Sea Surface Salinity (SSS) is an Essential Climate Variable (ECV) that plays a fundamental role in the density-driven global ocean circulation, the water cycle, and climate. The satellite SSS observation from the Soil Moisture and Ocean Salinity (SMOS), Aquarius, and Soil Moisture Active Passive (SMAP) missions have provided an unprecedented opportunity to map SSS over the global ocean since 2010 at 40-150km scale with a revisit every 2 to 3 days. This observation capability has no historic precedent and has brought new findings concerning the monitoring of SSS variations related with climate variability such as El Niño-Southern Oscillation, Indian Ocean Dipole, and Madden-Julian Oscillation, and the linkages of the ocean with different elements of the water cycle such as evaporation and precipitation and continental runoff. It has enhanced the understanding of various ocean processes such as tropical instability waves, Rossby waves, mesoscale eddies and related salt transport, salinity fronts, hurricane haline wake, river plume variability, cross-shelf exchanges. There are also emerging use of satellite SSS to study ocean biogeochemistry, e.g. linked to air-sea CO2 fluxes.
Following the success of the initial oceanographic studies implementing this new variable, the European Space Agency (ESA) funded a new Climate Change Initiative (CCI) SSS project (2018-2020), or simply CCI+SSS project. The CCI+SSS project (2018-2020) aims at generating improved calibrated global SSS fields over 10 years period (2010-2019) from all available satellite L-band radiometer measurements, extended at regional scale to 2002-2019 from C-band radiometer measurements. It will fully exploit the ESA/Earth explorer SMOS mission complemented with SMAP and AQUARIUS satellite missions. The project gathers teams involved in earth observation remote sensing, in the validation of satellite data and in climate variability study. In this presentation we will summarize results obtained during the first year of the project, the unique contribution of satellite measurements for monitoring SSS and the specific objectives of the CCI-SSS project:
- a definition of the requirements for SSS ECV products relevant for the climate studies and consistent with the satellite SSS achievable performances
- an harmonization of the SSS products and of the radiative transfer models for a long term consistent and stable SSS time series
- a thorough characterization of the uncertainties of the SSS ECV ,
- an assessment of the ECV product through five case studies related to ocean climate variability and hydrological cycle
- Exchange of knowledge between the CCI+SSS team and the international community.
The ESA CCI+SSS consortium gathers scientists and engineers from various European research institutes and companies (LOCEAN/IPSL, LOPS, University of Hambourg, NOC, ICM, ARGANS, ACRI-st, ODL) and is conducted in collaboration with US colleagues from NASA and Remote Sensing System.

In the Gulf of Guinea (GG), Sea Surface Temperature (SST) is a key parameter for modulating air-sea interactions that impact the boreal summer West African Monsoon (WAM). Also, SST can be modulated by the salinity through the upper ocean stratification set up by ocean circulation, turbulence, mixing and intra-seasonal to interannual of freshwater flux from high precipitation and strong river run off, namely Congo and Niger. In this region, strong barrier layers modulate mixed layer thickness, SST and heat content, hence exchange between atmosphere, ocean surface and interior. Therefore, surface thermohaline structure and variability at all scale is an essential element to better understand air-sea exchange in the eastern equatorial Atlantic. However, the 3-D temporal variability, intra-seasonnal to interannual time scale, and small scale thermohaline structure in the eastern GG freshwater plumes remain poorly documented from observations because of scarcity of available data. The main objective of this Ocean Salinity CCI case study is to provide a better knowledge of the surface and subsurface extension of these GG river plumes.
Using SMOS CATDS Sea Surface Salinity (SSS) L3 products, validated with in situ measurements (Argo and CTD profiles from scientific cruises) along with ISAS gridded Argo product, the variability of the plumes of Congo and Niger rivers is described on seasonal to interannual time scale. It is shown that river plumes are more extensive in boreal winter, then exhibit a maximum extension in April where they decrease in summer with a minimal extension in August.
In complement, the analysis of the stratification carried out via salinity, temperature, density, Brunt-Väisälä frequency and Turner angle shows that the water column is driven by the vertical gradient of salinity while, at depth, it is controlled by the temperature gradient. Complex vertical structure of salinity barrier layers is observed off the Congo during repeated scientific cruises and from individual Argo profiles. These results will be analyzed in details and their potential impacts on the physical variability will be addressed.

