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10 pages, 6 figures, 1 table, The Federated Satellite Systems/ 3 Cat-5 (FSSCat) mission was the winner of the European Space Agency (ESA) Sentinel Small Satellite (S 3 ) Challenge and overall winner of the 2017 Copernicus Masters competition. It consisted of two six-unit CubeSats. The Earth observation payloads were 1) the Flexible Microwave Payload 2 (FMPL-2) onboard 3 Cat-5/A, an L-band microwave radiometer and GNSS reflectometer (GNSS-R) implemented using a software-defined radio (SDR), and 2) the HyperScout-2 onboard 3 Cat-5/B, a hyperspectral camera, with the first experiment using artificial intelligence to discard cloudy images. FSSCat was launched on 3 September 2020 and injected into a 535-km synchronous orbit. 3 Cat-5/A was operated for three months until the payload was probably damaged by a solar flare and coronal mass ejection. During this time, all scientific requirements were met, including the generation of coarse-resolution and downscaled soil moisture (SM) maps, sea ice extent (SIE) maps, concentration and thickness maps, and even wind speed (WS) and sea surface salinity (SSS) maps, which were not originally foreseen. 3 Cat-5/B was operated a few more months until the number of images acquired met the requirements. This article briefly describes the FSSCat mission and the FMPL-2 payload and summarizes the main scientific results, With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)

52 pages, 33 figures, 7 tables, This technical note describes the Soil Moisture and Ocean Salinity (SMOS) soil moisture products freely distributed in netCDF format by the Barcelona Expert Center (BEC) on Remote Sensing. The products can be visualized by means of a web map service. The data files can be accessed and downloaded through a secure ftp (sftp) server, after registration as a user on our website: https://bec.icm.csic.es

185 pages, figures, tables, The main objectives of the WP3 are: 1) to identify the potential for retrieving additional variables from EO data linked to the state of the Polar Regions that are required for assimilation into models and forecasts of meteorological and environmental processes and their variations and 2) to assess the capabilities of future satellite missions (with special focus on the Copernicus Expansion Missions) for environmental monitoring and for providing data for integration/assimilation into modelling/forecast products, considering different In situ and airborne field measurement scenarios. To achieve these objectives we have prepared a comprehensive review of the current status of remotely sensed parameters acquired over Polar Regions and compared them with the products provided by the Copernicus service to identify current data gaps. Besides, an assessment of future satellite missions (in particular the HPCMs) has been performed, in terms of their benefit for environmental monitoring and their integration/assimilation in modelling/forecast products. We have also identified possible synergies between parameters obtained from different satellite missions to enhance the information content of specific data products considering the end-users requirements. Finally, we have identified the limitations of the currently assimilated variables as well as the potential of new variables that are relevant for assimilation into models for simulations and forecasts of conditions in the Polar Regions. Moreover, a concept for a move forward on data assimilation is presented

48 pages, 23 figures, 6 tables, This technical note describes the Soil Moisture and Ocean Salinity (SMOS) soil moisture products freely distributed in netCDF format by the Barcelona Expert Center (BEC). The soil moisture products can be visualized by means of a web map service. The data files can be accessed and downloaded through a secure ftp (sftp) server, after registration as user in our website: http://bec.icm.csic.es

Earth Observation for Water Cycle Science. 16-18 November 2020

World Soils User Consultation Meeting, 2-3 July 2019, Frascati, Italy

36 pages, 21 figures, 4 tables, This technical note describes the SMOS land products freely distributed in netCDF format by the BEC (http://bec.icm.csic.es). The maps can be visualized by means of a web map service. The data files can be accessed and downloaded through sFTP, after registration as use

