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This work was supported by the “la Caixa” Foundation (ID 100010434) under Grant LCF/PR/MIT19/51840001 (MIT-Spain Seed Fund), by MISTI-Germany and MISTI-Belgium Seed Funds, by the XXXIII Ramón Areces Postdoctoral Fellowship, by the NASA (Grant 1510842), by grants PID2020-114623RB-C32 and MDM-2016-0600 funded by MCIN/AEI/10.13039/501100011033, by the European Regional Development Fund (ERDF), and by the NASA Postdoctoral Program at the NASA Goddard Space Flight Center. D. Chaparro thanks the AKS department (DLR) and the CEE department (MIT) for hosting and supervision.

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

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

European Geosciences Union (EGU) General Assembly, 7-12 April 2019, Vienna, Austria.-- 1 page, High-resolution satellite derived sea surface wind data, such as those from scatterometers, are increasing lyrequired for operational monitoring and forecasting of the ocean. We present an improved version of ERA*, an ocean forcing product which keeps the time and space coverage of atmospheric model fields, but adds the accurately observed local mean and variability of wind scatterometers, to make these datasets suitable for, among others, high-resolution ocean forcing. Recent attempts of combining scatterometer data and numerical weather prediction (NWP) outputs, i.e. blended ocean forcing products, allows for an increased temporal resolution (e.g., daily) but generally only resolves NWP spatial scales of about 100-150 km. Therefore, information on the wind-current interaction, the diurnal wind cycle and the wind variability in moist convection areas is lost in such products. Moreover, known systematic NWP model (parameterization) errors are in fact propagated at times and locations where no scatterometer winds are available. The alternative, direct forcing from NWP results in even more extensive physical drawbacks. We propose to maintain the increased temporal coverage in a gridded wind and stress product (ERA*), but also to maintain the most beneficial physical qualities of the scatterometer winds, i.e. 25-km spatial resolution, wind-current interaction, variability due to moist convection, etc., and, at the same time correct the large-scale NWP parameterization and dynamical errors. Additionally, we correct these winds for the effects of atmospheric stability and mass density, using stress equivalent 10 m winds, U10S. A scatterometer-based correction, using accurate, unbiased, high spatial resolution ocean vector winds from several scatterometers, i.e. the Advanced Scatterometers (ASCATs) on board Metop satellites and the OSCAT scatterometer onboard Oceansat-2, is proposed as a new angle to tackle this problem, i.e. to reduce NWP local wind biases accounting for satellite sampling characteristics. Since ERA local biases are relatively persistent over time but such persistence is regionally dependent (e.g., persistency is longer in the tropics than in the extratropics), we test different configurations of ERA*, i.e. with different temporal windows (from 1 to 5 days) and varying number of scatterometers (i.e. different combinations of the above mentioned scatterometer systems) to find the best quality forcing product. The new ERA* gridded ocean forcing product is validated against independent scatterometer data, i.e. the 25-km HSCAT (onboard HY-2A) wind product. HSCAT is a good wind reference since the orbit pass (6am/6pm) is very different from that of ASCAT-A/B (9:30am/9:30pm) and OSCAT (12:00am/12:00pm). Globally, there is a reduction of the vector root-mean-square error in ERA* w.r.t. ERA interim of more than 10%. Overall, the 1-day temporal window and the multiple scatterometer correction lead to the best quality ERA* global wind product, although such wind quality depends on the region. In particular, this ERA* product outperforms ERA in the tropics, where moist convection and wind-current interaction are not well resolved by the latter. Scores of the bias and standard deviation error support the above statements. Moreover, in contrast with ERA, ERA* is able to resolve eddy scales similar to those resolved by scatterometers, as shown by wind spectral analysis

