastal flight (20 May 2009), in the Gulf of Biscay, characterized by strong SSS gradients (28 to 35 pss-78). Extensive in-situ measurements were gathered along the plane track. Brightness temperature (Tb) integrated over 800 ms correlates well with simulated Tb (correlation coefficients between 0.80 and 0.96; standard deviations of the difference of 0.2 K). Over the whole flight, the standard deviation of the difference between CAROLS and in-situ SSS is about 0.3 pss-78 more accurate than SSS fields derived from coastal numerical model or objective analysis. In the northern part of the flight, CAROLS and in-situ SSS agree. In the southern part, the best agreement is found when using only V-polarization measured at 30° incidence angle or when using a multiparameter retrieval assuming large error on Tb (suggesting the presence of biases on H-polarization). When compared to high-resolution model SSS, the CAROLS SSS underlines the high SSS temporal variability in river plume and on continental shelf border, and the importance of using realistic river run-offs for modeling coastal SSS. [ABSTRACT FROM AUTHOR]

With the view of preparing the strategy for the calibration/validation of future L-band satellite radiometers, we examine the salinity variability recorded by Array for Real-Time Geostrophic Oceanography (ARGO) floats in the upper 10-m layer of the surface ocean. Using one year of ARGO measurements,we show that the surface salinity variability at ten days and 200-km scales is above ±0.1 psu for 30% of the drifters and that this variability is larger than 0.2 psu in tropical regions affected by strong river discharges and by precipitations, and in frontal areas characterized by strong mesoscale activity. Vertical gradient observed between 5-10-m depth is much lower than the horizontal variability but leads to systematic biases in the tropics. The South Pacific Ocean appears to be the less variable both vertically and horizontally. [ABSTRACT FROM PUBLISHER]

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]