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201. Soil moisture from space: techniques and limitations

Author: Kerr, Yann H., Wigneron, Jean-Pierre, Ahmad, Al Bitar, Mialon, Arnaud, Srivastava, P.K., Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), NASA Goddard Space Flight Center (GSFC), Banaras Hindu University [Varanasi] (BHU), Prashant K. Srivastava (ed.), George P. Petropoulos (ed.), and Yann H. Kerr (ed.)
Subjects: [SDV]Life Sciences [q-bio]
Abstract: Chapitre 1; International audience; Soil moisture has always been an important surface variable, but its retrieval in a global fashion has always proved very difficult. From dedicated science networks to operational ones, it is almost impossible to access a global view of our planet, not to mention measurement homogeneity. Remote sensing can provide a solution in the sense that the coverage can be global and the uniqueness of the instruments favors homogeneity. However, the requirements are very stringent and only “all weather” direct measurements could provide an answer. Currently, this is only possible with low-frequency, passive microwave measurements. Moreover, these measurements only concern the surface layer. To access the vadose zone, indirect methods using models and assimilation are required. Finally, specific surface conditions (dense rain forest, snow covered soils, etc.) can significantly hamper the measurements, making global coverage a difficult goal to attain. Considering the importance of soil moisture in a range of fields, it seems important to see how, by merging different approaches, we can try to offer a complete coverage and provide long temporal series. The second goal is to provide a feeling of what could be the future evolution required to obtain, from space, accurate, adequate, and useful information on soil moisture.
Published: 2016

202. Testing simple local regression equations to derive long‐term global soil moisture datasets from passive microwave observations

Author: Al Yaari, Amen, Wigneron, Jean-Pierre, Kerr, Yann, De Jeu, Richard, Rodriguez‐Fernandez, Nemesio, Van der Schalie, Robin, Dolman, Han, Drusch, Matthias, Mecklenburg, Susanne, Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), University of Amsterdam [Amsterdam] (UvA), European Space Research and Technology Centre (ESTEC), European Space Agency (ESA), ESA Centre for Earth Observation (ESRIN), European Space Research Institute (ESRIN). ITA., Interactions Sol Plante Atmosphère (ISPA), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), and Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)
Subjects: [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract: The European Space Agency's Water Cycle Multimission Observation Strategy (WACMOS) was set up in 2010‐2012 and supported by the Support To Science Element (STSE) program. Within WACMOS first long term soil moisture (SM) data records from passive and active microwave data have been developed. In January 2012 the ESA Climate Change Initiative (CCI) SM program started and refined the SM products obtained during the preliminary WACMOS project. In June 2012, the first long term SM datasets have been made public available through the ESA CCI portal (Su et al., 2010) and in July 2014 the second version was available also on the same portal. This product was computed by merging surface SM (SSM) data sets retrieved from several microwave sensors in an attempt to produce the most complete and consistent long‐term time series of SM (1978‐2013) (http://www.esa‐cci.org/)(Liu et al., 2012). Two dedicated SM spaceborne missions, the Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active/Passive (SMAP) satellites, were launched just recently, and therefore not yet considered for the CCI product. SMOS is an innovative in space technology that has been providing multi‐angular microwave brightness temperatures TB observations at L‐band since 2010 (Kerr et al., 2012). The ESA established a passive microwave SSM fusion study to investigate the inclusion of SMOS SSM in a long‐term SM datasets. For this purpose, three approaches have been selected: the Land Parameter Retrieval Model (LPRM) algorithm (Owe et al., 2001; Owe et al., 2008; Van der Schalie et al., 2015), neural networks (Rodriguez‐Fernandez et al., 2014; Rodríguez‐Fernández et al., 2015), and local statistical regressions (Wigneron et al., 2004). The present study addresses only the local regressions, as the first two methods are addressed by other groups. Objectives: The main objectives of this study are to: (i) test a physically based local regression method to retrieve SSM from the AMSR‐E TB observations at the global scale, (ii) extend the SMOS SSM into the past (2003‐2009), (iii) compare the quality of this product to the other SM datasets produced from the two other approaches, with reference to modelled SSM datasets and in situ measurements at both global and local scales. Methods: Wigneron et al. (2004) and Saleh et al. (2006) have developed and evaluated physically‐based regression equations between the SSM and microwave reflectivity (i.e. one minus emissivity) derived analytically from the radiative transfer model (τ‐ω model) (Mo et al., 1982; Wigneron et al., 1995). More specifically, this study investigated the use of these local regression methods to retrieve SSM based on a combination of passive microwave remote sensing observations from the Advanced Microwave Scanning Radiometer (AMSR‐E; 2003 ‐ Sept. 2011) and the SMOS sensors. Regression coefficients were calibrated “locally” over each pixel using AMSR‐E horizontal and vertical TB observations and SMOS level 3 SM (SMOSL3; as a training data). This calibration process was carried out over the June 2010 ‐ Sept. 2011 period, over which both SMOS and AMSRE observations coincide. Results and conclusion: Based on these calibrated coefficients, global SSM maps were computed from the AMSR‐E TB observations during the 2003‐2011 period (referred here to as AMSR‐reg). The regression quality was assessed by evaluating the AMSR‐reg SSM maps against the SMOSL3 SSM products over the period of calibration, in terms of correlations (R) and Root Mean Square Error (RMSE). A good agreement, R (mostly > 0.75) and RMSE (mostly < 0.04 m3/m3), was obtained between the AMSR‐reg and SMOSL3 SSM products particularly over Australia, central USA, central Asia, and the Sahel. AMSR‐reg retrievals were compared to the original AMSR‐E SSM retrievals derived from the Land Parameter Retrieval Model (AMSR‐LPRM), against two kinds of reference SSM: (i) global MERRA‐Land SSM simulations (2003 ‐ 2009) and (ii) in situ measurements (2008‐2009). The results demonstrated that both AMSR‐reg and AMSR‐LPRM (better) successfully captured the temporal dynamics of the used SM references in terms of correlation values. The AMSR‐reg was more consistent with MERRA‐land than AMSR‐LPRM in terms of unbiased RMSE (unbRMSE) particularly over high latitude regions with a global average of unbRMSE of 0.059 and 0.098 m3/m3, respectively. In conclusion, the statistical regression appears to be a promising approach for merging the SSM data sets retrieved from both AMSR‐E and SMOS in the framework of the ESA CCI project.
Published: 2015

203. SMOS the water cycle mission : an overview, Earth Observation for water cycle science

Author: Kerr, Yann H., Delwart, Steven, Mecklenburg, Susanne, Boutin, Jacqueline, Ferrazzoli, Patricia, Mahmoodi, Ali, Al-Yaari, Amen, Mialon, Arnaud, Richaume, Philippe, Wigneron, Jean-Pierre, Bircher, Simone, Rodriguez‐fernandez, Nemesio, Reul, Nicolas, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), ESA Centre for Earth Observation (ESRIN), European Space Agency (ESA), Interactions et Processus au sein de la couche de Surface Océanique (IPSO), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Università degli Studi di Roma Tor Vergata [Roma], Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Agence Spatiale Européenne = European Space Agency (ESA), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636))
Subjects: [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract: International audience; The SMOS (Soil Moisture and Ocean Salinity) satellite was successfully launched in November 2009. This ESA led mission for Earth Observation is dedicated to provide soil moisture over continental surface (with an accuracy goal of 0.04 m3/m3) vegetation water content over land and ocean salinity. These geophysical features are important as they control the energy balance between the surface and the atmosphere. Their knowledge at a global scale is of interest for climatic and weather researches in particular in improving models forecasts. The SMOS instrument measures the passive microwave emission of the Earth surface at a frequency of 1,4 GHz (L‐band). The instrument is an interferometer and provides brightness temperatures with an average resolution of 40 km, at several angles and dual polarizations. Data are acquired at two times in a day at 6 am and 18 pm (local time) and insure a complete coverage of the Earth surface in 3 days with a sampling of 15 km. The main products of the mission are of course Soil Moisture and Sea Surface salinity, but also vegetation opacity (directly related to water content) of vegetation covers including forests, surface dielectric constant for level two but also brightness temperatures at the surface, strong winds, root zone soil moisture and RFI (radio frequency interferences) maps. From Level 2 SMOS data several groups have started making new products several of them being either operational or on the verge of being such. We will show some of them or refer to related presentations. They include freeze defreeze (FMI), thin sea ice (Klimat Center Hamburg), near real time brightness temperatures and soon soil moisture (ECMWF), root zone soil moisture and drought indices (USDA and CESBIO). We are also working on more elaborate products such as water fractions, flood risk indexes, improved precipitation with use of assimilated SMOS data, etc. The focus in this presentation will be given to the latter new science products. The purpose of this communication is to present the mission results after almost 6 years in orbit and a major re‐processing as well as some outstanding results already obtained. A special attention will be devoted to level 2 products and to the retrieval quality improvements from version 3 (at launch) to the current version 620.
Published: 2015

