A Coupled Cloud and Snow Detection Algorithm (CCSDA) for improving satellite capabilities to estimate downward surface short-wave radiation under snow conditions has been developed and will be described here. Four channels of the GOES-8 imager are used to detect clouds, snow, and to perform background analysis for each hour of the diurnal cycle. The Clear-Sky Background Analysis (CSBA) is used as a reference state to generate dynamic and location-dependent thresholds for cloud detection tests, and the CSBA of the visible channel is used as a required input for the solar radiation model. The implementation of any one component requires a priori information on the other two. Therefore the three components are coupled to iteratively update cloud detection variables, cloud amount, and snow cover. Snow detection aims to distinguish between snow-covered and snow-free pixels after a pixel is classified as clear. The CCSDA algorithm will be described, and preliminary evaluation of the impact of the improvements on surface radiative flux estimates will be presented in part 2 (Pinker et al., 2007).
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