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Abstract Changes in the Earth’s water cycle can be estimated by analyzing sea surface salinity. This variable reflects the balance between precipitation and evaporation over the ocean, since the upper layers of the ocean are the most sensitive to atmosphere–ocean interactions. In situ measurements lack spatial and temporal synopticity and are typically acquired at few meters below the surface. Satellite measurements, on the contrary, are synoptic, repetitive and acquired at the surface. Here we show that the satellite-derived sea surface salinity measurements evidence an intensification of the water cycle (the freshest waters become fresher and vice-versa) which is not observed at the in-situ near-surface salinity measurements. The largest positive differences between surface and near-surface salinity trends are located over regions characterized by a decrease in the mixed layer depth and the sea surface wind speed, and an increase in sea surface temperature, which is consistent with an increased stratification of the water column due to global warming. These results highlight the crucial importance of using satellites to unveil critical changes on ocean–atmosphere fluxes.

We present a comprehensive review of the current status of remotely sensed and in situ sea ice, ocean, and land parameters acquired over the Arctic and Antarctic and identify current data gaps through comparison with the portfolio of products provided by Copernicus services. While we include several land parameters, the focus of our review is on the marine sector. The analysis is facilitated by the outputs of the KEPLER H2020 project. This project developed a road map for Copernicus to deliver an improved European capacity for monitoring and forecasting of the Polar Regions, including recommendations and lessons learnt, and the role citizen science can play in supporting Copernicus’ capabilities and giving users ownership in the system. In addition to summarising this information we also provide an assessment of future satellite missions (in particular the Copernicus Sentinel Expansion Missions), in terms of the potential enhancements they can provide for environmental monitoring and integration/assimilation into modelling/forecast products. We identify possible synergies between parameters obtained from different satellite missions to increase the information content and the robustness of specific data products considering the end-users requirements, in particular maritime safety. We analyse the potential of new variables and new techniques relevant for assimilation into simulations and forecasts of environmental conditions and changes in the Polar Regions at various spatial and temporal scales. This work concludes with several specific recommendations to the EU for improving the satellite-based monitoring of the Polar Regions.

This study assesses the capability of Surface Quasi-Geostrophy (SQG) to reconstruct the three-dimensional (3D) dynamics in four critical areas of the Arctic Ocean: the Nordic, Barents, East Siberian, and Beaufort Seas. We first reconstruct the upper ocean dynamics from TOPAZ4 reanalysis of sea surface height (SSH), surface buoyancy (SSB), and surface velocities (SSV) and validate the results with the geostrophic and total TOPAZ4 velocities. The reconstruction of upper ocean dynamics using SSH fields is in high agreement with the geostrophic velocities, with correlation coefficients greater than 0.8 for the upper 400 m. SSH reconstructions outperform surface buoyancy reconstructions, even in places near freshwater inputs from river discharges, melting sea ice, and glaciers. Surface buoyancy fails due to the uncorrelation of SSB and subsurface potential vorticity (PV). Reconstruction from surface currents correlates to the total TOPAZ4 velocities with correlation coefficients greater than 0.6 up to 200 m. In the second part, we apply the SQG approach validated with the reanalysis outputs to satellite-derived sea level anomalies and validate the results against in-situ measurements. Due to lower water column stratification, the SQG approach’s performance is better in fall and winter than in spring and summer. Our results demonstrate that using surface information from SSH or surface velocities, combined with information on the stratification of the water column, it is possible to effectively reconstruct the upper ocean dynamics in the Arctic and Subarctic Seas up to 400 m. Future remote sensing missions in the Arctic Ocean, such as SWOT, Seastar, WaCM, CIMR, and CRISTAL, will produce enhanced SSH and surface velocity observations, allowing SQG schemes to characterize upper ocean 3D mesoscale dynamics up to 400 m with higher resolutions and lower uncertainties.

The Vendée Globe is the world’s most famous solo, non-stop, unassisted sailing race. The Institute of Marine Sciences and the Barcelona Ocean Sailing Foundation installed a MicroCAT on the One Ocean One Planet boat. The skipper, Dídac Costa, completed the round trip in 97 days, from 8 November 2020 to 13 February 2021, providing one measurement of temperature and conductivity every 30 s during navigation. More than half of the ship’s route was in the sub-Antarctic zone, between the tropical and polar fronts, and it passed through areas of oceanographic interest such as Southern Patagonia (affected by glacier melting), the Brazil–Malvinas confluence, the Southern Pacific Ocean, and the entire Southern Indian Ocean. This sailing race gave a rare opportunity to measure in-situ sea surface salinity in a region where satellite salinity measurements are not reliable. Due to the decreased sensitivity of brightness temperature to salinity in cold seas, retrieving sea surface salinity at high latitudes remains a major challenge. This paper describes how the data are processed and uses the data to validate satellite salinity products in the sub-Antarctic zone. The sailing race measurements represent surface information (60 cm depth) not available from drifters or Argo floats. Acquiring measurements using round-the-world sailing races would allow us to analyse the evolution of ocean salinity and the impact of changes in the ice extent around Antarctica.

Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission capable of measuring sea surface salinity and soil moisture from space. Its novel instrument (the L-band radiometer MIRAS) has required the development of new algorithms to process SMOS data, a challenging task due to many processing issues and the difficulties inherent in a new technology. In the wake of SMOS, a new community of users has grown, requesting new products and applications, and extending the interest in this novel brand of satellite services. This paper reviews the role played by the Barcelona Expert Centre under the direction of Jordi Font, SMOS co-principal investigator. The main scientific activities and achievements and the future directions are discussed, highlighting the importance of the oceanographic applications of the mission.

This article summarizes some of the activities in which Jordi Font, research professor and head of the Department of Physical and Technological Oceanography, Institut de Ciències del Mar (CSIC, Spanish National Research Council) in Barcelona, has been involved as co-Principal Investigator for Ocean Salinity of the European Space Agency Soil Moisture and Ocean Salinity (SMOS) Earth Explorer Mission from the perspective of the Remote Sensing Lab at the Universitat Politècnica de Catalunya. We have probably left out some of his many contributions to salinity remote sensing, but we hope that this review will give an idea of the importance of his work. We focus on the following issues: 1) the new accurate measurements of the sea water dielectric constant, 2) the WISE and EuroSTARRS field experiments that helped to define the geophysical model function relating brightness temperature to sea state, 3) the FROG 2003 field experiment that helped to understand the emission of sea foam, 4) GNSS-R techniques for improving sea surface salinity retrieval, 5) instrument characterization campaigns, and 6) the operational implementation of the Processing Centre of Levels 3 and 4 at the SMOS Barcelona Expert Centre.

This book celebrates the ten year anniversary of the Barcelona Expert Center by presenting recent contributions related to the topics on which the team has been working during those years. The Barcelona Expert Center’s expertise covers a wide variety of remote sensing fields, but the main focus of the research is on the SMOS data processing and its ocean, land, and ice applications. This book contains 14 scientific papers addressing topics that go from the description of the new data processing algorithms that are implemented in the last version of the operational SMOS level 1 processor to scientific applications derived from SMOS: results on the sea-surface salinity assimilation in coastal models, synergies of the sea-surface salinity with temperature and chlorophyll and their impact on the better retrieval of ocean surface currents, quality assessment of SMOS-derived sea ice thickness, sea-surface salinity, and soil moisture products, among others. Moreover, one of the papers verifies the potential of the future Copernicus Imaging Microwave Radiometer (CIMR) mission within the CMEMS sea-surface salinity (SSS) operational production after the SMOS era.

Hudson Bay (HB) is the largest semi-inland sea in the Northern Hemisphere, connecting with the Arctic Ocean through the Foxe Basin and the northern Atlantic Ocean through the Hudson Strait. HB is covered by ice and snow in winter, which completely melts in summer. For about six months each year, satellite remote sensing of sea surface salinity (SSS) is possible over open water. SSS links freshwater contributions from river discharge, sea ice melt/freeze, and surface precipitation/evaporation. Given the strategic importance of HB, SSS has great potential in monitoring the HB freshwater cycle and studying its relationship with climate change. However, SSS retrieved in polar regions (poleward of 50°) from currently operational space-based L-band microwave instruments has large uncertainty (~ 1 psu) mainly due to sensitivity degradation in cold water (

The authors wish to make the following corrections to this paper [...]

Capability for sea surface salinity observation was an important gap in ocean remote sensing in the last few decades of the 20th century. New technological developments during the 1990s at the European Space Agency led to the proposal of SMOS (Soil Moisture and Ocean Salinity), an Earth explorer opportunity mission based on the use of a microwave interferometric radiometer, MIRAS (Microwave Imaging Radiometer with Aperture Synthesis). SMOS, the first satellite ever addressing the observation of ocean salinity from space, was successfully launched in November 2009. The determination of salinity from the MIRAS radiometric measurements at 1.4 GHz is a complex procedure that requires high performance from the instrument and accurate modelling of several physical processes that impact on the microwave emission of the ocean’s surface. This paper introduces SMOS in the ocean remote sensing context, and summarizes the MIRAS principles of operation and the SMOS salinity retrieval approach. It describes the Spanish SMOS high-level data processing centre (CP34) and the SMOS Barcelona Expert Centre on Radiometric Calibration and Ocean Salinity (SMOS-BEC), and presents a preliminary validation of global sea surface salinity maps operationally produced by CP34.

