Brief Communication: Retrieval-Driven Spread in Antarctic Winter Freeboards (CryoSat-2, 2013&ndash;2018)

Liu, Xinlong; Corney, Stuart Paul; Tilling, Rachel Louise; Heil, Petra

doi:10.5194/egusphere-2026-662

Preprints

https://doi.org/10.5194/egusphere-2026-662

Preprints

12 Feb 2026

| 12 Feb 2026

Brief Communication: Retrieval-Driven Spread in Antarctic Winter Freeboards (CryoSat-2, 2013–2018)

Xinlong Liu, Stuart Paul Corney, Rachel Louise Tilling, and Petra Heil

Abstract. The accuracy of remotely-sensed Antarctic sea-ice thickness is limited by assumptions of snow properties and processing choices that are often informed from the Arctic. To quantify retrieval-driven spread, we compare winter radar freeboard and snow-corrected sea-ice freeboard from four CryoSat-2–era products for 2013–2018. All products reproduce the large-scale spatial structure, yet each shows systematic offsets relative to CCI that persist across multiple spatial scales. Both the Western Weddell and Ross Sea sectors display interannual variability, while correlation, bias and RMSE exhibit sector- and variable dependent performance relevant to thickness.

Received: 04 Feb 2026 – Discussion started: 12 Feb 2026

Competing interests: At least one of the (co-)authors is a member of the editorial board of The Cryosphere.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.

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Xinlong Liu, Stuart Paul Corney, Rachel Louise Tilling, and Petra Heil

Status: final response (author comments only)

RC1:
'Comment on egusphere-2026-662', Anonymous Referee #1, 01 Apr 2026
A well-written manuscript with clear purpose and description as a ‘compact comparison benchmark’ captures the scope well. However, a lack of specifics on the retrieval methods limits the accessibility of key points in the manuscript.

Additionally, is there a reason why all sectors are not included in the main paper making a longer paper? More clarification should be given as to why these two sectors (Western Weddell and Ross) are chosen. This may result in a stronger regular length paper than the current brief communication which is too short on detail, to fully explore the difference between the products.
We have provided details comments below.
Abstract
Line 5 CCI should be defined

Numerical quantification could be included

Introduction
Line 11 change word 'space' to satellites or remote sensing more precisely

Line 11 specify deep as relative to the Arctic or provide a number e.g. X in the Antarctic vs Y in the Arctic.

Additionally Willatt 2025 (already referenced later) could be referenced here regarding the heterogeneity and second year snow in the Weddell Sea.

Consider phrasing of altimeter retrieval sensitivity relative to Arctic - whilst it has often been assumed that the radar will penetrate through cold, dry snow on Arctic sea ice and scatter from the snow-ice interface, providing basis for original parameterisations as pointed out, not all recent studies support this (e.g. Nab et al., 2023; 2024, King et al., 2018, Willatt et al., 2023; 2011).

Line 13 should be Willatt et al., 2010 (not 2009), and Giles 2008 should be included.

Line 21 explain what the retrievals are based on (to later aid interpretation at line 77 of results).

Data and Methods
Why does it begin in 2013 rather than 2010 for the Cryosat common era?

Line 31-32 define LEGOS/CTOH as all other abbreviated products are defined in full here.

Line 36 'To maintain a concise and reproducible intercomparison, we analyse the freeboard fields as distributed by each provider' please explain why this is more precise and reproducible exactly, with further detail.

Lines 38-40 what else differs between the products e.g. atmospheric corrections, retracking, that would not be snow related? Could it just be called a correction rather than snow-related correction? E.g. you mention 'associated processing choices', what are those choices and are they all related to the snow?

Was there a reason the CCI grid is chosen as the practical reference / the one to compare relative to? And why bilinear interpolation? Please expand more.

Line 59 opening parenthesis missing to parenthesis used after Supplement.

Line 58-59, was there a reason these two sectors were chosen? Noted as contrasting but in what sense? Please explain how you decided on these two regions, whether it was based on the study data or assumptions made prior to conducting the study.

Results
Figure 1 should have the sectors labelled as referred to throughout the text.

Figure 1 (or another figure) should show the original products themselves before differences to CCI.

Figure 1 small l on LEGOS.

Figure 2 explain panels a-d in the caption.

Figures 2 and 3 text too small and text cut off on LHS of Figure 3.

Figure 3, over what time period? Is it monthly data over full 2013-2018 period? How many data points are there? Include in caption or text.

Line 74 and 75, move (Figure 1) to end of sentence and replace : with ;

Line 77 see comment re line 21 to make this result clear.

