Radar-Based Estimates of Particle Shapes as a Means to Reduce Ice Cloud Microphysical Retrieval Uncertainties

Abstract:

Assumptions on ice particle shapes are typically made when developing algorithms to retrieve ice cloud microphysical properties. Many remote sensing algorithms assume either a spherical shape or some sort of pristine hexagonal crystal shapes. In situ cloud sampling data, however, indicate that cloud populations with the dominance of pristine crystals or quasi-spherical ice particles are not very common. Uncertainties in particle shape model assumptions result in the microphysical retrieval uncertainties. Polarimetric measurements available with advanced scanning cloud radars provide opportunities to infer particle type and shape information. This presentation will focus on prospects for the use of radar depolarization ratio measurements to infer particle types (e.g., planar-type particles versus columnar-type particles) and estimations of their mean aspect ratios. Different types of radar depolarization measurements will be analyzed for their suitability for inferring hydrometeor shape information. Independent estimates of particle shape parameters will potentially result in reducing uncertainties of ice cloud microphysical retrievals.