Soil moisture retrieval at global scale using the SRP (Simplified Roughness Parameterization)
Résumé
The estimation of soil moisture by SMOS is based on the relationship between the dielectric constant and the brightness temperature at L-band (~1.4 MHz). Furthermore, certain physical contributions which perturb the signal must be taken into account: soil and vegetation temperatures, texture and roughness, vegetation cover and litter. The parameterization of roughness in the SMOS level 2 retrieval algorithm is based on four parameters (HR, QR, NRH and NRV) which are set as default contributions depending on a land classification. As some studies have suggested, there is the possibility of combining soil roughness and vegetation contributions as a single parameter in the retrieval algorithm (method referred to as SRP, Simplified Roughness Parameterization). Classical retrieval approaches considers SM and TAU (vegetation optical depth) as retrieved parameters, while the SRP is based on the retrieval of SM and the new TR parameter combining TAU and soil roughness (TR = TAU + HR /2), besides the assumption of thermodynamic equilibrium at 6 am and 6 pm (ground and canopy temperature are equal). This method leads to an important simplification in the algorithm and allows accounting for time changes in the value of the roughness parameter HR. In this study, the SRP was tested over the Valencia Anchor Station (VAS) with satisfactory results. Later, this method was analyzed against SM data measured over many in situ sites worldwide. The use of SRP is a promising alternative for SM estimation at L-Band. This method implies that soil roughness parameter HR does no longer need to be calibrated since HR is retrieved simultaneously to vegetation optical depth.