PhD Proposal: Daniel Miller

TITLE: Passive remote sensing of clouds with realistic horizontal and vertical structure and the impact on cloud microphysics retrievals. ABSTRACT: Marine boundary layer (MBL) clouds cover over 1/5th of the earth’s oceans. They play a crucial role in the Earth’s climate through impacts on the radiation budget and interactions with aerosols and precipitation. Satellite cloud remote sensing techniques provide us the opportunity to study the spatial and temporal distributions of MBL clouds, as well as their connections with environments on global scale. However, cloud remote sensing is not without difficulties; retrievals require numerous simplifying assumptions, placing limits on our understanding when they are invalidated. Passive remote sensing retrievals often assume that clouds are homogeneous slabs. In reality these clouds often have complex inhomogeneous vertical and horizontal structures driven by a variety of physical processes. An integrated modeling and observational study is proposed to explore how realistic cloud structure and associated 3D radiative effects influence passive cloud retrievals. The modeling study is based on a cloud retrieval simulator our group developed utilizing a cloud model (Large-Eddy Simulation) and a suite of radiative transfer models. Observational studies will draw upon data from airborne instruments obtained during various NASA sub-orbital field campaigns. The LES-satellite simulator can be used to study the source of retrieval biases by providing the underlying realistic cloud structure as a reference, informing conclusions about its impact on various cloud retrieval methods. With lessons learned in hand, the observational study will be used to extend our conclusions from the model to real clouds under actual observation conditions.