204. SMOS and hydrology

Author: Kerr, Yann H., Ahmad, Al Bitar, Leroux, Delphine, Pellarin, Thierry, Molero, Beatriz, Choné, Audrey, Parrens, Marie, Wigneron, Jean-Pierre, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'étude des transferts en hydrologie et environnement (LTHE), Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), and Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)
Subjects: radiométrie microonde, impact régional, télédétection, [SDE.MCG]Environmental Sciences/Global Changes, Signal and Image processing, Traitement du signal et de l'image, projet smos, Milieux et Changements globaux, donnée satellite, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract: International audience; SMOS, a L Band radiometer using aperture synthesis to achieve a good spatial resolution, was successfully launched on November 2, 2009. It was developed and made under the leadership of the European Space Agency (ESA) as an Earth Explorer Opportunity mission. It is a joint program with the Centre National d’Etudes Spatiales (CNES) in France and the Centro para el Desarrollo Teccnologico Industrial (CDTI) in Spain. SMOS carries a single payload, an L band 2D interferometric, radiometer in the 1400‐1427 MHz protected band. This wavelength penetrates well through the vegetation and the atmosphere is almost transparent enabling to infer both soil moisture and vegetation water content. SMOS achieves an unprecedented spatial resolution of 50 km at L‐band maximum (43 km on average) with multi angular‐dual polarized (or fully polarized) brightness temperatures over the globe and with a revisit time smaller than 3 days. SMOS has been now acquiring data for 5.5 years. The data quality exceeds what was expected, showing very good sensitivity and stability. The data is however impaired by man‐made emission in the protected band, leading to degraded measurements in several areas including parts of Europe and of China. However, many different international teams are now addressing data use in various fields including hydrology. We have now acquired data over a number of significant “extreme events” such as droughts and floods giving useful information of potential applications. We are now working on the coupling with other models and or disaggregation to address soil moisture distribution over watersheds. We are also concentrating efforts on water budget and regional impacts. From all those studies, it is now possible to express the “lessons learned” and derive a possible way forward. This paper thus gives an overview of the water cycle science goals of the SMOS mission, a description of its main elements, and a taste of the first results including performances at brightness temperature as well as at geophysical parameters level and how they are being put in good use for hydrological applications.
Published: 2015

205. SMOS soil moisture assimilation for improved hydrologic simulation in the Murray Darling Basin, Australia

Author: Ahmad, Al Bitar, Lievens, H., Tomer, Sat-Kumar, De Lannoy, G.J.M., Drusch, M., Dumedah, G., Hendricks Franssen, H.-J., Kerr, Yann H., Martens, B., Pan, M., Roundy, J.K., Vereecken, H., Walker, J.P., Wood, E.F., Verhoest, N.E.C., Pauwels, V.R.N., Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Universiteit Gent = Ghent University [Belgium] (UGENT), SATYUKT ANALYTICS PVT LTD BANGALORE IND, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Department of Earth and Environmental Sciences [Leuven] (EES), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), ESA/ESTEC, and Princeton University
Subjects: 010504 meteorology & atmospheric sciences, Hydrological modelling, 0207 environmental engineering, Drainage basin, Soil Science, Streamflow, Murray Darling Basin, 02 engineering and technology, Structural basin, 01 natural sciences, [SPI]Engineering Sciences [physics], Data assimilation, Computers in Earth Sciences, 020701 environmental engineering, Water content, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, Hydrology, geography, geography.geographical_feature_category, Geology, 15. Life on land, 6. Clean water, 13. Climate action, Environmental science, Ensemble Kalman filter, Soil moisture, Surface runoff, SMOS
Abstract: This study explores the benefits of assimilating SMOS soil moisture retrievals for hydrologic modeling, with a focus on soil moisture and streamflow simulations in the Murray Darling Basin, Australia. In this basin, floods occur relatively frequently and initial catchment storage is known to be key to runoff generation. The land surface model is the Variable Infiltration Capacity (VIC) model. The model is calibrated using the available streamflow records of 169 gauge stations across the Murray Darling Basin. The VIC soil moisture forecast is sequentially updated with observations from the SMOS Level 3 CATDS (Centre Aval de Traitement des Données SMOS) soil moisture product using the Ensemble Kalman filter. The assimilation algorithm accounts for the spatial mismatch between the model (0.125°) and the SMOS observation (25km) grids. Three widely-used methods for removing bias between model simulations and satellite observations of soil moisture are evaluated. These methods match the first, second and higher order moments of the soil moisture distributions, respectively. In this study, the first order bias correction, i.e. the rescaling of the long term mean, is the recommended method. Preserving the observational variability of the SMOS soil moisture data leads to improved soil moisture updates, particularly for dry and wet conditions, and enhances initial conditions for runoff generation. Second or higher order bias correction, which includes a rescaling of the variance, decreases the temporal variability of the assimilation results. In comparison with in situ measurements of OzNet, the assimilation with mean bias correction reduces the root mean square error (RMSE) of the modeled soil moisture from 0.058m3/m3 to 0.046m3/m3 and increases the correlation from 0.564 to 0.714. These improvements in antecedent wetness conditions further translate into improved predictions of associated water fluxes, particularly runoff peaks. In conclusion, the results of this study clearly demonstrate the merit of SMOS data assimilation for soil moisture and streamflow predictions at the large scale. publisher: Elsevier articletitle: SMOS soil moisture assimilation for improved hydrologic simulation in the Murray Darling Basin, Australia journaltitle: Remote Sensing of Environment articlelink: http://dx.doi.org/10.1016/j.rse.2015.06.025 content_type: article copyright: Copyright © 2015 Elsevier Inc. All rights reserved. ispartof: Remote Sensing of Environment vol:168 pages:146-162 status: published
Published: 2015

206. Stochastic Bias Correction and Uncertainty Estimation of Satellite-Retrieved Soil Moisture Products

Author: Lee, Ju Hyoung, primary, Zhao, Chuanfeng, additional, and Kerr, Yann, additional
Published: 2017
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207. Accurate geolocation of RFI sources from SMOS interferometric data

Author: Anterrieu, Eric, primary, Khazaal, Ali, additional, Cabot, Francois, additional, and Kerr, Yann, additional
Published: 2017
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208. Impact of Direct Solar Radiations Seen by the Back-Lobes Antenna Patterns of SMOS on the Retrieved Images

Author: Khazaal, Ali, primary, Anterrieu, Eric, additional, Cabot, Francois, additional, and Kerr, Yann H., additional
Published: 2017
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209. SMOS and applications: First glance at synergistic and new results

Author: Kerr, Yann H., primary, Rodriguez-Fernandez, Nemesio, additional, Parrens, Marie, additional, Al-Yaari, Amen, additional, Fernandez, Roberto, additional, Wigneron, Jean-Pierre, additional, Mahmoodi, Ali, additional, Al Bitar, Ahmad, additional, Mialon, Arnaud, additional, Bircher, Simone, additional, Molero, Beatriz, additional, Richaume, Philippe, additional, and Cabot, Francois, additional
Published: 2017
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210. Integration of SMAP and SMOS L-band observations

Author: Bindlish, Rajat, primary, Jackson, Thomas J., additional, Chan, Steven, additional, Colliander, Andreas, additional, and Kerr, Yann, additional
Published: 2017
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211. Evaporation-based disaggregation of surface soil moisture data: The dispatch method, the CATDS product and on-going research

Author: Merlin, Olivier, primary, Olivera-Guerra, Luis, additional, Hssaine, Bouchra Ait, additional, Amazirh, Abdelhakim, additional, Malbeteau, Yoann, additional, Stefan, Vivien, additional, Molero, Beatriz, additional, Rafi, Zoubair, additional, Escorihuela, Maria Jose, additional, Ezzahar, Jamal, additional, Khabba, Said, additional, Walker, Jeffrey, additional, Kerr, Yann, additional, Simonneaux, Vincent, additional, and Er-Raki, Salah, additional
Published: 2017
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212. Soil moisture retrieval using SMOS brightness temperatures and a neural network trained on in situ measurements

Author: Rodriguez-Fernandez, Nemesio J., primary, de Souza, Veronica, additional, Kerr, Yann H., additional, Richaume, Philippe, additional, and Al Bitar, Ahmad, additional
Published: 2017
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213. Lessons learnt from SMOS after 7 years in orbit

Author: Martin-Neira, Manuel, primary, Oliva, Roger, additional, Corbella, Ignasi, additional, Torres, Francesc, additional, Duffo, Nuria, additional, Duran, Israel, additional, Kainulainen, Juha, additional, Closa, Josep, additional, Zurita, Alberto, additional, Cabot, Francois, additional, Khazaal, Ali, additional, Anterrieu, Eric, additional, Barbosa, Jose, additional, Lopes, Goncalo, additional, Tenerelli, Joe, additional, Diez-Garcia, Raul, additional, Fauste, Jorge, additional, Gonzalez-Gambau, Veronica, additional, Turiel, Antonio, additional, Delwart, Steven, additional, Crapolicchio, Raffaele, additional, Suess, Martin, additional, Mecklenburg, Susanne, additional, Drusch, Matthias, additional, Sabia, Roberto, additional, Daganzo-Eusebio, Elena, additional, Kerr, Yann, additional, and Reul, Nicolas, additional
Published: 2017
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214. Global retrieval of soil moisture using neural networks trained with synthetic radiometric data

Author: Rodriguez-Fernandez, Nemesio J., primary, Richaume, Philippe, additional, Kerr, Yann H., additional, Aires, Filipe, additional, Prigent, Catherine, additional, and Wigneron, Jean-Pierre, additional
Published: 2017
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215. The global SMOS Level 3 daily soil moisture and brightness temperature maps

