<title>Threshold functions for the automated analysis of clouds in daytime global meteorolical satellite imagery</title>

Abstract

Algorithms used to produce automated cloud analyses from global meteorological satellite imagery must compensate for variations in cloud spectral signatures caused by changes in atmospheric attenuation and solar scattering geometry that occur as the satellite orbits the Earth. In this paper, a methodology is presented that describes the variations in the spectral signatures of optically-thick (water) clouds for a wide range of solar illumination conditions. Functions are developed that describe these changes and are demonstrated in the analysis of high resolution NOAA AVHRR imagery. The accuracy of the automated cloud analyses is measured against ground truth (manual) cloud, no-cloud analyses.