As the dominant variable in atmospheric radiation processes, it is recognized that clouds must be accurately represented in both weather and climate predictive models. The need to assimilate cloud properties or validate derived cloud properties in these models will rise with increasing model sophistication. The capability for deriving accurate cloud properties in a timely fashion has also risen to meet that need. This paper describes the methodology for deriving cloud and radiation properties, including cloud fraction, height, optical depth, phase, particle size, albedo, OLR, and skin temperature, in near real time and presents results from several different satellite imagers. Clear sky radiances are determined from an surface albedo and emissivity data base developed for the Clouds and earth’s Radiant Energy System (CERES) project together with forecast analyses. Calibrations are provided from a newly developed inter-satellite calibration system developed for the Atmospheric Radiation Measurement (ARM) Program. A simplified parameterization of ice and liquid water cloud properties is used to derive cloud properties from the observed radiances for clouds identified as cloudy. Broadband shortwave albedo and OLR are computed from narrowband-to-broadband relationships derived from CERES data matched with various satellite imager data. Examples of results are shown for sequential GOES imagery over the USA, global retrievals from the Terra and TRMM satellites, and selected retrievals from AVHRR data. Results from these analyses can be valuable for development of cloud climatologies, examination of cloud processes and the relationships between clouds and the local radiation budget, icing diagnostics, as well as model validation and initialization.