International audience

Measurements have been made at P-band (0.707 GHz) to construct a model for the dielectric constant of sea water and extend the model for the dielectric constant to high salinity [$S \gt 50$practical salinity scale (pss)]. The measurements are part of research to develop a model for the dielectric constant suitable for future wide-bandwidth (BW) remote sensing of salinity and for application to water bodies, such as the Great Salt Lake with salinity significantly above that found in the open ocean. Measurements have been made at temperatures from 2 °C to 30 °C and salinity from 0 to 138 pss. The data have been fit to a Debye model for the dielectric constant with a single relaxation mode as has been employed at L-band (1.413 GHz), where remote sensing of salinity is currently done. Comparison with contemporary models developed from data at L-band indicates that the L-band model and new P-band model do well at both frequencies for salinity less than 50 pss, but at higher values of salinity, the L-band models diverge from the data. The data have also been used to test at high salinity the mathematical relationship between salinity and conductivity, which is the basis for the pss.

above article [1], the corrections are needed for signs in (3b) and (5a) and for the location of the decimal point in the first term in (8b). Equations (3b) and (5a) with the correct signs are \begin{align*} & \varepsilon _{s}\left ({{S, T}}\right) =\varepsilon _{s}\left ({{0, T}}\right)\left [{{1-\text {SR}\left ({{S, T}}\right)}}\right]\tag {3b}\\[8pt] & \tau \left ({{0, ~T }}\right) = \left [{{17.9539-0.6955 ~T+ 0.0177 ~T ^{2}-0.0002 ~T ^{3}}}\right]10^{-12.} \tag {5a}\end{align*}

This research focuses on the impact of Radio Frequency Interference (RFI) on the accuracy of Sea Surface Salinity (SSS) measurements obtained from the Soil Moisture Ocean Salinity (SMOS) mission. RFI can affect the accuracy of SSS measurements in regions that are crucial for understanding ocean dynamics and climate change. The extent of RFI contamination in SMOS SSS data varies based on the location of SSS across the swath. This variability is exploited in our study by comparing SSS fields constructed from different swath locations. We employ Principal Component Analysis (PCA) and regression techniques to correct RFI signatures in SMOS SSS data. The effectiveness of this correction is validated through comparison with independent SSS data derived from an in-situ dataset (global SSS field), and with RFI probability (CESBIO dataset). Our results show that this approach significantly improves the accuracy of SSS data in regions affected by RFI. In particular, the correction procedure is able to restore the SSS variability associated with El Nino Southern Oscillation (ENSO) using a method based solely on the anomalies of the SMOS measurements. We also explore two correction methods: a regional correction (RM) and a pointwise correction (PM). While PM allows for independent correction of RFI contamination at each location without needing prior information about the RFI source or affected area, RM is more effective in areas with high SSS variability. The potential for combining these two methods will be further discussed at the conference.

Our study focuses on the variability of Sea Surface Salinity (SSS) near south Greenland. This is based on extensive in situ data gathered from a variety of sources, including Argo floats, CTD casts, thermosalinographs, and drifters, as well as the satellite-derived SSS product from the Climate Change Initiative (CCI). The CCI SSS effectively captures a significant portion of the salinity’s seasonal and interannual variability beyond 50km from the coast, outperforming SSS from individual satellite missions. The examination of a well-sampled fresh blob in fall 2021 suggests that satellite SSS is a valuable tool for studying freshwater transfer from the shelves to the deeper ocean, particularly during ice-free periods. However, we found positive biases in the CCI SSS on the shelves, highlighting the need for improved absolute calibration in these areas. For a more detailed study of SSS within 50km of the coast, a satellite SSS with a higher spatial resolution would be required.

The Fine Resolution Explorer for Salinity, Carbon and Hydrology (FRESCH) is presented. The science case and the mission objectives are discussed before presenting the mission concept. FRESCH is an L-band antenna array operated in beamforming mode providing data at a spatial resolution of 10-15 km to study the biogeochemical and physical phenomena taking place at the interfaces of ocean, land and ice. FRESCH has been submitted to the European Space Agency Earth Explorer 12 program.

The Soil Moisture and Ocean Salinity (SMOS) satellite mission, operational since 2010, relies on an L-Band microwave interferometric radiometer to generate brightness temperature images along the swath, with global coverage every 3 days. These images are then used to derive sea surface salinity (SSS) with an effective resolution of less than 50 km. However, signal acquisition in some ocean regions is intermittently and significantly disrupted by radio-frequency interferences (RFI) from various terrestrial military or civilian sources worldwide. We develop a new methodology based on principal component and regression analyses to extract the RFI signatures in time and space, thereby enabling the construction of a corrected SSS estimate along the swath. This method successfully filters out many disruptive features characterized by long and wide branches occurring around the RFI sources, hence recovering SSS variability as demonstrated in comparison to in situ reference data. This correction methodology is an alternative to separate filtering procedures that were applied on brightness temperature at Level 1. Independent information indicating the probability of RFI occurrence on land areas or nearby is used to verify the timing of oceanic RFI contamination inferred by the correction process. The methodology performs particularly well in areas where the probability is close to 1 for a significant and contiguous portion of the entire period. Already applied with significant improvement in three selected regions, this correction method is a starting point for expanding and systematizing the methodology to treat as many RFI-polluted regions as possible and to recover SMOS SSS variability.