European Space Agency’s 2019 Living Planet Symposium, 13-17 May 2019, Milan, Italy, Soil moisture is an essential climate variable which plays a crucial role linking the Earth’s water, energy and carbon cycles between the land and the atmosphere. Although it represents a small percentage of all the water on Earth, it provides key information about evaporation, transpiration, infiltration and runoff. As a result, accurate knowledge of soil moisture is crucial for both global and local applications. Currently there are two operating missions, SMOS (Soil Moisture and Ocean Salinity) and SMAP (Soil Moisture Active and Passive), launched by ESA and NASA, which are specifically devoted to measure the (surface) soil moisture. Their passive microwave instruments operate at L-band, which is favorable for measuring soil moisture due to the high sensitivity of the microwave signal to the soil dielectric constant at this frequency. The Copernicus Imaging Microwave Radiometer (CIMR) high priority candidate mission is planned to have an L-band radiometer on-board and could provide continuation of the observational data stream. Accurate high-resolution soil moisture maps are needed to fulfill a growing number of application tasks e.g., prevention of wildfires [1][2], early-detection of forest decline [3], monitoring the evolution of insect pests [4]. To downscale soil moisture from the coarse-scale radiometer resolution to a finer one, downscaling algorithms typically use additional observations at fine scales. A wide variety of downscaling algorithms exists [5]. They may use observations from different sensors, use different ancillary data or rely on different physical assumptions. The performance of these algorithms depends on the physics they are based on, and on the information at fine scale that they use, which may also depend on season, climate and land cover. This makes a direct comparison difficult, since their performance is intrinsically time and region dependent, and the algorithm set-up will therefore reflect into the results. The baseline downscaling approach for the SMAP mission uses active and passive microwaves. SMAP was designed to have a radar and a radiometer on-board, but the radar stopped operating on July 7, 2015. An alternative active-passive soil moisture product is now available merging SMAP and Sentinel-1 data [6]. Recently a spatially-consistent downscaling algorithm has been developed to obtain high-resolution soil moisture maps at 1 km from the ~30-40 km native resolution of current passive microwave instruments using optical data. This algorithm is based on the semi-empirical downscaling approach implemented at the Barcelona Expert Center (BEC) to blend SMOS and MODIS data into 1 km soil moisture estimates [7]. The novelty is that it introduces the concept of a shape adaptive window, improving its spatial consistency and thereby allowing for its global implementation [8]. The objective of this study is to provide insight into the physical mechanisms that can influence the production (downscaling) of high-resolution soil moisture maps with a special focus on soil moisture anomalies. We will investigate soil moisture maps produced by the BEC (microwave-optical) and the SMAP-Sentinel (active-passive microwave) algorithms presented above and understand the characteristics of the downscaled soil moisture maps with a focus on spatial and temporal anomalies., [1] D. Chaparro, M. Piles, M. Vall-Llossera, A. Camps, “Surface moisture and temperature trends anticipate drought conditions linked to wildfire activity in the Iberian Peninsula,” European Journal of Remote Sensing, vol. 49, issue 1, pp. 955-971, 2016. [2] D. Chaparro, M. Vall-llossera, M. Piles, A. Camps, C. Rüdiger and R. Riera-Tatché, "Predicting the Extent of Wildfires Using Remotely Sensed Soil Moisture and Temperature Trends," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, no. 6, pp. 2818-2829, June 2016. [3] D. Chaparro, J. Vayreda, M. Vall-llossera, M. Banqué, M. Piles, A. Camps, J. Martínez-Vilalta, “The role of climatic anomalies and soil moisture in the decline of drought-prone forests,”. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, issue 2, pp. 503-514, 2017. [4] M. J. Escorihuela, O. Merlin, V. Stefan, G. Moyano, O. A. Eweys, M. Zribi, ... & S. Ghaout. “SMOS based high resolution soil moisture estimates for Desert locust preventive. [5] J. Peng, A. Loew, O. Merlin, N. Verhoest, “A review of spatial downscaling of satellite remotely sensed soil moisture,” Reviews of Geophysics, 10.1002/2016RG000543, March 2017. [6] N. Das, R.S. Dunbar, “Level 2 SMAP/Sentinel Active/Passive Soil Moisture Product Specification Document,” Jet Propulsion Laboratory, D-56548, August 2017. [7] M. Piles, N. Sánchez, M. Vall-llossera, A. Camps, J. Martínez-Fernández, J. Martínez, V. González-Gambau, “A Downscaling Approach for SMOS Land Observations: Evaluation of High-Resolution Soil Moisture Maps Over the Iberian Peninsula,” IEEE Journal of Sel. Topics in Applied Earth Obs. and Remote Sens., vol. 7, no. 9, pp. 3845-3857, 2014. [8] G. Portal et al., "A Spatially Consistent Downscaling Approach for SMOS Using an Adaptive Moving Window," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 6, pp. 1883-1894, June 2018

