Underrepresentation of the Linkage between the Barents–Kara Sea Ice and East Asian Rainfall in Early Summer by CMIP6 Models
Round 1
Reviewer 1 Report
This article aims to assess the performance of CMIP6 models in simulating the linkage between Barents–Kara sea ice variability in winter and eastern China rainfall anomalies in early summer. They found that only a few models can roughly reproduce the observed rainfall dipole pattern in eastern China associated with Barents–Kara sea ice variability. They suggested that the relatively short memory of Barents–Kara sea ice in low-skill models partially explain the underrepresentation of the Arctic sea ice–China climate relationship, and model biases in simulating the stratosphere–troposphere also play a role. These results have implication for model improvement and future climate projection, and is recommended for publication with the following revisions:
1) Lines 20-22: The authors concluded that the over-strong covariance of sea ice across the Arctic may contribute to destructing the Arctic sea ice–eastern China rainfall relationship. But I can’t find such conclusion arises from which part of this study, and therefore suggest that more evidences should be shown in the manuscript to support their conclusions.
2) Section 4: The authors mentioned that the MME for high-top models better simulate the Arctic sea ice memory and stratospheric variability than the MME for low-top models. High-skill models and their MME show a longer SIC memory, a more reasonable stratospheric variability, and a better tropospheric wave train like circulation, and therefore a more realistic rainfall anomaly dipole in eastern China. However, the high-skill models showed in Figure 3 (i.e., BCC-ESM1 with a model top at 2.19 hPa and CAMS-CSM1-0 at 10 hPa) are both not high-top models. Can the authors make some explanations on such a conflict?
3) Figure 3: In addition to BCC-ESM1 and CAMS-CSM1-0, what is the performance of the other high-skill/low-skill models? There are only four models chosen respectively as high-skill and low-skill models in this study. So I suggest that the authors show the results for all the individual high-skill/low-skill models in Figure 3.
4) Figure 3, Figure 5 and Figure 7: Why the representative models are different among these figures? The authors should make an exploration on such inconsistency.
5) Lines 230-241: How to generate the MME of high-skill models and low-skill models? Please make a statement about it.
6) Line 235: Please replace “its low-skill models MME” with “its MME”.
Author Response
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Author Response File: 
Author Response.docx
Reviewer 2 Report
In this study, the authors evaluated the performance of multiple models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating the linkage between Barents-Kara sea ice and rainfall in eastern China. The results show that most CMIP6 models overestimate the Arctic sea ice concentration (SIC) and cannot reproduce the Arctic sec ice-related rainfall dipole pattern, while only a few models can roughly reproduce the observed rainfall dipole pattern associated with Arctic sea ice variability. The topic is interesting and there is potential possibility for this manuscript to be published on Atmosphere. However, some clarifications and additional work are needed to be done.
This study evaluates the performance of CMIP6 in simulating the Linkage between the Barents-Kara Sea Ice and East Asian Rainfall in Early Summer. In addition, the selected high-skill models better represent this linkage. Physical processes and atmospheric circulation changes associated with sea ice forcing are compared through different models. The analysis is generally reasonable, and the results of this work may rich our understanding on impact of sea ice forcing on rainfall over East Asia. Therefore, I believe that the paper has the potential to be published in Atmosphere and I suggest the authors make further revise to improve the quality of this manuscript. Comments and suggestions are listed below.
1. Different models have different horizontal resolutions (Table 1), have the authors did some preprocessing (such as using bilinear interpolation scheme to interpolate all model results to a common 1*1° grid) to facilitate the inter-comparison.
2. As shown in Figure 1, what criteria the authors use to select the high- and low-skill model experiments, I suggest the authors to present the Taylor diagrams to provide a visual framework for comparing a suite of variables from one or more test data sets to one or more reference data sets.
3. “Some previous studies mainly focus on ……, while other studies also emphasized ……”. (L69-70) The tenses of the first and second sentences are inconsistent.
4. Verb “is” is absent before “also be used to confirm statistical result” (L119-120).
5. Figure 1f seems to show the simulation of low-skill models on sea ice variability (L176), I suggest the authors have a check.
6. “the mean SIC …… but falls into the value range between the observations and the MME of all CMIP6 models”. (L203) “range” should be replaced with “ranging”.
7. “Barents-Kara Seas are a key region……”. (L221) Replace the verb “are” with “is”.
8. The adjective “illusive” is inappropriate in this statement of simulated pattern. (L235) I would try to reformulate another word. (e.g. “unrealistic”, “illusory”)
9. The position order of adverb “also” in the sentence “Besides, responses of weather and climate in mid-to-high ……. also are not identical [29, 57],” (L245) should be exchanged with verb “are”.
10. The color of dot and yellow shaded in Figure 3 are difficult to distinguish, especially in Figure 3e.
11. Authors suggest that the SIC anomalies are largest in November and December, which gradually weaken in following months. (L309-310) However, the SIC anomalies in Barents-Kara Seas seems to be modestly enhanced in May-June (Figure 5a3, 5b3, 5d3).
12. In Figure 6, the SIC persistency lines obtained from the low-skill model and OBS are very similar, I suggest author check it.
13. “at the tropospheric pressure levels,” (L385) should be expressed professionally. (e.g. “the entire troposphere”, “from 200 hPa to 850 hPa in troposphere”)
14. The statement of “but high-top models simulate better than low-top models in this pathway” (L443-L444) seems to uncovered in article, please clarify or testify expression.