Recent applications of passive L-band observations from space are summarized for ocean, land surface and cryosphere applications. The main limitation of the measurements performed by the current generation of sensors is the spatial resolution. The need of a mission ensuring the continuation of L-band measurements from space with high spatial resolution (10-15 km) is discussed.

The accuracy of the Sea Surface Salinity (SSS) retrieved from L-Band radiometer measurements is strongly dependent on the reliability of the dielectric constant model. Two new parametrizations were recently developed based on one hand on the Soil Moisture and Ocean Salinity (SMOS) satellite multi-angular brightness temperature measurements by Boutin et al. (2021) (BV), and on the other hand on new George Washington University laboratory measurements by Zhou et al. (2021) (GW2020). These two approaches are fully independent. For most SSS and Sea Surface Temperature (SST) conditions commonly observed over the open ocean, the relative variations of brightness temperatures Tb simulated through the BV and GW2020 parametrizations agree particularly well, and better than with earlier parametrizations previously used in the SMOS, Soil Moisture Active Passive (SMAP) and Aquarius SSS retrievals. Nevertheless, uncertainty remains, especially below 10°C where a ~0.1K relative difference between the two models is observed. This motivates the development of a revised parameterization, BVZ, based on a methodology similar to that used to derive BV but using GW2020 instead of SMOS measurements. Compared to the GW2020 parameterization, BVZ is derived with a reduced number of degrees of freedom, it relies on TEOS10 PSS78 conductivity-salinity relationship and on previously derived static permittivity of fresh water. One month per season of SMOS data have been reprocessed in 2018 using BV, GW2020 and BVZ. We find the best overall agreement between SMOS SSS and Argo SSS with BVZ parametrization, with noticeable improvement in the 5°C-15°C SST range.

We model the sea foam emissivity at frequencies from 1 to 89 GHz. This model is part of the work done by an international science team to develop a radiative transfer model of reference quality for the ocean surface emissivity from L band to infrared frequencies. A study of the sensitivity to different foam properties (foam layer thickness and upper limit of the foam void fraction) guided the effort to tune the foam emissivity model by frequency and polarization. The results show that the differences between simulated and observed brightness temperatures decrease when using the tuned foam model.

International audience

Sea surface salinity is retrieved for more than 11 years from the Soil Moisture and Ocean Salinity (SMOS) satellite mission. This data set provides a unique monitoring of the Sea Surface Salinity (SSS) spatio-temporal variability at global scale. It is particularly useful to follow the surface ocean pathway of fresh river plumes water as illustrated here in the Bay of Bengal. A revised adjustment of the whole SMOS SSS time series (CATDS Expertise Center version 5, 2010–2020) leads to clear reduction of local biases in very variable regions and in very noisy regions. The robust std difference between SMOS CEC v5 (18-day, ~70km SSS) and Argo in situ SSS is 0.17 in regions warmer than 5°C. We will discuss how future CATDS products will be improved in view of two ongoing reprocessings, the CATDS L1/L2 v7 reprocessing and the ESA CCI+SSS L2 SMOS reprocessing.

The accuracy of the Sea Surface Salinity (SSS) retrieved from L-Band radiometer measurements is strongly dependent on the accuracy of the modelling of the dielectric constant (ε). Two new ε parametrizations have recently been developed based on one hand on the Soil Moisture and Ocean Salinity (SMOS) satellite multi-angular brightness temperature measurements and on the other hand on new laboratory measurements. These two approaches are fully independent. These new ε parametrizations are compared with each other and with the ε models previously in use in the SMOS, Soil Moisture Active Passive (SMAP) and Aquarius SSS retrievals. The two new ε parametrizations are found to be in closer agreement than with earlier parametrizations for most common ocean conditions. We will further study to which extent the recent SMOS CCI+SSS v3 reprocessing confirms the above results and could help resolve remaining inconsistencies.

The European Space Agency (ESA) Climate Change Initiative (CCI+) for Sea Surface Salinity (SSS) aims at generating global SSS fields from all available satellite L-band radiometer measurements over the longest possible period with a great stability (including Soil Moisture and Ocean Salinity, SMOS). Version 1 and 2 of CCI+SSS level 4 fields combine SSS form the three satellite L-Band radiometer missions and have been found to be in a very good agreement with in situ measurements (global rms difference of 0,16 pss). Nevertheless, some systematic differences still remain between CCI+SSS and in situ SSS. We study here to which extent some errors coming from the SMOS SSS processing are reduced, when making some key changes in the SMOS level 2 OS processing. Then, we discuss the contribution of each change in the preliminary results we obtain.