European Space Agency’s 2019 Living Planet Symposium, 13-17 May 2019, Milan, Italy, The European Space Agency (ESA)’s Soil Moisture and Ocean Salinity (SMOS) mission is the first satellite specifically dedicated to measuring soil moisture (SM) [1]. SMOS was launched in November 2009 and is still in orbit, providing an unprecedented record of L-band brightness temperature (TB) observations at tens of km of spatial resolution (~40 km) with a 3-day revisit time. Since its launch, SMOS has exhibited a successful performance, fulfilling the scientific requirements in terms of both SM and ocean salinity [2]. SMOS as well as the Soil Moisture Active Passive (SMAP) mission have allowed obtaining the most ever accurate SM measurements at global scale [3]. The operational continuity of L-band observations after SMOS and SMAP is now being proposed via the Copernicus Microwave Imaging Radiometer (CIMR) high priority candidate mission [4]. The latest release (v650) of the ESA’s SMOS Level 2 (L2) Soil Moisture User Data Product (SMUDP) has several improvements on the L2 processor [5]. SMOS L2 SMUDP is generated for each orbit at a 15 km Icosahedral Snyder Equal Area (ISEA) 4H9 grid. Due to that, SMOS Level 3 (L3) SM products, which are a composite map of all orbits within the day at a 25 km Equal Area Scalable Earth (EASE)-2 grid, are preferred by research community in some cases to avoid the manipulation difficulties of ISEA. Nevertheless, all SMOS L2 and L3 SM products, and even a higher spatial resolution Level 4 (L4) SM product [6], have demonstrated to be useful for a wide range of scientific and operational applications up to date, being used in predictive hydrological and atmospheric models [7, 8], to monitor flood and drought events [9, 10], to predict wildfire risks [11] and to estimate root zone SM [12]. Nowadays, there are three different available daily SMOS L3 SM products. The first one is a composite of binned data generated by the Centre Aval de Traitement des Données SMOS (CATDS). The SMOS-CATDS L3 SM product is retrieved using a multi-orbit algorithm developed by the Centre d’Etudes Spatiales de la Biosphere (CESBIO) [13]. The second L3 SM product is generated by the Barcelona Expert Centre (BEC). The SMOS-BEC L3 SM product is obtained directly from L2 SMUDP, after applying a filtering based on the Data Quality Index (DQX) parameter and a weighted binning [14]. However, this filtering criterion may be questioned by a general increase of DQX in L2 v650 compared to the previous version (v620) [5]. As an alternative, a filtering based on the retrieval fit quality index, called Chi-Squared (Χi2) parameter, is currently being evaluated. The third L3 SM product is generated by the Institut National de la Recherche Agronomique (INRA) and CESBIO. The SMOS-IC L3 SM product is retrieved with an algorithm that has some simplifications with respect to the official L2 processor, mainly related to the pixel heterogeneity, angle geometry, and vegetation scattering albedo and soil roughness parameters [15]. This study assesses the SMOS-CATDS, SMOS-BEC and SMOS-IC L3 SM products from January 2015 to December 2016. The alternative SMOS-BEC L3 SM filtered by Χi2 (instead of DQX) has also been tested for several thresholds. Different in situ SM networks have been used to validate all possible L3 SM products over several climate types and land covers. Many present and upcoming applications could get benefit of the improvement and refinement of these global SM products. The obtained results and the inferred conclusions will be presented at the conference., References [1] Kerr, Y.K.; Waldteufel, P.; Wigneron, J.P.; Delwart, S.; Cabot, F.; Boutin, J.; Escorihuela, M.J.; Font, J.; Reul, N.; Gruhier, C.; et al. (2010) “The SMOS Mission: New