2019 Living Planet Symposium, 13-17 May 2019, Milan, Italy, High-resolution satellite derived sea surface wind data, such as those from scatterometers, are increasingly required for operational monitoring and forecasting of the ocean. We present an improved version of ERA*, an ocean forcing product which keeps the time and space coverage of atmospheric model fields, but adds the accurately observed local mean and variability of wind scatterometers, to make these datasets suitable for, among others, high-resolution ocean model forcing. Recent attempts of combining scatterometer data and numerical weather prediction (NWP) outputs, i.e., blended ocean forcing products, allows for an increased temporal resolution (e.g., daily) but generally only resolves NWP spatial scales of about 100-150 km. Therefore, information on the wind-current interaction, the diurnal wind cycle and the wind variability in moist convection areas is lost in such products. Moreover, known systematic NWP model (parameterization) errors are in fact propagated at times and locations where no scatterometer winds are available. The alternative, direct forcing from NWP results in even more extensive physical drawbacks. We propose to maintain the increased temporal coverage in a gridded wind and stress product (ERA*), but also to maintain the most beneficial physical qualities of the scatterometer winds, i.e., 25-km spatial resolution, wind-current interaction, variability due to moist convection, etc., and, at the same time correct the large-scale NWP parameterization and dynamical errors. Additionally, we correct these winds for the effects of atmospheric stability and mass density, using stress equivalent 10 m winds, U10S. A scatterometer-based correction, using accurate, unbiased, high spatial resolution ocean vector winds from several scatterometers, i.e., the Advanced Scatterometers (ASCATs) on board Metop satellites and the OSCAT scatterometer onboard Oceansat-2, is proposed as a new angle to tackle this problem, i.e., to reduce NWP local wind biases accounting for satellite sampling characteristics (note that the scatterometer temporal sampling is latitudinal dependent and rather poor in the tropics). The correction consists of geolocated (i.e., at every ocean grid point), temporally - averaged differences between the scatterometer and the collocated NWP reanalysis (ERA-interim) U10S. Since ERA local biases are relatively persistent over time but such persistence is regionally dependent (e.g., such persistence is longer in the tropics than in the extratropics), we test different configurations of ERA*, i.e., with different temporal windows (from 1 to 5 days) and varying number of scatterometers (i.e., different combinations of the above mentioned scatterometer systems) in order to find the best quality forcing product. The new ERA* gridded ocean forcing product is validated against independent scatterometer data, i.e., the 25-km HSCAT (onboard HY-2A) wind product. HSCAT is a good wind reference since the orbit pass (6am/6pm) is very different from that of ASCAT-A/B (9:30am/9:30pm) and OSCAT (12:00am/12:00pm). Globally, there is a reduction of the vector root-mean-square error in ERA* w.r.t. ERA interim of more than 10%. Overall, the 1-day temporal window and the multiple scatterometer correction lead to the best quality ERA* global wind product, although such wind quality depends on the region. In particular, this ERA* product outperforms ERA in the tropics, where moist convection and wind-current interaction are not well resolved by the latter. Scores of the bias and standard deviation error support the above statements. Moreover, in contrast with ERA, ERA* is able to resolve eddy scales similar to those resolved by scatterometers, as shown by wind spectral analysis

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

This article summarizes some of the activities in which Jordi Font, research professor and head of the Department of Physical and Technological Oceanography, Institut de Ciències del Mar (CSIC, Spanish National Research Council) in Barcelona, has been involved as co-Principal Investigator for Ocean Salinity of the European Space Agency Soil Moisture and Ocean Salinity (SMOS) Earth Explorer Mission from the perspective of the Remote Sensing Lab at the Universitat Politècnica de Catalunya. We have probably left out some of his many contributions to salinity remote sensing, but we hope that this review will give an idea of the importance of his work. We focus on the following issues: 1) the new accurate measurements of the sea water dielectric constant, 2) the WISE and EuroSTARRS field experiments that helped to define the geophysical model function relating brightness temperature to sea state, 3) the FROG 2003 field experiment that helped to understand the emission of sea foam, 4) GNSS-R techniques for improving sea surface salinity retrieval, 5) instrument characterization campaigns, and 6) the operational implementation of the Processing Centre of Levels 3 and 4 at the SMOS Barcelona Expert Centre., Este artículo resume algunas de las actividades en las que Jordi Font, profesor de investigación y jefe del Departamento de Física y Tecnología Oceanográfica, del Institut de Ciències del Mar (CSIC) en Barcelona, ha estado desarrollando como co-Investigador Principal de la parte de la misión SMOS de la ESA, una misión Earth Explorer, desde la perspectiva del Remote Sensing Lab, de la Universitat Politècnica de Catalunya. Seguramente, estamos olvidando algunas de sus muchas contribuciones a la teledetección de la salinidad, pero esperamos que esta revisión dé una idea de la importancia de su trabajo. Este artículo se focaliza en los siguientes puntos: 1) las medidas de alta calidad de la constante dieléctrica del agua marina, 2) las campañas de medidas WISE y EuroSTARRS que ayudaron a la definición del modelo geofísico relacionando la temperatura de brillo con el estado del mar, 3) la campaña de medidas FROG 2003 que ayudó a entender la emisión de la espuma marina 4) presentación de las técnicas de GNSS-R para la mejora de la recuperación de la salinidad superficial 5) campañas para la caracterización del instrumento y 6) la implantación del centro de procesado operacional de niveles 3 y 4 en el SMOS Barcelona Expert Centre.

