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.

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 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.

After almost 10 years in operation (SMOS- Aquarius - SMAP) the very high potential of L band radiometry is clearly demonstrated. Several applications are already operational (assimilation at ECMWF, for hurricanes, for sea ice etc.) so it is crucial to maintain such measurements. To do so while satisfying the current missions specifications is also of prime importance. Degrading spatial resolution is thus a significant step back which will impact science and applications). These missions are now getting older and the goal of the study presented in this paper is to assess which planned mission could fulfill the requirements to ensure data continuity. For this purpose, an extensive users' requirements study was performed in 2018-2019 assessing what would be required in the near future as well as when L band radiometry was absolutely necessary to satisfy the requirements. From the gathered results a cluster analysis was performed and the only.

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.

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).

Swath mode processing of CryoSat-2 Synthetic Aperture Radar Interferometric (SARIn) mode has been used to monitor elevation of areas with complex topography such as over ice sheet and ice cap margins. Swath processing relies on an accurate measure of the angle of arrival of the measured echo and, therefore, requires custom strategies in order to resolve the ambiguous phase measurement. In mountainous regions of complex terrain, it may be necessary to apply different phase ambiguities across a waveform record when returns come from different scatters distributed perpendicularly to the CryoSat-2 ground tracks. In this letter, we present modifications to the conventional swath processing method whereby a multisurface retracker is first applied to the record in order to identify potential different scattering surfaces. Phase ambiguity is then independently resolved for each of these subsurfaces. The improvements with this new method over the Karakoram glaciers are a 10% increase in the number of measurements with improvements of almost 50% for individual glaciers and a reduction in the median absolute deviation of the elevations from 20.18 to 14.69 m.

This paper presents the the first attempt to include soil moisture information from remote sensing in the tools available to desert locust managers. The soil moisture requirements were first assessed with the users. The main objectives of this paper are: i) to describe and validate the algorithms used to produce a soil moisture dataset at 1 km resolution relevant to desert locust management based on DisPATCh methodology applied to SMOS and ii) the development of an innovative approach to derive high (100 m) resolution soil moisture products from Sentinel-1 in synergy with SMOS data. For the purpose of soil moisture validation, 4 soil moisture stations where installed in desert areas (one in each user country). The soil moisture 1km product was thoroughly validated and its accuracy is amongst the best available soil moisture products. Current comparison with in-situ soil moisture stations shows good values of correlation (R > 0.7) and low RMSE (below 0.04 m3m-3). The low number of acquisitions on wet dates has limited the development of the soil moisture 100m product over the Users Areas. The Soil Moisture product at 1km will be integrated into the national and global Desert Locust early warning systems in national locust centres and at DLIS-FAO, respectively.

The water level of inland water bodies plays an essential role in water balance management. Satellite altimeters can play an important role in monitoring water level, namely in remotely access places. However, satellite altimeters are normally designed to monitor homogeneous surfaces such as oceans or ice sheets, which results in poor performance over small inland water bodies because of the land contamination contribution in the returned waveforms. This paper presents three specialized algorithms or retrackers to retrieve water levels from radar altimeter data over inland water bodies dedicated to restricting the land contamination of the signal. The performances of the waveform portion selection method and the three retrackers which are the threshold retracker, Offset Center of Gravity (OCOG) retracker and 2-step analytical retracker are compared. Time series of water level results are retrieved over water bodies in Ebre river basin (Catalunya, Spain) and Lake Volta (West Africa). The standard deviation for 2-step analytical retracker combined with the waveform portion selection ranges from 0.02m to 0.05m, for OCOG retracker ranges from 0.07m to 0.13m, and for threshold re-tracker, it ranges from 0.05m to 0.1m over Lake Volta. The results show good accuracy with the insitu measurements over lake Ebre and Ribarroja reservoir with RMSE about 0.44 m and 0.18 m separately. All performances of the three retrackers are compared with the onboard retracker as well.