Author: Al Bitar, Ahmad, primary, Mialon, Arnaud, additional, Kerr, Yann H., additional, Cabot, François, additional, Richaume, Philippe, additional, Jacquette, Elsa, additional, Quesney, Arnaud, additional, Mahmoodi, Ali, additional, Tarot, Stéphane, additional, Parrens, Marie, additional, Al-Yaari, Amen, additional, Pellarin, Thierry, additional, Rodriguez-Fernandez, Nemesio, additional, and Wigneron, Jean-Pierre, additional
Published: 2017
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216. Mapping Dynamic Water Fraction under the Tropical Rain Forests of the Amazonian Basin from SMOS Brightness Temperatures

Author: Parrens, Marie, primary, Al Bitar, Ahmad, additional, Frappart, Frédéric, additional, Papa, Fabrice, additional, Calmant, Stephane, additional, Crétaux, Jean-François, additional, Wigneron, Jean-Pierre, additional, and Kerr, Yann, additional
Published: 2017
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217. SMOS near real time soil moisture product: processor overview and first validation results

Author: Rodríguez-Fernández, Nemesio, primary, Muñoz Sabater, Joaquin, additional, Richaume, Philippe, additional, de Rosnay, Patricia, additional, Kerr, Yann, additional, Albergel, Clement, additional, Drusch, Matthias, additional, and Mecklenburg, Susanne, additional
Published: 2017
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218. SMOS-IC: An Alternative SMOS Soil Moisture and Vegetation Optical Depth Product

Author: Fernandez-Moran, Roberto, primary, Al-Yaari, Amen, additional, Mialon, Arnaud, additional, Mahmoodi, Ali, additional, Al Bitar, Ahmad, additional, De Lannoy, Gabrielle, additional, Rodriguez-Fernandez, Nemesio, additional, Lopez-Baeza, Ernesto, additional, Kerr, Yann, additional, and Wigneron, Jean-Pierre, additional
Published: 2017
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219. A Comparative Study of the SMAP Passive Soil Moisture Product With Existing Satellite-Based Soil Moisture Products

Author: Burgin, Mariko S., primary, Colliander, Andreas, additional, Njoku, Eni G., additional, Chan, Steven K., additional, Cabot, Francois, additional, Kerr, Yann H., additional, Bindlish, Rajat, additional, Jackson, Thomas J., additional, Entekhabi, Dara, additional, and Yueh, Simon H., additional
Published: 2017
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220. Supplementary material to "The Global SMOS Level 3 daily soil moisture and brightness temperature maps"

Author: Al Bitar, Ahmad, primary, Mialon, Arnaud, additional, Kerr, Yann, additional, Cabot, François, additional, Richaume, Philippe, additional, Jacquette, Elsa, additional, Quesney, Arnaud, additional, Mahmoodi, Ali, additional, Tarot, Stephane, additional, Parrens, Marie, additional, Al-yaari, Amen, additional, Pellarin, Thierry, additional, Rodriguez-Fernandez, Nemesio, additional, and Wigneron, Jean-Pierre, additional
Published: 2017
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221. Efficiency of end effect probes for in-situ permittivity measurements in the 0.5–6GHz frequency range and their application for organic soil horizons study

Author: Demontoux, François, primary, Razafindratsima, Stephen, additional, Bircher, Simone, additional, Ruffié, Gilles, additional, Bonnaudin, Fabrice, additional, Jonard, François, additional, Wigneron, Jean-Pierre, additional, Sbartaï, Mehdi, additional, and Kerr, Yann, additional
Published: 2017
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222. Development and Assessment of the Sand Dust Prediction Model by Utilizing Microwave-Based Satellite Soil Moisture and Reanalysis Datasets in East Asian Desert Areas

Author: Kim, Hyunglok, primary, Zohaib, Muhammad, additional, Cho, Eunsang, additional, Kerr, Yann H., additional, and Choi, Minha, additional
Published: 2017
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223. Apport de l'observation satellitaire à l'hydrologie continentale

Author: Biancamaria, Sylvain, primary and Kerr, Yann, additional
Published: 2017
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224. L-Band Relative Permittivity of Organic Soil Surface Layers—A New Dataset of Resonant Cavity Measurements and Model Evaluation

Author: Bircher, Simone, primary, Demontoux, François, additional, Razafindratsima, Stephen, additional, Zakharova, Elena, additional, Drusch, Matthias, additional, Wigneron, Jean-Pierre, additional, and Kerr, Yann, additional
Published: 2016
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225. MAPSM: A Spatio-Temporal Algorithm for Merging Soil Moisture from Active and Passive Microwave Remote Sensing

Author: Tomer, Sat, primary, Al Bitar, Ahmad, additional, Sekhar, Muddu, additional, Zribi, Mehrez, additional, Bandyopadhyay, Soumya, additional, and Kerr, Yann, additional
Published: 2016
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226. Long Term Global Surface Soil Moisture Fields Using an SMOS-Trained Neural Network Applied to AMSR-E Data

Author: Rodríguez-Fernández, Nemesio, primary, Kerr, Yann, additional, van der Schalie, Robin, additional, Al-Yaari, Amen, additional, Wigneron, Jean-Pierre, additional, de Jeu, Richard, additional, Richaume, Philippe, additional, Dutra, Emanuel, additional, Mialon, Arnaud, additional, and Drusch, Matthias, additional
Published: 2016
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227. Eleven-years of an homogeneous soil moisture dataset from AMSR-E and SMOS observations

Author: Rodriguez-Fernandez, Nemesio, Kerr, Yann, Wigneron, Jean-Pierre, Al Yaari, Amen, De Jeu, Richard, Van der Schalie, Robin, Mecklenburg, Susanne, Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Faculty of Earth and Life Sciences, VU University, ESRIN, European Space Agency (ESA), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Interactions Sol Plante Atmosphère (UMR ISPA), Vrije Universiteit Amsterdam [Amsterdam] (VU), ESA Centre for Earth Observation (ESRIN), Agence Spatiale Européenne = European Space Agency (ESA), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), VU University Amsterdam, and Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU)
Subjects: analyse de données, remote sensing, télédétection, [SDE.MCG]Environmental Sciences/Global Changes, data analysis, Signal and Image processing, Traitement du signal et de l'image, Milieux et Changements globaux, donnée satellite, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract: Eleven-years of an homogeneous soil moisture dataset from AMSR-E and SMOS observations. 2015 International Geoscience and Remote Sensing Symposium IGARSS
Published: 2015

228. SMOS after five years in operations : from tentative research to operational applications

Author: Kerr, Yann H., Mecklenburg, Susanne, Delwart, Steven, Drusch, Matthias, Ferrazzoli, Paolo, Font, Jordi, Hahne, Achim, Mahmoodi, Ali, Reul, Nicolas, Richaume, Philippe, Waldteufel, Philippe, Wigneron, Jean-Pierre, Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), European Space Research and Technology Centre (ESTEC), European Space Agency (ESA), Università degli Studi di Roma Tor Vergata [Roma], Institute of Marine Sciences / Institut de Ciències del Mar [Barcelona] (ICM), Consejo Superior de Investigaciones Científicas [Spain] (CSIC), Laboratoire d'Océanographie Spatiale (LOS), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), ESTER - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Écologie fonctionnelle et physique de l'environnement (EPHYSE - UR1263), Institut National de la Recherche Agronomique (INRA), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Agence Spatiale Européenne = European Space Agency (ESA), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Écologie fonctionnelle et physique de l'environnement (EPHYSE), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)
Subjects: [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], ComputingMilieux_MISCELLANEOUS
Abstract: International audience
Published: 2015

229. Rainfall estimation by inverting SMOS soil moisture estimates: A comparison of different methods over Australia

Author: Brocca, Luca, primary, Pellarin, Thierry, additional, Crow, Wade T., additional, Ciabatta, Luca, additional, Massari, Christian, additional, Ryu, Dongryeol, additional, Su, Chun-Hsu, additional, Rüdiger, Christoph, additional, and Kerr, Yann, additional
Published: 2016
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230. Validation of SMOS level 3 soil moisture data

Author: Mialon, Arnaud, Ahmad, Al Bitar, Cabot, François, Bircher, Simone, Leroux, Delphine, Parrens, Marie, Pellarin, Thierry, Richaume, Philippe, Rodriguez‐Fernandez, Nemesio, Kerr, Yann H., Wigneron, Jean-Pierre, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'étude des transferts en hydrologie et environnement (LTHE), Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), European Space Agency (ESA). INT., Centre National d'Etudes Spatiales (CNES). FRA., and SMOS MODE (Mission Oceanographic Data Exploitation). INT.
Subjects: [SPI.ELEC]Engineering Sciences [physics]/Electromagnetism, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract: International audience; The SMOS ground segment “CATDS” (Centre Aval de Traitement des Données SMOS) has been delivering level 3 data, which are temporal aggregated products (1-day, 3-day, 10-day, monthly average). The retrieval is based on a modified version of ESA level 2 soil moisture processor to account for multi-orbit retrievals, correlated vegetation optical depth, projection on the EASE Grid. The soil moisture retrieval has evolved and improved since its first version and major changes lead to reprocessing campaigns to obtain homogeneous time series, i.e. data done using one processor. Three campaigns have been done so far at the CATDS and the last one, referred to as reprocessing RE03, uses the last calibrated brightness temperatures (version 620 for ESA level1C, version 280 for CATDS level3TB) and the last soil moisture processor (version 620 for EASE level 2 SM and version 280 for CATDS level 2 SM). The new set of products will be available in Spring 2015. The validation of SMOS data (level 2 and 3) has been a constant activity since the beginning of the mission. It consists in evaluating the performances of these products by comparing them at various climate areas like for example in Australia, West Africa, Denmark, France, in the US. It is done for every release to insure that the new data are consistent and closer to in-situ observations, as for instance when it was decided to switch the dielectric constant model. The aim of this communication is then to present data from the RE03 campaign and to discuss the changes and improvements of the new releases. A first analysis over a week (sept. 2013) shows that the new soil moisture values (RE03 version V280) are globally lower than the previous version by 0.01 m3/m3. This result is preliminary and the analysis will be extended to a longer time period.
Published: 2015

