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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 10, issue 10
Geosci. Model Dev., 10, 3889–3912, 2017
https://doi.org/10.5194/gmd-10-3889-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: The externalised surface model SURFEX

Geosci. Model Dev., 10, 3889–3912, 2017
https://doi.org/10.5194/gmd-10-3889-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Model evaluation paper 25 Oct 2017

Model evaluation paper | 25 Oct 2017

Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area

Clément Albergel et al.
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Cited articles  
Agreste: http://agreste.agriculture.gouv.fr/page-d-accueil/article/donnees-en-ligne, last access: December 2016.
Albergel, C., Rüdiger, C., Carrer, D., Calvet, J.-C., Fritz, N., Naeimi, V., Bartalis, Z., and Hasenauer, S.: An evaluation of ASCAT surface soil moisture products with in-situ observations in Southwestern France, Hydrol. Earth Syst. Sci., 13, 115–124, https://doi.org/10.5194/hess-13-115-2009, 2009.
Albergel, C., Calvet, J.-C., Mahfouf, J.-F., Rüdiger, C., Barbu, A. L., Lafont, S., Roujean, J.-L., Walker, J. P., Crapeau, M., and Wigneron, J.-P.: Monitoring of water and carbon fluxes using a land data assimilation system: a case study for southwestern France, Hydrol. Earth Syst. Sci., 14, 1109–1124, https://doi.org/10.5194/hess-14-1109-2010, 2010.
Albergel, C., Dorigo, W., Reichle, R. H., Balsamo, G., de Rosnay, P., Munoz-Sabater, J., Isaksen, L., de Jeu, R., and Wagner, W.: Skill and global trend analysis of soil moisture from reanalyses and microwave remote sensing, J. Hydrometeorol., 14, 1259–1277, https://doi.org/10.1175/JHM-D-12-0161.1, 2013a.
Albergel, C., Dorigo, W., Balsamo, G., Muñoz-Sabater, J., de Rosnay, P., L. Isaksen, Brocca, L., R. de Jeu and Wagner, W.: Monitoring multi-decadal satellite earth observation of soil moisture products through land surface reanalyses, Remote Sens. Environ., 138, 77–89, https://doi.org/10.1016/j.rse.2013.07.009, 2013b.
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LDAS-Monde, a global land data assimilation system, is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. It is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the ISBA land surface model coupled with the CTRIP continental hydrological system. Assimilation of SSM and LAI leads to a better representation of evapotranspiration and gross primary production.
LDAS-Monde, a global land data assimilation system, is applied over Europe and the Mediterranean...
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