Articles | Volume 22, issue 23
https://doi.org/10.5194/acp-22-15313-2022
https://doi.org/10.5194/acp-22-15313-2022
Research article
 | 
02 Dec 2022
Research article |  | 02 Dec 2022

Cluster-based characterization of multi-dimensional tropospheric ozone variability in coastal regions: an analysis of lidar measurements and model results

Claudia Bernier, Yuxuan Wang, Guillaume Gronoff, Timothy Berkoff, K. Emma Knowland, John T. Sullivan, Ruben Delgado, Vanessa Caicedo, and Brian Carroll

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Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Claudia Bernier on behalf of the Authors (02 Jul 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (13 Jul 2022) by Yafang Cheng
RR by Anonymous Referee #2 (30 Jul 2022)
RR by Anonymous Referee #3 (25 Aug 2022)
RR by Anonymous Referee #4 (28 Aug 2022)
RR by Anonymous Referee #5 (31 Aug 2022)
RR by Anonymous Referee #1 (06 Sep 2022)
ED: Publish subject to minor revisions (review by editor) (19 Sep 2022) by Yafang Cheng
AR by Claudia Bernier on behalf of the Authors (30 Sep 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (08 Nov 2022) by Yafang Cheng
AR by Claudia Bernier on behalf of the Authors (08 Nov 2022)  Author's response   Manuscript 
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Short summary
Coastal regions are susceptible to variable and high ozone which is difficult to simulate. We developed a method to characterize large datasets of multi-dimensional measurements from lidar instruments taken in coastal regions. Using the clustered ozone groups, we evaluated model performance in simulating the coastal ozone variability vertically and diurnally. The approach allowed us to pinpoint areas where the models succeed in simulating coastal ozone and areas where there are still gaps.
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