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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 14, issue 11
Hydrol. Earth Syst. Sci., 14, 2177–2191, 2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 14, 2177–2191, 2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 03 Nov 2010

Research article | 03 Nov 2010

Cross-evaluation of modelled and remotely sensed surface soil moisture with in situ data in southwestern France

C. Albergel1, J.-C. Calvet1, P. de Rosnay2, G. Balsamo2, W. Wagner3, S. Hasenauer3, V. Naeimi3, E. Martin1, E. Bazile1, F. Bouyssel1, and J.-F. Mahfouf1 C. Albergel et al.
  • 1CNRM/GAME (Météo-France, CNRS), URA 1357, Toulouse, France
  • 2European Centre for Medium-Range Weather Forecasts, Reading, UK
  • 3Institute of Photogrammetry and Remote Sensing, Vienna University of Technology, Vienna, Austria

Abstract. The SMOSMANIA soil moisture network in Southwestern France is used to evaluate modelled and remotely sensed soil moisture products. The surface soil moisture (SSM) measured in situ at 5 cm permits to evaluate SSM from the SIM operational hydrometeorological model of Météo-France and to perform a cross-evaluation of the normalised SSM estimates derived from coarse-resolution (25 km) active microwave observations from the ASCAT scatterometer instrument (C-band, onboard METOP), issued by EUMETSAT and resampled to the Discrete Global Grid (DGG, 12.5 km gridspacing) by TU-Wien (Vienna University of Technology) over a two year period (2007–2008). A downscaled ASCAT product at one kilometre scale is evaluated as well, together with operational soil moisture products of two meteorological services, namely the ALADIN numerical weather prediction model (NWP) and the Integrated Forecasting System (IFS) analysis of Météo-France and ECMWF, respectively. In addition to the operational SSM analysis of ECMWF, a second analysis using a simplified extended Kalman filter and assimilating the ASCAT SSM estimates is tested. The ECMWF SSM estimates correlate better with the in situ observations than the Météo-France products. This may be due to the higher ability of the multi-layer land surface model used at ECMWF to represent the soil moisture profile. However, the SSM derived from SIM corresponds to a thin soil surface layer and presents good correlations with ASCAT SSM estimates for the very first centimetres of soil. At ECMWF, the use of a new data assimilation technique, which is able to use the ASCAT SSM, improves the SSM and the root-zone soil moisture analyses.

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