the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 21 Jan 2026
Distinct atmospheric drivers of Ross Sea coastal polynya variability during winter
Abstract. Coastal polynyas in the Ross Sea have well-documented links to atmospheric circulation, but the role of specific circulation patterns in driving extreme wind events and their differential impact on individual polynyas remains poorly explored. This study examines peak-winter (Aug–Oct) variability in the Ross Sea, Terra Nova Bay, and McMurdo Sound polynyas using EOF analysis of high-resolution passive microwave sea-ice concentration data. Patterns of variability are related to surface extreme winds and 500 hPa geopotential height anomalies from ERA5, allowing concurrent assessment of local forcing and hemispheric-scale circulation connections.
Results reveal that each polynya responds differently to shifts in large-scale atmospheric features. Variations in the position and intensity of the Amundsen Sea Low, and its influence on Ross Ice Shelf Air Stream winds, are associated with marked changes in polynya area. By combining high-resolution sea ice concentration records with targeted extreme-wind analysis, this work identifies previously unresolved, location-specific atmospheric controls on Ross Sea polynya variability.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2025-5369', Anonymous Referee #1, 26 Feb 2026
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AC1: 'Reply on RC1', Girija Kalyani Burada, 18 May 2026
- Without e.g. composites (ideally lagged composites) of absolute conditions occurring during the high/low phases of different EOF modes it’s quite difficult to reach a physical interpretation.
E.g. northerly wind anomalies in the Ross could be associated with either actual northerlies (potentially driving sea ice compaction) or weak southerlies (reduced divergence).
For example, in the paper (e.g. L201) there is description of physical features such as jets in Figure 3Ad, but the Figure shows the association between winds and SIC, rather than physical jets. Similarly, it’s difficult to understand the interpretation of low-sea-ice conditions in mode 2 if thermodynamic factors play a role as no thermodynamic fields are shown.
Response:
We thank the reviewer for this thoughtful comment regarding the physical interpretation of the EOF-associated circulation patterns. We agree that anomaly fields alone may not uniquely distinguish between true flow reversals and variations in the strength of the prevailing circulation regime. To address this concern, we have now included composite maps of the absolute near-surface winds during the positive and negative phases of the leading EOF modes (Fig. S5 and S6). These additional diagnostics help clarify the background circulation states and support our interpretation that the identified anomalies primarily reflect changes in the strength and positioning of the prevailing flow regimes over the Ross Sea sector.
We also acknowledge that lagged composite analysis could provide further insight into the temporal evolution and potential causality of the circulation–sea ice relationships. However, the primary objective of the present study is to identify the dominant modes of coupled SIC–circulation variability and their associated large-scale atmospheric structures, rather than to investigate the lifecycle or predictability of individual events. Therefore, the analysis is intentionally focused on simultaneous relationships, while lagged evolution is acknowledged as an important avenue for future work.
In addition, we agree that the regression patterns represent circulation anomalies associated with SIC variability rather than direct diagnostics of jet structure or intensity. Accordingly, we have revised the manuscript throughout to avoid overinterpretation and now refer more generally to circulation anomalies associated with the Ross Ice Shelf Air Stream region.
Finally, we agree that thermodynamic fields would be necessary to fully evaluate the role of thermodynamic forcing mechanisms in driving the observed SIC variability. Since the primary focus of this study is on the large-scale dynamical circulation patterns associated with SIC variability, we have moderated the discussion related to thermodynamic influences and clarified that such interpretations remain speculative within the scope of the present analysis.
- Based on the methodology I would caution against the use of ‘extreme wind events’ in this paper. Papers describing extreme wind events usually focus on e.g. specific percentiles or thresholds. Here, the focus is on the daily maximum wind speed which may not be extreme. The name ‘ExWinds’ should be updated accordingly (maybe ‘MaxWinds’?).
Response:
We appreciate this important point. In response, we have replaced the term “ExWinds” throughout the manuscript with “MaxWinds” to better reflect the nature of the metric used. We agree that the term “extreme wind events” may imply a threshold-based definition that is not applicable here.
- Related to the above, what’s the justification for using daily maximum wind speeds (potentially noisier) compared to daily mean?
Response:
We thank the reviewer for raising this point. We use daily maximum wind speed because our focus is on the strongest wind forcing occurring within each day. In polar regions, short-lived but intense wind bursts can be highly effective in driving rapid sea-ice divergence, polynya opening, and related ice-dynamic responses, even if they are not sustained throughout the day. Daily mean winds may smooth out these short-duration peaks and therefore underestimate the instantaneous forcing most relevant to sea-ice motion and deformation.