Line 88 please define freeboards as used in rest of paper, i.e. is the high-freeboard regime, radar or ice freeboard?

Line 94 'The' missing before Western Weddell.

Discussion
Extra full stop after the word Figures is not needed (only needed if abbreviating to Fig.) e.g. line 120.

Line 123 please clarify why this can only be attributed to the snow propagation-speed correction.

Conclusion
Point 1 - referring back to our recommendation to show the actual products before comparison to CCI in Figure 1, this would show the large-scale structure that you highlight here.

Point 3 is nicely made.

In final sentence please describe other sources of uncertainty e.g. retracking. Please also mention the importance and status of in-situ comparisons (given the scope you outline in the final sentence of the discussion).
Citation: https://doi.org/10.5194/egusphere-2026-662-RC1
- AC2:
  'Reply on RC1', Xinlong Liu, 09 May 2026
  Response to Reviewer 1
  Manuscript egusphere–2026–662
  “Antarctic Sea-Ice Freeboard from Envisat and CryoSat-2: Attributing Inter-Product Spread to Snow Assumptions and Radar-Retrieval Baselines”
  Xinlong Liu, Rachel L. Tilling, Stuart P. Corney, Alexander D. Fraser, Petra Heil
  May 9, 2026
  
  Dear Reviewer 1,
  We thank you for your thorough and constructive review of our manuscript. Your comments have substantially shaped the revised Research Article, which now addresses each of the substantive points you raised. Your central recommendation, that the manuscript be expanded into a stronger regular-length paper rather than retained as a Brief Communication, has been adopted, and the editor has confirmed that the journal will reclassify the submission accordingly. Below we respond to each comment in turn, with each comment quoted verbatim in italics and our response provided beneath it in upright text.
  
  1 General Comment on Manuscript Structure and Sector Selection
  A well-written manuscript with clear purpose and description as a ‘compact comparison benchmark’ captures the scope well. However, a lack of specifics on the retrieval methods limits the accessibility of key points in the manuscript. Additionally, is there a reason why all sectors are not included in the main paper making a longer paper? More clarification should be given as to why these two sectors (Western Weddell Sea and Ross Sea) are chosen. This may result in a stronger regular length paper than the current brief communication which is too short on detail, to fully explore the difference between the products.
  We agree that a regular-length paper provides the appropriate framework for the analytical depth required, and we have restructured the manuscript accordingly. The revised Research Article now presents results for all six circumpolar Antarctic sectors in the main body (Western Weddell Sea, Eastern Weddell Sea, Indian Ocean, Pacific Ocean, Ross Sea, and Amundsen–Bellingshausen Sea), with three deep-dive sectors (Western Weddell Sea, Indian Ocean, and, Ross Sea) retained for time-series and scatter analysis on a priori physical grounds. The Western Weddell Sea is selected for its thick, multi-year ice regime with the largest snow loads in the Antarctic; the Indian Ocean sector for its thinner ice and intermediate snow conditions, providing a contrast to the Weddell regime; and the Ross Sea for its polynya-influenced thin-ice regime where non-snow retrieval differences are expected to dominate. This sector selection is motivated explicitly in the second last paragraph starting with “To capture the full range of Antarctic sea-ice regimes, this study highlights three contrasting sectors selected a priori on physical grounds." of Section 1. Introduction of the revised manuscript, with the physical contrast among the three regimes used to interpret the harmonisation experiment results in Section 4.1 What Snow Harmonisation Can and Cannot Fix.
  
  The retrieval-method specifics have been substantially expanded in Section 2.3 Freeboard Variables and Snow Propagation-Speed Correction, where each of the four product families is described in a dedicated paragraph covering the retracker, lead-detection method, seasurface-anomaly retrieval, snow-thickness source, snow-density parameterisation, and wave-speed correction implementation. A detailed product-characteristics table is provided in Appendix B: Detailed Characteristics of the Four Antarctic Sea-Ice Freeboard Products, supporting the methodological transparency that the snow-harmonisation experiments require.
  
  2 Abstract
  Line 5: CCI should be defined.
  CCI is now defined at first use in the revised Abstract as “ESA Climate Change Initiative (CCI)”.
  
  Numerical quantification could be included.
  The revised Abstract now includes specific numerical findings, including the winter-mean inter-product sea-ice-freeboard spread magnitudes (approximately 0.10 m in the Western Weddell Sea and 0.04–0.05 m in the Ross Sea and Indian Ocean sectors), the snow-attribution percentages (66–100% for the snow propagation-speed correction, 7–21% for sea-ice freeboard with 95% bootstrap confidence intervals), and the residual non-snow attribution (78–93%).
  
