Remote sensing of particle size profiles from cloud sides: Observables and retrievals in a 3D environment

Abstract

Deep convection plays an essential role for climate since it is a key processor of aerosol particles and trace gases and it influences the solar radiation budget as well as the global water cycle. However, remote sensing applications (usually from space, viewing cloud tops) face huge challenges due to the vertical extent of the process from aerosol activation to rainout of large cloud droplets. Remote sensing of convective cloud sides using reflected solar radiation was recently proposed as complement to active methods like cloud radar to obtain vertical profiles of phase and particle size. While classical retrievals of the cloud droplet size perform well in ID environments on moderate spatial resolution, they fail when faced with complex cloud geometries and high spatial resolution. Therefore, different solutions have to be found for the proposed observations of complex cloud sides on high spatial resolution. Here, the latest advances in the development of a 3D retrieval of the cloud droplet effective radius and the corresponding uncertainties using a statistical approach are presented. To this end, extensive Monte-Carlo calculations of the 3D radiative transfer are conducted to account for the ill-posed problem which is caused by various 3D-effects. We show that by using a statistical approach the application of cloud droplet effective radius retrievals to complex geometries of cloud sides becomes possible.