The Soil Moisture and Ocean Salinity (SMOS) satellite is performing systematic L-band observations since 2009, allowing a large number of science and operational applications. Several recent studies have shown the need of the continuity of L-band observations, in particular with an increased angular resolution. In this contribution, two instrumental concepts are presented to reach native resolutions of 5–10 km. In addition, using airborne data, it is also shown that the accuracy of downscaling coarser resolution L-band data to 5–10 km using a high resolution auxiliary data set, is significantly lower than that of native high resolution observations.

Earlier studies have pointed out systematic differences between sea surface salinity retrieved from L-band radiometric measurements and measured in situ, which depend on sea surface temperature (SST). We investigate how to cope with these differences given existing physically based radiative transfer models. In order to study differences coming from seawater dielectric constant parametrization, we consider the model of Somaraju and Trumpf (2006) (ST) which is built on sound physical bases and close to a single relaxation term Debye equation. While ST model uses fewer empirically adjusted parameters than other dielectric constant models currently used in salinity retrievals, ST dielectric constants are found close to those obtained using the Meissner and Wentz (2012) (MW) model. The ST parametrization is then slightly modified in order to achieve a better fit with seawater dielectric constant inferred from SMOS data. Upgraded dielectric constant model is intermediate between KS and MW models. Systematic differences between SMOS and in situ salinity are reduced to less than +/-0.2 above 0 °C and within +/-0.05 between 7 °C and 28 °C. Aquarius salinity becomes closer to in situ salinity, and within +/-0.1. The order of magnitude of remaining differences is very similar to the one achieved with the Aquarius version 5 empirical adjustment of wind model SST dependence. The upgraded parametrization is recommended for use in processing the SMOS data. Further assessment or improvement using new laboratory measurements should consider keeping the physics-based formulation by ST that has been shown here to be very efficient.

The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) has been providing the longest consistent data record of passive L-band (1.4 GHz) observations for more than ten years. SMOS, as well as the NASA missions SMAP and Aquarius have demonstrated the interest of L-band observations for land, ocean and cryosphere studies. The continuity of L-band observations must be assured taking into account that the spatial resolution (~ 40 km) of SMOS and SMAP is too coarse for some applications. Disaggregation strategies can be implemented but using airborne data, we show that the quality of the downscaled data cannot match that of an instrument with higher native resolution. The goal of the SMOS-HR (High Resolution) mission is to ensure the continuity of L-band observations while increasing the native resolution to 10 km. SMOS-HR will carry an array of ~ 230 antennas to perform aperture synthesis. The antenna distribution has been optimized to reduce the aliasing in the reconstructed images and SMOS-HR will incorporate advanced on-board Radio Frequency Interferences (RFI) mitigation techniques.

We present comparisons between satellite sea surface salinity products from the SMOS, Aquarius and SMAP missions and assess some of the reasons for the observed differences. We reprocess Aquarius retrievals using the dielectric constant model and ancillary sea surface temperature product used for SMOS. We also quantify the impact of the recently revised atmospheric model for Aquarius end of mission product. One recurrent feature of the SSS difference between satellite retrieval and in situ observation has been its dependence on sea surface temperature. We discuss the performances of the latest algorithms in mitigating this bias and possible improvements in theoretical models.

The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite has provided, for the first time, systematic passive L-band (1.4 GHz) measurements from space. This new data set, with a spatial resolution of ~40 km, has allowed a number of outstanding results over land (soil moisture, vegetation properties, frozen soils, ...), ocean (salinity, meso-scale phenomena, river plumes, high winds, ...) and cryosphere. SMOS, together with the NASA missions SMAP and Aquarius, have demonstrated the interest of the continuity of L-band observations. However, higher spatial resolution (1-10 km) is needed for applications related to water resources management and food security, for instance. Over the ocean as well as in coastal areas, higher resolution will bring the possibility to study in detail meso-scale processes and salinity (and density) variations closer to the coast. Over ice, higher spatial resolution will allow to monitor melting events in the coastal regions of Antarctica, for instance. In order to ensure the continuity of Earth observations in the L-band, while improving the resolution of the current generation of radiometers, new mission concepts are needed. We present the SMOS-HR (High-Resolution) project, which is currently in Phase 0 at CNES (Centre National d'Etudes Spatiales).

An important contribution of satellite Sea Surface Salinity (SSS) is the spatio-temporal monitoring of rivers fresh water plumes at mesoscale. In this paper, we detail a new correction for systematic errors in the Soil Moisture and Ocean Salinity (SMOS) measurements that is implemented in the Centre Aval de Traitement des Donnees SMOS (CATDS). With this new mitigation, the SMOS and Soil Moisture Active Passive (SMAP) SSS monitor very consistent features in most areas close to continents. The rms-difference between bi-weekly SMOS and SMAP SSS over 20 months and in selected coastal regions is about 0.3pss (once outliers are filtered out), rather consistent with the rms-difference between satellite and in situ SSS (on the order of 0.2pss). The coefficient of determination (r2) between SMOS and SMAP SSS is above than 0.8 in very fresh areas (river plumes). Over the open ocean, the rms difference between SMOS and ship SSS is 0.2pss.

