Validation of SMOS L1C and L2 products and important parameters of the retrieval algorithm in the Skjern River catchment, Western Denmark

Abstract : The Soil Moisture and Ocean Salinity (SMOS) satellite with a passive L-band radiometer is dedicated to surface soil moisture monitoring. In addition to soil moisture, vegetation optical thickness NAD is retrieved (L2 product) from the acquired brightness temperatures (L1C product). The objective of this article is to present the validation work carried out in the Skjern River Catchment, Denmark. L1C/L2 data and the most sensitive parameters in the retrieval algorithm were analyzed by in situ data sets collected within one SMOS pixel (44 km diameter), including network and airborne campaign data. Consistent with worldwide findings, the retrieved soil moisture captures the precipitation dynamics well, but with too large amplitudes and a significant dry bias. The retrieved NAD exhibits too high values and day-to-day variability. A filter based on L2 criteria removed RFI affected data and improved the R2 between retrieved and in situ soil moisture from 0.49 to 0.61, while the bias remained (-0.092/-0.087 m3/m3, resp.). Likely error sources for the bias were located as (1) still present RFI, (2) potential link between low soil moisture and high NAD and/or low roughness parameter (HR), (3) 18/8% lower sand/higher clay fractions and 0.35 g/cm3 lower bulk density in SMOS algorithm than in situ, and (4) caveats in the Dobson dielectric mixing model. Substitution with the Mironov model and SMOS processor runs with site-specific input are planned. Differences in sampling depth between SMOS and in situ sensors (held responsible for too large SMOS amplitudes) and the role of organic surface layers will be investigated.
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IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2013, 51 (5), pp.2969 - 2985. 〈10.1109/TGRS.2012.2215041〉
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S. Bircher, N. Skou, Y.H. Kerr. Validation of SMOS L1C and L2 products and important parameters of the retrieval algorithm in the Skjern River catchment, Western Denmark. IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2013, 51 (5), pp.2969 - 2985. 〈10.1109/TGRS.2012.2215041〉. 〈ird-00828746〉

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