An ARM-Enhanced Analysis of GOES-10 Cloud Optical Property Retrievals

The vertical variation of cloud microphysical properties (e.g., droplet size distribution, total number concentration, phase, habit) complicates the interpretation of multi-spectral cloud reflection and emission as measured by passive radiometers in space. Solar reflection-based retrievals of cloud optical properties from sensors such as the Geostationary Operational Environmental Satellite (GOES) Imager are based predominantly on a single-layer, plane-parallel assumption (i.e., vertically and horizontally homogeneous) with a single particle size distribution both for computational simplicity and the constraints of the observing system itself. While the particular properties retrieved under these assumptions may yield radiative equivalence for measured cloud top spectral flux, the liquid/ice water paths derived from them can be in significant error owing to a misrepresentation of the true liquid/ice water profile. Feeding these erroneous representations into general circulation models, in turn, will only confuse further the issue of clouds and their role in the current and future climate.