This paper presents the methodology for irrigation mapping using the Sentinel-1 SAR data. The study is performed using VV polarization over an agricultural site in Urgell, Catalunya (Spain). From the time series for each field, the indices including the mean value and variance of the signal, the correlation length, the fractal dimension which are derived from the backscatter time series are analyzed. The classification of irrigated and nonirrigated fields is done with the indices vector formed by the parameters analyzed. The result is compared with the supervised classification from Sentinel-2 multi-band data. The accuracy is 77%. The methodology uses only SAR data, which makes it usable for all areas even with cloud cover most times of the year.

The European Space Agency's (ESA) SMOS mission, in orbit since more than 8 years, carries a passive microwave interferometric radiometer measuring in L-Band and provides accurate global observations of emitted radiation originating from the Earth's surfaces since the atmosphere is almost transparent in this spectral range. In addition, over land the effect of vegetation on the measurements is smaller than for shorter wavelengths. The scientific objectives of the SMOS mission directly respond to the need for global observations of soil moisture and ocean salinity, two key variables used in predictive hydrological, oceanographic and atmospheric models. SMOS observations also provide information on the characterisation of ice and snow covered surfaces and the sea ice effect on ocean-atmosphere heat fluxes and dynamics, which affects large-scale processes of the Earth's climate system.

The main objective of this study is to analyze the potential use of Sentinel-l (S1) radar data for the estimation of soil moisture in agricultural areas. Simultaneously to several S1 acquisitions made between 2015 and 2017 over different sites, ground measurements of soil roughness, soil water content, LAI and crop height were recorded. The sensitivity of S1 signal to variations in soil moisture is discussed. A modelling based on Water Cloud Model was proposed to simulate radar signal backscattered over covered vegetation surfaces. Three inversion approaches were proposed to retrieve surface soil moisture at field scale.

The inland water level plays an essential role in water balance management. This paper presents methodology to retrieve water level from radar altimeter data including Cryosat-2 and Jason-2 over lakes in Western Africa. The idea is to combine both Level-1 and Level-2 data to retrieve water level more precisely and automatically over small lakes. From Level-1 data, the waveform is analyzed for data filtering and the possibility of water level retrieval. Then an iteration method is proposed to retrieve the height from Level-2 altimeter data with a strict water mask. The preliminary results of water level time series, derived from Level-2 data, in Lake Volta and Lake Kainji are presented in this paper, and the results are compared with the data from DAHITI (Database for Hydrological Time Series of Inland Waters). The standard deviation is controlled below 0.3 meters.

This paper presents two methodologies retrieving soil moisture from SAR remote sensing data. The study is based on Sentinel-1 data in the VV polarization, over a site in Urgell, Catalunya (Spain). By modeling the backscatter difference w.r.t. NDVI, the soil moisture corresponding to a specific NDVI value can be retrieved. The first algorithm is already developed in West Africa[1] from ERS scatterometer data to estimate soil water status. In this study, it is adapted to Sentinel-1 data and take into account the high repetitiveness of data in optimizing the inversion approach. Another new method is developed based on the backscatter difference between two adjacent days of Sentinel-1 data w.r.t. NDVI, with smaller vegetation change, the backscatter difference is more sensitive to soil moisture. The validation of the two methods is done with field data acquired in study site, with an rms error about 0.08 m3/m3for method 1 and 0.07 m3/m3for method 2 in volumetric moisture.

The soil evaporation is under atmospheric conditions non-limited in energy-strongly linked to the near-surface soil moisture sensed by microwave radiometers. This has been the rationale for developing the DisPATCh (Disaggregation based on Physical And Theoretical scale Change) method, which relies on thermal-derived evaporation to improve the spatial resolution of SMOS (Soil Moisture and Ocean Salinity) like data. In practice, the disaggregation scheme estimates the 0-5 cm soil moisture at 1 km resolution by combining 40 km SMOS soil moisture, 1 km resolution MODIS (MODerate resolution Imaging Spectroradiometer) data, and a multi-scale soil evaporation model. This paper provides an overview of 1) the current status and main assumptions of DisPATCh, 2) the DisPATCh-based processor implemented in the Centre Aval de Traitement des Données SMOS (CATDS), and 3) related ongoing research including advanced modeling of soil evaporation and the prospect of coupling thermal- and radar-based soil moisture downscaling approaches.