The southeast Asian Seas (SEAS), situating in the middle of the tropical western-Pacific and eastern Indian Ocean warm pool and under the ascending branch of the Walker Circulation, influence global ocean circulation, climate variability, water cycle, and marine biogeochemistry. Sea surface salinity (SSS) variations in this region are intimately linked to these Earth system elements. The paucity of in-situ salinity measurements in the region has hindered the understanding of SSS variability, the underlying physical processes, and the impacts on ocean circulation. Recent advances in satellite remote sensing has provided a great potential to fill the related knowledge gaps. Here we demonstrate the unprecedented capability of NASA’s SMAP and ESA’s SMOS satellites to depict SSS variations in the SEAS on seasonal-to-interannual time scales during the period of 2010-2018. In particular, we elucidate the roles of monsoon, El Nino, and Indian Ocean Dipole in affecting SEAS SSS changes as well as the impacts on the Indonesian throughflow, which is a critical low-latitude connection of the global ocean circulation.
The monsoonal seasonal cycles in the northern and southern parts of the SEAS are out-of-phase. This results in precipitation patterns that are offset 6 months in time between the northern and southern SEAS, thereby playing important roles in modulating the seasonal variations of SSS in the SEAS. These SSS changes impact the vertical structure and transports of the Indonesian throughflow with important consequences on the exchanges between the Pacific and Indian Oceans. The satellite SSS, together with other satellite measurements (including precipitation, soil moisture, ocean color, and sea level anomaly), help identified the sources of freshwater that control the seasonal SSS of the SEAS and corrected a previous interpretation of the physical mechanism about seasonal variation of SSS in the SEAS. El Nino and Indian Ocean Dipole both tend to suppress atmospheric convection and precipitation in the SEAS region. The relative timing of these two climate modes left clear signature in SSS in the SEAS regions that were captured by SMAP and SMOS. The results have strong implications to longer time scales associated with variability and changes of the Indo-Pacific climate, indicating the importance of sustaining spaceborne SSS measurement capability to monitor longer-term changes and help improve climate models and projections.

A number of weather systems can produce extreme rainfall over the ocean, including squall lines, mesoscale convective complexes, and tropical cyclones (TCs). Intense TCs generate extreme rainfall events with rain rates that can reach local values significantly greater than 45 mm/h, generally found in the vicinity of the storm inner core, but also at the storm’s periphery within the spiraling rain bands (Houze, 2010). These events can last sometimes more than 72 hours with such high rain fall rates (Shepherd et al., 2007). Due to those typically very heavy rains associated with TC, the upper ocean salinity can be substantially freshened by those very large and intermittent fresh water flux into the ocean. Intense vertical mixing at the base of the oceanic mixed layer that is generated concomitantly in the wake of these storms by the TC-induced inertial current shear generally upwells colder and saltier subsurface waters from below the mixed-layer (Price, 1981). The latter rapidly mixes with the fresh water that falls from the atmosphere into the upper ocean: the post-storm upper ocean salinity found in the wake of these extreme is therefore the resultant of these two counter-acting effects. Post-storm salinity in the deepened and homogenized mixed layer can thus exhibit in the storm’s wake alternating spatial patterns of positive and negative salinity anomalies, depending on the pre-storm hydrological conditions and the local balance during the TC passage between the downward freshwater fluxes and the salty water upwelling/mixing strength. Increase in SSS has been observed from SMOS and Aquarius data in the wake of some TCs in the Atlantic when the TCs crossed the Amazon river Plume (Grodsky et al., 2012; Reul et al., 2014).
Whether the imprints of heavy rain impacts on the sea surface salinity can be detected in the wakes of TCs using current observation systems such as satellites and in situ data is one of the questions we attempt to answer here. The variability of both surface and mixed-layer salinity changes in all active TC areas are determined over the period 2000-2018 from the data of the SMOS, Aquarius and SMAP satellite missions and from the ARGO float upper level data as well as surface drifters. TC induced rainfall is characterized using the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM) satellites and TC track databases. Averaged SSS changes in the wake of TCs are characterized as function of TC intensity, translation speed, vertical wind shear, rain fall rate, pre-storm ocean stratification and distance to TC track. We show that both SSS drops and SSS increase are observed dependent on ocean pre-storm stratification, TC translation speed, distance to TC center, TC intensity and local rain rate.

