Passive meteorological satellites have long served as the main workhorse for observing cloud parameters, but operational satellite cloud retrieval algorithms have typically assumed the simple model of a single-layer cloud in retrieving the cloud top location and cloud bulk properties. The imager used on the old Geostationary Operational Environmental Satellite-I series (GOES-I) imagers (e.g., GOES-8, GOES-10) was modified, replacing the 12.0-µm channel with the 13.3-µm channel, and placed on the GOES-M imagers (GOES-12/13). The 13.3-µm channel, also on the future GOES-R Advanced Baseline Imager, measures spectra attenuated by CO₂ absorption permitting the application of CO₂ absorption technique to improve the cloud-layer height retrieval.

In this study, an iterative retrieval of the upper and lower cloud layer properties using the GOES-12 imagery data is presented for future operational inferences of single-layered and multilayer cloud properties. The new iterative retrieval invokes two techniques: an iterative CO₂-IR absorbing technique and an iterative IR-Visible cloud optical depth technique. The former is a modified CO₂ absorption method that determines the upper and lower cloud layer locations using the 10.8 and 13.3-µm data, while the latter determines the upper and lower cloud layer optical depths using two-layered cloud radiative transfer modeling. Results are presented from retrieval sensitivity tests in terms of instrument noise and model uncertainties. The retrievals are validated by comparing with ground- and satellite-based active remote sensing data. Finally, results obtained from near real-time image analyses using the new iterative retrieval are demonstrated for the GOES-12 and Meteosat Second Generation (MSG) satellite imagers.