The Soil Moisture and Ocean Salinity (SMOS) mission is the first satellite dedicated to providing global surface soil moisture (SM). SMOS operates at L-band and at this frequency, the signal depends on soil moisture but is also significantly affected by surface soil roughness. Using the Combined soil Roughness & Vegetation Effects (CRVE) method detailed in this paper, the effect of vegetation and soil roughness can be combined using a single parameter, referred to as TR here. SM and TR were retrieved by inverting the SMOS observations using the forward emission model (L-MEB). Assuming a linear relationship between TR and LAI obtained by the MODIS data, an Australian map of soil roughness was computed. This map could lead to improved soil moisture retrievals for present and future microwave remote sensing missions such as SMOS and the Soil Moisture Active Passive (SMAP) scheduled for launch in November 2014.

In the above paper (ibid., vol. 49, no. 4, pp. 1177-1189, Apr. 2011), there is an error in equation (7). The explanation and corrected equation are presented here.

The Salar de Uyuni is a large, flat and radiometrically homogeneous area. Its extent is several tenths the SMOS footprint and its emissivity is high and rather homogeneous except when flooded (about 3 months per year). It is located in a rather un-inhabitated area with no RFI. Therefore it provides a perfect calibration site for SMOS brightness temperature and the dielectric constant product validation. In this paper several calibration/validation issues were assessed: SMOS and AMSR-E brightness temperature cross-validation over the site, the influence of Full/Dual polarisation mode on SMOS angular signature and L2 dielectric constant product validation.

The objective of the SMOScat project is to operationally provide soil moisture at 1 km resolution or better over Catalonia. A downscaling algorithm is applied to 40 km resolution L2 SMOS (Soil Moisture and Ocean Salinity) soil moisture product using 1 km resolutionMODIS (MODerate resolution Imaging Spectroradiometer) data. High resolution soil moisture is compared with in situ measurements collected each month from April to October 2011 in a dryland and irrigated area. Our results show and increase of correlation coefficient with in-situ measurements when high resolution soil moisture is used. The 2012 experimental field campaign will address topography issues.

The present paper analyzes the effects of roughness on the surface emission at L-band based on observations acquired during a long-term experiment. At the Surface Monitoring of the Soil Reservoir Experiment site near Toulouse, France, a bare soil was plowed and monitored over more than a year by means of an L-band radiometer, profile soil moisture and temperature sensors, and a local weather station, accompanied by 12 roughness campaigns. The aims of this paper are the following: 1) to present this unique database and 2) to use this data set to investigate the semiempirical parameters for the roughness in L-band Microwave Emission of the Biosphere, which is the forward model used in the Soil Moisture and Ocean Salinity soil moisture retrieval algorithm. In particular, we studied the link between these semiempirical parameters and the soil roughness characteristics expressed in terms of standard deviation of surface height (σ) and the correlation length (LC). The data set verifies that roughness effects decrease the sensitivity of surface emission to soil moisture, an effect which is most pronounced at high incidence angles and soil moisture and at horizontal polarization. Contradictory to previous studies, the semiempirical parameter Qr was not found to be equal to 0 for rough conditions. A linear relationship between the semiempirical parametersNand σ was established, while NHand NVappeared to be lower for a rough (NH~ 0.59 and NV~ -0.3) than for a quasi-smooth surface. This paper reveals the complexity of roughness effects and demonstrates the great value of a sound long-term data set of rough L-band surface emissions to improve our understanding on the matter.