  3 Introduction
  Line 11: change word ‘space’ to satellites or remote sensing more precisely.
  The wording has been changed to “satellite remote sensing” throughout the Introduction.
  
  Line 11: specify deep as relative to the Arctic or provide a number e.g. X in the Antarctic vs Y in the Arctic. Additionally Willatt 2025 (already referenced later) could be referenced here regarding the heterogeneity and second year snow in the Weddell Sea.
  The Introduction now provides explicit numerical comparison: typical Antarctic snow depths of 0.1–0.5 m or more, compared with 0.05–0.30 m in the Arctic, with citations to Massom et al. (2001), Webster et al. (2018), and Willatt et al. (2025) for the Antarctic range and to standard Arctic references for the comparison. The Willatt et al. (2025) reference has been added at this earlier point in the manuscript to support the heterogeneity and second-year snow characterisation in the Weddell Sea.
  
  Consider phrasing of altimeter retrieval sensitivity relative to Arctic — whilst it has often been assumed that the radar will penetrate through cold, dry snow on Arctic sea ice and scatter from the snow–ice interface, providing basis for original parameterisations as pointed out, not all recent studies support this (e.g. Nab et al., 2023; 2024, King et al., 2018, Willatt et al., 2023; 2011).
  The Introduction has been revised to acknowledge the recent literature questioning the snow–ice interface scattering assumption. We now cite Willatt et al. (2011), King et al. (2018), Nab et al. (2023), Willatt et al. (2023), and Nab et al. (2024) in support of the more nuanced statement that the dominant scattering surface in radar altimetry of snow-covered sea ice remains an active research question, and that this uncertainty propagates differently into Antarctic versus Arctic retrievals.
  
  Line 13: should be Willatt et al., 2010 (not 2009), and Giles 2008 should be included.
  The Willatt reference has been corrected to Willatt et al. (2010), and Giles et al. (2008) has been added at this location.
  
  Line 21: explain what the retrievals are based on (to later aid interpretation at line 77 of results).
  The Section 2.3 Freeboard Variables and Snow Propagation-Speed Correction now describes explicitly that the four product families are based on combinations of TFMRA-family retrackers (LEGOS, CCI, CSAO with TFMRA50; CryoTEMPO with SAMOSA+ in the Baseline-D processing) applied to CryoSat-2 SAR-mode echoes, paired with snow inputs derived from passive-microwave climatologies (CCI, Cryo-TEMPO) or from altimetric methods (LEGOS II’s SARAL/CryoSat-2 dual-frequency approach). This methodological foundation is referenced again in the Results and Discussion sections when interpreting the harmonisation outcomes.
  
  4 Data and Methods
  Why does it begin in 2013 rather than 2010 for the CryoSat common era?
  The CryoSat-2 common analysis period begins in 2013 because LEGOS II requires SARAL/AltiKa data for its dual-frequency snow retrieval, and SARAL was launched in February 2013. Restricting the common analysis to 2013 onward ensures that all five CryoSat-2-era product variants (LEGOS I, LEGOS II, CCI, CSAO, and Cryo-TEMPO) are available for direct comparison on a consistent basis. This rationale is now stated explicitly in Section 2.2 Common Grid, Masks, Sectors, and Winter Averaging of the revised manuscript.
  
  Line 31–32: define LEGOS/CTOH as all other abbreviated products are defined in full here.
  LEGOS/CTOH is now defined in full at first use as “Laboratoire d’Études en Géophysique et Océanographie Spatiales / Centre de Topographie des Océans et de l’Hydrosphère (LEGOS/CTOH).”
  
  Line 36: “To maintain a concise and reproducible intercomparison, we analyse the freeboard fields as distributed by each provider” please explain why this is more precise and reproducible exactly, with further detail.
  The Section 2. Methods now explains that analysing the freeboard fields as distributed by each provider preserves each product’s complete processing chain, including the retracker, lead-detection algorithm, sea-surface-anomaly retrieval, geophysical corrections, and gridding conventions. This approach allows the inter-product comparison to reflect genuine choices made by each processing team rather than ad hoc reprocessing by us. The reproducibility advantage is that any reader with access to the publicly distributed product files can reproduce our comparisons without requiring access to internal processing code or intermediate data products.
  
