Articles | Volume 14, issue 6
https://doi.org/10.5194/amt-14-4335-2021
https://doi.org/10.5194/amt-14-4335-2021
Research article
 | 
11 Jun 2021
Research article |  | 11 Jun 2021

Deriving boundary layer height from aerosol lidar using machine learning: KABL and ADABL algorithms

Thomas Rieutord, Sylvain Aubert, and Tiago Machado

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Interactive discussion

Status: closed
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 Thomas Rieutord on behalf of the Authors (06 Aug 2020)  Author's response   Manuscript 
ED: Referee Nomination & Report Request started (28 Sep 2020) by E. J. O'Connor
RR by Anton Sokolov (18 Oct 2020)
RR by Anonymous Referee #3 (03 Nov 2020)
ED: Reconsider after major revisions (12 Nov 2020) by E. J. O'Connor
AR by Thomas Rieutord on behalf of the Authors (18 Dec 2020)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (12 Jan 2021) by E. J. O'Connor
RR by Anonymous Referee #3 (16 Mar 2021)
RR by Anonymous Referee #4 (18 Mar 2021)
ED: Publish subject to minor revisions (review by editor) (08 Apr 2021) by E. J. O'Connor
AR by Thomas Rieutord on behalf of the Authors (16 Apr 2021)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (21 Apr 2021) by E. J. O'Connor
AR by Thomas Rieutord on behalf of the Authors (29 Apr 2021)  Manuscript 
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Short summary
This article describes two methods to estimate the height of the very first layer of the atmosphere. It is measured with aerosol lidars, and the two new methods are based on machine learning. Both are open source and available under free licenses. A sensitivity analysis and a 2-year evaluation against meteorological balloons were carried out. One method has a good agreement with balloons but is limited by training, and the other has less good agreement with balloons but is more flexible.