Articles | Volume 15, issue 6
https://doi.org/10.5194/amt-15-1931-2022
https://doi.org/10.5194/amt-15-1931-2022
Research article
 | 
30 Mar 2022
Research article |  | 30 Mar 2022

Assessing the benefits of Imaging Infrared Radiometer observations for the CALIOP version 4 cloud and aerosol discrimination algorithm

Thibault Vaillant de Guélis, Gérard Ancellet, Anne Garnier, Laurent C.-Labonnote, Jacques Pelon, Mark A. Vaughan, Zhaoyan Liu, and David M. Winker

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2021-419', Anonymous Referee #1, 20 Jan 2022
  • RC2: 'Comment on amt-2021-419', Bryan A. Baum, 23 Jan 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Thibault Vaillant de Guélis on behalf of the Authors (10 Feb 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (11 Feb 2022) by Andrew Sayer
RR by Bryan A. Baum (24 Feb 2022)
ED: Publish as is (24 Feb 2022) by Andrew Sayer
AR by Thibault Vaillant de Guélis on behalf of the Authors (01 Mar 2022)
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Short summary
A new IIR-based cloud and aerosol discrimination (CAD) algorithm is developed using the IIR brightness temperature differences for cloud and aerosol features confidently identified by the CALIOP version 4 CAD algorithm. IIR classifications agree with the majority of V4 cloud identifications, reduce the ambiguity in a notable fraction of not confident V4 cloud classifications, and correct a few V4 misclassifications of cloud layers identified as dense dust or elevated smoke layers by CALIOP.