This study investigates the sea surface salinity (SSS) observed by the Soil Moisture Active Passive (SMAP) mission (2015-present) and Soil Moisture Ocean Salinity (SMOS) mission (2011-present) in the open water season in the Hudson Bay and its association with the freshwater flux. A unique large inland sea in northern Canada located in the southern margin of the Arctic Circle, the Hudson Bay is covered by ice and snow in winter. Around 1300 km3 low salinity liquid water trapped in ice is completely melt and released in summer. The length of the open water season has been increasing in recent years, allowing more days during which the SSS can be retrieved from satellite microwave radiometer data (from SMAP and SMOS). The SSS reflects and links the impact of freshwater inputs from river discharge, sea ice changes, surface forcing (P-E), and exchange with northern Atlantic Ocean through the Hudson Strait and Arctic Ocean through the Foxe Basin. Both SMAP (JPL V4) and SMOS (BEC) SSS shows a general pattern of freshening in the James and southern Hudson bay, salty in the northern part, and saltier in the Hudson Strait and the Foxe Basin, which are consistent for three years during (2015-2017). However, the SMAP SSS shows some patches of extreme low SSS with large inter-annual variations, particularly early in the melt season; which is missing in SMOS. Dividing the Hudson Bay system into sub-regions, we examine local freshwater inputs in these regions using data of river discharge, sea ice concentration, surface precipitation and evaporation data. We found river discharges and seasonal sea ice changes are the two dominant processes affecting SSS inter-annual variability, but at different time and places; while the surface forcing (P-E) may play a secondary role. Daily discharge rate from the rivers surrounding the Hudson Bay (Canadian EC) was analyzed. We identified that the low SSS in the eastern Hudson and James Bay in August 2015 could be linked with anomalous positive river discharge through the James Bay, which is 20% more than the three years average. We also derived the local freshwater flux from sea ice change , Ilocal, from the daily sea ice concentration (NSIDC) and ice thickness. Due to a lack of ice thickness observation coincident with SSS data, we used a uniform ice thickness of 1 m (~previous knowledge of average thickness cross the bay) in calculating Ilocal. We found that the low SSS in the northern Hudson Bay interior observed in June 2017 was associated with the early onset of ice melt, which quickly released huge amount of freshwater; while the Bay was mostly frozen in the June of 2015 and 2016. Monthly surface freshwater flux from P (CMAP) minus E (OAflux) shows magnitude much smaller than sea ice melt contribution than Ilocal.

This study deals with the use of Sea Surface Salinity (SSS) space measurements in the context of operational oceanography. The salinity plays an important role in the ocean-atmosphere coupling, especially in the Tropical Pacific when an El-Nino event occurs. However, it is still difficult to assimilate SSS from space in ocean models. This is due to a large extent to large scale observation biases.
Two different ocean forecast systems (Mercator Ocean and Met Office) at ¼° were used to perform an observing system experiment in the context of the ESA SMOS-Nino15 project. These two ocean forecasting systems were tuned and tested to first estimate a consistent residual SSS bias. The proper specification of the observation operator and error covariance matrices were also based on discussions with data providers.
Satellite SSS observations from SMOS, Aquarius and SMAP have been assimilated in the two ocean assimilation systems for more than 2 years simulations (Jan 2014-March 2016). This study helped us to progress in the understanding of the biases and errors that can degrade the satellite SSS assimilation performance. This study shows that with recent data treatment improvements and with a suitable bias correction scheme it is now possible to a have positive impact on short-range ocean forecasts in the tropical Pacific.
SSS data assimilation constrains the model SSS to be closer to the observations in a coherent way with the other data sets already routinely assimilated. Figure 1 shows the Root Mean Square Error (RMSE) differences between the control Run and the run assimilating SSS SMOS for in situ salinity at 5 m depth from both systems during December 2015 and March 2016. This shows that the RMSE is reduced when satellite SSS are assimilated in both systems. We found a slight positive impact over the upper 30 meters when satellite SSS are assimilated.
In addition to the reduction in the near-surface salinity RMS error, other prognostic model variables have also been slightly impacted. For example, at larger space-time scales, the sea surface height has been positively impacted to lead to a reinforcement of the westward phase speed of the Tropical Instability Waves (TIW).
One of the major next steps will be to assimilate SSS from space at higher latitudes where low sea surface temperature (SST) degrades the brightness temperature sensitivity to SSS. A longer ocean reanalysis with continuously improved SSS SMOS (available for over 9 years) and SMAP (available since 2015) data could also bring new information on the water cycle. There is a need to sustain SSS from space in the future, but also to increase the number of in situ data in order to calibrate the satellite data but also to improve the accuracy of the bias correction.