We have revised the manuscript to make clear that this metric is intended as a proxy for peak daily forcing rather than a formally defined extreme.
- Several figure improvements are needed:
- All Figures’ DPI is quite low.
We have revised the figures with improved resolution where possible and also includes clearer labeling and captions.
- The BWCJ mechanism is central to the Mode 3 interpretation. Can you provide a suitable composite or at least local wind vectors as in Figure 3B over the BWCJ region?
We also note that barrier winds are difficult to resolve at the 0.25° horizontal resolution used here, and we have added text acknowledging this limitation. Where feasible, we have also included additional local wind-vector information over the BWCJ region to better support the discussion of Mode 3.
- Figure 3B does not have panel labels or a descriptive caption (are the wind vectors MCA spatial patterns?). Figure 4 caption should refer to panel labels.
The panels labels are now added
- It’s not clear whether Figure 3Ad,e,f is or should be different from the right panels of Figure 3B. Figure 3B Modes 1 and 2 look similar to Figure 3A(d,e) but Mode 3 looks completely different to Figure 3A(f)?
Thank you for pointing this out. Figures 3A(d–f) and the right-hand panels of Figure 3B are related but not identical diagnostics. Figure 3A(d–f) presents the circulation patterns associated with the identified modes in the large-scale wind field, whereas the right-hand panels of Figure 3B show the composite local wind vectors over the Ross Sea sector. The close similarity for Modes 1 and 2 reflects the fact that these modes are primarily associated with large-scale synoptic circulation anomalies that are well represented in the 0.25° ERA5 data. In contrast, Mode 3 is interpreted as being linked to the Barrier Wind Coastal Jet (BWCJ) mechanism along the Transantarctic Mountains. Because barrier winds are mesoscale features confined to narrow coastal regions, they are not fully resolved in the present dataset. We have revised the manuscript to clarify this distinction and to explicitly note the resolution limitations for capturing such localized coastal jets.
Specific comments
- L113 Square root of the cosine of latitude?
We have corrected the text as suggested.
- L191 ‘PCs associated 3’?
We have revised the sentence to refer explicitly to “mode 3.”
- L212: No 3B(e) is marked on the figure. Also ‘Northwest-southeast pattern’ please clarify using e.g. northwesterly, southeasterly
Thank you for this observation. The figure has been revised, with all relevant panels clearly labeled. We have also clarified the wind-direction terminology for improved readability.
- L219: Stammerjohn et al. (2008) in the references gives a DOI: https://doi.org/10.1016/j.pocean.2008.02.002 which leads to a paper called “Statistics from Lagrangian observations”. I cannot find any paper entitled “Sea ice in the Southern Ocean: The Weddell Sea and Ross Sea”.
Thank you for identifying this reference issue. We have corrected the citation and updated the reference list accordingly.
- L210 This paragraph needs supporting evidence to interpret the Mode 2 pattern. I think it’s important to help readers understand how weak winds conditions can be associated with low sea ice states (it’s intuitive to understand how strong winds can be associated with low sea ice). I feel that composites of physical quantities are needed. Is it thermodynamic factors (e.g. increased shortwave absorption, low cloud cover) as you propose, or perhaps memory from previous high-wind states?
Response:
We thank the reviewer for this insightful comment. We agree that the physical interpretation of low sea-ice conditions associated with comparatively weak wind anomalies in Mode 2 is less straightforward than in strong-wind regimes. Our intention was not to imply a definitive attribution to specific thermodynamic mechanisms, but rather to discuss plausible contributing processes that may accompany the observed circulation patterns.
To avoid overinterpretation, we have revised the text to clarify that the proposed thermodynamic influences, including enhanced shortwave absorption and cloud-related effects, remain speculative within the scope of the present analysis. We also acknowledge that persistence or memory effects associated with preceding circulation states could contribute to the observed SIC anomalies. However, a detailed assessment of these mechanisms would require additional thermodynamic and lagged composite analyses, which are beyond the primary focus of this study. The manuscript has been revised accordingly to emphasize that our results primarily identify large-scale dynamical associations rather than establish direct process-level attribution.
- It may be worth looking at cutting down on acronyms a bit as there are many to keep track of – RS for Ross Sea is probably not needed. Similarly, no need to define AP as an acronym.
We agree and have simplified the terminology accordingly. “RS” has been replaced with “Ross Sea,” and “AP” has been removed where unnecessary.
