2018•EPJ Web of ConferencesOpen access

Application of a multiple scattering model to estimate optical depth, lidar ratio and ice crystal effective radius of cirrus clouds observed with lidar.

Diego Alvés Gouveia, Holger Baars, Patric Seifert, Ulla Wandinger, Henrique M. J. Barbosa, Boris Barja, Paulo Eduardo Artaxo, Fábio Lopes, Eduardo Landulfo, Albert Ansmann

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Abstract

Lidar measurements of cirrus clouds are highly influenced by multiple scattering (MS). We therefore developed an iterative approach to correct elastic backscatter lidar signals for multiple scattering to obtain best estimates of single-scattering cloud optical depth and lidar ratio as well as of the ice crystal effective radius. The approach is based on the exploration of the effect of MS on the molecular backscatter signal returned from above cloud top.

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Lidar measurements of cirrus clouds are highly influenced by multiple scattering (MS). We therefore developed an iterative approach to correct elastic backscatter lidar signals for multiple scattering to obtain best estimates of single-scattering cloud optical depth and lidar ratio as well as of the ice crystal effective radius. The approach is based on the exploration of the effect of MS on the molecular backscatter signal returned from above cloud top.

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Available abstract

Lidar measurements of cirrus clouds are highly influenced by multiple scattering (MS). We therefore developed an iterative approach to correct elastic backscatter lidar signals for multiple scattering to obtain best estimates of single-scattering cloud optical depth and lidar ratio as well as of the ice crystal effective radius. The approach is based on the exploration of the effect of MS on the molecular backscatter signal returned from above cloud top.

Key concepts: Lidar, Cirrus, Backscatter (email), Ice crystals, Scattering, RADIUS, Effective radius, Remote sensing

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Application of a multiple scattering model to estimate optical depth, lidar ratio and ice crystal effective radius of cirrus clouds observed with lidar. — Research Paper | ScholarLens