  Lines 38–40: what else differs between the products e.g. atmospheric corrections, retracking, that would not be snow related? Could it just be called a correction rather than snow-related correction? E.g. you mention ‘associated processing choices’, what are those choices and are they all related to the snow?
  We agree that the original wording was insufficiently precise. The revised manuscript now distinguishes explicitly between snow-related processing choices (snow-thickness source, snow-density parameterisation, wave-speed correction implementation) and non-snow processing choices (retracker selection, lead-detection method, sea-surface-anomaly retrieval, geophysical corrections, gridding conventions). Section 2.4 Snow Harmonisation Experiments isolate the snow-related contribution to inter-product divergence by holding snow inputs fixed across products, leaving the residual spread attributable to non-snow choices. This distinction is central to the revised manuscript’s analytical framework.
  
  Was there a reason the CCI grid is chosen as the practical reference / the one to compare relative to? And why bilinear interpolation? Please expand more.
  The CCI grid (50 km EASE-Grid 2.0, polar stereographic projection) is selected as the common reference grid because it is the only one of the four product families that distributes a native gridded freeboard product on a regular Antarctic grid spanning both the Envisat and CryoSat-2 eras. The other three product families distribute either along-track data (LEGOS, CSAO) or use different native grids that would require additional regridding for inter-product comparison. Choosing the CCI grid minimises the cumulative regridding burden across products and aligns the comparison with a publicly available reference grid that other research groups can reproduce. Bilinear interpolation is used as the default regridding method because it preserves the smooth spatial structure of the gridded freeboard fields without introducing the smoothing artefacts of higher-order interpolation. Section 2.2 Common Grid, Masks, Sectors, and Winter Averaging of the revised manuscript provides the expanded justification.
  
  Line 59: opening parenthesis missing to parenthesis used after Supplement.
  The parenthesis error has been corrected.
  
  Line 58–59: was there a reason these two sectors were chosen? Noted as contrasting but in what sense? Please explain how you decided on these two regions, whether it was based on the study data or assumptions made prior to conducting the study.
  As noted in our response to the general comment above, the sector selection has been substantially expanded. All six circumpolar Antarctic sectors are now presented in the main body, and the three deep-dive sectors (Western Weddell Sea, Indian Ocean, Ross Sea) are selected on a priori physical grounds reflecting distinct ice and snow regimes. The selection is based on the assumed physical contrast among regimes, not on prior inspection of the study data, and this is now stated explicitly in Section 1 Introduction.
  
  5 Results
  Figure 1 should have the sectors labelled as referred to throughout the text.
  Figure 1 and Figure 2 have been redesigned to label all six sectors directly on the spatial-mean maps, ensuring that the sector terminology used in the text is visually anchored to the map.
  
  Figure 1 (or another figure) should show the original products themselves before differences to CCI
  The revised Figure 1 and Figure 2 now show the spatial means of each product before any differencing, with separate panels for the Envisat era and the CryoSat-2 era. Difference maps relative to CCI are presented in two separate figures (Figure 3 and Figure 4 in the revised manuscript), allowing the reader to inspect both the absolute freeboard fields and their differences relative to the reference.
  
  Figure 1: small l on LEGOS.
  The capitalisation has been corrected throughout.
  
  Figure 2: explain panels a–d in the caption.
  The figure caption has been expanded to identify each panel explicitly.
  
  Figures 2 and 3: text too small and text cut off on LHS of Figure 3.
  All figure font sizes have been increased to a minimum 18-point base, and the layout of the affected figures has been revised to eliminate text truncation.
  
  Figure 3: over what time period? Is it monthly data over full 2013–2018 period? How many data points are there? Include in caption or text.
  The figure caption now specifies that scatter plots use monthly sector-mean values across the May–October winters of 2013 to 2018, yielding 36 data points per panel. The sample size is also annotated within each panel.
  
  Line 74 and 75: move “(Figure 1)” to end of sentence and replace “:” with “;”.
  The punctuation and figure-reference placement have been corrected.
  
  Line 77: see comment re line 21 to make this result clear.
  The Section 3. Results now interprets the spatial-pattern findings in light of the retrieval-method foundation established in the revised Introduction, with explicit reference to which products use TFMRA versus SAMOSA+ retrackers and which use passive-microwave versus altimetric snow inputs.
  
  Line 88: please define freeboards as used in rest of paper, i.e. is the high-freeboard regime, radar or ice freeboard?
  The terminology has been clarified throughout: “radar freeboard” refers to the elevation difference between the radar scattering surface and the local sea level, and “sea-ice freeboard” refers to the elevation difference between the snow–ice interface and the local sea level. Both terms are now defined and explained explicitly in Section 2.1 Freeboard Products and Product Variants of the revised manuscript and used consistently thereafter.
  