231. Testing simple regression equations to derive long-term global soil moisture datasets from satellite-based brightness temperature observations

Author: Al-Yaari, Amen, Wigneron, Jean-Pierre, Ducharne, Agnès, Kerr, Yann H., De Jeu, Richard, Schalie, Robin, Rodriguez‐Fernandez, Nemesio, Drusch, Matthias, Dolman, Han, Mecklenburg, Susanne, Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols (METIS), Université Pierre et Marie Curie - Paris 6 (UPMC)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), VU University Amsterdam, European Space Research and Technology Centre (ESTEC), European Space Agency (ESA), ESA Centre for Earth Observation (ESRIN), European Space Agency (ESA). INT., Centre National d'Etudes Spatiales (CNES). FRA., SMOS MODE (Mission Oceanographic Data Exploitation). INT., Université Pierre et Marie Curie - Paris 6 (UPMC)-École Pratique des Hautes Études (EPHE), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Vrije Universiteit Amsterdam [Amsterdam] (VU), Agence Spatiale Européenne = European Space Agency (ESA), Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC), and Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU)
Subjects: [SPI.ELEC]Engineering Sciences [physics]/Electromagnetism, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract: International audience; Passive microwave sensors offer the opportunity to retrieve surface SM (SSM) information from the measured brightness temperatures (TB) signals. Nevertheless, these microwave sensors provide individually SSM datasets which may not be consistent worldwide and across time. Therefore, the European Space Agency (ESA) established the Climate Change Initiative (CCI) project with a purpose to merge different observations acquired by several microwave sensors in an attempt to produce the most complete and consistent long-term time series of SSM over 1978-2010 as a first phase [1]. A new innovation in space technology, namely the SMOS (Soil Moisture and Ocean Salinity) SSM datasets has been providing multi-angular microwave TB observations at L-band [2] since 2010. SSM can be retrieved from the SMOS TB observations using several approaches such as a Radiative Transfer based model inversion (e.g. the ESA and CNES operational algorithms [2]), neural networks [3], and statistical regressions. The SMOS satellite being the first mission specifically designed to measure SSM from space, this study -an ESA-funded project- aims at studying the inclusion of SMOS SSM as reference for the long-term SSM datasets. Specifically, investigating the use of physically based multiple-linear regressions [4] to retrieve a global and long-term (e.g. 2003-2014) SSM record based on a combination of passive microwave remote sensing observations from the AMSR-E (2003 - 2011) and SMOS (2010 - 2014) sensors. The overlap measurement period (June 2010-Sept 2011) between AMSR-E and SMOS was used for calibration and validation. The coefficients of the regression equations were calibrated using AMSR-E TB and SMOS Level 3 (SMOSL3, V2.72) SSM (used here as a reference) over the Oct 2010 - Sept 2011 period while the rest of the overlap period (June – Sept 2010) was used for validation. Based on the calibrated coefficients, global SSM maps were computed from the AMSR-E TB observations over the validation period (referred here to as AMSR-reg product). First results showed that the regression approach is very promising as it produces realistic SSM values from the AMSR-E TB product in terms of absolute values. Fig 1 displays a comparison between the temporal mean of the SMOSL3 and AMSR-reg SSM products over the validation period (June – Sept 2010). The global distributions of SSM and its spatial patterns are similar for both products with low values over arid and semi-arid regions, moderate values over India, the Sahel and the Eastern part of Australia. An overall mean of SSM of 0.129 m3/m3 and 0.128 m3/m3 was computed for SMOSL3 and AMSR-reg, respectively. This study is in progress and further investigations will be directed to (i) evaluate the AMSR-reg SSM retrievals against land surface SSM simulations (e.g., MERRA-Land) and in situ observations over the period 2003-2009, at the global and local scales and (ii) investigate the temporal consistency of AMSR-reg (2003-2009) and SMOSL3 (2010-2014) SSM time series. Based on the results, the final goal of this study will be to merge the AMSR-reg (2003-2009) and SMOSL3 (2010-2014) SSM time series to produce a long term and consistent SSM product.
Published: 2015

232. The SMOS level2 soil moisture algorithm. Principles and future trends

Author: Kerr, Yann H., Richaume, Philippe, Wigneron, Jean-Pierre, Ferrazzoli, Paolo, Mahmoodi, Ali, Delwart, Steven, Drusch, Matthias, Mecklenburg, Susanne, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Università degli Studi di Roma Tor Vergata [Roma], European Space Research and Technology Centre (ESTEC), European Space Agency (ESA), and European Space Agency (ESA). INT.
Subjects: [SPI.ELEC]Engineering Sciences [physics]/Electromagnetism, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract: International audience; The Soil Moisture and Ocean Salinity (SMOS) mission is ESA’s (European Space Agency) second Earth Explorer Opportunity mission, launched in November 2009. It is a joint programme between ESA CNES (Centre National d’Etudes Spatiales) and CDTI (Centro para el Desarrollo Tecnologico Industrial). SMOS carries a single payload, an L-Band 2D interferometric radiometer in the 1400-1427 MHz protected band. The goal of the level 2 algorithm is to deliver global soil moisture maps with a desired accuracy of 0.04 m3/m3. To reach this goal a retrieval algorithm was developed and implemented in the Ground segment which processes level 1 to level 2 data. In this context, a group of institutes prepared the soil moisture Algorithm Theoretical Basis document (ATBD) to be used to produce the operational algorithm. The principle of the soil moisture retrieval algorithm is based on an iterative approach which aims at minimizing a cost function. The main component of the cost function is given by the sum of the squared weighted differences between measured and modelled brightness temperature (TB) data, for a variety of incidence angles. The algorithm finds the best set of the parameters, e.g. soil moisture (SM) and vegetation characteristics, which drive the direct TB model and minimizes the cost function. The end user Level 2 SM product contains soil moisture, vegetation opacity, and estimated dielectric constant of any surface, brightness temperatures computed at 42.5°, flags and quality indices, and other parameters of interest. Based on recent study and analysis (see paper by JP Wigneron on LMEB, P Ferrazzoli on forest etc.. and results acquired since launch we have revisited the algorithm(flags, retrievals outputs, aux data). The goal of this presentation is to give an update on the algorithm changes and trends. Validation will be presented in other papers.
Published: 2015

233. A review of the recent improvements in the L-MEB Model (SMOS Mission) - Impact on the accuracy of the soil moisture retrievals

Author: Wigneron, Jean-Pierre, Kerr, Yann H., Ferrazzoli, Paolo, Schwank, Mike, Lopez-Baeza, Ernesto, Parrens, Marie, Fernandez-Moran, Roberto, Al-Yaari, Amen, Richaume, Philippe, Bircher, Simone, Mialon, Arnaud, Ahmad, Al Bitar, Delwart, Steven, Mecklenburg, Susanne, Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Università degli Studi di Roma Tor Vergata [Roma], Gamma Remote Sensing, Universitat de València (UV), European Space Research and Technology Centre (ESTEC), European Space Agency (ESA), ESA Centre for Earth Observation (ESRIN), European Space Agency (ESA). INT., Centre National d'Etudes Spatiales (CNES). FRA., and European Society for Agronomy (ESA). INT.
Subjects: [SDV]Life Sciences [q-bio], [SDE]Environmental Sciences
Abstract: International audience; The L-MEB (L-band Microwave Emission of the Biosphere) is the forward model used in the operational SMOS algorithm to retrieve surface soil moisture (SM). This model is based on a well-known zero-order solution of the radiative transfer equations: the so called τ-ω model, L-MEB includes several parameterisations which were developed specifically to account for the multi-angular and bi-polarization capabilities of the SMOS brightness temperature (TB) observations in the retrieval process. A detailed description of the L-MEB model has been given in Wigneron et al. (2007). Since then, the model has been implemented in the SMOS algorithm which produced time series of the Level 2 (ESA) and Level 3 (CATDS) SM products, since the beginning of 2010. These SM products have been evaluated against numerical modelling products, in situ data from large SM networks included in the SMOS cal/val initiative and in a series of experimental campaigns based on field (SMOSREX, MELBEX, Upper Danube, etc.) or airborne measurements (NAFE-06, Australia; CAROLS, France; etc.). Eventually, numerical and physical models were used to develop new parameterizations of the soil roughness, soil permittivity, forests and low vegetation effects. Based on this very dense scientific activity some possible future improvements of the L-MEB model have been proposed. In a first step, this communication makes a quick review of the most significant recent results obtained in this field of research. In a second step, we present an illustration of the impact on the SM retrievals of using of a new parameterization of soil surface roughness in L-MEB which consists in combining both the roughness and vegetation effects in a single parameter (TR). The advantages of the SRP approach are twofold: firstly it not necessary to calibrate roughness effects (this is quite an open issue for large scale SMOS pixels) and secondly, the SRP method allows accounting for possible time changes in both the roughness characteristics and the vegetation optical depth. In this study, we present results of the evaluation of the SRP method against in situ measurements made within the SCAN network in 2011 in the USA. Even though first results are very encouraging, more studies evaluating the improvement in SM retrievals using the SRP method from the SMOS observations will be crucial to consolidate the novel retrieval method as a feasible option in the determination of SM at global scale.
Published: 2015