- L228 Barrier wind corner jet mechanism (BWCJ): it’s hard to discern this from the wind vectors (which are presumably anomalies anyway so not clear how the real wind field looks).
We appreciate this comment. We have revised the discussion to make clear that the barrier wind corner jet mechanism is inferred from the broader circulation context and local geography, rather than directly resolved in the wind-vector fields alone. We also emphasize that the available resolution limits the explicit representation of this feature
- L248-249 Not sure what is meant by this localized analysis? Do you mean that the BWCJ doesn’t appear when you look at local wind vectors?
We have clarified this point in the revised manuscript. The local wind vectors are derived from ERA5 10 m u and v components averaged over the day, whereas the “MaxWinds” metric captures the daily maximum wind speed. Because the daily-mean wind vectors smooth short-lived variability, they may not fully represent a barrier wind structure, although they do reproduce the broader patterns associated with Modes 1 and 2. We have revised the text to make this distinction explicit.
- Figure 4: please explain what the hatching/stippling denotes. Also, because the regressions are computed from daily ASO data concatenated across years, the underlying time series are serially correlated and the nominal sample size will overstate the effective degrees of freedom. Please clarify how the p-values were calculated (e.g., using an effective sample size adjustment). If no autocorrelation treatment was applied, please revisit the significance masking accordingly.
Response:
We thank the reviewer for this important comment regarding the statistical significance assessment. In the revised manuscript, we have clarified that the hatching/stippling in Figure 4 denotes regions exceeding the chosen statistical significance threshold for the regression analysis.
We agree that the use of daily ASO data may introduce serial autocorrelation, which can reduce the effective degrees of freedom and potentially lead to overestimation of nominal significance levels when using standard statistical tests. The original analysis did not explicitly apply an effective sample size correction for temporal autocorrelation. We have therefore revised the manuscript text to clarify this limitation and moderated the interpretation of statistically significant regions accordingly.
In addition, we have updated the figure caption and associated discussion to emphasize that the stippling should be interpreted as indicative of robust spatial associations rather than strict pointwise significance under fully independent sampling assumptions.
- L268–271: ‘weak ExWin anomalies’ indicates winds close to the seasonal mean, not necessarily weak absolute winds. I suggest avoiding interpreting near-zero anomalies as ‘subdued in speed’ unless you show composites of absolute ExWin. Unless you mean negative anomalies?
We agree and have revised the wording to refer to near-zero wind anomalies rather than implying weak absolute winds. The text has been adjusted accordingly to avoid ambiguity.
- L283: Perhaps avoid using Cape Colbeck as it’s not a widely known geographic marker.
We appreciate the suggestion. We have revised the wording to use a clearer geographic reference that will be more familiar to readers.
- L287: The figures are not really sufficient to interpret the BWCJ
We thank the reviewer for this important observation, we do agree that the present figures do not directly diagnose the Barrier Wind Convergence Jet (BWCJ) structure or intensity. Our intention was to describe circulation anomalies that are spatially consistent with variability in the BWCJ region, rather than to claim a direct observation or explicit dynamical characterization of the jet itself. To avoid overinterpretation, we have revised the relevant text throughout the manuscript to more carefully describe these features as circulation patterns associated with the BWCJ sector.
- L300 This paragraph’s wording (‘dominated by a small set’) conflicts with the earlier acknowledgement that EOF1-3 leave 63% of SIC variance unexplained. I may have misunderstood so please qualify what is meant by ‘dominated’ or soften the claim.
We agree that the term ‘dominated’ may overstate the variance explained by the leading EOF/MCA modes, given that EOF1–3 account for approximately 37% of the SIC variability. We have therefore revised the text to soften the interpretation and clarify that these modes represent the leading coherent patterns associated with Ross Sea polynya variability rather than the entirety of the variability
- L304: please explain somewhere the use of ‘accumulation’ in this paper and how you observe it?
We thank the reviewer for this helpful suggestion. We have now moved the detailed discussion of study limitations from the Conclusions to the Discussion section in order to keep the Conclusions more concise and focused on the primary findings and implications of the study.
We also clarified the use of the term ‘accumulation’ throughout the manuscript. Specifically, we now define accumulation as regions of relatively enhanced SIC interpreted as sea-ice convergence or retention within a coastal sector associated with circulation-driven advection and compaction, rather than a direct observation of ice mass increase or thickness
- I suggest moving discussion of limitations to the Discussion section and keeping the conclusion concise.