  Line 94: “The” missing before Western Weddell Sea.
  The grammatical error has been corrected.
  
  6 Discussion
  Extra full stop after the word Figures is not needed (only needed if abbreviating to Fig.) e.g. line 120.
  All instances of “Figure.” with a stray full stop have been corrected to “Figure” throughout the manuscript, consistent with Copernicus style.
  
  Line 123: please clarify why this can only be attributed to the snow propagation-speed correction.
  The Discussion has been substantially restructured. The revised attribution is no longer “only” to the snow propagation-speed correction; instead, the snow-harmonisation experiments in Section 4.1 What Snow Harmonisation Can and Cannot Fix partition the inter-product spread into snow-related and non-snow-related components, finding that snow inputs explain only 7–21% of the total sea-ice freeboard spread (95% bootstrap confidence intervals) and that the residual 78–93% is associated with non-snow elements of the retrieval chains. This more precise attribution replaces the earlier, less defensible single-factor claim.
  
  7 Conclusion
  Point 1: referring back to our recommendation to show the actual products before comparison to CCI in Figure 1, this would show the large-scale structure that you highlight here.
  As described in our response to the Figure 1 comment above, the actual product fields are now shown before the differencing. Conclusion Point 1 has been revised to reference the absolute spatial-mean maps directly.
  
  Point 3 is nicely made.
  We thank the reviewer for this positive feedback. Point 3 has been retained with minor wording adjustments to align with the bootstrap confidence intervals reported in the Results.
  
  In final sentence please describe other sources of uncertainty e.g. retracking. Please also mention the importance and status of in-situ comparisons (given the scope you outline in the final sentence of the discussion).
  The Conclusions have been substantially extended. Other sources of uncertainty are now described explicitly, including retracker selection, lead-detection method, sea-surface-anomaly retrieval, geophysical corrections, and product-specific sampling. The status and importance of in-situ comparisons are addressed in a dedicated paragraph that references the limitations of current Antarctic in-situ validation infrastructure and the value of the IceBird, Operation IceBridge, CRYO2ICE, and forthcoming Copernicus Polar Ice and Snow Topography Altimeter (CRISTAL) campaigns for providing the validation data that this study cannot itself supply.
  
  We thank the reviewer again for the constructive engagement that has materially strengthened the revised manuscript.
  Yours sincerely,
  Xinlong Liu, on behalf of the author team:
  Rachel L. Tilling, Stuart P. Corney, Alexander D. Fraser, and Petra Heil.
  
  References
  Giles, K. A., Laxon, S. W., and Worby, A. P. (2008). Antarctic sea ice elevation from satellite radar altimetry. Geophysical Research Letters, 35(3).
  King, J., Skourup, H., Hvidegaard, S. M., Rösel, A., Gerland, S., Spreen, G., Polashenski, C., Helm, V., and Liston, G. E. (2018). Comparison of freeboard retrieval and ice thickness calculation from ALS, ASIRAS, and CryoSat-2 in the Norwegian Arctic to field measurements made during the N-ICE2015 expedition. Journal of Geophysical Research: Oceans, 123(2):1123– 1141.
  Massom, R. A., Eicken, H., Hass, C., Jeffries, M. O., Drinkwater, M. R., Sturm, M., Worby, A. P., Wu, X., Lytle, V. I., Ushio, S., et al. (2001). Snow on Antarctic sea ice. Reviews of Geophysics, 39(3):413–445.
  Nab, C., Mallett, R., Gregory, W., Landy, J., Lawrence, I., Willatt, R., Stroeve, J. C., and Tsamados, M. (2023). Synoptic variability in satellite altimeter-derived radar freeboard of Arctic sea ice. Geophysical Research Letters, 50(2):e2022GL100696.
  Nab, C., Mallett, R., Nelson, C., Stroeve, J. C., and Tsamados, M. (2024). Optimising interannual sea ice thickness variability retrieved from CryoSat-2. Geophysical Research Letters, 51(21):e2024GL111071.
  Webster, M. A., Gerland, S., Holland, M., Hunke, E., Kwok, R., Lecomte, O., Massom, R. A., Perovich, D., and Sturm, M. (2018). Snow in the changing sea-ice systems. Nature Climate Change, 8(11):946–953.
  Willatt, R., Giles, K. A., Laxon, S. W., Stone-Drake, L., and Worby, A. P. (2010). Field investigations of Ku-band radar penetration into snow cover on Antarctic sea ice. IEEE Transactions on Geoscience and remote sensing, 48(1):365–372.
  Willatt, R., Laxon, S., Giles, K., Cullen, R., Haas, C., and Helm, V. (2011). Ku-band radar penetration into snow cover on Arctic sea ice using airborne data. Annals of Glaciology, 52(57):197–205.
  Willatt, R., Mallett, R., Stroeve, J., Wilkinson, J., Nandan, V., and Newman, T. (2025). Ku-and Ka-band polarimetric radar waveforms and snow depth estimation over multi-year Antarctic sea ice in the Weddell Sea. Geophysical Research Letters, 52(13):e2024GL112870.
  Willatt, R., Stroeve, J. C., Nandan, V., Newman, T., Mallett, R., Hendricks, S., Ricker, R., Mead, J., Itkin, P., Tonboe, R., et al. (2023). Retrieval of snow depth on Arctic sea ice from surface-based, polarimetric, dual-frequency radar altimetry. Geophysical Research Letters, 50(20):e2023GL104461.
  
