Toward improved satellite estimates of short‐wave radiative fluxes—Focus on cloud detection over snow: 1. Methodology

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).