Abstract
Abstract. Soil Moisture and Ocean Salinity (SMOS) L1c brightness temperature and L2 optical depth data are analysed with a coupled land surface (PROMET) and radiative transfer model (L-MEB). The coupled models are validated with ground and airborne measurements under contrasting soil moisture, vegetation and land surface temperature conditions during the SMOS Validation Campaign in May and June 2010 in the SMOS test site Upper Danube Catchment in southern Germany. The brightness temperature root-mean-squared errors are between 6 K and 9 K. The L-MEB parameterisation is considered appropriate under local conditions even though it might possibly be further optimised. SMOS L1c brightness temperature data are processed and analysed in the Upper Danube Catchment using the coupled models in 2011 and during the SMOS Validation Campaign 2010 together with airborne L-band brightness temperature data. Only low to fair correlations are found for this comparison (R between 0.1–0.41). SMOS L1c brightness temperature data do not show the expected seasonal behaviour and are positively biased. It is concluded that RFI is responsible for a considerable part of the observed problems in the SMOS data products in the Upper Danube Catchment. This is consistent with the observed dry bias in the SMOS L2 soil moisture products which can also be related to RFI. It is confirmed that the brightness temperature data from the lower SMOS look angles and the horizontal polarisation are less reliable. This information could be used to improve the brightness temperature data filtering before the soil moisture retrieval. SMOS L2 optical depth values have been compared to modelled data and are not considered a reliable source of information about vegetation due to missing seasonal behaviour and a very high mean value. A fairly strong correlation between SMOS L2 soil moisture and optical depth was found (R = 0.65) even though the two variables are considered independent in the study area. The value of coupled models as a tool for the analysis of passive microwave remote-sensing data is demonstrated by extending this SMOS data analysis from a few days during a field campaign to a longer term comparison.
Highlights
The European Space Agency’s (ESA) Soil Moisture and Ocean Salinity (SMOS) mission was launched in November 2009 to monitor surface soil moisture and ocean salinity globally with a temporal resolution of 2–3 days and a spatial resolution in the order of 43 km (Kerr et al, 2010)
This study aims at assessing how coupled land surface and radiative transfer models can contribute to the validation and analysis of passive microwave remote-sensing data
While Schlenz et al (2012a) have focussed on the validation and uncertainties related to the land surface modelling from point to SMOS-like scale in the Upper Danube Catchment and brightness temperature modelling on the SMOS-like scale in the Vils test site, Schlenz et al (2012b) have analysed the radiative transfer modelling on the point scale in a test site roughly 100 km southwest of the Vils test site
Summary
The European Space Agency’s (ESA) Soil Moisture and Ocean Salinity (SMOS) mission was launched in November 2009 to monitor surface soil moisture and ocean salinity globally with a temporal resolution of 2–3 days and a spatial resolution in the order of 43 km (Kerr et al, 2010). Soil moisture is derived from multiangular interferometric passive microwave L-band brightness temperature measurements at 1.4 GHz and delivered on an ISEA (icosahedral Snyder equal area projection) grid with a mean distance between grid points of 12.5 km (Kerr et al, 2010). An accuracy target of 0.04 m3 m−3 soil moisture random error is set for the SMOS L2 soil moisture measurements (Kerr et al, 2010; ESA, 2002).
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