Articles | Volume 14, issue 2
https://doi.org/10.5194/amt-14-1593-2021
https://doi.org/10.5194/amt-14-1593-2021
Research article
 | 
26 Feb 2021
Research article |  | 26 Feb 2021

Two-dimensional and multi-channel feature detection algorithm for the CALIPSO lidar measurements

Thibault Vaillant de Guélis, Mark A. Vaughan, David M. Winker, and Zhaoyan Liu

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Interactive discussion

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Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Thibault Vaillant de Guélis on behalf of the Authors (22 Dec 2020)  Author's response   Manuscript 
ED: Publish as is (29 Dec 2020) by Ulla Wandinger
AR by Thibault Vaillant de Guélis on behalf of the Authors (30 Dec 2020)
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Short summary
We introduce a new lidar feature detection algorithm that dramatically improves the fine details of layers identified in the CALIOP data. By applying our two-dimensional scanning technique to the measurements in all three channels, we minimize false positives while accurately identifying previously undetected features such as subvisible cirrus and the full vertical extent of dense smoke plumes. Multiple comparisons to version 4.2 CALIOP retrievals illustrate the scope of the improvements made.