Determination of three-dimensional cloud structures from high-resolution radiance data

The three-dimensional structure and the inhomogeneity of clouds pose a field of challenges. The characterization of their spatial structure, their microphysical properties, and their variability is difficult. This kind of knowledge is crucial to any investigation on the impact of clouds on the radiation budget or on the reliability of cloud remote sensing data. In this article the characteristics of radiation transport in inhomogeneous clouds are studied using three-dimensional (3-D) simulations of radiative transport and the independent pixel approximation (IPA). The opposing effects of radiative smoothing and sharpening due to horizontal photon transport are examined in terms of the Green's function, which describes the interrelation of the radiance fields calculated using IPA and 3-D radiative transport. On the basis of these considerations a novel method was developed for the retrieval of realistic 3-D stratocumulus structures from high-spatial-resolution radiance fields observed by a compact airborne spectrographic imager (CASI, 15 m resolution). An initial distribution of liquid water content and effective droplet size retrieved using the IPA assumption and an adiabatic microphysical model is iteratively adjusted with the objective of matching the observation by the 3-D forward radiative transfer simulation for the derived cloud. For the iterative adjustment an approximate Green's function is utilized to remove 3-D effects from the observation. The performance of the method is characterized by application to a known cloud structure and by comparison of the derived cloud properties to in situ data from various field campaigns. The method provides the ideal basis for our studies on the remote sensing of inhomogeneous clouds.