This work summarizes the activities carried out by the SMOS (Soil Moisture and Ocean Salinity) Barcelona Expert Center (SMOS-BEC) team in conjunction with the CIALE/Universidad de Salamanca team, within the framework of the European Space Agency (ESA) CALIMAS project in preparation for the SMOS mission and during its first year of operation. Under these activities several studies were performed, ranging from Level 1 (calibration and image reconstruction) to Level 4 (land pixel disaggregation techniques, by means of data fusion with higher resolution data from optical/infrared sensors). Validation of SMOS salinity products by means of surface drifters developed ad-hoc, and soil moisture products over the REMEDHUS site (Zamora, Spain) are also presented. Results of other preparatory activities carried out to improve the performance of eventual SMOS follow-on missions are presented, including GNSS-R to infer the sea state correction needed for improved ocean salinity retrievals and land surface parameters. Results from CALIMAS show a satisfactory performance of the MIRAS instrument, the accuracy and efficiency of the algorithms implemented in the ground data processors, and explore the limits of spatial resolution of soil moisture products using data fusion, as well as the feasibility of GNSS-R techniques for sea state determination and soil moisture monitoring.

This paper aims to present and assess the quality of seven years (2011⁻2017) of 25 km nine-day Soil Moisture and Ocean Salinity (SMOS) Sea Surface Salinity (SSS) objectively analyzed maps in the Arctic and sub-Arctic oceans ( 50 ∘ N⁻ 90 ∘ N). The SMOS SSS maps presented in this work are an improved version of the preliminary three-year dataset generated and freely distributed by the Barcelona Expert Center. In this new version, a time-dependent bias correction has been applied to mitigate the seasonal bias that affected the previous SSS maps. An extensive database of in situ data (Argo floats and thermosalinograph measurements) has been used for assessing the accuracy of this product. The standard deviation of the difference between the new SMOS SSS maps and Argo SSS ranges from 0.25 and 0.35. The major features of the inter-annual SSS variations observed by the thermosalinographs are also captured by the SMOS SSS maps. However, the validation in some regions of the Arctic Ocean has not been feasible because of the lack of in situ data. In those regions, qualitative comparisons with SSS provided by models and the remotely sensed SSS provided by Aquarius and SMAP have been performed. Despite the differences between SMOS and SMAP, both datasets show consistent SSS variations with respect to the model and the river discharge in situ data, but present a larger dynamic range than that of the model. This result suggests that, in those regions, the use of the remotely sensed SSS may help to improve the models.

In preparation for the European Space Agency SMOS (Soil Moisture and Ocean Salinity) satellite mission, radiometric and oceanographic measurements were performed in December 2000 and January 2001 and in November 2001 from a fixed platform in the NW Mediterranean to improve the modelling of the sea surface emissivity at L-band and new semi-empirical models were derived. Now one of these models has been used to retrieve sea surface salinity from L-band radiometric data acquired with a different instrument and different location. These data were acquired in August 2003 over the continental shelf within the influence of the Rio de la Plata, from Argentina to Brazil, southern Atlantic ocean with the STARRS airborne radiometer. Results show that the radiometer is capable of realistically detecting natural variations in surface salinity even though the model was derived in very different oceanographic conditions and from data collected by a different instrument.

The retrieval of sea ice thickness using L-band passive remote sensing requires robust models for emission from sea ice. In this work, measurements obtained from surface-based radiometers during the MOSAiC expedition are assessed with the Burke, Wilheit and SMRT radiative transfer models. These models encompass distinct methodologies: radiative transfer with/without wave coherence effects, and with/without scattering. Before running these emission models, the sea ice growth is simulated using the Cumulative Freezing Degree Days (CFDD) model to further compute the evolution of the ice structure during each period. Ice coring profiles done near the instruments are used to obtain the initial state of the computation, along with Digital Thermistor Chain (DTC) data to derive the sea ice temperature during the analyzed periods. The results suggest that the coherent approach used in the Wilheit model results in a better agreement with the horizontal polarization of the in situ measured brightness temperature. The Burke and SMRT incoherent models offer a more robust fit for the vertical component. These models are almost equivalent since the scattering considered in SMRT can be safely neglected at this low frequency, but the Burke model misses an important contribution from the snow layer above sea ice. The results also suggest that a more realistic permittivity falls between the spheres and random needles formulations, with potential for refinement, particularly for L-band applications, through future field measurements.