2016 European Space Agency (ESA) Living Planet Symposium, 9-13 May 2016, Prague, Czech Republic, Soil moisture observations are expected to play an important role in monitoring global climate trends. However, measuring soil moisture remains challenging because of its high spatial and temporal variability. Point-scale in situ measurements are scarce and remote sensing is the only practical means for obtaining regional- and global-scale soil moisture estimates. The ESA SMOS mission, launched in 2009, is measuring the Earth´s surface soil moisture at daily time scales with an unprecedented level of accuracy. Yet, incorporating these soil moisture observations to land surface models is complex since it is usually represented as an index of water content in the soil using different hydrological schemes and different physical approaches of the soil-water interaction. In this context, it has become important to characterize the climatological differences between models, satellite estimates, and ground-based measurements of soil moisture. This study investigates the temporal dynamics of soil moisture and its anomalies based on three main data sources: SMOS, in situ observations, and the land surface reanalysis ERA-Interim. The analysis includes the determination of mean annual conditions, trends and anomalies for modeled and satellite-based soil moisture estimates. Their spatial coherence and relationships through precipitation and evaporation are also analyzed to improve understanding of global water cycle dynamics. Ground-based estimates are used as a benchmark in four target regions representative of arid, semi-arid, sub-humid and humid climates across global land biomes. Results show that, despite still being a short data set, SMOS data provide coherent and reliable variability patterns at both seasonal and inter-annual scales. This work is an important support to all land data assimilation projects that are using remote sensing products to initialize forecast systems

21 pages, 9 figures, 1 table, Wildfires are an increasingly concerning issue due to their impact on safety, environment, and the economy. Although natural fires are in part essential to maintain dynamics, biodiversity, and productivity in some ecosystems, their damages are huge in economic and environmental terms (FAO, 2006; Ireland and Petropoulos, 2015; Karamesouti et al., 2016). Usually, forest fires occur in patchy landscapes, affecting agricultural and urban areas, and in some cases, seriously threatening human lives. [...], This study was funded by the Spanish government through the project PROMISES: Productos y servicios innovadors con sensores de microondas, SMOS y Sentinels para tierra (ESP2015-67549-C3-1-R), the pre-doctoral grant Ayudas para contratos predoctorales para la Formación de Doctores, with reference BES-2013-066240, and the European Regional DevelopmentFund (ERDF)

2nd SMOS Science Conference, 25-29 May 2015, Madrid), Spain.-- 2 pages

4th International Symposium on Recent Advances in Quantitative Remote Sensing (RAQRS'IV), 22-26 September 2014, Torrent, Valencia, Spain.-- 2 pages, Soil moisture observations are expected to play an important role in monitoring global climate trends. However, measuring soil moisture is challenging because of its high variability; point-scale in situ measurements are scarce being remote sensing the only practical means to obtain regional- and global-scale soil moisture estimates. The ESA’s Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission ever designed to measuring the Earth’s surface soil moisture at daily time scales with an unprecedented level of accuracy. Since its launch in November 2009, significant efforts have been dedicated to validate, and finetune, the retrieval algorithms so that SMOS-derived soil moisture estimates meet the standards required for a wide variety of applications. The SMOS Barcelona Expert Center (BEC) is distributing daily, monthly, seasonal and annual temporal averages of 0.25° global soil moisture maps, which have proved useful for assessing drought conditions and monitoring water stress. These products include a downscaling algorithm to combine SMOS and NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) data into fine-scale (< 1km) soil moisture estimates, which permits extending the applicability of the data to regional and local studies. These soil moisture products can also be a useful tool to monitor the effectiveness of land restoration management practices. The aim of this work is to assess the reliability of novel global SMOS-derived soil moisture products produced at BEC. The analysis includes determination of variability at seasonal and interannual scales, focusing on six target regions representative of arid, semi-arid, sub-humid and humid areas across global land biomes. In addition, the dry-normal-humid ranges from SMOS products are being generated to provide maps of their spatial and temporal distribution. These soil moisture climatologies are further used for analyzing the anomalies during the four-year of SMOS in orbit

