Articles | Volume 20, issue 11
https://doi.org/10.5194/tc-20-6521-2026
© Author(s) 2026. This work is distributed under the Creative Commons Attribution 4.0 License.
Effects of snow redistribution parameterization on simulated snow thickness validated by MOSAiC observations
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- Final revised paper (published on 12 Nov 2026)
- Preprint (discussion started on 02 Jun 2026)
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-2026-2179', Anonymous Referee #1, 22 Jun 2026
- AC1: 'Reply on RC1', Fengguan Gu, 06 Aug 2026
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RC2: 'Comment on egusphere-2026-2179', Anonymous Referee #2, 22 Jul 2026
- AC2: 'Reply on RC2', Fengguan Gu, 20 Aug 2026
Peer review completion
AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
ED: Submit a revised manuscript (29 Aug 2026) by John Yackel
AR by Fengguan Gu on behalf of the Authors (30 Aug 2026)
Author's response
Author's tracked changes
Manuscript
ED: Referee Nomination & Report Request started (03 Sep 2026) by John Yackel
RR by Anonymous Referee #1 (23 Sep 2026)
RR by Anonymous Referee #2 (20 Oct 2026)
ED: Publish as is (22 Oct 2026) by John Yackel
AR by Fengguan Gu on behalf of the Authors (25 Oct 2026)
Manuscript
This manuscript assesses the influence of snow redistribution on snow-thickness simulations using the Icepack model and conducts sensitivity analyses to evaluate the parameterisation of snow redistribution. The topic is important for the snow and sea-ice modelling community. However, the manuscript requires further improvement before it can be recommended for publication.
Major points:
Specific points:
Line 36: The statement that snow accumulation can lead to flooding should be clarified. Please explain under what conditions flooding occurs and what is meant by flooding in this context. This would make the sentence clearer for readers who are less familiar with sea-ice processes.
Section 2.2: Please add more information about the MOSAiC expedition data used in this study, including ice types, loop positions, transect types, and the temporal coverage of each dataset.
Section 2.3: Could it be combined with Section 2.1, which introduces the Icepack model?
Section 2.3: The equations are not numbered.
Lines 173–184: This paragraph seems somewhat disconnected from the surrounding text. It may fit better in the Introduction or Discussion?
line 179: it mentions that Icepack assumes a uniform snow thickness. However, observations show strong spatial variability in snow thickness at sub-grid scales (https://doi.org/10.1017/jog.2022.18 and https://doi.org/10.5194/tc-20-2825-2026). Would this uniform-snow assumption introduce bias or uncertainty into the results presented in the manuscript? This issue should be discussed.
Line 220: The authors state that the snwITDrdg scheme performs better than the none and bulk schemes for SWE. However, the simulated SWE remains substantially higher than the mean observations. Does this indicate that none of the three schemes fully captures the observed SWE evolution?
Lines 221–223: The authors state that the snwITDrdg scheme significantly reduces SWE, particularly during high-wind periods. However, I am not sure this is clearly supported by Figures 1b and 1d. Please provide more explanation or evidence to support this statement. In addition, the statement that “snow particles are suspended and redistributed or deposited in the leads” requires more supporting evidence or references too.
Line 248: Please explain how the range of P values from 0.3 to 4 was selected. Are these values based on observations? Since the minimum MAE appears to occur at the maximum tested value of P = 4, it would be useful to know whether MAE increases again for P values greater than 4.
Figure 2 caption: Explain the meaning of P and gamma in the caption so that the figure can be understood independently.