We appreciate the reviewer’s suggestion. In the revised manuscript, discussion related to study limitations and interpretational constraints has been moved to the Discussion section, while the Conclusion section has been streamlined to focus primarily on the main findings and broader implications of the study.
- References section: I see many references listed which don’t appear in the text. I also see e.g. ‘n.d.’ for dated papers and typos e.g. “Academic Press.sss” and the Turner et al. citation.
We thank the reviewer for carefully checking the reference list. The references section has been thoroughly revised to remove unused citations, correct formatting inconsistencies, update missing publication information, and fix typographical errors including those noted by the reviewer.
Technical corrections
- L29 double comma - We thank the reviewer for carefully identifying this typographical error. The double comma has been corrected in the revised manuscript.
- L198/L199 ExWin? Or ExWinds? See other references to it as well. - The terminology has now been revised and standardized to “MaxWinds” throughout the manuscript for clarity and consistency.
- L208 WinVec? Thanks for this suggestion. “WinVec” has been replaced with “wind vectors” in the revised manuscript for improved readability.
- L246 periods - The punctuation has been corrected as suggested.
- L311 erroneous full stop – The erroneous full stop has been removed.
- Consistency of eg. Localised, localized… - The terminology has now been standardized to “localised” throughout the manuscript.
- L635 typo –The correction has been made in the revised manuscript.
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AC1: 'Reply on RC1', Girija Kalyani Burada, 18 May 2026
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CC1: 'Comment on egusphere-2025-5369', Lavkush Patel, 11 Mar 2026
General Assessment:
The manuscript is well-organized, clearly written, and scientifically sound. The methodology is rigorous, combining long-term statistical analyses with process-aware interpretation. The use of high-resolution SIC data is particularly valuable, as it resolves frazil and young-floe bands critical for polynya dynamics. The study contributes significantly to understanding atmosphere–sea ice interactions in the Ross Sea, providing a valuable multi-decadal context.Major Comments:
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Scientific Contribution:
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The manuscript effectively bridges the temporal-resolution divide in polynya studies, combining multi-decadal datasets with event-scale extreme wind analyses.
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Linking upper-level circulation (H500 anomalies) to local extreme winds and SIC variability is a notable strength, allowing attribution of polynya responses to specific atmospheric regimes.
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The EOF and MCA analyses are appropriate, and the interpretation is consistent with previous process studies.
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Methodology:
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Data preprocessing, anomaly calculation, and standardization are described clearly. Area-weighting by √cosφ is appropriate for high-latitude grids.
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Use of daily maximum wind (ExWinds) is justified, but discussion of sensitivity to hourly vs. daily maxima could enhance robustness.
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MCA is correctly applied; the squared covariance fraction (SCF) provides clear information about coupled variability.
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Validation against Sentinel-1 SAR and ARTIST datasets is briefly mentioned. Including representative examples or quantitative metrics in supplementary materials would strengthen confidence in SIC retrievals.
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Results:
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The identification of three dominant EOF modes and corresponding MCA modes is convincing. EOF1 captures coherent variability across all polynyas, while EOF2 and EOF3 reveal dipole and east–west patterns.
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The study successfully links MCA modes to physical processes: Mode 1 (RAS-driven offshore advection), Mode 2 (weak/anticyclonic winds affecting ice redistribution), and Mode 3 (BWCJ-induced lateral transport).
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Temporal trends, particularly post-2016 SIC reduction in EOF1, are clearly documented and plausibly connected to large-scale Antarctic-wide sea-ice decline.
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Discussion and Context:
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The manuscript contextualizes findings with previous work on ASL modulation, katabatic flows, and oceanic preconditioning.
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The discussion of dynamic vs. thermodynamic contributions is thoughtful and consistent with targeted field observations.
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Limitations are acknowledged, particularly regarding temporal gaps in high-resolution datasets and event-scale variability.
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Minor Comments / Suggestions:
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Ensure all acronyms (ExWinds, RAS, BWCJ) are clearly defined on first use in the main text.
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Figures: It would be helpful to provide a small schematic summarizing the circulation regimes associated with each MCA mode.
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Consider discussing the potential implications for coupled climate model evaluation or future predictions of Ross Sea polynya activity.
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Check minor typographical errors (e.g., “∼ 1500 W” likely should be “∼150° W”).
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References to figures in supplementary materials (e.g., Figure S1, S2, S3) should explicitly note whether they are available online or included in the submission package.