234. SMOSHiLat: Microwave L-band emissions of organic-rich soils in the northern cold climate zone in support of the SMOS mission

Author: Bircher, Simone, Richaume, Philippe, Demontoux, François, Mahmoodi, Ali, Jonard, François, Weihermüller, Lutz, Andreasen, Mie, Ikonen, Jaakko, Vehviläinen, Juho, Razafindratsima, Stephen, Rautiainen, Kimmo, Schwank, Mike, Mialon, Arnaud, Wigneron, J.-P., Kerr, Yann, Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de l'intégration, du matériau au système (IMS), Université Sciences et Technologies - Bordeaux 1-Institut Polytechnique de Bordeaux-Centre National de la Recherche Scientifique (CNRS), Université de Bordeaux (UB), Institute of Bio- and Geosciences Agrosphere (IBG-3), Research Center Jülich, Germany, ∗Agrosphere (IBG-3), Institute of Bio- and Geosciences, Forschungszentrum Jülich GmbH, Jülich, Germany, Institute of Bio- and Geosciences [Jülich] (IBG), Forschungszentrum Jülich GmbH-Forschungszentrum Jülich GmbH-Institute of Bio- and Geosciences [Jülich] (IBG), Forschungszentrum Jülich GmbH-Forschungszentrum Jülich GmbH, Institute of Bio- and Geosciences Agrosphere (IBG-3), Department of Geosciences and Natural Resource Management [Copenhagen] (IGN), Faculty of Science [Copenhagen], University of Copenhagen = Københavns Universitet (KU)-University of Copenhagen = Københavns Universitet (KU), Finnish Meteorological Institute (FMI), Department of Computer Science [ETH Zürich] (D-INFK), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology in Zürich [Zürich] (ETH Zürich), Écologie fonctionnelle et physique de l'environnement (EPHYSE - UR1263), Institut National de la Recherche Agronomique (INRA), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Université Sciences et Technologies - Bordeaux 1, Forschungszentrum Jülich GmbH | Centre de recherche de Juliers, Helmholtz-Gemeinschaft = Helmholtz Association, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), European Space Agency (ESA). INT., Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), and Écologie fonctionnelle et physique de l'environnement (EPHYSE)
Subjects: [SPI.ELEC]Engineering Sciences [physics]/Electromagnetism, [SDE.MCG]Environmental Sciences/Global Changes, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, ComputingMilieux_MISCELLANEOUS
Abstract: International audience; L-band microwave (1.4 GHz) brightness temperature (TB) observations of the Soil Moisture and Ocean Salinity (SMOS) satellite are used to retrieve global soil moisture data, taking advantage of the large difference between the dielectric constant of dry soil and water. The retrieval is based on the L-band Microwave Emission of the Biosphere (L-MEB) model using tuning parameters derived from study sites in dry and temperate climate zones. Thus, the aim of the SMOSHiLat project (ESA’s STSE Changing Earth Science Network) is to improve our understanding of L-band emissions and supporting SMOS data quality in more northern climate zones covered by pronounced organic surface layers. A database is created including L-band TB and dielectric constant measurements of organic-rich soils, mainly from (1) Sodankylä, Finland (Finish Meteorological Institute), and (2) Gludsted, Denmark (HOBE). Additional organic samples are available from Islay, Scotland, and the West Siberian Plain, Russia. The L-band dielectric constant measurements conducted at the IMS Laboratory (Bordeaux, France), show no distinct variability between a range of humus types encountered in the four regions. Due to the increased bound water fraction in porous organic material dielectric constants are consistently lower than measured in the underlying sandy mineral soils. Hence, one function was fitted through all organic soil moisture – dielectric constant couples, and tested in L-MEB by means of the tower-based ELBARA radiometer dataset acquired at the Research Center Jülich using Danish organic-rich soil. The derived relation proved satisfactory, and consequently, was implemented in the SMOS Soil Moisture Level 2 Prototype Processor (SML2PP). First runs were conducted over the Sodankylä test site and compared with retrieved soil moisture using the Dobson and Mironov dielectric mixing models. Results demonstrated significantly wetter retrieved soil moisture when using the organic fit function. This is in better agreement with an in situ surface soil moisture network average from measurements specifically calibrated for organic material and representative for prevailing land cover and soil types. Further test runs over other sites are planned in the near future. In this presentation, the SMOSHiLat project will be presented with special focus on the SML2PP studies.
Published: 2015

235. Soil moisture retrieval at global scale using the SRP (Simplified Roughness Parameterization)

Author: Fernandez-Moran, Roberto, Wigneron, Jean-Pierre, Lopez-Baeza, Ernesto, Al-Yaari, Amen, Bircher, Simone, Coll-Pajaron, Amparo, Mahmoodi, Ali, Parrens, Marie, Richaume, Philippe, Kerr, Yann H., Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Universitat de València (UV), Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Array Systems Computing, Partenaires INRAE, European Space Agency (ESA). INT., Centre National d'Etudes Spatiales (CNES). FRA., and SMOS MODE (Mission Oceanographic Data Exploitation). INT.
Subjects: [SPI.ELEC]Engineering Sciences [physics]/Electromagnetism, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract: International audience; The estimation of soil moisture by SMOS is based on the relationship between the dielectric constant and the brightness temperature at L-band (~1.4 MHz). Furthermore, certain physical contributions which perturb the signal must be taken into account: soil and vegetation temperatures, texture and roughness, vegetation cover and litter. The parameterization of roughness in the SMOS level 2 retrieval algorithm is based on four parameters (HR, QR, NRH and NRV) which are set as default contributions depending on a land classification. As some studies have suggested, there is the possibility of combining soil roughness and vegetation contributions as a single parameter in the retrieval algorithm (method referred to as SRP, Simplified Roughness Parameterization). Classical retrieval approaches considers SM and TAU (vegetation optical depth) as retrieved parameters, while the SRP is based on the retrieval of SM and the new TR parameter combining TAU and soil roughness (TR = TAU + HR /2), besides the assumption of thermodynamic equilibrium at 6 am and 6 pm (ground and canopy temperature are equal). This method leads to an important simplification in the algorithm and allows accounting for time changes in the value of the roughness parameter HR. In this study, the SRP was tested over the Valencia Anchor Station (VAS) with satisfactory results. Later, this method was analyzed against SM data measured over many in situ sites worldwide. The use of SRP is a promising alternative for SM estimation at L-Band. This method implies that soil roughness parameter HR does no longer need to be calibrated since HR is retrieved simultaneously to vegetation optical depth.
Published: 2015

236. Improvements of the most recent reprocessed SMOS soil moisture products

Author: Al-Yaari, Amen, Wigneron, Jean-Pierre, Ducharne, Agnès, Kerr, Yann H., Mecklenburg, Susanne, Delwart, Steven, Fernandez-Moran, Roberto, Parrens, Marie, Ahmad, Al Bitar, Mialon, Arnaud, Richaume, Philippe, Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols (METIS), Université Pierre et Marie Curie - Paris 6 (UPMC)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), ESA Centre for Earth Observation (ESRIN), European Space Agency (ESA), Universitat de València (UV), European Space Agency (ESA). INT., Centre National d'Etudes Spatiales (CNES). FRA., European Society for Agronomy (ESA). INT., Université Pierre et Marie Curie - Paris 6 (UPMC)-École Pratique des Hautes Études (EPHE), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Agence Spatiale Européenne = European Space Agency (ESA)
Subjects: [SPI.ELEC]Engineering Sciences [physics]/Electromagnetism, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract: International audience; Soil Moisture and Ocean Salinity (SMOS) satellite has been providing soil moisture (SM) and ocean salinity (OS) retrievals at L-band for five years (2010-2014). During these five years, the SM retrieval algorithm, the L-MEB (L-Band Microwave Emission of the Biosphere; (Wigneron et al., 2007)) model has been progressively improved and hence results in different versions of the SMOS SM products. This study aims at evaluating the last improvement in the SM products of the most recent SMOS level 3 (SMOSL3) reprocessing (SMOSL3_New, Processor V2.72) vs. the earlier versions (SMOSL3_Old, retrieval algorithm processors V2.45-48). The new SM product (V2.72) includes improvements, but not limited to, in (i) Level 1 brightness temperature reprocessing including a better detection of Radio Frequency interferences (RFI) and (ii) the L-MEB SM retrieval model such as replacing the Dobson dielectric model (Dobson et al., 1985) by the Mironov dielectric mixing model (Mironov et al., 2009). METHOD The SMOSL3_New and SMOSL3_Old versions were compared against SM-DAS-2 SM data assimilation system produced by the European Center for Medium range Weather Forecasting (ECMWF) forecast model at the global scale. RESULTS Correlation, bias, Root Mean Square Difference (RMSD) and unbiased RMSD (unbRMSD) were used as performance criteria in this study. First results show that the SMOS SM estimates have been improved: (i) SMOSL3_New was closer to SM-DAS-2 over most of the globe-with the exception of arid regions-in terms of bias, RMSD, and unbRMSD (ii) SMOSL3_New was closer to SM-DAS-2 over Europe and India but comparable with SMOSL3_Old over most of the rest of the globe in terms of correlations. For instance, Fig. 1 shows the areas, in green, where SMOSL3_New has the lowest unbRMSD (66% of the considered pixels), and the areas, in red, where SMOSL3_Old has the lowest unbRMSD (34% of the considered pixels). The positive impact of introducing the improvements mentioned above in the new processing of SMOS datasets is clearly observed in the figure with the exception of deserts, particularly over sand dunes areas, where the Dobson model may be more accurate than the Mironov model. This study is in progress and will be extended using other existing satellites (ASCAT, AMSR-E, etc.) and in situ observations to precisely evaluate the improvements of the most recent SMOS soil moisture reprocessing.
Published: 2015