15. “when Barents-Kara sea ice leads eastern China rainfall by nearly half a year”. (L465) “to” is absent behind “leads”.
16. The statement of “Four models quantitively reproduce…….” (L490) should be consistent with “selected typical CMIP6 models”. Modify the expression as “Four representative models (# name1; ……; # name2)”.
Author Response
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Author Response File: Author Response.docx
Reviewer 3 Report
I found the manuscript very interesting and I think it will help to better understand the relationship between sea ice concentration and precipitation in China, at least in two regions. However, the document needs some improvements in English for a better understanding of the text by the reader. The figures need to be enlarged, in the current size, it is difficult to see the details. I worked on the pdf version, where you can find some text suggestions, comments, and questions. Also, I would like the authors to include some text on the role (if any) that topography plays in the precipitation distribution. Although there may be a relationship between the concentration of sea ice and rainfall in China, and this may be related to the downward propagation of stratospheric air, I wonder, once the movement (or wave) is triggered, what role do mountains play in the area? And how well models perform considering this.
Comments for author File: 
Comments.pdf
Although the text is in general understandable, the document needs some improvements in English for a better understanding of the text by the reader.
Author Response
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Author Response File: Author Response.docx
Reviewer 4 Report
1. What is the main question addressed by the research?
The paper is dedicated to the linkage reveal between the Barents-Kara Sea ice and East Asian rainfall in early summer season. Authors have used multiple models from phase 6 of the Coupled Model Intercomparison Project (CMIP6). Main biases in the mean state and variability of the Arctic sea ice and the sea ice concentration (SIC), and China rainfall linkage have been evaluated.
2. Do you consider the topic original or relevant in the field, and if so, why?
The topic is original and relevant in the field. The linkage between Arctic sea ice variability in winter and eastern China rainfall in early summer is realized through a long memory of the sea ice, the stratospheric variability as the mediator, and downward propagation of stratospheric signals.
3. What does it add to the subject area compared with other published material?
Authors used multiple models from CMIP6. Most CMIP6 models can simulate the Arctic sea ice coverage in the present climate system, although the sea ice extent in the edge areas show some biases. Only sevaral models can roughly reproduce the observed rainfall dipole pattern associated with Arctic sea ice variability. The linkage between Arctic sea ice variability in winter and eastern China rainfall in early summer is realized through a long memory of the sea ice, the stratospheric variability as the mediator, and downward propagation of stratospheric signals. Very few CMIP6 models can exhibit a realistic interannual relationship between the Arctic sea ice and China rainfall. Compared with observations, sea ice in Barents-Kara Seas shows an over-strong covariance with sea ice in other parts of Arctic, which might destruct the observed linkage between Arctic sea ice and China rainfall. The selected high-skill models with a more realistic linkage between sea ice and China rainfall present a clear downward impact of the stratospheric circulation anomalies associated with the sea ice variability. The reversal of the Northern Hemisphere Annular Mode (NAM) from the negative phase in early winter to the positive phase in spring in the high-skill models and observations denotes the important role of the stratosphere as the mediator to bridge the Arctic sea ice and China rainfall.
4. What specific improvements could the authors consider regarding the methodology?
There is no need to make any improvements or something else. The authors outlined the current achievements in the field in the introduction, and provided detailed description of the materials and method, as well as the obtained results, and conclusions.
5. Are the conclusions consistent with the evidence and arguments presented and do they address the main question posed?
The conclusions are consistent with the evidence and arguments presented in the manuscript and address the main questions of their study. However, where the obtained results can be applied and the future research perspective should be outlined in Conclusions.
6. Are the references appropriate?
The references are appropriate, and most of them are fairly up-to-date.
7. Please include any additional comments on the tables and figures.
All the tables and figures are appropriate. They show well the research and experiment details and results.
Nevertheless, the resolution in Figure 1, 2, 4, 7 should be increased.
8. Other comments.
It is not clear in the first sentence in Abstract and Conclusions who performed “Previous study”. Please, concretize who exactly performed it, you or somebody else.
Please, describe in Abstract where the obtained results can be used.
After detailed consideration of the manuscript, I have found that the results obtained are new and significant for the field. The manuscript is mostly written well but needs some corrections before its publication in the journal.
So, the paper needs a minor revision.
Author Response
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Author Response File: Author Response.docx
Reviewer 5 Report
Dear Editor, Dear Authors,
This is an interesting engineering study of the relationship between sea ice extent in the Barents-Kara sea in early winter and the low/high pressure dipole in East Asia in summer, with implications for rainfall.
The different models are categorized into 1) high-top or low-top according to their ability to reproduce the stratosphere variability, and high-skill/low-skill according to their ability to reproduce the memory effect of sea ice.
The scientific approach is clear and reveals both the strengths and the weaknesses of the CMIP6 models, which is well recapitulated in the conclusion.
I have only minor recommendations:
Line 347: Figure 7 shows the regressed stratospheric anomalies in May and June against the November–December Barents–Kara sea ice for two representative high-skill models.
Why was the same representation not made with ERA5?
Lines 446-447: An increase in the Arctic SIC over Barents-Kara Seas is followed by weakened planetary waves and a strong stratospheric polar vortex in winter.
Isn't there a contradiction between the weakening of planetary waves and the strengthening of stratospheric polar vortex in winter?
Line 478: Most CMIP6 models overestimate the Arctic SIC, but the SIC variability in Barents- Kara Seas in early winter are weaker than in observations obviously.
This assertion is not obvious from Figure 1.
Author Response
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Author Response File: Author Response.docx
