Aircraft icing occurs in supercooled clouds, which can be detected using operational imagery from the Geostationary Operational Environmental Satellite (GOES) and the Meteosat-9 Spinning Enhanced Visible and Infrared Imager (SEVIRI). Current detection methods are only valid when ice clouds do not occur above the supercooled layers. In those multilayered conditions, the detection methods can produce false supercooled clouds when the overlying cirrus cloud is relatively thin and the underlying clouds are warmer than the freezing point. More often, the scene is identified as indeterminate, that is, the presence of supercooled clouds cannot be determined because the single-layer detection method identifies the clouds as being composed of ice but the presence of lower supercooled water layers cannot be ruled out. In the last few years, several methods have been developed to detect multilayered ice-over-water cloud systems from satellite imager data using either the brightness temperature difference (BTD) between 10.9 and 12.0-µm channels or the CO2-slicing multilayer detection (COMUD) method that employs the visible, infrared, and CO2-slicing (e.g., 13.4 µm) channels. These techniques can be used to detect multilayered clouds when the optical depth of the upper cloud layer is less than about 3. Theoretically, these can be used reduce the occurrence of false supercooled cloud detection and increase the positive identification of supercooled clouds. The occurrence of supercooled clouds under the higher cirrus clouds is estimated using information from adjacent areas. In this paper, the accuracies of employing the single-layer cloud retrieval algorithms with and without the COMUD and BTD methods are examined using GOES-10, 11 & 12 and SEVIRI data taken over the United States and Europe, respectively. Data from pilot reports, the Ice, Cloud and Land Elevation Satellite (ICESat), CloudSat, and the Cloud and Aerosol Lidar in Space Observation (CALIPSO) satellite are compared with the data to evaluate the improvement in supercooled cloud detection using the enhanced algorithms.