In the forward model [L-band microwave emission of the biosphere (L-MEB)] used in the Soil Moisture and Ocean Salinity level-2 retrieval algorithm, modeling of the roughness effects is based on a simple semiempirical approach using three main “roughness” model parameters:$H_{R}$,$Q_{R}$, and$N_{R}$. In many studies, the two parameters$Q_{R}$and$N_{R}$are set to zero. However, recent results in the literature showed that this is too approximate to accurately simulate the microwave emission of the rough soil surfaces at L-band. To investigate this, a reanalysis of the PORTOS-93 data set was carried out in this paper, considering a large range of roughness conditions. First, the results confirmed that$Q_{R}$could be set to zero. Second, a refinement of the L-MEB soil model, considering values of$N_{R}$for both polarizations (namely,$N_{\rm RV}$and$N_{\rm RH}$), improved the model accuracy. Furthermore, simple calibrations relating the retrieved values of the roughness model parameters$H_{R}$and$(N_{\rm RH} - N_{\rm RV})$to the standard deviation of the surface height were developed. This new calibration of L-MEB provided a good accuracy (better than 5 K) over a large range of soil roughness and moisture conditions of the PORTOS-93 data set. Conversely, the calibrations of the roughness effects based on the Choudhury approach, which is still widely used, provided unrealistic values of surface emissivities for medium or large roughness conditions.

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 future Soil Moisture and Ocean Salinity satellite time of overpass is 6 A.M. and 6 P.M. at the equator. In many regions, morning dew is expected at the time of the satellite overpass and might play a role in soil moisture retrievals. The aim of this study was to assess the effects of dew on L-band measurements. Radiometric, biomass, and dew measurements were performed over a natural grass field. Our results show that at the diurnal scale, vegetation internal water content changes play a major role in emission. A direct impact of dew on measurements was not identified. However, a brightness temperature increase of 0.5 and 1 K was observed at vertical and horizontal polarizations, respectively. This increase was detected later after dew, suggesting that it was not directly caused by the presence of dew on the grass blades. Our hypothesis is that the observed increase in brightness temperatures is due to the absorption of dew water by the litter layer.

The spatial and temporal invariance of Soil Moisture and Ocean Salinity (SMOS) forward model parameters for soil moisture retrieval was assessed at 1-km resolution on a diurnal basis with data from the National Airborne Field Experiment 2006. The approach used was to apply the SMOS default parameters uniformly over 27 1-km validation pixels, retrieve soil moisture from the airborne observations, and then to interpret the differences between airborne and ground estimates in terms of land use, parameter variability, and sensing depth. For pastures (17 pixels) and nonirrigated crops (5 pixels), the root mean square error (rmse) was 0.03 volumetric (vol./vol.) soil moisture with a bias of 0.004 vol./vol. For pixels dominated by irrigated crops (5 pixels), the rmse was 0.10 vol./vol., and the bias was -0.09 vol./vol. The correlation coefficient between bias in irrigated areas and the 1-km field soil moisture variability was found to be 0.73, which suggests either 1) an increase of the soil dielectric roughness (up to about one) associated with small-scale heterogeneity of soil moisture or/and 2) a difference in sensing depth between an L-band radiometer and thein situmeasurements, combined with a strong vertical gradient of soil moisture in the top 6 cm of the soil.

The CoSMOS (Campaign for validating the Operation of the Soil Moisture and Ocean Salinity mission) campaign was conducted during November of 2005 in the Goulburn River Catchment, in SE Australia. The main objective of CoSMOS was to obtain a series of L-band measurements from the air in order to validate the L-band emission model that will be used by the SMOS (Soil Moisture and Ocean Salinity) ground segment processor. In addition, the campaign was designed to investigate open questions including the sun-glint effect over land, the application of polarimetric measurements over land, and to clarify the importance of dew and interception for soil moisture retrievals. This paper summarises the campaign activities, and presents progress on the analysis of the CoSMOS data set.