237. Long time series of soil moisture obtained using neural networks : application to AMSR-E and SMOS

Author: Rodriguez‐Fernandez, Nemesio, Kerr, Yann H., De Jeu, Richard, Van der Schalie, Robin, Wigneron, Jean-Pierre, Al-Yaari, Amen, Dolman, Han, Drusch, Matthias, Mecklenburg, Susanne, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU), Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), European Space Research and Technology Centre (ESTEC), European Space Agency (ESA), ESA Centre for Earth Observation (ESRIN), European Geosciences Union (EGU). DEU., Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Vrije Universiteit Amsterdam [Amsterdam] (VU), Agence Spatiale Européenne = European Space Agency (ESA), and VU University Amsterdam
Subjects: analyse de données, télédétection par satellite, capteur smos, Signal and Image processing, Earth Sciences, Traitement du signal et de l'image, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, radiomètre, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Sciences de la Terre, ComputingMilieux_MISCELLANEOUS
Abstract: International audience
Published: 2015

238. Global SMOS soil moisture retrievals using the land parameter retrieval model

Author: Van der Schalie, Robin, De Jeu, Richard, Kerr, Yann H., Wigneron, Jean-Pierre, Rodriguez‐Fernandez, Nemesio, Al-Yaari, Amen, Drusch, Matthias, Mecklenburg, Susanne, Dolman, Han, VU University Amsterdam, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), European Space Research and Technology Centre (ESTEC), European Space Agency (ESA), ESA Centre for Earth Observation (ESRIN), European Geosciences Union (EGU). DEU., Vrije Universiteit Amsterdam [Amsterdam] (VU), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Agence Spatiale Européenne = European Space Agency (ESA), and Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU)
Subjects: capteur smos, télédétection, [SDE.MCG]Environmental Sciences/Global Changes, Earth Sciences, Signal and Image processing, Traitement du signal et de l'image, humidité du sol, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, Milieux et Changements globaux, donnée satellite, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Sciences de la Terre, ComputingMilieux_MISCELLANEOUS
Abstract: International audience
Published: 2015

239. Mapping water bodies over tropical basins from SMOS L-band brightness temperature

Author: Parrens, Marie, Al-Bitar, Ahmad, Kerr, Yann, Cote, Rémi, Richaume, Philippe, Crétaux, Jean-François, Cherchali, Selma, Wigneron, Jean-Pierre, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées, Centre National d’Etudes Spatiales, Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), European Geosciences Union (EGU). DEU., Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Université de Toulouse (UT)
Subjects: [SPI.ELEC]Engineering Sciences [physics]/Electromagnetism, Electromagnetism, niveau d'eau, télédétection par satellite, [SDE.MCG]Environmental Sciences/Global Changes, Signal and Image processing, méthode de cartographie, Traitement du signal et de l'image, Electromagnétisme, température de brillance, Milieux et Changements globaux, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, ComputingMilieux_MISCELLANEOUS
Abstract: International audience
Published: 2015

240. A radiative transfer based approach to merge SMOS and AMSR‐e soil moisture retrievals into one consistent record

Author: Van der Schalie, Robin, De Jeu, Richard, Kerr, Yann, Wigneron, Jean-Pierre, Rodriguez‐Fernandez, Nemesio, Al Yaari, Amen, Drusch, Matthias, Mecklenburg, Susanne, Dolman, Han, University of Amsterdam [Amsterdam] (UvA), Transmissivity, Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), European Space Research and Technology Centre (ESTEC), European Space Agency (ESA), ESA Centre for Earth Observation (ESRIN), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (UMR ISPA), European Space Research Institute (ESRIN). ITA., Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Agence Spatiale Européenne = European Space Agency (ESA)
Subjects: analyse de données, [SDV]Life Sciences [q-bio], télédétection, projet smos, transfert radiatif, humidité du sol, donnée satellite
Abstract: In 2010 Soil moisture was recognized as an Essential Climate Variable (ECV) by the Global Climate Observation System (GCOS) and in the same year ESA started the development of a consistent, long‐term, multi‐sensor time series of satellite derived soil moisture. First as part of the Water Cycle Observation Multi‐mission Strategy (WACMOS) and later as a part of the Climate Change Initiative (CCI) program. In 2014,a one year project was initiated by ESA to provide guidelines for the inclusion of soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) sensor. With this project testing three different fusion methods were be included; one based on a neural network approach (Rodriguez‐Fernandez et al., 2014), one based on a linear regression approach (Wigneron et al., 2004) and one based on the CCI soil moisture baseline algorithm, the Land Parameter Retrieval Model (LPRM, Owe et al., 2008). This study focused on the last method. The LPRM was applied to the SMOS observations by optimizing the single scattering albedo and roughness, against two different modelled soil moisture products (MERRA and ERA‐Land) , comparison against SMOS networks from the international soil moisture network over the period of July 2010 to December 2013 (Van der Schalie et al., 2015). The comparison against SMOS Level 3 soil moisture reached correlations of over 0.9 for the continents that are mostly free of radio frequency interference. Then AMSR‐E and SMOS retrievals were combined by updating the AMSR‐E LPRM and optimizing its parameters to best match the SMOS LPRM retrievals. Other updates included an improved approach to estimate the effective temperature at C‐band. The resulting AMSR‐E LPRM retrievals were evaluated against MERRA and ERA‐Land and validated against available In Situ networks and revealed a lower RMSE as compared to the original AMSR‐E LPRM v5 products while still having high correlations with the mentioned datasets.
Published: 2015

241. Global map of soil roughness using L-band SMOS data

Author: Parrens, Marie, Wigneron, Jean-Pierre, Richaume, Philippe, Ahmad, Al Bitar, Mialon, Arnaud, Wang, Shu, Fernandez-Moran, Roberto, Al-Yaari, Amen, Kerr, Yann H., Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), European Geosciences Union (EGU). DEU., Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: analyse de données, capteur smos, télédétection par satellite, Earth Sciences, Signal and Image processing, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, Traitement du signal et de l'image, radiomètre, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, ComputingMilieux_MISCELLANEOUS, Sciences de la Terre
Abstract: International audience
Published: 2015

