Remote Sensing of Cloud Droplet Radius Profiles using solar
reflectance from cloud sides. Part I: Retrieval development and
characterization
Abstract. Convective clouds play an essential role for Earth's climate as well as for regional weather events since they have a large influence on the radiation budget and the water cycle. In particular, cloud albedo and the formation of precipitation are influenced by aerosol particles within clouds. In order to improve the understanding of processes from aerosol activation, over cloud droplet growth to changes in cloud radiative properties, remote sensing techniques become more and more important. While passive retrievals for spaceborne observations have become sophisticated and commonplace to infer cloud optical thickness and droplet size from cloud tops, profiles of droplet size have remained largely uncharted territory for passive remote sensing. In principle they could be derived from observations of cloud sides, but faced with with the small-scale structure of cloud sides, classical passive remote sensing techniques are rendered inappropriate. In this work the feasibility is demonstrated to gain new insights into the vertical evolution of cloud droplet effective radius by using reflected solar radiation from cloud sides. Central aspect of this work on its path to a working cloud side retrieval is the analysis of the impact unknown cloud surface geometry has on effective radius retrievals. Using extensive 3D radiative transfer calculations on the basis of realistic droplet size resolving cloud simulations, the sensitivity of reflected solar radiation to cloud droplet size is examined. Sensitivity is enhanced by considering the pixel surrounding to resolve ambiguities caused by illumination and cloud geometry. Based on these findings, a statistical approach is used to provide an effective radius retrieval. An in-depth sensitivity study of the presented approach on the basis of a wide range of radiative transfer test cases demonstrates the feasibility to retrieve cloud particle size profiles from cloud sides.