View article

Root-zone soil moisture controls the land–atmosphere exchange of water and energy, and exhibits memory that may be useful for climate prediction at monthly scales. Assimilation of satellite-based surface soil moisture observations into a land surface model is an effective way to estimate large-scale root-zone soil moisture. The propagation of surface information into deeper soil layers depends on the model-specific representation of subsurface physics that is used in the assimilation system. In a suite of experiments, synthetic surface soil moisture observations are assimilated into four different models [Catchment, Mosaic, Noah, and Community Land Model (CLM)] using the ensemble Kalman filter. The authors demonstrate that identical twin experiments significantly overestimate the information that can be obtained from the assimilation of surface soil moisture observations. The second key result indicates …