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Journal Article

First results of SMOS soil moisture validation in the Upper Danube catchment


Loew,  A.
Terrestrial Remote Sensing / HOAPS, The Land in the Earth System, MPI for Meteorology, Max Planck Society;
CRG Terrestrial Remote Sensing, Research Area A: Climate Dynamics and Variability, The CliSAP Cluster of Excellence, External Organizations;

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Dall'Amico, J. T., Schlenz, F., Loew, A., & Mauser, W. (2012). First results of SMOS soil moisture validation in the Upper Danube catchment. IEEE Transactions on Geoscience and Remote Sensing, 50(5, Part 1), 1507-1516. doi:10.1109/TGRS.2011.2171496.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0012-3365-0
With the Soil Moisture and Ocean Salinity (SMOS) satellite launched in 2009, global measurements of L-band microwave emissions and processed soil moisture products at a fine time resolution are available. They may, after validation, lead to quantitative maps of global soil moisture dynamics. This paper presents a first validation of the SMOS soil moisture product delivered by the European Space Agency in the upper Danube catchment (southern Germany). Processing of the SMOS soil moisture product and the methodology to compare it with in situ and model data are described. The in situ data were taken from May to mid-July 2010 in a small and homogeneous area within the catchment, while the modeled time series spans from April to October 2010 for the whole catchment. The comparisons exhibit a dry bias of the SMOS data of about 0.2 m 3m -3 with respect to in situ measurements. Throughout the catchment, the SMOS data product shows a dry bias between 0.11 and 0.3 m 3m -3 when compared to modeled soil moisture. Correlation coefficients between both data were found to be mostly below 0.3. Radio-frequency interference (RFI) over Europe appears to be the main problem in obtaining valuable information from the SMOS soil moisture product over this region. RFI is not adequately captured by current methods for filtering and flagging. Nevertheless, some improvements of these results might be achievable through refinements of the soil moisture modeling as well as through improvements to the processors used to generate the SMOS soil moisture product. © 2012 IEEE.