Classification of particle effective shape ratios in cirrus clouds based on the lidar depolarization ratio.

Abstract

A shape classification technique for cirrus clouds that could be applied to future spaceborne lidars is presented. A ray-tracing code has been developed to simulate backscattered and depolarized lidar signals from cirrus clouds made of hexagonal-based crystals with various compositions and optical depth, taking into account multiple scattering. This code was used first to study the sensitivity of the linear depolarization rate to cloud optical and microphysical properties, then to classify particle shapes in cirrus clouds based on depolarization ratio measurements. As an example this technique has been applied to lidar measurements from 15 mid-latitude cirrus cloud cases taken in Palaiseau, France. Results show a majority of near-unity shape ratios as well as a strong correlation between shape ratios and temperature: The lowest temperatures lead to high shape ratios. The application of this technique to space-borne measurements would allow a large-scale classification of shape ratios in cirrus clouds, leading to better knowledge of the vertical variability of shapes, their dependence on temperature, and the formation processes of clouds.