SMOS has now been in operation for 12 years and is still in good shape. Throughout those years, several steps had to be done to ensure scientific successes, as it was both the first L band mission and the first interferometer in space. The focus was first on basic variables (soil moisture and sea surface salinity) but very quickly several other science domain and applications emerged. This very rapid transition can be explained by the simple fact that for the first time a space instrument (L band radiometer) could give access directly and in an absolute fashion to surface soil moisture (i.e., without scaling, change detection or strong assumptions).
Soil moisture and derived quantities
The first direct application was to infer root zone soil moisture from surface soil moisture using simplified approaches. This led to a number of very interesting research topics such as elaboration of reliable drought indices and analysis of interactions between water storage and vegetation stress. Soil moisture was also used was proved to be also a very important variable when assessing flood risks. With soil saturation coupled with heavy rainfall forecasts, it is possible to delineate area where flood risks (or flash floods in another context) are very likely. One limitation of soil moisture products is the current spatial resolution (typically 40 km even when distributed on higher resolution grids. So many efforts have been made to infer higher resolution products for use in agriculture and hydrology. Using different disaggregation approaches relying either on optical data sets or on radar/ SAR measurements, high resolution soil moisture fields were derived. They enabled studies on irrigation for example or for locust prevention, but such approaches have also been used to get finer information on other variables such as biomass, water bodies etc. It is well understood that the quality of the outputs is slightly degraded when compared to what would be obtained by a real radiometer with a higher resolution but it fills a gap.
Having access to either brightness temperatures or soil moisture fields in near real time fostered the use of SMOS in NWP. It was used first for monitoring at ECMWF and then assimilated in the model. The results show improvements but limited as models are not designed to assimilate real soil moisture. So soil moisture was improved but not necessarily the scores. SMOS significantly contributed to establish where models will always have issues and need improvements to be able to assimilate not only SMOS but also other sensors in land data assimilation systems.
It is well known the precipitations derived from satellite are very useful but suffer from inaccuracies in several areas. using an assimilation scheme ingesting SMOS data enabled to significantly improve rainfall estimates . Using such information was also very useful for food security programs as demonstrated as early as 2011 at USDA and then in Europe.
SMOS data proved to be also useful in hydrology. First studies were made to see how assimilating SMOS data in hydrological models could improve model outputs and recent studies should that some improvements were noticeable. Other groups studies how it was possible to monitor water bodies even below dense canopies with a relatively high temporal sampling, quantities not necessarily measurable from space with other sensors. It led to a seasonal monitoring of the Amazon and Congo basins for instance, monitoring which could be enhanced using disaggregation approaches. This offered the first opportunity to understand and monitor the hydrology of these large basins largely covered with dense forests. With now 12 years of data with several El Nino / la Nina events we can better describe and thus understand climate teleconnections. Monitoring water bodies also opens a new research field related to gas exchanges between water bodies and the atmosphere.
Sea Surface salinity
Estimating sea surface salinity (SSS) represented a very significant challenge as the signal is rather weak. Nevertheless, very soon SMOS delivered SSS fields and most of the efforts from then on was to both improve the signal accuracy and to extend the retrievals to very complex areas. Actually, retrieving SSS can be even more challenging either because of land contamination (near the coasts) and it is now possible to retrieve reliable information closer to the coast and or in cold seas (due to reduced sensitivity as temperature decreases). Currently both issues have been tackled and SSS map now get close to coasts and also at high latitudes, opening new studies and climate related analysis. It can be mentioned that, thanks to the high quality of the SMOS data the possibility to infer rainfall over oceans has been demonstrated.
The ability to infer wind speed, especially for strong winds (i.e., hurricanes for instance) was also demonstrated at an early stage and this without any notable saturation effect. After an extensive validation, a wind speed product has been established and is now run operationally.
Now the data is also used in mesoscale ocean circulation, to infer ocean alkalinity, assess river plumes and fresh water “tongues” in ocean. All these results leading to a better understanding of ocean circulation and air sea interactions together with an improved understanding of climate signals such as the IOD, ENSO or NAO.
Vegetation opacity
Using the multi-angular capability of SMOS it is possible to infer both soil moisture and vegetation opacity (often called L-VOD for L band Vegetation Optical Depth). So this quantity is part of the SMOS data since day one but suffered at the beginning the trial and errors of accurate image reconstruction and related calibration. After the second reprocessing though, brightness temperatures became sufficiently good to be used even over dense canopies to infer L-VOD which is linked to low vegetation water content (i.e., grass, crops etc) and branch/ trunk biomass for trees and forested areas. Very early it was shown that the relationship between L-VOD and tree height (and thus Biomass) was clear but since the last reprocessing, significant advances were made leading to a number of very significant results related to biomass monitoring and more generally carbon related issues.
Obviously monitoring both biomass and vegetation water content together with surface soil moisture puts forward a new venue in terms of deforestation and deforestation impact fire risks mapping or fire recovery.
Cryosphere
Even though not one of the priorities at launch, SMOS proved to be a very valuable tool to monitor cryosphere. The first application was to infer thin sea ice as the signal is very complementary to that of altimeters such as CryoSat-2 as it measures well thin sea ice while CryoSat measures well thick sea ice. As a consequence, by fusing both measurements, it is possible to monitor globally sea ice with an unprecedented accuracy the artic polar cap and described its shrinking trend since 2010 as well as monitoring sea ice around Antarctica.
Studying Antarctica also enabled to make significant progresses in terms of assessing snow melt periods (which are increasing regularly) and ice sheet internal temperatures. It was also found that SMOS could allow assessing the amount of water in liquid form in either snow or ice, opening new paths on Greenland deep melting and avalanche risks mapping. Such results are leading to the possibility in the mid-term to reach at long last a way to estimate snow water equivalent.
Over land masses, due to the sharp change in dielectric constant when soil freezes, a freeze thaw detection approach was rapidly established at FMI giving way to an operational F/T product. This information is obviously of paramount interest for assessing climate induced changes at high latitudes but also can be related to methane exchanges which are very much linked to the thawed period. To extend this high latitude monitoring further, as L band enables to estimate soil’s temperature below a snow layer, studies to monitor soils temperature throughout the year and thus to monitor permafrost extent variations have been initiated, capitalizing on the 12 years of SMOS data.
Summary
After 12 years in space and being the first of its kind SMOS has enable a wealth of science results. The results also cover and very large range of science topics going from smart irrigation to climate trends and from locust mitigation dust transport. The impressive publication record is one of the most traceable indicator and, should the satellite stay healthy for several years, new insights of our changing climate will be at hand.

