Using a multi-dimensional satellite rainfall error model to characterize uncertainty in soil moisture fields simulated by an offline land surface model

In this study, we investigate the significance of using an improved error modeling strategy to characterize the spatio-temporal characteristics of uncertainty in simulation of soil moisture fields from an off-line land surface model forced with satellite rainfall data. We coupled a Two-Dimensional Satellite Rainfall Error Model (SREM2D) with the Common Land Model to propagate ensembles of simulated satellite rain fields for the prediction of soil moisture at depths of 5 cm ( near surface) and 50 cm ( root zone). Our investigations revealed that multi-dimensional error modeling captures the spatio-temporal characteristics of soil moisture uncertainty with higher consistency than simpler bi-dimensional error modeling strategies. The proposed error modeling strategy appears to have the potential for delineating a more robust framework for the optimal integration of satellite rainfall data into models towards the study of global water and energy cycle.