Retrieving 3D cloud properties using solar radiances and scanning cloud radar with a flexible ensemble optimal estimation framework

Obtaining reliable three-dimensional (3D) observations of clouds is a key step to understanding the impact of their 3D radiative effects on climate. We showcase a novel method for obtaining high resolution, 3D cloud fields in both overcast and broken-cloud situations. The retrieval has three key novelties: zenith radiances are combined with ground-based scanning cloud radar; 3D radiative transfer is used as a forward model; and an Iterative Ensemble Kalman Filter is used as an optimal estimation framework. These elements come together to allow us to simultaneously reveal the previously out-of-reach horizontal and vertical structure of cloud water content and effective radius. We will show the method performs well for stratocumulus and even in challenging cumulus cases, using a combination of synthetic measurements from large eddy simulations and real measurements from the Atmospheric Radiation Measurement Mobile Facility deployment at the Azores. These new observations will help unravel the influence of aerosol on clouds in both a macro- and microphysical sense and also give insight to the 3D radiative properties of clouds.