Tool for Monitoring Key Elements of the Global Water Cycle”, Proceedings of IEEE, 98: 666-687. [2] Mecklenburg, S.; Drusch, M.; Kaleschke, L.; Rodriguez-Fernandez, N.; Reul, N.; Kerr, Y.H.; Font, J.; Martin-Neira, M.; Oliva, R.; Daganzo-Eusebio, E.; et al. (2016) “ESA's Soil Moisture and Ocean Salinity mission: From science to operational applications”, Remote Sensing of Environment, 180: 3-18. [3] Kerr, Y.H.; Al-Yaari, A.; Rodríguez-Fernández, N.; Parrens, M.; Molero, B.; Leroux, D.; Bircher, S.; Mahmoodi, A.; Mialon, A.; Richaume, P.; et al. (2016) “Overview of SMOS performance in terms of global soil moisture monitoring after six years in operation”, Remote Sensing of Environment, 180: 40-63. [4] Donlon, C.J. (2018) “Copernicus Imaging Microwave Radiometer (CIMR). Mission Requirements Document”, Technical report ESA-EOPSM-CIMR-MRD-3236, revision 1.5, Mission Science Division, European Space Agency (ESA), Noordwijk, Netherlands. [5] ESA (2017) “Read-me-first note for the release of the SMOS Level 2 Soil Moisture data products”, Technical report, Expert Support Laboratory (ESL) Level 2 Soil Moisture and Array Systems Computing Inc. [6] Portal, G.; Vall-llossera, M.; Piles, M.; Camps, A.; Chaparro, D.; Pablos, M.; Rossato, L. (2018) “A spatially consistent downscaling approach for SMOS using an adaptive moving window”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(6): 1883-1894.. [7] Ridler, M.E.; Madsen, H.; Stisen, S.; Bircher, S.; Fensholt, R. (2014) “Assimilation of SMOS‐derived soil moisture in a fully integrated hydrological and soil‐vegetation‐atmosphere transfer model in Western Denmark”, Water Resources Research, 50: 8962-8981. [8] Leroux, D.J.; Pellarin, T.; Vischel, T.; Cohard, J.M.; Gascon, T.; Gibon, F.; Mialon, A.; Galle, S.; Peugeot, C.; Seguis, L. (2016) “Assimilation of SMOS soil moisture into a distributed hydrological model and impacts on the water cycle variables over the Ouémé catchment in Benin”, Hydrological Earth System Sciences, 20: 2827-2840. [9] Wanders, N.; Karssenberg, D.; de Roo, A.; de Jong, S. M.; Bierkens, M.F.P. (2014) “The suitability of remotely sensed soil moisture for improving operational flood forecasting”, Hydrological Earth System Sciences, 18: 2343-2357. [10] Pablos, M.; Martínez-Fernández, J.; Sánchez, N.; González-Zamora, Á. (2017) “Temporal and Spatial Comparison of Agricultural Drought Indices from Moderate Resolution Satellite Soil Moisture Data over Northwest Spain”, Remote Sensing, 9:1168. [11] Chaparro, D.; Vall-llossera, M.; Piles, M.; Camps, A.; Rüdiger, C.; Riera-Tatché, R. (2016) "Predicting the Extent of Wildfires Using Remotely Sensed Soil Moisture and Temperature Trends," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(6): 2818-2829. [12] Pablos, M.; González-Zamora, Á.; Sánchez, N.; Martínez-Fernández, J. (2018) “Assessment of Root Zone Soil Moisture Estimations from SMAP, SMOS and MODIS Observations”, Remote Sensing, 10: 981. [13] Al Bitar, A.; Mialon, A.; Kerr, Y.H.; Cabot, F.; Richaume, P.; Jacquette, E.; Quesney, A.; Mahmoodi, A.; Tarot, S.; Parrens, M.; et al. (2017) “The global SMOS Level 3 daily soil moisture and brightness temperature maps”, Earth System Science Data, 9, 293–315. [14] González-Zamora, Á.; Sánchez, N.; Martínez-Fernández, J.; Gumuzzio, Á.; Piles, M.; Olmedo, E. (2015) “Long-term SMOS soil moisture products: A comprehensive evaluation across scales and methods in the Duero Basin (Spain)”, Physics and Chemistry of the Earth, Parts A/B/C, 83-84: 123-136. [15] Fernández-Morán, R.; Al-Yaari, A.; Mialon, A.; Mahmoodi, A.; Al Bitar, A.; De Lannoy, G.; Rodríguez-Fernández, N.; López-Baeza, E.; Kerr, Y.H.; Wigneron, J.P. (2017) "SMOS-IC: An Alternative SMOS Soil Moisture and Vegetation Optical Depth Product", Remote Sensing, 9: 457

