IMPROVED DETECTION OF OPTICALLY THIN CIRRUS CLOUDS IN NIGHTTIME MULTISPECTRAL METEOROLOGICAL SATELLITE IMAGERY USING TOTAL INTEGRATED WATER-VAPOR INFORMATION

The accurate identification of optically thin cirrus clouds in global meteorological satellite imagery by automated cloud analysis algorithm s is critical to environmental remote sensing studies, such as those r elated to climate change. While significant improvements have been rea lized with the arrival of multispectral, meteorological satellite imag ery, collected by NOAA's Advanced Very High Resolution Radiometer (AVH RR), difficulties can be encountered when attempting to make pixel-lev el cloud decisions over large and diverse geographic areas found aroun d the globe. These problems are due, in part, to the effects of atmosp heric attenuation on cloud spectral signatures, caused primarily by va riations in water vapor, since the signatures of water vapor and optic ally thin cirrus are similar in the nighttime AVHRR infrared channels. In this paper, the authors describe an improved thin-cirrus detection technique that uses the brightness temperature differences between AV HRR channel 3 and channel 5 along with total integrated water vapor in formation. It is concluded that algorithms must accurately compensate for the impact of water vapor on cloud spectral signatures for enhance d detection of optically thin cirrus clouds in nighttime AVHRR imagery .