After almost 9 years in orbit L band satellite radiometry has demonstrated its impacts and values for a wide range of science and applications. In some cases it has demonstrated its uniqueness for assessing key environmental variables and in many others its high impact.

Earth's cold regions are key elements of the planet's climate system: they have strong feedbacks with global change and they have a direct impact on human activities. Despite their importance, at present they are not adequately monitored by state-of-the-art instruments. In order to fill this gap, a dedicated spaceborne mission called Cryorad has been proposed in the framework of the ESA Earth Explorer 10 call. The mission would comprise a 0.4-2 GHz nadir-looking radiometer installed on a polar-orbit satellite. Scientific and technical studies are underway, as well as experimental campaigns in Greenland and Antarctica.

We present comparisons between satellite sea surface salinity products from the SMOS, Aquarius and SMAP missions and assess some of the reasons for the observed differences. To do so, we reprocess Aquarius retrievals using the dielectric constant model and ancillary sea surface temperature product used for SMOS. We quantify their impact on the differences between SMOS and Aquarius, and validate the various Aquarius algorithms using in situ salinity measurements. Among the significant difference in retrieved sea surface salinity are the dependence to sea surface temperature and coastal biases. New approaches to for land contamination correction will be presented.

Sea Surface Salinity (SSS) measurements from the Soil Moisture and Ocean Salinity (SMOS) mission during 3 years (June 2010-May 2013) provide an unprecedented opportunity to observe the salinity structure of Tropical Instability Waves (TIWs) from space. The variations of SMOS SSS signals follow Tropical Atmosphere Ocean (TAO) SSS signals with high correlation coefficients and close peak amplitudes at 5 locations where strong TIW signals are observed in TAO SSS. The east-west contrast in peak amplitudes of SMOS SSS signals is stronger than OSTIA SST signals. Band of negative correlations between SSS and SST signals appears just north of the equator west of 100°W and around 8°N west of 110°W for the 33-day signals.

The sea surface salinity (SSS) retrieved from the Soil Moisture and Ocean Salinity (SMOS) mission are systematically lower than ARGO SSS in rainy regions. These freshenings increase (in absolute value) with increasing SSM/I rain rates (−0.2psu/mm/hr) closely collocated in time with SMOS SSS. They are attributed to a stratification of the salinity in the first meters of the ocean surface following a rain event.

The variability observed on SMOS (Soil Moisture and Ocean Salinity) SSS (sea surface salinity) recorded in 2010 and 2011 is partly attributable to geophysical variations but also to imperfections in various corrections (e.g. sun aliases, sea surface scattering of the galactic signal). We perform a retrieval of bistatic coefficients from SMOS Tbs, suggesting more peaked coefficients than the ones currently used for simulating the galactic contribution.

Two years after the launch of SMOS (Soil Moisture and Ocean Salinity) in November 2009, the level 1C brightness temperatures processed with the ESA SMOS L1 operational prototype v504, the up-to-date ESA reprocessing version, were released. Systematic biases of several Kelvins, which depend on the location of the measurement in the field of view, are still observed between averaged TB measurements and simulations. Biases in the field of view derived from comparisons between measurements and simulations (the so-called Ocean Target Transformations, OTTs) during 38 periods in phase with the NIR calibration events from June 2010 to December 2012 are analyzed.

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$ \times$100 km and 10 days is between 0.3 and 0.5 pss far from land and sea ice borders. These results have been obtained with forward models not fitted to satellite L-band measurements, and image reconstruction and instrument calibration are expected to improve. Hence, we anticipate that deducing, from SMOS measurements, SSS maps at 200 km$\times$200 km, 10 days resolution with an accuracy of 0.2 pss at a global scale is not out of reach.

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$(T_{b})$integrated over 800 ms correlates well with simulated$T_{b}$(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$^{\circ}$incidence angle or when using a multiparameter retrieval assuming large error on$T_{b}$(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.

Multi-angular images of the brightness temperature (TB) of the Earth at 1.4 GHz are reconstructed from the Soil Moisture and Ocean Salinity (SMOS) satellite sensor data since end 2009. Sea surface salinity (SSS) products remote sensing from space is being attempted using these data over the world oceans. The quality of the first version of the European Space Agency operational Level 2 (L2) SSS swath products is assessed in this paper, using satellite/in situ SSS data match-ups that were collected over the second half of 2010. This database reveals that 95% of the SMOS L2 products show a global error standard deviation on the order of ~ 1.3 practical salinity scale. Simple spatiotemporal aggregation of the L2 products to generate monthly SSS maps at 1° ×1° spatial resolution reduces the error down to about 0.6 globally and 0.4 in the tropics for 90% of the data. Several major problems are, however, detected in the products. Systematically, SMOS SSS data are biased within a ~ 1500 km wide belt along the world coasts and sea ice edges, with a contamination intensity and spread varying from ascending to descending passes. Numerous world ocean areas are permanently or intermittently contaminated by radio-frequency interferences, particularly in the northern high latitudes and following Asia coastlines. Moreover, temporal drifts in the retrieved SSS fields are found with varying signatures in ascending and descending passes. In descending passes, a time-dependent strong latitudinal bias is found, with maximum amplitude reached at the end of the year. Errors in the forward modeling of the wind-induced emissivity and of the sea surface scattered galactic sources are as well identified, biasing the sss retrievals at high and low winds and when the galactic equator sources are reflected toward the sensor.