Citation: https://doi.org/10.5194/egusphere-2025-5369-CC1 -
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RC2: 'Comment on egusphere-2025-5369', Anonymous Referee #2, 21 Apr 2026
Summary
In this study, the authors analyze the local- and large-scale controls on the presence of polynyas in the Ross Sea sector of Antarctica. They use EOF analysis to identify recurring spatial patterns of sea ice variability, then perform two sets of maximum covariance analysis to link spatial patterns of (a) extreme winds and sea ice variability, and (b) 500-hPa heights and extreme winds. They find that SIC in the region's three major polynyas most often varies in sync with one another, but less frequently, SIC anomalies in the three polynyas are of different sign. These dominant modes of SIC variability are driven by variable patterns of large-scale circulation and local-scale extreme winds, and a notable finding is that the three polynyas can respond differently to the same 500-hPa height anomaly pattern.
In my assessment, the methods and scientific merit of the paper are sound. It provides some novel insight into the atmospheric contribution to polynya variability in the Ross Sea region. However, I feel there is still work to be done in connecting the study objectives to the results and in cleaning up various other aspects of the paper, as detailed in my comments below.
Major comments
- In general, I feel that something is missing in providing the detailed process understanding promised in the introduction – i.e. mechanistic, process-aware interpretation of the interactions between large-scale flow, local-scale extreme winds, and detailed sea ice processes within the polynyas – compared with what is actually found in the results. Reading lines 63–70, I'm satisfied that gap (i) in the existing literature has been addressed by this study, but what about (ii) and (iii)? Are the "process zones" (frazil/accumulation/young floe) described in (ii) actually resolved in this study's results? Can the authors clearly point them out in the figures if so? Likewise, can melting vs inhibited freeze-up (iii) processes actually be seen in the figures? I realize this is a somewhat vague comment, but I would like to see a more conclusive and explicit connection between what can be seen in the figures and the study objectives described in the introduction.
- A set of overview maps at the beginning of the Results section would be helpful to orient the reader. I realize the location of the study domain in Antarctica can be seen in Fig. 4, but as it stands, the results jump straight into a zoomed view of the Ross Sea sector of Antarctica without any spatial context. A map of the region's topography would also make the results more interpretable, given that topographic modification of the air flow is emphasized in reporting the study results (e.g. L281–289). I suggest a large-scale map showing the location of the Ross Sea sector within Antarctica, and a more zoomed-in map that shows the topography of the study region.
- ~L632: Why is this conceptual diagram included in the manuscript PDF? It is not assigned a figure number and does not appear to be discussed anywhere in the text.
Minor comments
- The abstract would be more impactful if it included more details and specific results in the second paragraph. For example, there are details of the study findings in L370–382 that could be summarized with more specifics in the abstract.
- L35: I think "satellite imagery" would be more accurate to use rather than "satellite soundings" here. Although passive microwave satellite instruments are capable of both "imagery" and "sounding" products, I think "imagery" is typically the term used when referring to a 2D retrieved field such as sea ice concentration, while "soundings" is reserved for retrievals of vertical profile variables (such as temperature and moisture profiles). See e.g. Rouzegari et al. (2025).
- L87–99: This paragraph provides a convincing justification for why late austral winter through early spring (ASO) was chosen as the time period of analysis for this study. However, the primary motivation for the study as whole given in the Introduction is the role of Ross Sea polynyas in air-sea heat exchange and shelf water / deep water formation. Is ASO a critical part of the year for these globally relevant processes? Some effort should be made to connect the time period chosen in the study to its background and motivation.
- L105–106: What are the properties of the grid on which the SIC data are provided (the "SIC grid")? Is this an equal-area polar stereographic grid (such as the NSIDC EASE grid?)
- L112–113: I am confused as to why the area-weighting by the square of latitude is necessary for the SIC fields. Per my comment above, I assume that the SIC data are provided on an equal-area grid?
- L160–162: This sentence appears to state that 3.125 km sea ice products were used in this study for validation and for illustrating process detail. However, I don't see anywhere in the text, figures, or Supplement where the higher-resolution product is compared to the 6.25 km product used in this study. I do think that some comparison of the 6.25 km data to the 3.125 km product would be convincing to prove that it is sufficient for process-aware interpretation and has sufficient spatial resolution to resolve the active frazil/young=flow bands, as stated in L80–84. This appears to be the intention of Figure S1 in the Supplement, although this figure is difficult to interpret.