Eurisy - Aplicaciones satelitales para la gestión multinivel de riego: capitalización de experiencias para impulsar la innovación regional, 31 October 2013, Badajoz, Spain

Capability for sea surface salinity observation was an important gap in ocean remote sensing in the last few decades of the 20th century. New technological developments during the 1990s at the European Space Agency led to the proposal of SMOS (Soil Moisture and Ocean Salinity), an Earth explorer opportunity mission based on the use of a microwave interferometric radiometer, MIRAS (Microwave Imaging Radiometer with Aperture Synthesis). SMOS, the first satellite ever addressing the observation of ocean salinity from space, was successfully launched in November 2009. The determination of salinity from the MIRAS radiometric measurements at 1.4 GHz is a complex procedure that requires high performance from the instrument and accurate modelling of several physical processes that impact on the microwave emission of the ocean’s surface. This paper introduces SMOS in the ocean remote sensing context, and summarizes the MIRAS principles of operation and the SMOS salinity retrieval approach. It describes the Spanish SMOS high-level data processing centre (CP34) and the SMOS Barcelona Expert Centre on Radiometric Calibration and Ocean Salinity (SMOS-BEC), and presents a preliminary validation of global sea surface salinity maps operationally produced by CP34., La imposibilidad de observar la salinidad superficial del mar desde el espacio era uno de los problemas importantes para la teledetección oceánica a finales del siglo XX. Nuevos desarrollos tecnológicos durante los años 90 en la Agencia Espacial Europea llevaron a formular la propuesta de SMOS (Soil Moisture and Ocean Salinity), una misión de oportunidad de observación de la Tierra basada en un radiómetro interferométrico de microondas, MIRAS (Microwave Imaging Radiometer with Aperture Synthesis). SMOS, el primer satélite que intenta observar la salinidad desde el espacio, fue lanzado en noviembre de 2009. La determinación de salinidad a partir de las mediciones de MIRAS a 1,4 GHz es un procedimiento complejo que requiere un excelente funcionamiento del instrumento y una modelización muy precisa de los procesos físicos que intervienen en la emisión de la superficie del océano en el dominio de las microondas. Este artículo presenta SMOS en el contexto de la teledetección oceánica, y resume los principios de operación de MIRAS y el enfoque utilizado en SMOS para obtener la salinidad. Describe el Centro español de Proceso de datos SMOS de alto nivel (CP34) y el Centro Experto SMOS en Barcelona para Calibración Radiométrica y Salinidad Oceánica (SMOS-BEC), así como presenta una primera validación de los mapas globales de salinidad superficial producidos operacionalmente por el CP34.

SMOS-Barcelona Expert Center (BEC) Workshop, One year of SMOS data, 15 December 2010, Barcelona, Spain

SMOS-Barcelona Expert Center (BEC) Workshop, One year of SMOS data, 15 December 2010, Barcelona, Spain