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$\hbox{ms}^{-1}$. 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.

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.

SMOS (Soil Moisture and Ocean Salinity) satellite, launched in November 2009, carries the first interferometric radiometer at L band (1.4GHz) in orbit. Over the open ocean and for moderate wind speeds, SMOS brightness temperatures (TB) are at first order consistent with simulated TB of theoretical pre-launch models implemented in the ESA Level 2 Ocean Salinity processor. However, we found large discrepancies between measurements and model simulations when wind speed 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 wind speed is proposed based on the deduced wind induced component from SMOS data. The quality of SMOS retrieved SSS with the new emissivity model is estimated by comparing it with WOA05 climatological SSS.

SMOS (Soil Moisture and Ocean Salinity), launched in November 2, 2009 is the first satellite mission addressing the salinity measurement from space through the use of MIRAS (Microwave Imaging Radiometer with Aperture Synthesis), a new two-dimensional interferometer designed by the European Space Agency (ESA) and operating at L-band. This paper presents a summary of the sea surface salinity retrieval approach implemented in SMOS, as well as first results obtained after completing the mission commissioning phase in May 2010. A large number of papers have been published about salinity remote sensing and its implementation in the SMOS mission. An extensive list of references is provided here, many authored by the SMOS ocean salinity team, with emphasis on the different physical processes that have been considered in the SMOS salinity retrieval algorithm.

Soil Moisture and Ocean Salinity, European Space Agency, is the first satellite mission addressing the challenge of measuring sea surface salinity from space. It uses an L-band microwave interferometric radiometer with aperture synthesis (MIRAS) that generates brightness temperature images, from which both geophysical variables are computed. The retrieval of salinity requires very demanding performances of the instrument in terms of calibration and stability. This paper highlights the importance of ocean salinity for the Earth's water cycle and climate; provides a detailed description of the MIRAS instrument, its principles of operation, calibration, and image-reconstruction techniques; and presents the algorithmic approach implemented for the retrieval of salinity from MIRAS observations, as well as the expected accuracy of the obtained results.

It is now well understood that data on soil moisture and sea surface salinity (SSS) are required to improve meteorological and climate predictions. These two quantities are not yet available globally or with adequate temporal or spatial sampling. It is recognized that a spaceborne L-band radiometer with a suitable antenna is the most promising way of fulfilling this gap. With these scientific objectives and technical solution at the heart of a proposed mission concept the European Space Agency (ESA) selected the Soil Moisture and Ocean Salinity (SMOS) mission as its second Earth Explorer Opportunity Mission. The development of the SMOS mission was led by ESA in collaboration with the Centre National d'Etudes Spatiales (CNES) in France and the Centro para el Desarrollo Tecnologico Industrial (CDTI) in Spain. SMOS carries a single payload, an L-Band 2-D interferometric radiometer operating in the 1400-1427-MHz protected band . The instrument receives the radiation emitted from Earth's surface, which can then be related to the moisture content in the first few centimeters of soil over land, and to salinity in the surface waters of the oceans. SMOS will achieve an unprecedented maximum spatial resolution of 50 km at L-band over land (43 km on average over the field of view), providing multiangular dual polarized (or fully polarized) brightness temperatures over the globe. SMOS has a revisit time of less than 3 days so as to retrieve soil moisture and ocean salinity data, meeting the mission's science objectives. The caveat in relation to its sampling requirements is that SMOS will have a somewhat reduced sensitivity when compared to conventional radiometers. The SMOS satellite was launched successfully on November 2, 2009.

The CAROLS L-band radiometer, which is built and designed as a copy of DTU EMIRAD II instrument will be used in conjunction with other airborne instruments (in particular the C-Band scatterometer STORM) in coordination with in situ field campaigns for futur SMOS CAL/VAL activities. A validation campaign with four flights was made over the South West of France and the Bay of Biscay (Atlantic Ocean) in September 2007. Different instrumented sites were over ocean and land surfaces were coverecd. Moreover, in order to qualify the radiometric data, different types of aircraft maneuvers were performed over ocean: circle flights, wing and nose wags. We present in this paper the first analysis of the data quality using these ocean measurements. We show a very good sensitivity of both channels.