This paper compares L-band measurements from three different experiments in areas covered by grass. The main objective is to assess soil moisture retrievals based on the L-band Microwave Emission of the Biosphere model (L-MEB) used by the Soil Moisture and Ocean Salinity mission (SMOS). Results indicate that over grass the vegetation is isotropic to the microwave propagation at horizontal polarisation, while at vertical polarisation non-zero scattering is observed for all the grass data sets. Surface soil moisture is retrieved with enough accuracy for all data sets as long as the soil roughness and litter emission are calibrated beforehand. The study also highlights the importance of detecting strong attenuation by wet vegetation and litter due to rainfall interception. We show that strong rainfall interception can be flagged using a microwave polarisation index.

A simple reflectivity model of a bare soil at L-band is developed to account for the effects of soil roughness at different angles and polarizations. This model was developed using a long-term dataset acquired over the bare soil in the framework of the Surface Monitoring Of the Soil Reservoir EXperiment (SMOSREX). It is shown that the roughness effects are different depending on the measurement configuration, in terms of incidence angle and polarization. However, in this paper, a simple parameterization that is based on a single roughness parameter was calibrated in order to account for this angular and polarization dependencies. This parameter was found to be dependent on soil moisture: drier conditions were associated to higher ldquoroughnessrdquo conditions. The root-mean-square error between the measured and modeled reflectivities on days when no precipitation events were detected at vertical polarization (V-pol) is 0.0275, and at horizontal polarization (H-pol), the rmse is 0.0237; all incidence angles were considered. When all data are considered, the rmsd for V-pol is 0.0350, and for H-pol, the rmse is 0.0373. This new simple model is suitable for soil moisture retrieval from Soil Moisture and Ocean Salinity data. By means of this simple parameterization, almost two years of soil moisture data were retrieved with a good accuracy. The SMOSREX dataset allowed to ensure a long-term suitability of the proposed parameterization.

In this paper, microwave remote sensing, together within situmoisture probes, is used to investigate temperature effects on the soil dielectric constant. Field and specific laboratory measurements were performed for different soil water content over a wide range of temperatures. The experimental results lead to the following evidences: (1) temperature effect is different for bound and free waters in soil; (2) bound-water relaxation frequency falls within the range of frequencies that are used by impedance soil moisture probes for field measurements; and (3) the increase of bound-water relaxation frequency with soil temperature interferes in a significant way with moisture measurements when bound-water fraction is important. These results have implications in field experimentation since most moisture sensors operate under 500 MHz and are affected by this phenomena of relaxation.

This paper is part of an ongoing study aimed at exploring the potential of biangular measurements at L band to estimate near surface soil moisture. A statistical approach based on a physical radiative transfer model is tested over a natural grassland. Soil moisture shows an encouraging correlation with a combination of brightness temperatures measurements performed at two different angles. Nevertheless, the assumptions involved into the definition of a valid statistical index need to be studied. For that purpose, an insight into the modeling of grassland L band emission is also presented

A simple approach for correcting the effect of vegetation in the estimation of soil moisture (w/sub S/) from L-band passive microwave observations is presented in this study. The approach is based on statistical relationships, calibrated from simulated datasets, which requires only two observations made at distinct incidence angles (/spl theta//sub 1/,/spl theta//sub 2/). A sensitivity study was carried out, and best retrieval remote sensing configurations, in terms of polarization and couple of incidence angles (/spl theta//sub 1/,/spl theta//sub 2/), were investigated. Best estimations of w/sub S/ could be made at H polarization, for /spl theta//sub 1/ varying between 15/spl deg/ and 30/spl deg/, and with a difference (/spl theta//sub 2/-/spl theta//sub 1/) larger than 30/spl deg/. The method was tested against two experimental datasets acquired over crop fields (soybean and wheat). The average accuracy in the soil moisture retrievals during the whole crop cycle was found to be about 0.05 m/sup 3//m/sup 3/ for both crops.