The bi-spectral spatial coherence approach for the detection and masking of clouds is revisited with modifications for operational applications to GOES Imager and Sounder data. The approach applies an edge detection algorithm to a “difference” image to identify the edges or contours of the clouds. The difference image is generated as the difference between the 3.9 and 11-micrometer channels of the GOES sensors. This difference image better highlights cloud edges than either image alone and draws upon the emissivity differences in the various channels. The cloud contours are “filled-in” by referencing the thermal gradients in the 11-micrometer channel or difference image associated with the cloud edge. This paper and associate poster will present a preliminary validation of the bi-spectral spatial coherence approach and will compare the cloud masks generated with this approach to the NOAA/NESDIS operational cloud products.