  Citation: https://doi.org/10.5194/egusphere-2026-662-AC2
RC2:
'Comment on egusphere-2026-662', Anonymous Referee #2, 27 Apr 2026
This study compares winter (2013–2018) Antarctic radar and sea ice freeboard from four CryoSat-2–era products to quantify differences arising from different processing algorithms and snow assumptions.
Overall, the main findings are that i) spatial distribution of freeboard is similar among the investigated products and ii) the snow propagation speed correction is different among the products and therefore affects the ice freeboard.
General Comments:
The paper is easy to read but it lacks precision and substantive contributions. The overall analysis remains rather superficial. One could argue if a “brief communication” is the right format for an intercomparison paper. But even for a brief communication, there is not enough depth in the analysis.
My main concerns are as follows:
The overall study remains superficial, and the stated objectives are not convincingly addressed. For example, “by isolating retrieval-driven spread within a single-sensor era, we provide guidance on where improved Antarctic snow constraints and harmonised processing would have the largest impact on hfᵢconsistency” is not addressed by the analysis presented. It is unclear how the results lead to such guidance, particularly considering the rather limited conclusions. In practice, the main findings, i) the agreement in large-scale spatial patterns of freeboard and ii) the basic influence of snow propagation speed correction on sea ice freeboard, are not particularly novel nor specific to the Southern Ocean.

Differences between the products should be described and discussed in more detail. The paper tries to focus on the differences driven by the snow-propagation correction. However, there is no discussion on the snow depth and density products/parametrisations used for the different freeboard retrievals. But they drive the snow propagation speed correction. There needs to be at least a short section/paragraph for each product, specifying the assumptions made on snow depth and density. The same is true for the different retracking methods, which heavily affect the radar freeboard. These differences need to be discussed in the context of the observed differences to make this study a benefit to the community. Moreover, flooding and snow-ice formation as important processes that affect the radar signal over Antarctic sea ice are neither mentioned nor discussed.

The conclusions remain somewhat vague and do not provide clear guidance for the reader. For example, the statement “high correlation does not imply agreement in absolute freeboard” is correct but rather generic, as it reflects a basic property of the correlation metric. While it may be used as a reminder, it is not sufficient for a key conclusion. In the last sentence the authors write: “we suggest that future product development should prioritise tighter constraints on the snow propagation correction linking hf_r to hf_i.”: What does this mean? The conclusions would benefit from more concrete suggestions of how such improvements could be achieved.

In view of the points raised above, I cannot recommend publication in its current form. The idea of an intercomparison study of Antarctic sea-ice freeboard products is valuable and would be of clear benefit to the community. However, the manuscript requires more analysis, and a substantially more in-depth discussion of the differences between products. I therefore recommend rejection at this stage. I encourage the authors to significantly revise the manuscript, with a stronger focus on analysis and interpretation, and to consider resubmission.
Other comments:
Figure 2: Here, you show only annual means. How does it look for monthly means, i.e. May-mean to October-mean? This would help to compare the seasonal evolution of each product. This could be presented in the same figure.
Figure 3: I would consider to present scatter plots instead (including the numbers presented here). This adds more information than just the bare numbers for bias, correlation and RMSE. For example, how do they intercompare over thin/thick ice? Are there differences?
Citation: https://doi.org/10.5194/egusphere-2026-662-RC2
- AC3:
  'Reply on RC2', Xinlong Liu, 09 May 2026
  Response to Reviewer 2
  Manuscript egusphere–2026–662
  “Antarctic Sea-Ice Freeboard from Envisat and CryoSat-2: Attributing Inter-Product Spread to Snow Assumptions and Radar-Retrieval Baselines”
  Xinlong Liu, Rachel L. Tilling, Stuart P. Corney, Alexander D. Fraser, Petra Heil
  May 9, 2026
  
