Observations of cloud and aerosol properties play an important role in areas of research such as climate modeling, large eddy simulations, aerosol-cloud interactions, and air quality. The uncertainty in the measurements of clouds and aerosols propagates to the studies from such fields. Hence, it is imperative that we make accurate measurements of cloud optical and microphysical properties to reduce uncertainty in the numerous studies that require these observations. Current remote sensing methods to retrieve these cloud properties suffer from assumptions such as the plane parallel assumption and the independent pixel approximation, which cause biased measurements in regimes such as trade cumulus where there is high spatial heterogeneity. The recent method called Atmospheric Tomography with 3D Radiative Transfer (AT3D) makes use of 3D radiative transfer to remove these assumptions providing the opportunity to make more accurate measurements while also having the advantage of retrieving the 3-dimensional distribution of cloud and aerosol properties. Initial validation in a theoretical framework demonstrates accurate retrievals in conditions of low optical thickness and high spatial heterogeneity – conditions where current methods make biased measurements. My work focuses on examining the practical application of AT3D using observations from the Multi-angle Imaging SpectroRadiometer (MISR) aboard the NASA TERRA satellite, which has been collecting multi-angle images for over 20 years. I am exploring the practical limitations likely to be encountered with real observations.