Articles | Volume 21, issue 6
Atmos. Chem. Phys., 21, 4249–4265, 2021
https://doi.org/10.5194/acp-21-4249-2021

Special issue: EARLINET aerosol profiling: contributions to atmospheric and...

Atmos. Chem. Phys., 21, 4249–4265, 2021
https://doi.org/10.5194/acp-21-4249-2021

Research article 19 Mar 2021

Research article | 19 Mar 2021

Atmospheric boundary layer height estimation from aerosol lidar: a new approach based on morphological image processing techniques

Gemine Vivone et al.

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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 Simone Lolli on behalf of the Authors (12 Jan 2021)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (12 Jan 2021) by Eduardo Landulfo
RR by Anonymous Referee #2 (13 Jan 2021)
RR by Anonymous Referee #1 (30 Jan 2021)
ED: Publish subject to minor revisions (review by editor) (09 Feb 2021) by Eduardo Landulfo
AR by Simone Lolli on behalf of the Authors (12 Feb 2021)  Author's response    Manuscript
ED: Publish as is (13 Feb 2021) by Eduardo Landulfo
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Short summary
We developed a methodology to retrieve the atmospheric boundary layer height from elastic and multi-wavelength lidar observations that uses a new approach based on morphological image processing techniques. The intercomparison with other state-of-the-art algorithms shows on average 30 % improved performance. The algorithm also shows excellent performance with respect to the running time, i.e., just few seconds to execute the whole signal processing chain over 72 h of continuous measurements.
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