The Soil Moisture and Ocean Salinity mission (SMOS) is the European Space Agency (ESA) second Earth Explorer. It was launched on 2nd November 2009, and it continues to provide L-band Brightness Temperature (BT) measurements from which a number of applications are derived. More notoriously, soil moisture measurements, sea surface salinity, sea-ice thickness and high wind speeds. Its payload, the Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) continues to be the first and only 2D radiometer interferometer ever flown to space for Earth Observation.
12 years after launch, SMOS is still in good health, and the SMOS calibration team continues to further improve the quality of the data. Most recently, the 3rd Mission Reprocessing level 1 data set was released, after a number of improvements performed in calibration and the image reconstruction process.
Among the changes introduced in calibration for the 3rd Mission Reprocessing release, there was the change in strategy for the Noise Injection Radiometer calibration, that became fixed after the team realised that this particular receiver is far more stable than what can be measured in calibration; the update of the Power Measurement System (PMS) thermal sensitivity and NIR antenna losses characterization values, and the introduction of a thermal latency parameter for the thermal sensor in the NIR antenna.
Among the changes in the image reconstruction process, the most relevant were the refinement of the Gibbs correction (called Gibbs-2) to account for differences in the Sea and Land BT, the introduction of the super-sampled Sun BT correction, to account for inhomogeneities of the L-band Sun BT signal within the Sun disk, the correction of the Sun BT signal even when the Sun is in the back of the instrument, which is observed through the side-lobes, and the addition of new Radio Frequency Interference (RFI) flags to alert users of a degradation of certain BT measurements.
All these changes introduced a clear positive jump in the quality of the level 1 SMOS data, as assessed by the different metrics that the SMOS team uses to assess it. The most important changes were a clear improvement in the stability of the data and a reduction on the spatial biases observed. The improvement in the different metrics will be presented at the conference.
Currently, the team still continues to improve the data in view of a 4th Mission Reprocessing. Some of the most important new changes that the team is working on are the introduction of a RFI correction, to remove RFI signal from the BT measurements, a new antenna thermal model, to account for variations of the antenna losses parameters as function of the antenna temperature, further refinements of certain calibration parameters, to reduce Land-Sea contamination and some residual orbital instability drift in certain times of the year where the variation of physical temperature is larger.