The CAROLS, L band radiometer, is built and designed as a copy of EMIRAD II radiometer of DTU team. It is a Correlation radiometer with direct sampling and fully polarimetric (i.e 4 Stockes). It will be used in conjunction with other airborne instruments (in particular the C-Band scatterometer (STORM) and IEEC GPS system, Infrared CIMEL radiometer, one visible camera), in coordination with in situ field campaigns for SMOS CAL/VAL. The instruments are implemented on board the French research airplane ATR42. A validation campaign with four flights was made over south west of France, Hourtin Lake and Bay of Biscay (Atlantic Ocean) in September 2007. In order to qualify the radiometer data, different types of aircraft movements were realized: circle flights, wing and nose wags. Simultaneously to flights, different ground measurements were made over continental surfaces and ocean. First results show a good quality of data over ocean surfaces. For continental surfaces, important Radio-Frequency Interferences (RFI) were observed over a large part of the studied region.

The L-band interferometric radiometer onboard the Soil Moisture and Ocean Salinity mission will measure polarized brightness temperatures (Tb). The measurements are affected by strong radiometric noise. However, during a satellite overpass, numerous measurements are acquired at various incidence angles at the same location on the Earth's surface. The sea surface salinity (SSS) retrieval algorithm implemented in the Level 2 Salinity Prototype Processor (L2SPP) is based on an iterative inversion method that minimizes the differences between Tb measured at different incidence angles and Tb simulated by a full forward model. The iterative method is initialized with a first-guess surface salinity that is iteratively modified until an optimal fit between the forward model and the measurements is obtained. The forward model takes into account atmospheric emission and absorption, ionospheric effects (Faraday rotation), scattering of celestial radiation by the rough ocean surface, and rough sea surface emission as approximated by one of three models. Potential degradation of the retrieval results is indicated through a flagging strategy. We present results of tests of the L2SPP involving horizontally uniform scenes with no disturbing factors (such as sun glint or land proximity) other than wind-induced surface roughness. Regardless of the roughness model used, the error on the retrieved SSS depends on the location within the swath and ranges from 0.5 psu at the center of the swath to 1.7 psu at the edge, at 35 psu and 15degC. Dual-polarization (DP) mode provides a better correction for wind-speed (WS) biases than pseudofirst Stokes mode (ST1). For a WS bias of -1 mmiddots-1, the corresponding SSS bias at the center of the swath is equal to -0.3 psu in DP mode and to -0.5 psu in ST1 mode. The inversion methodology implicitly assumes that WS errors follow a Gaussian distribution, even though these errors should follow more closely a Rayleigh distribution. For this reason, the use of wind components, which typically exhibit Gaussian error distributions, may be preferred in the retrieval. However, the use of noisy wind components creates WS and SSS biases at low WSs (0.1 psu at 3 mmiddots-1). At a sea surface temperature (SST) of 15degC, the retrieved SSS is weakly sensitive to the SST biases, with the SSS bias always lower than 0.3 psu for SST biases ranging from -0.5degC to -2degC. In DP mode, biases in the vertical total electron content (TEC) of the atmosphere result in SSS biases smaller than 0.2 psu. The pseudofirst Stokes mode is insensitive to TEC. Failure to fully account for sea surface roughness scattering effects in the computation of sky radiation contribution leads to a maximum SSS bias of 0.2 psu in the selected configuration, i.e., a descending orbit over the Northern Pacific in February. To achieve SSS biases that are smaller than 0.2 psu, special care must be taken to correct for biases at low WS and to ensure that the bias on the mean WS (averaged over 200 km times 200 km and ten days) remains smaller than 0.5 mmiddots-1.

In preparation for SMOS Cal/Val phase, we simulate SMOS retrieved data (first cm) from in situ data (a few meters depth). We study vertical gradients of salinity in the Tropical Atlantic Ocean with three types of data: TSG and XCTD measurements from boats (POLARSTERN and ARAMIS project) and from ARGO floats. Between 0 and 10degnorth, nearly 5% of vertical gradients between 5 and 10 m are larger than 0.1 psu. They appeared in a zone characterized by warm SST and low wind and are linked to rain events or river discharges. The mean value of all the data stays less than 0.02 psu. However their distribution is skewed towards positives values, implying a non Gaussian repartition of differences between SMOS and in situ data.

The Soil Moisture and Ocean Salinity (SMOS) mission (launch scheduled for 2008) aims at obtaining global maps of soil moisture and sea surface salinity (SSS). It uses an L-band (1.4 GHz) microwave interferometric radiometer to obtain brightness temperatures (Tb) at the Earth surface at horizontal and vertical polarizations. They will be used to retrieve both geophysical variables, following specifically designed algorithms that will be applied when the satellite field-of-view is covering land or ocean surfaces respectively. The retrieval of salinity is a complex process that requires the knowledge of environmental information and an accurate processing of the radiometer measurements, because of the narrow range of ocean Tb and the strong impact on the measures of geophysical parameters (such as sea state). Here we present the baseline approach chosen to retrieve sea surface salinity from SMOS data, as developed and implemented by the joint team of scientists and engineers responsible for the SMOS Salinity Level 2 Prototype Processor. We present academic tests conducted over homogeneous scenes with the prototype. In these configurations, external perturbation sources (sky radiation, sun glint, ...) are not taken into account. Roughness is the main sea surface signal disturbing SSS retrieval.

