Understanding model spread in sea ice volume by attribution of model differences in seasonal ice growth and melt

West, Alex; Blockley, Edward; Collins, Matthew

doi:https://doi.org/10.5194/tc-16-4013-2022

Articles | Volume 16, issue 10

https://doi.org/10.5194/tc-16-4013-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-16-4013-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 16, issue 10

Research article

|

07 Oct 2022

Research article |

| 07 Oct 2022

Understanding model spread in sea ice volume by attribution of model differences in seasonal ice growth and melt

Alex West, Edward Blockley, and Matthew Collins

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Final revised paper (published on 07 Oct 2022)
Supplement to the final revised paper
Preprint (discussion started on 22 Nov 2021)
Supplement to the preprint

Interactive discussion

Status: closed

RC1:
'Comment on tc-2021-351', Anonymous Referee #1, 18 Dec 2021
The authors analyse how differences in three climate models contribute to difference in the modelled sea ice. They apply the ISF method to break out contributions of individual components to drivers of melt and freeze throughout the year. Overall the manuscript is well written, clear, and has sound methodology. Well done! My concerns are primarily related to clarification and minor in scope.

Specific comments

Line 110, remove “and” after Wang et al.

Line 197: I would recommend rewording “thicker ice in HadGEM3-GC3.1-LL and UKESM1.0-LL causing a colder surface temperature, and less heat loss to space, than is the case in HadGEM2-ES” to: “compared to HadGEM2-ES, the two CMIP6 models have thicker ice which leads to a colder surface due to reduced heat conduction through the ice, and the colder surface results in less longwave radiative loss to space.”

Line 216: You haven’t cited or mentioned CICE yet. You may want to expand a bit about why or how the ice models are different.

Figure 3:

Could you plot surface albedo differences to show the net spatial impacts of all components?

It might be nice to compare with observations here, where appropriate. The different models have hugely different ice fractions and melt pond fractions. Which are most reasonable given observations?

Equation 2: instead of MODEL it says MODE. Same two lines above.

Equation 5: At first it is nearly impossible to tell the difference between a for area and alpha for albedo. Could Area be changed to A_i or bolded to make this clearer? Same for lines below.

Line 282: Please clarify how bare ice fraction is found.

Line 285: If this equation is relevant, may want to number it. Also, please define the albedo of the ocean. Is the albedo over different surface types output directly?

Line 304-306: Did you verify that the answer is similar by using either/both CMIP6 models and comparing ensemble mean to the individual ensemble members?

Figures 4,5,6:

These figures are really nice and clear, but I had a lot of trouble with the colors. Please modify the colors to improve readability, change dash patterns, or bold particular lines of relevance.

I think monthly mean figures of the spatial difference contributions might be useful as a supplementary figure to see which components dominate in different regions.

Line 328: Why is the snow thickness so different between these models?

Line 379: I would recommend rewording “differences in the thicker categories contribute much more towards the total” to: “contributions across all thickness categories are similar rather than being dominated by very thin ice as was found in the previous comparison.”
Citation: https://doi.org/10.5194/tc-2021-351-RC1
- AC1: 'Reply to RC1', Alex West, 23 May 2022
  
  Please see the attached supplement for our response to the review, including an apology and explanation for the time taken.
  
  Citation: https://doi.org/10.5194/tc-2021-351-AC1
RC2:
'Comment on tc-2021-351', Anonymous Referee #2, 22 Feb 2022

see the attachment

Citation: https://doi.org/10.5194/tc-2021-351-RC2
- AC2: 'Reply to RC2', Alex West, 23 May 2022
  
  Please see the attached supplement for our response to the review, including an apology and explanation for the time taken.
  
  Citation: https://doi.org/10.5194/tc-2021-351-AC2

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) (07 Jun 2022) by Yevgeny Aksenov

AR by Alex West on behalf of the Authors (29 Jul 2022) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (17 Aug 2022) by Yevgeny Aksenov

RR by Anonymous Referee #1 (27 Aug 2022)

Suggestions for revision or reasons for rejection

Thanks to the authors for addressing my comments thoroughly. Sorry about covid also delaying the response and I hope all are well now! I think the addition of the analysis with multiple ensemble members is beneficial and makes the work more robust. I also really appreciated the addition of section 3.2 as it really clarifies the method and processes going on in the analysis, and the addition of Figure 5 is also great. Additionally, I find the equations clearer. Overall, I am happy to recommend this for publication with the slight modifications detailed below.

