Total downwelling radiation, along with precipitation, is the primary forcing of land surface processes. Clouds are a first-order modulator in radiation processes as they attenuate solar insolation while simultaneously emitting longwave radiation and therefore are key to capturing the space-time variability in downwelling surface radiation. In this study, a cloud-coupled solar insolation and longwave radiation model is developed using readily available satellite-based measurements of land surface and atmospheric states. The clear-sky downwelling radiation model uses inputs from the Moderate Resolution Spectroradiometer (MODIS) and Atmospheric Infrared Sounder (AIRS) sensor products while cloud coupling is achieved via use of the NASA Visible Infrared Solar-Infrared Split Window Technique (VISST) cloud product. Use of the 4-km VISST product effectively downscales larger scale satellite-derived products (e.g. from AIRS) while at the same time provides finer-scale temporal estimates of atmospheric conditions (i.e., every 30 minutes instead of twice daily and four times daily for AIRS and MODIS measurements, respectively). Temporal gaps in AIRS and MODIS products are further refined by scaling a diurnal climatology look-up table that can be derived from ground-based data or climate model output. The resulting coupled downwelling radiation model provides estimates at high resolution (4-km spatial resolution at 30 minute intervals). Results from an application in the Southern Great Plains (SGP) region of the United States are presented. The model is designed to be implemented in an ensemble framework to generate prior estimates that are then used in an Ensemble Kalman Smoother to assimilate existing products derived from more sophisticated models. Additional work includes the development of a precipitation sub-model using the same inputs with the goal of providing coupled precipitation and downwelling radiation estimates for use in distributed hydrologic modeling applications.