Studying cloud droplet variability in the cloud transition zone using surface-based hyperspectral observations

The cloud transition zone is an optically thin mixture of cloud particles, aerosol, and water vapor that exists between visible clouds. Quantifying the makeup of the transition zone is challenging due to its optically thin nature and the 3D and cloud adjacency effects that result from broken cloud scenes. We present a qualitative algorithm to retrieve the variability and trend of the cloud droplet size at the cloud edge and through the transition zone. The algorithm uses surface-based hyperspectral observations which are normalized by a cloudless spectrum to mitigate the spectral effects of the background aerosol and the surface albedo. This helps isolate the effect of cloud droplets on the transmitted spectral radiance. The study of the cloud droplet variability will further our understanding of the makeup of the transition zone and its radiative impact. It also has the potential to contribute to the study of aerosol-cloud interactions and to cloud entrainment at the edge of the cloud. We present the results of the application of this algorithm to the observations of the Solar Spectral Flux Radiometer (SSFR) deployed as part of the Marine ARM GPCI Investigation of Clouds (MAGIC) field campaign.