242. Long time series of soil moisture retrieved from AMSR‐E and SMOS Observations

Author: Rodriguez‐Fernandez, Nemesio, Kerr, Yann H., Van der Schalie, Robin, De Jeu, Richard, Wigneron, Jean-Pierre, Al Yaari, Amen, Richaume, Philippe, Drusch, Matthias, Mecklenburg, Susanne, Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), University of Amsterdam [Amsterdam] (UvA), Interactions Sol Plante Atmosphère (ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), European Space Research and Technology Centre (ESTEC), European Space Agency (ESA), ESA Centre for Earth Observation (ESRIN), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (UMR ISPA), and European Space Research Institute (ESRIN). ITA.
Subjects: analyse de données, télédétection par satellite, Signal and Image processing, Traitement du signal et de l'image, projet smos, régression non linéaire, variable climatique, radiomètre, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract: Introduction: Soil moisture (SM) represents less than 1/10000 of the total water of our planet but it plays an important role as it affects the water and energy exchanges at the land surface/atmosphere interface and it is the reservoir of water for agriculture and vegetation in general. SM has been endorsed by the Global Climate Observing System (GCOS) as an Essential Climate Variable. In order to use SM information for climate modeling, SM datasets spanning long time periods are needed. In the context of the European Space Agency (ESA) Climate Change Initiative (CCI) several strategies have been evaluated to merge SM datasets from different microwave sensors (Owe et al. 2008). These strategies consist typically in merging a posteriori several SM datasets computed with different algorithms applied to data from different sensors. In addition, they do not include data from the Soil Moisture and Ocean Salinity (SMOS) satellite (Kerr et al. 2001), which is the first mission specifically designed to retrieve SM from space. Therefore, in the context of an ESA funded project, several approaches have been studied to add SMOS data to long term SM datasets. In a first phase, three different approaches are tested to merge ESA SMOS and NASA/JAXA Advanced Scanning Microwave Radiometer (AMSR‐E). This paper is devoted to a method using statistical retrieval algorithms to compute a priori a long time dataset that is consistent along time by construction. Methods Rodriguez‐Fernandez et al. (2015) have shown the good performances of a SM retrieval from SMOS observations using neural networks trained with ECMWF numerical weather prediction models (Balsamo et al. 2009). In addition, the same approach but using SMOS L3 SM as reference has proven to be useful to develop a Near‐Real‐Time SM retrieval algorithm (Rodriguez‐Fernandez et al. this conference). This study uses both approaches to obtain larger SM time series adding AMSR‐E as input: i) Using a Land Surface model as reference, two neural networks algorithms have been defined and optimized using AMSR‐E or SMOS as input data in the periods 2003‐Oct 2011 and 2010‐2014, respectively. ii) An alternative approach which is independent of land surface models has also been studied. It consist in using SMOS L3 SM retrievals as reference to train a NN using as input AMSR‐E Tb's. Results The best input data to retrieve SM using ASMR‐E data as input is using the three lower frequency bands and two polarizations. Soil temperature and a vegetation index improve the ability of the NN to capture the SM variability of the ECMWF model simulations and SMOS L3 SM. The NN performances are higher when using Tb's as input instead of the polarization index ( PI =(Tb^V ‐ Tb^H)/(Tb^V + Tb^H) ) used by the LPRM algorithm (Owe et al. 2001) or other NNs algorithms (Santi et al. 2012). As shown in Rodriguez‐Fernandez et al. (2015) for the SMOS case, the performance of the NN using AMSR‐E as input data and trained with ECMWF SM simulations improves when using soil texture maps as input (clay and sand fractions). For instance when using the lowest frequency channel, R increases from 0.79 to 0.83. In contrast, when more Tb's measured at higher frequencies are added as input, the contribution of NDVI decreases. When using all the frequency bands, including the 89 GHz channel, the NDVI contribution is negligible and the correlation of NN SM and ECMWF SM is as high as 0.9 (only using AMSR‐E plus soil texture information as input). For comparison, the global score obtained using SMOS Tb's from 7 angle bins from 25deg to 65deg, soil texture and NDVI is R = 0.88 (NN SM with respect to ECMWF SM). In conclusion, both NNs using AMSR‐E or SMOS data as input exhibit similar performances to capture the SM variability in the ECMWF models. Discussion In order to check the consistency of the two NN SM datasets, the trained NNs have been applied to AMSR‐E and SMOS \Tb's in the period from June to September 2010, which has not been used for the training of the NNs. The two maps are very similar, probing that the produced SM is consistent using SMOS or AMSR‐E as input. In addition, the performances of the NN retrieved SM have been evaluated against more than 1100 measurements from in situ sensors in America, Europe, Africa and Australia in the 2003‐2013 period. Results show that, on average, remote sensing retrievals performances in Europe are below those of ERA‐Interim/Land and MERRA‐Land models. In contrast, the remote sensing retrievals performances with respect to in situ measurements in other locations are, on average, similar or better than those of the land surface models. Therefore, this is a promising method to compute long time series of SM that can be used for hydrological and climate application and it is the first step towards a longer dataset which will include additional sensors.
Published: 2015

243. Validación a largo plazo de datos de nivel 3 de tierra de SMOS con medidas de ELBARA-II en la Valencia Anchor Station

Author: Fernandez-Moran, Roberto, Wigneron, Jean-Pierre, López-Baeza, Ernesto, Miernecki, Maciej, Salgado-Hernanz, Paula Maria, Coll, Amparo, Kerr, Yann, Schwank, Mike, Universitat de València (UV), Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: brightness temperature, L-MEB, télédétection, capteur smos, [SDV]Life Sciences [q-bio], [SDE]Environmental Sciences, humidité du sol, température de brillance, radiomètre, rugosité du sol, vegetation optical depth
Abstract: La misión de SMOS (Soil Moisture and Ocean Salinity) se lanzó el 2 de Noviembre de 2009 con el objetivo de proporcionar datos de humedad del suelo y salinidad del mar. La principal actividad de la conocida como Valencia Anchor Station (VAS) es asistir en la validación a largo plazo de productos de suelo de SMOS. El presente estudio se centra en una validación de datos de nivel 3 de SMOS en la VAS con medidas in situ tomadas en el periodo 2010-2012. El radiómetro Elbara-II está situado dentro de los confines de la VAS, observando un campo de viñedos que se considera representativo de una gran proporción de un área de 50×50 km, suficiente para cubrir un footprint de SMOS. Las temperaturas de brillo (TB) adquiridas por ELBARA-II se compararon con las observadas por SMOS en las mismas fechas y horas. También se utilizó la inversión del modelo L-MEB con el fin de obtener humedades de suelo (SM) que, posteriormente, se compararon con datos de nivel 3 de SMOS. Se ha encontrado una buena correlación entre ambas series de TB, con mejoras año tras año, achacable fundamentalmente a la disminución de precipitaciones en el periodo objeto de estudio y a la mitigación de las interferencias por radiofrecuencia en banda L. La mayor homogeneidad del footprint del radiómetro ELBARA-II frente al de SMOS explica la mayor variabilidad de sus TB. Los periodos de precipitación más intensa (primavera y otoño) también son de mayor SM, lo que corrobora la consistencia de los resultados de SM simulados a través de las observaciones del radiómetro. Sin embargo, se debe resaltar una subestimación por parte de SMOS de los valores de SM respecto a los obtenidos por ELBARA-II, presumiblemente debido a la influencia que la pequeña fracción de suelo no destinado al cultivo de la vid tiene sobre SMOS. Las estimaciones por parte de SMOS en órbita descendente (6 p.m.) resultaron de mayor calidad (mayor correlación y menores RMSE y bias) que en órbita ascendente (6 a.m., momento de mayor humedad de suelo)., The Soil Moisture and Ocean Salinity (SMOS) mission was launched on 2nd November 2009 with the objective of providing global estimations of soil moisture and sea salinity. The main activity of the Valencia Anchor Station (VAS) is currently to assist in a long-term validation of SMOS land products. This study focus on a level 3 SMOS data validation with in situ measurements carried out in the period 2010-2012 over the VAS. ELBARA-II radiometer is placed in the VAS area, observing a vineyard field considered as representative of a major proportion of an area of 50×50 km, enough to cover a SMOS footprint. Brightness temperatures (TB) acquired by ELBARA-II have been compared to those observed by SMOS at the same dates and time. They were also used for the L-MEB model inversion to retrieve soil moisture (SM), which later on have been compared to those provided by SMOS as level 3 data. A good correlation between both TB datasets was found, improving year by year, mainly due to the decrease of precipitations in the analyzed period and the mitigation of radio frequency interferences at L-band. The larger homogeneity of the radiometer footprint as compared to SMOS explains the higher variability of its TB. Periods of more intense precipitation (spring and autumn) also presented higher SM, which corroborates the consistency of SM retrieved from ELBARA-II’s observations. However, the results show that SMOS level 3 data underestimate SM as compared to ELBARA-II’s, probably due to the influence of the small soil fraction which is not cultivated in vineyards. SMOS estimations in descending orbit (6 pm) had better quality (higher correlation, lower RMSE and bias) than the ones in ascending orbit (6 am, when there is a higher soil moisture).
Published: 2015

244. Analysis of the behavior of microwave L-band emissions of organic-rich soils in the northern cold climate zone in support of the SMOS mission

Author: Bircher, Simone, Demontoux, François, Jonard, François, Razafindratsima, Stephen, Richaume, P., Weihermüller, Lutz, Mialon, Arnaud, Andreasen, Mie, Rautiainen, Kimmo, Schwank, Mike, Wigneron, J.-P., Kerr, Yann, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de l'intégration, du matériau au système (IMS), Université Sciences et Technologies - Bordeaux 1-Institut Polytechnique de Bordeaux-Centre National de la Recherche Scientifique (CNRS), Institute of Bio- and Geosciences Agrosphere (IBG-3), Research Center Jülich, Germany, ∗Agrosphere (IBG-3), Institute of Bio- and Geosciences, Forschungszentrum Jülich GmbH, Jülich, Germany, Institute of Bio- and Geosciences [Jülich] (IBG), Forschungszentrum Jülich GmbH | Centre de recherche de Juliers, Helmholtz-Gemeinschaft = Helmholtz Association-Helmholtz-Gemeinschaft = Helmholtz Association-Forschungszentrum Jülich GmbH | Centre de recherche de Juliers, Helmholtz-Gemeinschaft = Helmholtz Association-Helmholtz-Gemeinschaft = Helmholtz Association-Institute of Bio- and Geosciences [Jülich] (IBG), Helmholtz-Gemeinschaft = Helmholtz Association-Helmholtz-Gemeinschaft = Helmholtz Association, Institute of Bio- and Geosciences Agrosphere (IBG-3), Department of Geosciences and Natural Resource Management [Copenhagen] (IGN), Faculty of Science [Copenhagen], University of Copenhagen = Københavns Universitet (KU)-University of Copenhagen = Københavns Universitet (KU), Finnish Meteorological Institute (FMI), Department of Computer Science [ETH Zürich] (D-INFK), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Écologie fonctionnelle et physique de l'environnement (EPHYSE), Institut National de la Recherche Agronomique (INRA), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Forschungszentrum Jülich GmbH-Forschungszentrum Jülich GmbH-Institute of Bio- and Geosciences [Jülich] (IBG), Forschungszentrum Jülich GmbH-Forschungszentrum Jülich GmbH, Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology in Zürich [Zürich] (ETH Zürich), and Écologie fonctionnelle et physique de l'environnement (EPHYSE - UR1263)
Subjects: [SPI.ELEC]Engineering Sciences [physics]/Electromagnetism, [SDE.MCG]Environmental Sciences/Global Changes, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, ComputingMilieux_MISCELLANEOUS
Abstract: International audience
Published: 2014

245. A daily/25 km short-latency rainfall product for data scarce regions based on the integration of the GPM IMERG Early Run with multiple satellite soil moisture products.