  Dear Reviewer 2,
  We thank you for your detailed and substantive review of our manuscript. Your principal recommendation, that the analytical depth required for a meaningful Antarctic freeboard intercomparison cannot be accommodated within the Brief Communication format, has been adopted. The revised manuscript is now a full Research Article with substantially expanded analysis, and the editor has confirmed that the journal will reclassify the submission accordingly. Below we respond to each of your comments in turn, with each comment quoted verbatim in italics and our response provided beneath it in upright text.
  
  1 General Comment on Analytical Depth and Novelty
  The paper is easy to read but it lacks precision and substantive contributions. The overall analysis remains rather superficial. One could argue if a “brief communication” is the right format for an intercomparison paper. But even for a brief communication, there is not enough depth in the analysis.
  We agree that the Brief Communication format constrained the analytical depth in ways that ultimately undermined the manuscript’s contribution. The revised Research Article addresses the depth concern through five substantive analytical extensions: a controlled snowharmonisation experimental framework based on a 2 × 2 factorial design over snow thickness and snow density (Section 2.4 Snow-Harmonisation Experiments), year-level bootstrap confidence intervals on every quantitative claim (Section 2.5 Inter-Product Metrics and Uncertainty Estimation), an alternative-snow-reference sensitivity test (Appendix A: Sensitivity of the Snow-Harmonisation Attribution to the Choice of Common Snow Reference), an extended cross-mission analysis spanning the full Envisat–CryoSat-2 record from 2003 to 2018 (Section 2.6 Inter-Era Envisat—CryoSat-2 Comparison and Section 3.3 Inter-Era Envisat–CryoSat-2 Differences), and an expanded product-level methodology description with detailed snow-density parameterisations, retracking algorithms, and the snow propagation-speed correction equation given explicitly (Section 2.3 Freeboard Variables and Snow Propagation-Speed Correction and Appendix B: Detailed Characteristics of the Four Antarctic Sea-Ice Freeboard Products). Each of these extensions directly addresses a specific aspect of the analytical depth concern you raised, and together they convert the manuscript from a descriptive comparison into a controlled attribution study.
  
  2 Stated Objectives Not Convincingly Addressed
  The overall study remains superficial, and the stated objectives are not convincingly addressed. For example, “by isolating retrieval-driven spread within a single-sensor era, we provide guidance on where improved Antarctic snow constraints and harmonised processing would have the largest impact on hfi consistency” is not addressed by the analysis presented. It is unclear how the results lead to such guidance, particularly considering the rather limited conclusions. In practice, the main findings, i) the agreement in large-scale spatial patterns of freeboard and ii) the basic influence of snow propagation speed correction on sea ice freeboard, are not particularly novel nor specific to the Southern Ocean.
  This is a substantive concern that has shaped the revised manuscript’s analytical core. The original Brief Communication’s objectives have been replaced with a single, sharper objective: to attribute inter-product divergence quantitatively to snow-related and non-snowrelated sources using controlled harmonisation experiments. The revised manuscript demonstrates that snow assumptions explain 66–100% of the spread in the snow propagation-speed correction but only 7–21% of the total sea-ice freeboard spread, with the residual 78–93% attributable to non-snow elements of the retrieval chains. This finding is novel and specific to the Antarctic in two respects: first, it is the first quantitative partitioning of Antarctic inter-product divergence into snow and non-snow components using a controlled experimental design rather than descriptive comparison; second, the finding that non-snow retrieval differences dominate Antarctic interproduct divergence (rather than snow assumptions, as is widely assumed) provides clear guidance to the community that improving Antarctic snow constraints, while necessary, is not sufficient for harmonising Antarctic altimetry freeboard products. The broader implication, that retracker harmonisation and geophysical-correction harmonisation should be priorities for future Antarctic product development, is now stated explicitly in the Conclusions.
  