European Geosciences Union General Assembly 2014 (EGU2014), 27 april - 2 may 2014, Vienna, Austria.-- 1 page, Soil moisture plays an important role in determining the likelihood of droughts and floods that may affect an area. Knowledge of soil moisture distribution as a function of time and space is highly relevant for hydrological, ecological and agricultural applications, especially in water-limited or drought-prone regions. However, measuring soil moisture is challenging because of its high variability; point-scale in-situ measurements are scarce being remote sensing the only practical means to obtain regional- and global-scale soil moisture estimates. The ESA’s Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission ever designed to measuring the Earth’s surface soil moisture at near daily time scales with levels of accuracy previously not attained. Since its launch in November 2009, significant efforts have been dedicated to validate and fine-tune the retrieval algorithms so that SMOS-derived soil moisture estimates meet the standards required for a wide variety of applications. In this line, the SMOS Barcelona Expert Center (BEC) is distributing daily, monthly, and annual temporal averages of 0.25-deg global soil moisture maps, which have proved useful for assessing drought and water-stress conditions. In addition, a downscaling algorithm has been developed to combine SMOS and NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) data into fine-scale (< 1km) soil moisture estimates, which permits extending the applicability of the data to regional and local studies. Fine-scale soil moisture maps are currently limited to the Iberian Peninsula but the algorithm is dynamic and can be transported to any region. Soil moisture maps are generated in a near real-time fashion at BEC facilities and are used by Barcelona’s fire prevention services to detect extremely dry soil and vegetation conditions posing a risk of fire. Recently, they have been used to explain drought-induced tree mortality episodes and forest decline in the Catalonia region. These soil moisture products can also be a useful tool to monitor the effectiveness of land restoration management practices. The aim of this work is to demonstrate the feasibility of using SMOS soil moisture maps for monitoring drought and water-stress conditions. In previous research, SMOS-derived Soil Moisture Anomalies (SSMA), calculated in a ten-day basis, were shown to be in close relationship with well-known drought indices (the Standardized Precipitation Index and the Standardized Precipitation Evapotranspiration Index). In this work, SSMA have been calculated for the period 2010-2013 in representative arid, semi-arid, sub-humid and humid areas across global land biomes. The SSMA reflect the cumulative precipitation anomalies and is known to provide ’memory’ in the climate and hydrological system; the water retained in the soil after a rainfall event is temporally more persistent than the rainfall event itself, and has a greater persistence during periods of low precipitation. Besides, the Normalized Difference Vegetation Index (NDVI) from MODIS is used as an indicator of vegetation activity and growth. The NDVI time series are expected to reflect the changes in surface vegetation density and status induced by water-deficit conditions. Understanding the relationships between SSMA and NDVI concurrent time series should provide new insight about the sensitivity of land biomes to drought

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.

12th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRad), 5-9 March 2012, Villa Mondragone

12th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRad), 5-9 March 2012, Villa Mondragone

14 pages, 17 figures, This work describes the main effects that have to be taken into account to model the sea surface emission at L-band, and the existing approaches to perform the sea surface salinity retrieval from multiangular radiometric measurements. This manuscript reviews the activities carried out in these fields during the past years by the Universitat Politècnica de Catalunya (UPC) in collaboration with the Institut de Ciències del Mar (ICM - CSIC). They cover the precise measurement of the dielectric permittivity of the seawater at L-band, the sea surface emissivity (including the effect of wind-driven waves, swell, currents, rain, and oil spills), the comparison of experimental data with numerical models, and the development of sea surface salinity retrieval algorithms for SMOS using multiangular radiometric data. The first salinity retrievals using 2D aperture synthesis radiometry are also presented, This work has been supported by ESA Projects ESA, ESTEC contract 141888/00/NL/DC, CCN-1 and CCN2, ESA contract 18176/04/NL/CB, and Spanish Research projects and EU FEDER CICYT TIC 99-1050-C03-01, TIC2002-04451-C02-01, TEC2005-06863-C02-01, PNE-009/2001-C-02, ESP2002-11648-E, ESP2004-00671, and ESP2005-06823-C05

10th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment, 11-14 March 2008, Florence, Italy

7th SMOS Science Workshop, 29-31 October 2007, Frascati, Italy

Aquarius-SMOS-Hydros Joint Science Workshop, April 2004, Miami, USA.-- 1 page, 4 figures, SMOS: Soil Moisture and Ocean Salinity is an ESA mission to be launched on 2007. It carries an L-band polarimetric radiometer with multi-angular view capability. WISE (Wind and Salinity Experiment) field measurements were done to improve sea surface emissivity models at L-band for sea surface salinity (SSS) retrieval: A radiometer and several buoys were installed in a fixed platform in the NW Mediterranean to measure TB, SST, SSS, WSand SWH