Understanding the complexities of cloud-sky radiative fluxes is crucial for improving numerical predictions of climate change. NASA's upcoming Atmosphere Observing System (AOS) mission promises unprecedented observations that will present an opportunity to enhance our understanding of the role of clouds in modulating both Earth’s radiation budget and climate sensitivity. AOS will utilize a series of active (Radar, Lidar) and passive (Imaging multi-angle polarimeter) instruments. The active instruments will provide vertically resolved cloud and aerosol information over a narrow ground-track (shown in red in the Figure below), while the passive instruments will cover a much wider swath. The high spatial resolution of AOS (~1km) will allow us to study clouds at the process level. While this will give us the opportunity to gain new insights, it also provides an unprecedented challenge to deliver satellite products at such a high resolution at which horizontal photon transport cannot be neglected, leading to biases in traditional cloud retrieval algorithms. To estimate radiative fluxes over the whole swath, we propose to extrapolate the vertical information from the active instruments to the across-track passive observations using a scene construction algorithm. This algorithm is evaluated using data from Large-Eddy Simulations and synthetic imagery computed by radiative transfer models.