A New CloudSat Rainfall Retrieval Algorithm over Land Using a Collocated MRMS-Cloudsat Dataset and a Bayesian Framework

A new algorithm will be presented for retrieving rainfall rate over land using spaceborne millimeter wavelength radar observations from CloudSat. The approach uses collocated quality-controlled NEXRAD rainfall rate estimates from the MRMS (Multi-Radar/Multi-Sensor System) dataset and CloudSat vertical reflectivity profiles to fill an important gap in CloudSat's precipitation products. This presentation will describe the underlying probabilistic Bayesian framework utilized that produces both rainfall rates and estimates of associated uncertainties. Examples of retrievals under a wide range of environments and initial evaluation against independent ground-based observations will be presented.