Information on ultraviolet (UV) radiative fluxes is needed for public safety, understanding biodiversity, and for chemical transport modeling. Space-based observations can provide homogeneous and systematic estimates of the UV flux over large regions. In the past, UV flux estimates have been made from polar orbiting satellites; such estimates lack information on diurnal variability that can result in significant errors in UV dose (diurnally integrated UV flux). An algorithm has been developed to estimate diurnally varying spectral UV flux at the surface based on information from geostationary satellites (cloud amount, surface albedo and aerosols) and from polar orbiting satellites (ozone). Algorithm evaluation is done by comparison with ground-based observations made between January 1998 and December 2000 over eighteen stations of the United States Department of Agriculture (USDA)'s UV monitoring network. A good agreement between ground-based observations and satellite estimates is found with a mean bias (satellite − ground) of +3.5% for all-sky (cloudy + clear) cases. A negative mean bias of the same magnitude is found for clear-sky cases. Root mean square (RMS) differences are 25% and 14% for all-sky and clear-sky cases, respectively. Using simulations, it is shown that when only one observation near noontime is used to estimate UV dose, errors in the range of −61% to 48% can result, depending on cloud conditions. The RMS difference is 9% and it increases to 13% when off-noon hour (±2 hrs) observations are used to estimate the UV flux over Queenstown, MD.