Specific comments
• Figure 1: Clarify for Upwelling SW radiation that negative means upward. In the caption of the figure it would be good to clarify and maybe generally clarify positive/negative values for the fluxes and if they mean towards or away from the surface.
• Figure 3: It looks to me like in this figure have more upwelling Shortwave radiation (i.e. flux away from surface, so negative). Since the incoming shortwave radiation is very similar, this indicates a higher albedo in the CMIP6. At line 229 in the text (track changes version) you say the opposite and that CMIP6 models have “smaller upwelling SW flux”. Please make sure this is consistent. Same comment as above for Fig.1 about positive/negative flux conventions.
• Figure 4: I like the new observational values, but there are some oddities. In panels k-n some text is under the color bar? I’m also confused about proportion of June days with melt and NSIDC melt onset. The average NSIDC melt onset day that is dark blue is 0.5, but does that mean June 15? Is it possible to have these panels showing the same thing (i.e. proportion of June days that are melt?)? I don’t think there’s a fundamental method concern (based on wording around ~line 295 in the paper), but the title for panel n is very confusing and could benefit from rewording.

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ED: Publish subject to technical corrections (30 Aug 2022) by Yevgeny Aksenov

Dear Author,

Thank you for submitting a revised version of the manuscript. Reviewer #1 is satisfied with the replies and corrections. Therefore, I recommend that the manuscript can be published after addressing a few technical issues raised by reviewer and listed below. In addition, I suggest you should check out the text for references to the figures and typos in the equations. The details are in the non-public editor communication to the authors. The manuscript would not go again to the reviewers or to the editor at this stage. Please follow the guidelines from the editorial support how to submit the final version.

Congratulations and thank you for publishing with The Cryosphere journal.

Best wishes,

Yevgeny Aksenov (on behalf of TC)

______________________________________
Reviewer #1:

Thanks to the authors for addressing my comments thoroughly. Sorry about covid also delaying the response and I hope all are well now! I think the addition of the analysis with multiple ensemble members is beneficial and makes the work more robust. I also really appreciated the addition of section 3.2 as it really clarifies the method and processes going on in the analysis, and the addition of Figure 5 is also great. Additionally, I find the equations clearer. Overall, I am happy to recommend this for publication with the slight modifications detailed below.

Specific comments
• Figure 1: Clarify for Upwelling SW radiation that negative means upward. In the caption of the figure it would be good to clarify and maybe generally clarify positive/negative values for the fluxes and if they mean towards or away from the surface.
• Figure 3: It looks to me like in this figure have more upwelling Shortwave radiation (i.e. flux away from surface, so negative). Since the incoming shortwave radiation is very similar, this indicates a higher albedo in the CMIP6. At line 229 in the text (track changes version) you say the opposite and that CMIP6 models have “smaller upwelling SW flux”. Please make sure this is consistent. Same comment as above for Fig.1 about positive/negative flux conventions.
• Figure 4: I like the new observational values, but there are some oddities. In panels k-n some text is under the color bar? I’m also confused about proportion of June days with melt and NSIDC melt onset. The average NSIDC melt onset day that is dark blue is 0.5, but does that mean June 15? Is it possible to have these panels showing the same thing (i.e. proportion of June days that are melt?)? I don’t think there’s a fundamental method concern (based on wording around ~line 295 in the paper), but the title for panel n is very confusing and could benefit from rewording.

Hide

AR by Alex West on behalf of the Authors (08 Sep 2022) Manuscript

Short summary

In this study we explore a method of examining model differences in ice volume by looking at the seasonal ice growth and melt. We use simple physical relationships to judge how model differences in key variables affect ice growth and melt and apply these to three case study models with ice volume ranging from very thin to very thick. Results suggest that differences in snow and melt pond cover in early summer are most important in causing the sea ice differences for these models.