Author: Massari, Christian, Brocca, Luca, Pellarin, Thierry, Abramowitz, Gab, Filippucci, Paolo, Ciabatta, Luca, Maggioni, Viviana, Kerr, Yann, and Prieto, Diego Fernandez
Abstract: Rain gauges are unevenly spaced around the world with extremely low gauge density over developing countries. For instance, in some regions in Africa the gauge density is often less than one station per 10 000 km2. The availability of rainfall data provided by gauges is also not always guaranteed in near real time or with a timeliness suited for agricultural and water resource management applications as gauges are also subject to malfunctions and regulations imposed by national authorities. A potential alternative are satellite-based rainfall estimates, yet comparisons with in-situ data suggest they're often not optimal. In this study, we developed a short-latency (i.e., 2-3 days) rainfall product derived from the combination of the Integrated Multi-Satellite Retrievals for GPM early run (IMERG-ER) with multiple satellite soil moisture-based rainfall products derived from ASCAT, SMOS and SMAP L3 satellite soil moisture (SM) retrievals. We tested the performance of this product over four regions characterized by high quality ground-based rainfall datasets (India, Conterminous United States, Australia and Europe) and over data scarce regions in Africa and South America by using Triple Collocation analysis (TC). We found the integration of satellite SM observations with in-situ rainfall observations is very beneficial with improvements of IMERG-ER up to 20 % and 40 % in terms of correlation and error, respectively, and a generalized enhancement in terms of categorical scores with the integrated product often outperforming reanalysis and ground-based long latency datasets. Given the importance of a reliable and readily available rainfall product for water resource management and agricultural applications over data scarce regions, the developed product can provide a valuable and unique source of rainfall information for these regions. [ABSTRACT FROM AUTHOR]
Published: 2019
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246. Soil Moisture Retrieval from Space: The Soil Moisture and Ocean Salinity (SMOS) Mission

Author: Kerr, Yann H., Waldteufel, Philippe, Wigneron, Jean-Pierre, Martinuzzi, Jean-Michel, Font, Jordi, and Berger, Michael
Subjects: Interferometry -- Methods, Soil moisture -- Measurement, Salinity -- Measurement, Ocean-atmosphere interaction -- Research, Chemical oceanography -- Research, Business, Earth sciences, Electronics and electrical industries
Abstract: Microwave radiometry at low frequencies (L-band: 1.4 GHz, 21 cm) is an established technique for estimating surface soil moisture and sea surface salinity with a suitable sensitivity. However, from space, large antennas (several meters) are required to achieve an adequate spatial resolution at L-band. So as to reduce the problem of putting into orbit a large filled antenna, the possibility of using antenna synthesis methods has been investigated. Such a system, relying on a deployable structure, has now proved to be feasible and has led to the Soil Moisture and Ocean Salinity (SMOS) mission, which is described in this paper. The main objective of the SMOS mission is to deliver key variables of the land surfaces (soil moisture fields), and of ocean surfaces (sea surface salinity fields). The SMOS mission is based on a dual polarized L-band radiometer using aperture synthesis (two-dimensional [2-D] interferometer) so as to achieve a ground resolution of 50 km at the swath edges coupled with multiangular acquisitions. The radiometer will enable frequent and global coverage of the globe and deliver surface soil moisture fields over land and sea surface salinity over the oceans. The SMOS mission was proposed to the European Space Agency (ESA) in the framework of the Earth Explorer Opportunity Missions. It was selected for a tentative launch in 2005. The goal of this paper is to present the main aspects of the baseline mission and describe how soil moisture will be retrieved from SMOS data. Index Terms--2-D interferometry, passive microwaves, soil moisture retrievals.
Published: 2001

247. A Simple Parameterization of the L-Band Microwave Emission from Rough Agricultural Soils

Author: Wigneron, Jean-Pierre, Laguerre, Laurent, and Kerr, Yann H.
Subjects: Agricultural research -- Methods, Microwave detectors -- Usage, Soil research -- Methods, Radiation -- Measurement, Business, Earth sciences, Electronics and electrical industries
Abstract: A simple model for simulating the L-band microwave emission from bare soils is developed. The model is calibrated on a large set of measurements obtained during a three-month period over seven plots covering a wide range of surface roughness (representing the total range which can be expected on agricultural fields), soil moisture, and temperature conditions. The approach is based on the parameterization of an effective roughness parameter as a function of surface characteristics: surface roughness (standard deviation of height and correlation length) and the surface soil moisture. The parameterizations that are developed are independent of incidence angle and polarization and are valid over a large range in surface roughness conditions, representative of most of typical agricultural bare fields, from very smooth (rolled field after sowing) to very rough surfaces (deeply plowed soil). This approach will enable the use of microwave radiometric observations for soil moisture retrieval over agricultural areas.
Published: 2001

248. Radiative transfer solution for rugged and heterogeneous scene observations

Author: Miesch, Christophe, Briottet, Xavier, Kerr, Yann H., and Cabot, Francois
Subjects: Algorithms -- Design and construction, Radiative transfer -- Analysis, Meteorological optics -- Research, Monte Carlo method -- Usage, Astronomy, Physics
Abstract: A physical algorithm is developed to solve the radiative transfer problem in the solar reflective spectral domain. This new code, Advanced Modeling of the Atmospheric Radiative Transfer for Inhomogeneous Surfaces (AMARTIS), takes into account the relief, the spatial heterogeneity, and the bidirectional reflectances of ground surfaces. The resolution method consists of first identifying the irradiance and radiance components at ground and sensor levels and then modeling these components separately, the rationale being to find the optimal trade off between accuracy and computation times. The validity of the various assumptions introduced in the AMARTIS model are checked through comparisons with a reference Monte Carlo radiative transfer code for various ground scenes: flat ground with two surface types, a linear sand dune landscape, and an extreme mountainous configuration. The results show a divergence of less than 2% between the AMARTIS code and the Monte Carlo reference code for the total signals received at satellite level. In particular, it is demonstrated that the environmental and topographic effects are properly assessed by the AMARTIS model even for situations in which the effects become dominant. [C] 2000 Optical Society of America OCIS codes: 010.1300, 280.0280.
Published: 2000

249. Results of Combining L- and C-Band Passive Microwave Airborne Data over the Sahelian Area

Author: Magagi, Ramata D., Kerr, Yann H., and Meunier, Jean-Charles
Subjects: Radio relay systems -- Usage, Soil moisture -- Measurement, Vegetation dynamics -- Analysis, Business, Earth sciences, Electronics and electrical industries
Abstract: This study focuses on an area in the Sahelian zone, Niger, Western Africa, where the HAPEX-Sahel experiment took place in 1992. During the hydrologic atmospheric pilot experiment in the Sahel (HAPEX-Sahel), passive microwave data were acquired with airborne radiometer, the multifrequency (5 to 90 GHz) and dual polarization sensor, PORTOS, and the four-beam sensor push broom microwave radiometer (PBMR), operating at 1.4 GHz in H-polarization. The aim of this investigation is to monitor soil moisture and vegetation parameters by combining L-and C-Band passive microwave airborne measurements. Through the relationships between soil moisture measurements from the 2 cm and 0.5 cm top layers, soil moisture is estimated for PORTOS data using the estimated soil moisture along the transects covered by the PBMR flights. The simplified radiative transfer model is then used to extract the optical thickness and the single scattering albedo of vegetation at C-Band, and to evaluate the vegetation effect on the estimated soil moisture at L-Band. An attempt to relate the estimated optical thickness from PORTOS data to the measured vegetation biophysical parameters [water content, biomass, leaf area index (LAI)] is presented. Index Terms--PORTOS, push broom microwave radiometer (PBMR), semi-arid, soil moisture, vegetation.
Published: 2000

250. Monte Carlo approach for solving the radiative transfer equation over mountainous and heterogeneous areas

Author: Miesch, Christophe, Briottet, Xavier, Kerr, Yann H., and Cabot, Francois
Subjects: Monte Carlo method -- Usage, Mathematical models -- Analysis, Algorithms -- Analysis, Photons -- Evaluation, Astronomy, Physics
Abstract: An algorithm based on the Monte Carlo method is developed to solve the radiative transfer equation in the reflective domain (0.4-4 [micro]m) of the solar spectrum over rugged terrain. This algorithm takes into account relief, spatial heterogeneity, and ground bidirectional reflectance. The method permits the computation of irradiance components at ground level and radiance terms reaching an airborne or satelliteborne sensor. The Monte Carlo method consists of statistically simulating the paths of photons inside the Earth-atmosphere system to reproduce physical phenomena while introducing neither analytical modeling nor assumption. The potentialities of the code are then depicted over different types of landscape, including a seashore, a desert region, and a steep mountainous valley. [C] 1999 Optical Society of America OCIS codes: 010.1300, 280.0280, 000.5490.
Published: 1999

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