- L171–172: How and why was a value of 12% SIC SD chosen to represent the spatial extent of polynya domains for subsequent analyses? Also, it doesn't appear that these domain definitions are actually used in any subsequent analyses, other than to outline these areas in the map panels on the left side of Figure 2?
Technical corrections
- L24–26: I suggest breaking this into two separate sentences rather than joining two sentences with a semicolon. Please check for run-on sentences elsewhere (e.g. L35–38, L80–84).
- L28: "polynya" --> "polynyas"?
- L28: "is strongly modulated" - what is strongly modulated? The polynyas in the Ross Sea sector?
- L51–52: I suggest moving this sentence to be the topic sentence of the next paragraph
- L73: Insert the word "and" before "(b)"
- L87: "operate" --> "occur"?
- L188–189: "Within the SD boundary, east-west split in RS region" – what does this mean?
- L191: "PCs associated 3" – what does this mean?
- L248: "analysis of MCA analysis" – the word "analysis" is used twice redundantly here
References
- Rouzegari, N., Bolboli Zadeh, M., Jimenez Arellano, C., Afzali Gorooh, V., Nguyen, P., Meng, H., Ferraro, R. R., Kalluri, S., Sorooshian, S., & Hsu, K. (2025). Passive Microwave Imagers, Their Applications, and Benefits: A Review. Remote Sensing, 17(9), 1654. https://doi.org/10.3390/rs17091654
Citation: https://doi.org/10.5194/egusphere-2025-5369-RC2 -
AC2: 'Reply on RC2', Girija Kalyani Burada, 18 May 2026
- In general, I feel that something is missing in providing the detailed process understanding promised in the introduction – i.e. mechanistic, process-aware interpretation of the interactions between large-scale flow, local-scale extreme winds, and detailed sea ice processes within the polynyas – compared with what is actually found in the results. Reading lines 63–70, I'm satisfied that gap (i) in the existing literature has been addressed by this study, but what about (ii) and (iii)? Are the "process zones" (frazil/accumulation/young floe) described in (ii) actually resolved in this study's results? Can the authors clearly point them out in the figures if so? Likewise, can melting vs inhibited freeze-up (iii) processes actually be seen in the figures?
I realize this is a somewhat vague comment, but I would like to see a more conclusive and explicit connection between what can be seen in the figures and the study objectives described in the introduction.
Response:
We thank the reviewer for raising an important point regarding the level of process-based interpretation in relation to the study objectives. We acknowledge that this study does not use field observations to explicitly resolve or validate polynya process zones (e.g., frazil, accumulation, young floe). In the revised manuscript, we have clarified that our analysis is based solely on satellite derived SIC and atmospheric fields, and that the identified spatial patterns are interpreted as being consistent with known process regimes described in previous observational studies, rather than directly resolving them.
We have revised the Introduction to remove the implication of direct linkage to field observations and have ensured that the Results section more explicitly connects the observed SIC patterns to physically plausible process interpretations, while avoiding overstatement. We also clarify that processes such as melting versus inhibited freeze-up cannot be unambiguously distinguished from SIC alone. [This is a good response Girija. I think that toning down the promised results in the Abstract etc is crucial, and pointing out the data and what we see vs what we infer is also a good move.]
- A set of overview maps at the beginning of the Results section would be helpful to orient the reader. I realize the location of the study domain in Antarctica can be seen in Fig. 4, but as it stands, the results jump straight into a zoomed view of the Ross Sea sector of Antarctica without any spatial context. A map of the region's topography would also make the results more interpretable, given that topographic modification of the air flow is emphasized in reporting the study results (e.g. L281–289). I suggest a large-scale map showing the location of the Ross Sea sector within Antarctica, and a more zoomed-in map that shows the topography of the study region.
Response: We thank the reviewer for this helpful suggestion. In the revised manuscript, we have incorporated the requested spatial context into the first figure of the Results section. Specifically, this figure (Figure 1) now includes (i) a large-scale map showing the location of the Ross Sea sector within Antarctica, and (ii) a zoomed-in view of the study region with underlying topography. This addition is intended to better orient the reader and provide clearer context for the role of topographic influences discussed in the Results section.
- ~L632: Why is this conceptual diagram included in the manuscript PDF? It is not assigned a figure number and does not appear to be discussed anywhere in the text.
Response: The conceptual diagram was included solely to provide a simplified visual overview of the overall idea and physical framework of the study. It is not intended to be part of the main set of figures or the core results of the manuscript. We acknowledge that its placement in the current version may cause confusion; in the revised manuscript, we will either move it to supplementary material or remove it to maintain clarity and consistency.
