Abstract
The main goal of the Soil Moisture and Ocean Salinity (SMOS) mission over land surfaces is the production of global maps of soil moisture (SM) and vegetation optical depth (τ) based on multi-angular brightness temperature (TB) measurements at L-band. The operational SMOS Level 2 and Level 3 soil moisture algorithms account for different surface effects, such as vegetation opacity and soil roughness at 4 km resolution, in order to produce global retrievals of SM and τ. In this study, we present an alternative SMOS product that was developed by INRA (Institut National de la Recherche Agronomique) and CESBIO (Centre d’Etudes Spatiales de la BIOsphère). One of the main goals of this SMOS-INRA-CESBIO (SMOS-IC) product is to be as independent as possible from auxiliary data. The SMOS-IC product provides daily SM and τ at the global scale and differs from the operational SMOS Level 3 (SMOSL3) product in the treatment of retrievals over heterogeneous pixels. Specifically, SMOS-IC is much simpler and does not account for corrections associated with the antenna pattern and the complex SMOS viewing angle geometry. It considers pixels as homogeneous to avoid uncertainties and errors linked to inconsistent auxiliary datasets which are used to characterize the pixel heterogeneity in the SMOS L3 algorithm. SMOS-IC also differs from the current SMOSL3 product (Version 300, V300) in the values of the effective vegetation scattering albedo (ω) and soil roughness parameters. An inter-comparison is presented in this study based on the use of ECMWF (European Center for Medium range Weather Forecasting) SM outputs and NDVI (Normalized Difference Vegetation Index) from MODIS (Moderate-Resolution Imaging Spectroradiometer). A six-year (2010–2015) inter-comparison of the SMOS products SMOS-IC and SMOSL3 SM (V300) with ECMWF SM yielded higher correlations and lower ubRMSD (unbiased root mean square difference) for SMOS-IC over most of the pixels. In terms of τ, SMOS-IC τ was found to be better correlated to MODIS NDVI in most regions of the globe, with the exception of the Amazonian basin and the northern mid-latitudes.
Highlights
The estimation of surface soil moisture (SM) at global scale is a key objective for the recentL-band microwave missions SMOS (Soil Moisture and Ocean Salinity) (Kerr et al, 2012 [1]) and SMAP (Soil Moisture Active Passive) (Entekhabi et al, 2010 [2])
It should be kept in mind that ECMWF SM is representative of the first 0–7 cm of the soil surface (Albergel et al, 2012 [65]) and the inherent nature of the simulated soil moisture (Koster et al, 2009 [66])
Is different to that measured by the SMOS satellite observations, which are sensitive to the first ~0–3 cm of the soil surface (Escorihuela et al, 2010 [67]; Njoku and Kong et al, 1977 [68])
Summary
The estimation of surface soil moisture (SM) at global scale is a key objective for the recentL-band microwave missions SMOS (Soil Moisture and Ocean Salinity) (Kerr et al, 2012 [1]) and SMAP (Soil Moisture Active Passive) (Entekhabi et al, 2010 [2]). Measurements of soil moisture are needed for applications related to the study of climate change or agriculture (droughts, floods, etc.) and hydrological processes (Brocca et al, 2010 [3]) such as precipitation, infiltration, runoff and evaporation. An ECV is defined as a physical, chemical or biological variable that critically contributes to the characterization of the Earth’s climate. SMOS uses an interferometric radiometer, which delivers multi-angular brightness temperature measurements at L-band. Various products are derived from the SMOS data at Level 2 (Kerr et al, 2012 [1]) and at Level 3 (Al Bitar et al, 2017 [5]), such as the SMOSL3 Brightness Temperature (SMOSL3 TB) and the SMOSL3 SM and τ products, with a 625 km sampling. The SMOS SM retrieval algorithm, which is common to both SMOS Level 2 (L2) and
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