A review of the recent improvements in the L-MEB Model (SMOS Mission) - Impact on the accuracy of the soil moisture retrievals
Résumé
The L-MEB (L-band Microwave Emission of the Biosphere) is the forward model used in the operational SMOS algorithm to retrieve surface soil moisture (SM). This model is based on a well-known zero-order solution of the radiative transfer equations: the so called τ-ω model, L-MEB includes several parameterisations which were developed specifically to account for the multi-angular and bi-polarization capabilities of the SMOS brightness temperature (TB) observations in the retrieval process. A detailed description of the L-MEB model has been given in Wigneron et al. (2007). Since then, the model has been implemented in the SMOS algorithm which produced time series of the Level 2 (ESA) and Level 3 (CATDS) SM products, since the beginning of 2010. These SM products have been evaluated against numerical modelling products, in situ data from large SM networks included in the SMOS cal/val initiative and in a series of experimental campaigns based on field (SMOSREX, MELBEX, Upper Danube, etc.) or airborne measurements (NAFE-06, Australia; CAROLS, France; etc.). Eventually, numerical and physical models were used to develop new parameterizations of the soil roughness, soil permittivity, forests and low vegetation effects. Based on this very dense scientific activity some possible future improvements of the L-MEB model have been proposed. In a first step, this communication makes a quick review of the most significant recent results obtained in this field of research. In a second step, we present an illustration of the impact on the SM retrievals of using of a new parameterization of soil surface roughness in L-MEB which consists in combining both the roughness and vegetation effects in a single parameter (TR). The advantages of the SRP approach are twofold: firstly it not necessary to calibrate roughness effects (this is quite an open issue for large scale SMOS pixels) and secondly, the SRP method allows accounting for possible time changes in both the roughness characteristics and the vegetation optical depth. In this study, we present results of the evaluation of the SRP method against in situ measurements made within the SCAN network in 2011 in the USA. Even though first results are very encouraging, more studies evaluating the improvement in SM retrievals using the SRP method from the SMOS observations will be crucial to consolidate the novel retrieval method as a feasible option in the determination of SM at global scale.