VALIDATION OF AUTOMATED CLOUD-TOP PHASE ALGORITHMS - DISTINGUISHING BETWEEN CIRRUS CLOUDS AND SNOW IN A-PRIORI ANALYSES OF AVH RR IMAGERY

Quantitative assessments on the performance of automated cloud analysi s algorithms require the creation of highly accurate, manual cloud, no cloud (CNC) images from multispectral meteorological satellite data. In general, the methodology to create these a priori analyses for the evaluation of cloud detection algorithms is relatively straightforward , although the task becomes more complicated when little spectral sign ature is evident between a cloud and its background, as appears to be the case in advanced very high resolution radiometer (AVHRR) imagery w hen thin cirrus is present over snow-covered surfaces. In addition, co mplex procedures are needed to help the analyst distinguish between wa ter and ice cloud tops to construct the manual cloud tap phase analyse s and to ensure that inaccuracies in automated cloud detection are not propagated into the results of the cloud classification algorithm. Pr ocedures are described that enhance the researcher's ability to (1) di stinguish between thin cirrus clouds and snow-covered surfaces in dayt ime AVHRR imagery, (2) construct accurate a priori cloud top phase man ual analyses, and (3) quantitatively validate the performance of both automated cloud detection and cloud top phase classification algorithm s. The methodology uses all AVHRR spectral bands, including a band der ived from the daytime 3.7-mu m channel, which has proven most valuable for discriminating between thin cirrus clouds and snow. It is conclud ed that while the 1.6-mu m band is needed to distinguish between snow and water clouds in daytime data, the 3.7-mu m channel remains essenti al during the daytime to differentiate between thin ice clouds and sno w. Unfortunately this capability that may be lost if the 3.7-mu m data switches to a nighttime-only transmission with the launch of future N ational Oceanographic and Atmospheric Administration (NOAA) satellites . (C) 1997 Society of Photo-Optical Instrumentation Engineers.