Cloud retrieval algorithms have been developed and applied to the current generation of National Oceanic and Atmospheric Administration (NOAA) Geostationary Environmental Operational Satellite (GOES) imagery to produce a sixteen year climatology of cloudiness over the Continental United States (CONUS) and Hawaii. The database contains cloud / no cloud decisions at approximately fifteen minute and four kilometer resolution, respectively. Nearly 500,000 images have been processed over this sixteen year period. The GOES imager includes multi-spectral chan¬nels including one visible and four infrared. Cloud detec¬tion is accomp¬lished by modeling the radiance of the ground in the absence of clouds and comparing with the actual radiance values from the imagery. A composite cloud decision is formed by objectively com¬bining the results of the tests from the individual channels. The strength of using all bands as opposed to using a single band was demonstrated very early in the development. For example, low clouds radiating at a similar temperature to the earth are detectable at night with the use of the shortwave infrared channel. A combination of the visible and shortwave infrared channels helps to distinguish low and high clouds from snow cover. To date, this database has been used to study the impacts of clouds on optical communications for NASA deep space communications programs. Since clouds adversely affect the trans¬mission of optical communications, a reliable communication system is only possible through the use of multiple geographically diverse ground stations. The relatively high spatial and temporal resolution of this database makes it possible to study the cloud correlations between different locations. With the recent publicity of global warming and its impacts on the earth's weather and climate and investigation on whether the frequency of occurrence of clouds has increased, or decreased, has been initiated. Such changes may have a substantial impact on renewable energy deployment, particularly solar generation. Results produced by this database indicate a measurable variability in cloudiness over many reporting stations across CONUS as well as Hawaii during the 1995 – 2010 time period. Mean cloudiness varies from less than 30% in the desert regions and the mountain peaks of Maui and the Big Island to greater than 70% in the Great Lakes region and Pacific Northwest. Preliminary analysis, however, does not indicate any measurable increase or decrease in cloudiness over this period as indicated by the recent literature. Investigations into the variability and trends of cloud correlations over large geographic areas are currently being investigated.