Exploiting multiple scattering in CALIPSO measurements to retrieve liquid cloud properties

Liquid clouds are very important for climate, but current satellite retrieval methods cannot retrieve their vertical profile, cloud base height or their optical depth at night. Multiply-scattered lidar returns are often assumed to be a problem that needs to be corrected for or removed altogether but they contain useful information about cloud optical properties. Using a fast forward model of multiple-scattering we are able to incorporate this information into a retrieval scheme that works for optical depths far greater than the 2 or 3 that can be observed with direct lidar return alone. Improved retrievals of structure at cloud base are made by combining this algorithm with adiabatic constraints.

We have demonstrated this retrieval scheme for liquid water clouds using data from CALIOP and validated it against an independent retrieval using path integrated attenuation from CloudSat. Our new method can retrieve at least 30 optical depths with CALIOP. We consider issues with retrieval convergence in optically thin or thick clouds and how we may resolve them. We will explore how this retrieval performs for different receiver footprints and how lidar receiver field-of-view should be chosen to make use of the information contained in multiply scattered returns. We will also discuss what information this algorithm can give us about cloud base.