Articles | Volume 20, issue 6
https://doi.org/10.5194/tc-20-3467-2026
© Author(s) 2026. This work is distributed under the Creative Commons Attribution 4.0 License.
Airborne lidar and machine learning reveal decreased snow depth in burned forests
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- Final revised paper (published on 17 Jun 2026)
- Supplement to the final revised paper
- Preprint (discussion started on 15 Sep 2025)
- Supplement to the preprint
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
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RC1: 'Comment on egusphere-2025-4081', Elijah Boardman, 11 Nov 2025
- AC1: 'Reply on RC1', Arielle Koshkin, 25 Apr 2026
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RC2: 'Comment on egusphere-2025-4081', César Deschamps-Berger, 09 Mar 2026
- AC2: 'Reply on RC2', Arielle Koshkin, 25 Apr 2026
Peer review completion
AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
ED: Publish subject to revisions (further review by editor and referees) (28 Apr 2026) by Franziska Koch
AR by Arielle Koshkin on behalf of the Authors (28 Apr 2026)
Author's response
Author's tracked changes
Manuscript
ED: Referee Nomination & Report Request started (29 Apr 2026) by Franziska Koch
RR by Elijah Boardman (29 Apr 2026)
RR by César Deschamps-Berger (20 May 2026)
ED: Publish subject to minor revisions (review by editor) (20 May 2026) by Franziska Koch
AR by Arielle Koshkin on behalf of the Authors (22 May 2026)
Author's response
Author's tracked changes
Manuscript
ED: Publish as is (22 May 2026) by Franziska Koch
AR by Arielle Koshkin on behalf of the Authors (22 May 2026)
Manuscript
Dear authors, please see my comments in the attached PDF. I feel like my suggestions are mostly minor revisions, but I do raise two larger concerns about (1) treatment of non-forest alpine pixels and (2) cross-validation robustness in the presence of spatial autocorrelation.