Minor comments
- The abstract would be more impactful if it included more details and specific results in the second paragraph. For example, there are details of the study findings in L370–382 that could be summarized with more specifics in the abstract.
Response:
Thank you for this suggestion. We agree that the original abstract was a bit too general i. In response, we have revised the second paragraph of the abstract to include more specific details from the main findings presented in Lines 370–382. The revised abstract now more clearly summarizes the dominant spatial and temporal characteristics of the polynya variability, the associated atmospheric circulation patterns, and the identified links with large-scale climate drivers. We believe these additions improve the clarity and overall impact of the abstract by better reflecting the major outcomes and significance of the study.
- L35: I think "satellite imagery" would be more accurate to use rather than "satellite soundings" here. Although passive microwave satellite instruments are capable of both "imagery" and "sounding" products, I think "imagery" is typically the term used when referring to a 2D retrieved field such as sea ice concentration, while "soundings" is reserved for retrievals of vertical profile variables (such as temperature and moisture profiles). See e.g. Rouzegari et al. (2025).
Response: Modified as suggested in revised document (L36)
- L87–99: This paragraph provides a convincing justification for why late austral winter through early spring (ASO) was chosen as the time period of analysis for this study. However, the primary motivation for the study as whole given in the Introduction is the role of Ross Sea polynyas in air-sea heat exchange and shelf water / deep water formation. Is ASO a critical part of the year for these globally relevant processes? Some effort should be made to connect the time period chosen in the study to its background and motivation.
Response: In the revised manuscript, we have expanded this paragraph to explicitly highlight that ASO coincides with the period of peak sea-ice production in coastal polynyas, when enhanced brine rejection contributes to the formation of High-Salinity Shelf Water, a precursor to Antarctic Bottom Water. We now clarify that variability in polynya activity during ASO directly influences air–sea heat exchange and dense water formation, thereby linking the selected season to the primary motivation of the study.
- L105–106: What are the properties of the grid on which the SIC data are provided (the "SIC grid")? Is this an equal-area polar stereographic grid (such as the NSIDC EASE grid?)
Response:
For the AMSR-E/AMSR2 6.25 km SIC product, the grid is not an equal-area grid like the NSIDC EASE grid. Instead, the SIC data are provided on a polar stereographic projection grid, centered on the pole (separate grids for Arctic and Antarctic). The grid spacing of SIC data used in this work is 6.25 km, defined at a standard latitude (typically 70°), is regular in projected x–y space (i.e., evenly spaced in the projection plane), not in true surface area. As a result, grid cell areas are not constant and vary slightly with latitude (distortion increases away from the standard latitude). Therefore, this grid is not strictly equal-area, unlike the NSIDC EASE/EASE2 grids, which are specifically designed to preserve area. [Do we need to say any of this in the manuscript? Seems like a minor point to me.]
- L112–113: I am confused as to why the area-weighting by the square of latitude is necessary for the SIC fields. Per my comment above, I assume that the SIC data are provided on an equal-area grid?
Response: Although the SIC fields are provided on a near-equal-area grid, weighting was applied for consistency with the atmospheric fields used in the coupled analysis.
- L160–162: This sentence appears to state that 3.125 km sea ice products were used in this study for validation and for illustrating process detail. However, I don't see anywhere in the text, figures, or Supplement where the higher-resolution product is compared to the 6.25 km product used in this study. I do think that some comparison of the 6.25 km data to the 3.125 km product would be convincing to prove that it is sufficient for process-aware interpretation and has sufficient spatial resolution to resolve the active frazil/young=flow bands, as stated in L80–84. This appears to be the intention of Figure S1 in the Supplement, although this figure is difficult to interpret.
Response: Thank you for this insightful comment. We have now added an additional comparison figure (Figure S4) to provide a clearer evaluation of the 6.25 km and 3.125 km SIC products during a polynya event. The intention of including the 3.125 km product was to demonstrate that the 6.25 km AMSR-E/2 SIC dataset used in the primary analysis adequately resolves the major spatial characteristics of the thin-ice regions and associated polynya structures.
The 6.25 km SIC product was selected because it provides sufficient spatial detail to capture the major Ross Sea polynya regions while maintaining computational efficiency and reducing small-scale noise within the EOF/MCA framework. As the focus of this study is on large-scale SIC variability and its coupling with atmospheric circulation, rather than fine-scale lead morphology or instantaneous polynya edge detection, the 6.25 km resolution is appropriate for identifying the dominant spatial and temporal variability patterns. Similar-resolution passive microwave SIC products have also been widely used in Antarctic polynya and climate-scale studies.