This paper aims at studying the quality of the sea surface salinity (SSS) retrieved from soil moisture and ocean salinity (SMOS) data in coastal areas. These areas are characterized by strong and variable SSS gradients [several practical salinity units (psu)] on relatively small scales: the extent of river plumes is highly variable, typically at kilometric and daily scales. Monitoring this variability from SMOS measurements is particularly challenging because of their resolution (typically 30-100 km) and because of the contamination by the nearby land. A set of academic tests was conducted with a linear coastline and constant geophysical parameters, and more realistic tests were conducted over the Bay of Biscay. The bias of the retrieved SSS has been analyzed, as well as the root mean square (rms) of the bias, and the retrieved SSS compared to a numerical hydrodynamic model in the semirealistic case. The academic study showed that the Blackman apodization window provides the best compromise in terms of magnitude and fluctuations of the bias of the retrieved SSS. Whatever the type of vegetation cover, a strong negative bias, greater than 1 psu, was found when nearer than 36 km from the coast. Between 44 and 80 km, the type of vegetation cover has an impact of less than a factor 2 on the bias, and no influence further than 80 km from the coast. The semirealistic study conducted in the Bay of Biscay showed a bias over ten days lower than 0.2 psu for distances greater than 47 km, due to an averaging over various geometries (coastline orientation, swath orientation, etc.). The bias showed a weak dependence on the location of the grid point within the swath. Despite the noise on the retrieved SSS, contrasts due to the plume of the Loire River and the Gironde estuary remained detectable on ten-day averaged maps with an rms of 0.57 psu. Finally, imposing thresholds on the major axis of the measurements brought little improvement to the bias, whereas it increased the rms and could lead to strong swath restriction: a 49-km threshold on the major axis resulted in an effective swath of 800-900 km instead of 1200 km.

The European Space Agency SMOS (Soil Moisture and Ocean Salinity) mission aims at obtaining global maps of soil moisture and sea surface salinity from space for large scale and climatic studies. It uses an L-band (1400-1427 MHz) microwave interferometric radiometer by aperture synthesis (MIRAS) to measure brightness temperature at the Earth surface at horizontal and vertical polarizations (Th and Tv). These two parameters will be used together to retrieve the geophysical variables. The retrieval of salinity is a complex process that requires the knowledge of other environmental information and an accurate processing of the radiometer measurements, due to the narrow range of ocean brightness temperatures and the strong impact in the measured values of different geophysical parameters (as sea state) other than salinity. Here we present the baseline approach chosen by ESA to retrieve sea surface salinity from MIRAS data, as it has been developed and implemented by the joint team of scientists and engineers responsible for the SMOS ocean salinity level 2 prototype processor.

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 /spl plusmn/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.

Soil Moisture and Ocean Salinity (SMOS) is an Earth Explorer Opportunity Mission from the European Space Agency with a launch date in 2007. Its goal is to produce global maps of soil moisture and ocean salinity variables for climatic studies using a new dual-polarization L-band (1400-1427 MHz) radiometer Microwave Imaging Radiometer by Aperture Synthesis (MIRAS). SMOS will have multiangular observation capability and can be optionally operated in full-polarimetric mode. At this frequency the sensitivity of the brightness temperature (T/sub B/) to the sea surface salinity (SSS) is low: 0.5 K/psu for a sea surface temperature (SST) of 20/spl deg/C, decreasing to 0.25 K/psu for a SST of 0/spl deg/C. Since other variables than SSS influence the T/sub B/ signal (sea surface temperature, surface roughness and foam), the accuracy of the SSS measurement will degrade unless these effects are properly accounted for. The main objective of the ESA-sponsored Wind and Salinity Experiment (WISE) field experiments has been the improvement of our understanding of the sea state effects on T/sub B/ at different incidence angles and polarizations. This understanding will help to develop and improve sea surface emissivity models to be used in the SMOS SSS retrieval algorithms. This paper summarizes the main results of the WISE field experiments on sea surface emissivity at L-band and its application to a performance study of multiangular sea surface salinity retrieval algorithms. The processing of the data reveals a sensitivity of T/sub B/ to wind speed extrapolated at nadir of /spl sim/0.23-0.25 K/(m/s), increasing at horizontal (H) polarization up to /spl sim/0.5 K/(m/s), and decreasing at vertical (V) polarization down to /spl sim/-0.2 K/(m/s) at 65/spl deg/ incidence angle. The sensitivity of T/sub B/ to significant wave height extrapolated to nadir is /spl sim/1 K/m, increasing at H-polarization up to /spl sim/1.5 K/m, and decreasing at V-polarization down to -0.5 K/m at 65/spl deg/. A modulation of the instantaneous brightness temperature T/sub B/(t) is found to be correlated with the measured sea surface slope spectra. Peaks in T/sub B/(t) are due to foam, which has allowed estimates of the foam brightness temperature and, taking into account the fractional foam coverage, the foam impact on the sea surface brightness temperature. It is suspected that a small azimuthal modulation /spl sim/0.2-0.3 K exists for low to moderate wind speeds. However, much larger values (4-5 K peak-to-peak) were registered during a strong storm, which could be due to increased foam. These sensitivities are satisfactorily compared to numerical models, and multiangular T/sub B/ data have been successfully used to retrieve sea surface salinity.

