The previous operational GOES fog algorithm relied on differences between the 3.9 and 11-micron brightness temperatures. While this is a reliable approach for nighttime fog detection, solar contamination of the 3.9-micron channel makes this unreliable during the day, unless the solar component is accounted for. Here we present an algorithm that uses the physical properties of clouds to detect areas of fog and low stratus developed for the Advanced Baseline Imager (ABI) that will fly on GOES-R. Although no current GOES imager has the spectral resolution available from the ABI, the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) provides enough spectral information to test and evaluate the new ABI fog approach. This work will use an analysis software package called GEOCAT to evaluate and characterize the performance of the prototype ABI fog algorithm applied to SEVIRI using CALIPSO data and surface observations.