We agree that the purpose of this comparison was not sufficiently clear in the original manuscript, and that the earlier Supplementary Figure S1 was difficult to interpret. In response, we have revised the manuscript and Supplement to clarify the role of the 3.125 km product and improve the associated discussion. The revised Figure S4 now presents a direct qualitative comparison between the two SIC products. The updated discussion shows that, although the 3.125 km product captures finer-scale edge variability and sharper gradients, the 6.25 km product consistently reproduces the overall spatial organization, orientation, and evolution of the active thin-ice and polynya regions. This demonstrates that the 6.25 km product is sufficient for the process-aware interpretation and large-scale circulation analysis conducted in this study. The figure caption and accompanying text have also been revised to improve clarity and readability.
- L171–172: How and why was a value of 12% SIC SD chosen to represent the spatial extent of polynya domains for subsequent analyses? Also, it doesn't appear that these domain definitions are actually used in any subsequent analyses, other than to outline these areas in the map panels on the left side of Figure 2?
Response:
The 12% SIC standard deviation threshold was chosen empirically to delineate regions of persistently enhanced sea-ice variability associated with recurrent polynya activity. We tested a range of threshold values and found that 12% provides the most physically consistent representation of the active polynya zones, while avoiding excessive spatial expansion into the surrounding compact pack ice. Lower thresholds tended to include broad areas of seasonally mobile ice with weaker variability signals, whereas higher thresholds fragmented the coastal polynya regions and excluded known recurrent activity areas.
We agree that the original manuscript did not clearly justify this choice or its role in the analysis. The threshold-defined domains are intended primarily as a visual and interpretative aid to consistently highlight the principal regions of recurrent coastal polynya activity in Figures 1 and 2, rather than as strict masks used in subsequent quantitative calculations. To avoid ambiguity, we have revised the manuscript to explicitly clarify this interpretative purpose and to remove any implication that these domains were directly used in later statistical analyses.
Technical corrections
- L24–26: I suggest breaking this into two separate sentences rather than joining two sentences with a semicolon. Please check for run-on sentences elsewhere (e.g. L35–38, L80–84).
Response: We agree that the sentence was overly long and revised it for clarity by splitting it into two separate sentences. We have also reviewed the manuscript for similar run-on sentences and made additional edits where necessary to improve readability
- L28: "polynya" --> "polynyas"?
Response: Modified
- L28: "is strongly modulated" - what is strongly modulated? The polynyas in the Ross Sea sector?
Response: Thank you for pointing out this ambiguity. We agree that the phrase “is strongly modulated” was unclear in its reference. We have revised the sentence to explicitly specify that the modulation refers to sea-ice variability, improving clarity and readability.
- L51–52: I suggest moving this sentence to be the topic sentence of the next paragraph
Response: Moved the sentence to the beginning of next paragraph as suggested.
- L73: Insert the word "and" before "(b)"
Response: Modified as suggested in L73
- L87: "operate" --> "occur"?
Response: Thank you for this suggestion, modified in L87
- L188–189: "Within the SD boundary, east-west split in RS region" – what does this mean?
Response: Thank you for pointing this out. We agree that the phrase “east–west split” was unclear. We have revised the sentence to explicitly describe this feature as an east–west contrast (dipole) in sea-ice concentration across the Ross Sea region, improving clarity and interpretability
- L191: "PCs associated 3" – what does this mean?
Response: This is a typo, modified to PCs associated with Mode 3.
- L248: "analysis of MCA analysis" – the word "analysis" is used twice redundantly here
Response: Thank you for identifying this. Redundant word ‘analysis’ is deleted. The sentence now reads as “It is also worth noting, that in our localised analysis of MCA with wind vectors and MaxWinds (not shown).”
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General comments
This paper examines the relationship between satellite-observed sea ice and large-scale wind patterns using an EOF analysis and ERA5. The paper is well placed within the broader field and the discussion of the role of short-term variability in the context of longer-term changes is sound. The insight that different polynyas respond differently to similar large-scale anomalies is valuable. The methodology is useful for understanding distinct modes of SIC variability in polynya regions and their association with large-scale wind patterns. I feel that quite a bit more work is needed to physically interpret the results robustly, i.e. link EOFs and MCA back to physical processes. See below:
Specific comments
Technical corrections