The results from two field experiments in the Mediterranean Sea are used to study the wind speed dependence of brightness temperature at L-band. During the EuroSTARRS airborne experiment, an L-band radiometer made measurements across a large wind speed gradient, enabling us to study this dependence at high wind speed. We compare our results with a two-scale emissivity model using several representations of the sea state spectrum. While the results are encouraging, unfortunately the accuracy of the measurements does not permit us to distinguish between the so-called twice Durden and Vesecky spectrum and the Elfouhaily spectrum above 7 m/spl middot/s/sup -1/. The effect of foam is certainly small. During the WISE 2001 field experiment carried on an oil rig, we studied this dependence at low wind speed, finding an abrupt decrease of the wind speed effect on the brightness temperature below 3 m/spl middot/s/sup -1/.

In order to prepare the Soil Moisture and Ocean Salinity (SMOS) mission, we present 1) the sea surface salinity precision that could be achieved with the SMOS radiometer measurements and 2) the time and space scales over which averaged SMOS Tb should remain relatively constant in order to prepare after-launch monitoring of radiometer drifts. Leaving aside errors due to the instrument and the image reconstruction process, the SSS averaged over 200 /spl times/ 200 km/sup 2/ areas and over 10 days retrieved from SMOS measurements should meet the GODAE requirements with a precision better than 0.1 psu in most oceanic regions, assuming random noise on W and SST of 2 m s/sup -1/ and 1 /spl deg/C, respectively. On another hand, this requirement will not be met if no a priori information on the wind speed is available. However, it is likely that SMOS Tb will suffer from temporal drifts and/or from regional biases linked to sun disturbances for instance. In these biases are going to be monitored using Tb averages, it will be necessary to take into account wind speed variability.

We estimate the error on the sea surface salinity (SSS) retrieved in the SMOS (Soil Moisture and Ocean Salinity) configuration at 200-km and 10-day resolution. With reasonable assumptions on wind speed errors and sea surface temperature errors, we show that the retrieved SSS should meet the GODAE requirements. The Faraday rotation is shown to affect the SSS precision by less than 15% in most oceanic regions, because of a relatively weak sensitivity of the second Stokes parameter to SSS.

The WISE 2000 and WISE 2001 field campaigns were sponsored by ESA to gather experimental data to improve the knowledge of the L-band brightness temperature dependence with wind speed at different incidence angles and azimuth angles. The goal is to help the development of sea surface salinity retrieval algorithms for SMOS Earth Explorer Mission of the European Space Agency. The L-band AUtomatic RAdiometer (LAURA) plus other sensors to characterize the sea surface state were installed at the Casablanca oil rig, 40 km south east off the coast of Tarragona in Spain. During WISE 2000 wind conditions were low-to-moderate, but during WISE 2001 two strong storms beat the Catalonian coast with sustained winds higher than 100 km/h at the platform meteorological station (69 m height). The first results of the radiometric measurements (azimuth and elevation scans) acquired with LAURA during the WInd and Salinity Experiment (WISE-2001) are presented.

Two campaigns were conducted in October and November 2001 with the support of ESA to check the validity of existing emissivity models in L-band and to assess the accuracy which can be expected for sea surface salinity retrieved from the Soil Moisture and Ocean Salinity (SMOS) satellite measurements. Taking into account the influence of the various fetch conditions encountered during these campaigns, we study the influence of the sea state on emissivity. We use sea state measurements to estimate the wave age. Then we use a sea wave spectrum, which is wave age dependent, to compute brightness temperatures (Tb) with a two-scale emissivity model. We compare the simulated Tb with measurements and determine the validity of the sea state parameterization.

Two campaigns were conducted in November 2001 to measure the brightness temperature of the sea in L-band and the sea surface environmental parameters. The first results are presented below, especially an example of airborne radiometer measurements made during an abrupt change in the wind speed.

Sea surface salinity can be measured by passive microwave remote sensing at L-band. In May 1999, the European Space Agency (ESA) selected the Soil Moisture and Ocean Salinity (SMOS) Earth Explorer Opportunity Mission to provide global coverage of soil moisture and ocean salinity. To determine the effect of wind on the sea surface emissivity, ESA sponsored the Wind and Salinity Experiment (WISE 2000). This paper describes the field campaign, the measurements acquired with emphasis in the radiometric measurements at L-band, their comparison with numerical models, and the implications for the remote sensing of sea salinity.