Soil moisture plays a vital role in the partitioning of sensible and latent heat fluxes in the surface energy budget and the lack of a dense spatial and temporal network of ground-based observations provides a challenge to the initialization of the “true” soil moisture state in numerical weather prediction simulations. The retrieval of soil moisture using observations from both satellite-based thermal-infrared (TIR) and microwave sensors has been developed (Anderson et al., 2007; Hain et al., 2007; Jackson, 1993; Njoku et al., 2003). The ability of the TIR and microwave observations to diagnose soil moisture conditions within different layers of the soil profile provides an opportunity to use each in a synergistic data assimilation approach towards the goal of diagnosing the “true” soil moisture state from surface to root-zone.

The satellite-retrieved soil moisture products will be compared to soil moisture estimates provided by a retrospective Land Information System (LIS) simulation during the time period of 1997 to 2006 using the NOAH LSM and NLDAS forcing (Kumar et al., 2006). The TIR-based soil moisture product will be provided by a retrieval of soil moisture associated with surface flux estimates from the Atmosphere-Land-Exchange-Inversion (ALEXI) model (Anderson et al., 1997; Mecikalski et al., 1999; Hain et al., 2007). The microwave-based product will be provided by the USDA AMSR-E volumetric soil moisture product developed by Njoku et al. (2003). Each soil moisture product will be scaled accordingly, with respect to its climatology, to quantitatively compare anomaly correlations with the model-based soil moisture estimates. Comparisons between model and microwave-based soil moisture estimates will be made with respect to the 0-10 cm soil layer of the NOAH LSM, while comparisons with TIR-based soil moisture estimates will be made with respect to the root-zone (10-200 cm) soil layers.