Soil moisture retrieval at global scale using the SRP (Simplified Roughness Parameterization)

International audienceThe 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

Analyzing the impact of using the SRP (Simplified roughness parameterization) method on soil moisture retrieval over different regions of the globe

International audienceThis paper focuses on a new approach to account for soil roughness effects in the retrieval of soil moisture (SM) at L-band in the framework of the SMOS (Soil Moisture and Ocean Salinity) mission: the Simplified Roughness Parameterization (SRP). While the classical retrieval approach considers SM and τ nad (vegetation optical depth) as retrieved parameters, this approach is based on the retrieval of SM and the TR parameter combining τ nad and soil roughness (TR τ nad + Hr /2). Different roughness parameterizations were tested to find the best correlation (R), bias and unbiased RMSE (ubRMSE) when comparing homogeneous retrievals of SM and in situ SM measurements carried out at the VAS (Valencia Anchor Station) vineyard field. The highest R (0.68) and lowest ubRMSE (0.056 m3 m-3) were found using the SRP method. Using the SMOS observations comparisons against several SM networks were also made: AACES, SCAN, watersheds and SMOSMANIA. SM was retrieved over all these stations. The SRP and another similar approach (SRP2) improved the averaged ubRMSE, while the SRP2 method leaded to higher correlation values (R). A global underestimation of SM was noticed, which may be linked to the differences in the sampling depths of the L-band observations ( ~ 0-3 cm for both Elbara-II and SMOS) and of the in situ measurements ( ~ 0-5 cm)