Finally, the team is also working in developing new level 1 products: the SMOS solar flux, which can be provided in near-real time and could be extremely useful for the detection of Solar flares, and a new Total Electron Content (TEC) product derived from SMOS measurements. A summary of all these changes, improvements and metrics will be presented during the conference.

ElectroMagnetic (EM) reasons resulting in temperature dependence of L-band Vegetation Optical Depth (L-VOD) are currently overlooked in remote sensing products. Discrepancies in retrievals of geophysical surface properties over vegetated areas can result from this incompleteness. This perception motivated to explore EM considerations in how temperature drives L-VOD of a boreal forest. Thereto, a novel physics-based model is developed and evaluated to assess L-VOD sensitivities to canopy temperature and some other model parameters. The L-VOD model is compared to L-VOD derived from close-range L-band brightness temperatures measured through the tree canopy at the Finnish Meteorological Institute’s Arctic Research Center (FMI-ARC) in Sodankyl¨a (Finland) during a 4-week and a 1-day period in 2019. Furthermore, the model’s ability to explain L-VOD retrieved from brightness temperatures of the “Soil Moisture and Ocean Salinity” (SMOS) satellite over the “Sodankyl¨a grid cell” is investigated. Experimental L-VOD are maximal at around 0 ◦C and decrease when canopy temperature is moving away from zero degree Celsius. This temperature response, observed at different temporal- and spatial scales, is captured by the proposed L-VOD model and explained by freezing tree sap-water and the dependence of water permittivity on temperature. The demonstrated EM-induced temperature dependence suggest caution with interpreting satellite-based L-VOD, because increased L-VOD around the freezing point is not solely due to increased biomass or rehydration of the vegetation. Further, our study can find future application to compensate L-VOD for EM-induced temperature sensitivity. This potentially leads to improved explanatory power of temperature normalized L-VOD for characterization of forest phenology. Furthermore, we suggest examining the presence and strength of the demonstrated L-VOD temperature response as a practical L-VOD retrieval quality assessment method under steady forest phenology.

The Soil Moisture and Ocean Salinity (SMOS) satellite has provided, for the first time, systematic passive L-band (1.4 GHz) measurements from space with a spatial resolution of ~ 40 km. SMOS data are an essential brick of the ESA Climate Change Initiative (CCI) for sea surface salinity (SSS) and soil moisture (SM) and they are used by the CCI biomass. SMOS data are assimilated operationally at the European Centre for Medium Range Weather Forecasts (ECMWF). L-band surface SM measurements have also been used to estimate root zone soil moisture, to derive drought indices, to enable food security monitoring and to improve satellite precipitation estimates. An interferometric radiometer such as SMOS gives access to multi-incidence angle observations, which in addition to SM, allows to retrieve the L-band vegetation optical depth (L-VOD), which depends on the vegetation water content and can be used to estimate above ground biomass, linking water and carbon cycles. Over the ocean, SMOS enabled to study the SSS giving significant results on mesoscale variability, boundary currents and the interaction of freshwater in river plumes with the ocean. L-band passive radiometer observations also allow to measure strong winds over the ocean. Regarding the cryosphere, SMOS data have shown that passive L-band radiometry can be used to measure thin sea ice thickness or to measure the temperature of deep layers of ice in Antarctica.

