The authors compared methods for estimating surface fluxes under clear-sky conditions over a large heterogeneous area from a limited number of ground measurements and from satellite observations using data obtained from the southern Great Plains Cloud and Radiation Testbed (CART) site, an area of approximately 350 km × 400 km located in Kansas and Oklahoma. In situ measurements from 10 energy balance Bowen ratio (EBBR) stations showed large spatial variations in latent and sensible heat fluxes across the site because of differences in vegetation and soil conditions. This variation was reproduced by a model for parameterization of subgrid- scale (PASS) surface fluxes that was developed previously and extended in the present study to include a distribution of soil moisture inferred from combined visible and thermal infrared remote sensing data. In the framework of the PASS model, the satellite-derived normalized difference vegetation index and surface temperature were used to derive essential surface parameters including surface albedo, surface conductance, soil heat flux ratio, surface roughness length, and soil moisture, which were then used to calculate a surface energy budget at satellite-pixel scales with pixel-specific surface meteorological conditions appropriately distributed from their mean values using a distribution algorithm. Although the derived soil moisture may be influenced by various uncertainty factors involved in the satellite data and the model, spatial variations of soil moisture derived from the multichannel data from the Advanced Very High Resolution Radiometers on the NOAA-14 satellite appeared to have some correlation (the correlation coefficient is as large as 0.6) with the amount of accumulated previous rainfall measured at the 58 Oklahoma Mesonet stations located within the CART area. Surface net radiation, soil heat flux, and latent and sensible heat fluxes calculated at a spatial resolution of 1 km (the size of a satellite pixel) were evaluated directly by comparing with flux measurements from the EBBR stations and indirectly by comparing air temperature and humidity inferred from calculated sensible and latent heat fluxes with corresponding values measured at 1.5 m above the 58 meteorological stations. In calculating regional fluxes, biases caused by the sampling uncertainty associated with point measurements may be corrected by application of the satellite data.