A large number or scientific and operational applications depend on the continuity of L-band observations from space and with SMOS launched in 2009 and NASA SMAP in 2015, it is time to prepare a follow-on mission. In this context, an increased spatial resolution with respect to the current generation of sensors is needed for applications such as:
• Many applications in agriculture and hydrology require kilometric or better resolutions.
• Now that L-VOD has been proved to be a major variable to study above ground carbon stocks, there is a needed to complement biomass estimations from active microwaves and optical data with L-VOD at a higher resolution.
• The study of coastal oceans, marginal seas, and mesoscale processes in the ocean requires resolutions around 10 km.
• Distinguishing sea and ice contributions to the signal is crucial to study the evolution of the ice extend in the artic, one of the regions the most affected by global climate change, and to monitor melting events in Antarctica's coastal regions.
• State-of-the-art numerical weather prediction global models are already running at a resolution of 9 km. In the next years, efficient data assimilation will require higher resolution than the current generation of sensors.


Of course, downscaling approaches merging data from different sensors with different resolutions are a valuable tool for some applications. However, using airborne data, we will show that downscaled data sets cannot match the quality of a sensor with a native high resolution.

Ensuring the continuity of L-band observations with a radiometric sensitivity similar or better than that of SMOS, while increasing the spatial resolution, is the goal of SMOS-High Resolution(HR). Currently under under a Phase A study at the French Centre National d’Etudes Spatiales (CNES), the SMOS-HR satellite will perform aperture synthesis using an array of 160-230 small antennas distributed in a four-arm cross to reach an spatial resolution of 10-15 km.

"ESA’s Soil Moisture and Ocean Salinity (SMOS) mission was launched 2 Nov 2009 and, after more than 12 years in orbit, it is still in good health, providing very valuable L-band observations of the Earth surface. Besides the main mission products, global maps of soil moisture and sea surface salinity at an average resolution of 40 km, SMOS also delivers measurements of thin sea ice, frost/thaw soils, high winds, ocean surface wind and Sun brightness temperature.
Beyond SMOS, ESA’s Earth Observation program includes the Copernicus Imaging Microwave Radiometer (CIMR), a multi-frequency passive sensor with an L-band channel. CIMR will thus be able to provide continuity to the L-band observations of SMOS, although at a larger spatial resolution of the order of 60 km.
To better match the needs of the L-band scientific community, in particular regarding spatial resolution, multi-angular capability and sensitivity, ESA is carrying out several instrument pre-development activities where the technology that would be required to achieve that goal gets consolidated. Applying all the experience and lessons learnt in two-dimensional aperture synthesis gained from the currently flying SMOS, the following developments are pursued:
- the study of formation-flying L-band aperture synthesis arrays (FFLAS*)
- an antenna of a size compatible with an inter-element spacing enabling alias-free imaging
- two advanced L-band receivers with parallel dual polarisation, high sensitivity, high out-of-band interference rejection and digital in-phase quadrature demodulation
- development of an RF ASIC** with digital functionality for radiometer applications
- a multi-wavelength optical harness connecting the receivers and the correlator supporting the centralised distribution of the local oscillator and calibration signal as well as the acquisition of raw data
- the development of radio frequency interference filtering techniques and their implementation within an advanced correlator for aperture synthesis application
It is further intended to conduct end-to-end system tests by integrating these subsystems together and performing baseline tests.
This presentation describes and reports the status and early results of those technology activities, some completed, some still on-going, in preparation of a future advanced L-band interferometric radiometer mission which could achieve the wishes and, eventually, the 10 km spatial resolution goal requirement, of the scientific community using this type of observations.
(*) FFLAS: Formation Flying L-band Aperture Synthesis
(**) ASIC: Application Specific Integrated Circuit"