  3 Lack of Detail on Snow and Retracking Methods
  Differences between the products should be described and discussed in more detail. The paper tries to focus on the differences driven by the snow-propagation correction. However, there is no discussion on the snow depth and density products/parametrisations used for the different freeboard retrievals. But they drive the snow propagation speed correction. There needs to be at least a short section/paragraph for each product, specifying the assumptions made on snow depth and density. The same is true for the different retracking methods, which heavily affect the radar freeboard. These differences need to be discussed in the context of the observed differences to make this study a benefit to the community. Moreover, flooding and snow-ice formation as important processes that affect the radar signal over Antarctic sea ice are neither mentioned nor discussed.
  This is the most substantive single comment in your review and has driven a major restructuring of the methods section. Section 2.1 Freeboard Products and Product Variants now devotes a dedicated paragraph to each of the four product families. Each paragraph specifies the retracker (TFMRA50 for LEGOS, CCI, and CSAO; SAMOSA+ for Cryo-TEMPO Baseline-D), the lead-detection method, the sea-surface-anomaly retrieval, the snow-thickness source (CCI AMSR-E/AMSR2 passive-microwave climatology for CCI; the modified passive-microwave climatology by Kurtz and Markus (2012) for LEGOS I; the SARAL/CryoSat-2 dual-frequency altimetric snow for LEGOS II; the AMSR2-derived snow depth for CSAO; the AMSR2 climatology for Cryo-TEMPO), the snow-density parameterisation (300 kg m⁻³ fixed for CCI; the seasonal scheme for LEGOS and CSAO by Kurtz and Markus (2012); the seasonally varying scheme for Cryo-TEMPO by Fons et al. (2023)), and the snow propagation-speed correction implementation. A comprehensive product-characteristics table is provided in Appendix B.
  
  Flooding and snow-ice formation are also addressed explicitly in Section 4.3 Ku-Band Penetration, Flooding and Snow-Ice Formation, which discusses the physical processes that complicate the snow–ice interface scattering assumption underlying conventional radar-altimetry freeboard retrieval. We also cite recent observational findings from the CRYO2ICE campaign and related airborne work to support the discussion of how flooding and snow-ice formation contribute to the residual non-snow inter-product divergence in the Antarctic.
  
  4 Vague Conclusions
  The conclusions remain somewhat vague and do not provide clear guidance for the reader. For example, the statement “high correlation does not imply agreement in absolute freeboard” is correct but rather generic, as it reflects a basic property of the correlation metric. While it may be used as a reminder, it is not sufficient for a key conclusion. In the last sentence the authors write: “we suggest that future product development should prioritise tighter constraints on the snow propagation correction linking hfr to hf i.”: What does this mean? The conclusions would benefit from more concrete suggestions of how such improvements could be achieved.
  The Conclusions have been substantially rewritten to provide concrete guidance. The generic correlation-versus-bias observation has been removed, and the closing recommendations are now framed as below specific actions: Future product development should prioritise harmonisation of retracker selection and tuning thresholds, since retracker choice contributes the largest non-snow component of inter-product divergence; Geophysical-correction harmonisation, particularly the sea-surface-anomaly retrieval, should be a coordinated priority across processing teams; Improved Antarctic snow constraints (through expanded passive-microwave validation, dual-frequency altimetric retrieval, and forthcoming CRISTAL Ka-band measurements) are necessary but not sufficient for harmonising freeboard products; Future comparison studies should include in-situ validation against IceBird, Operation IceBridge, and CRYO2ICE measurements to quantify absolute accuracy alongside relative consistency. These recommendations are stated as action items in the revised Conclusions.
  
  5 Recommendation for Rejection
  In view of the points raised above, I cannot recommend publication in its current form. The idea of a comparison study of Antarctic sea-ice freeboard products is valuable and would be of clear benefit to the community. However, the manuscript requires more analysis, and a substantially more in-depth discussion of the differences between products. I therefore recommend rejection at this stage. I encourage the authors to significantly revise the manuscript, with a stronger focus on analysis and interpretation, and to consider resubmission.
  We thank you for the constructive framing of the rejection recommendation, which explicitly encouraged significant revision and resubmission. The revised Research Article incorporates the analytical depth, product-level detail, and concrete conclusions that you identified as missing from the original Brief Communication. The editor has confirmed that the journal will reclassify the submission as a full Research Article rather than requiring a fresh manuscript number, preserving the editorial history and the open-discussion record that you and Reviewer 1 contributed to. We hope the revised manuscript addresses the substantive concerns that motivated your rejection recommendation and meets the standard for publication you have set out.
  
  6 Other Comments
  Figure 2: Here, you show only annual means. How does it look for monthly means, i.e. May-mean to October-mean? This would help to compare the seasonal evolution of each product. This could be presented in the same figure.
  The revised manuscript now presents monthly time series for the three deep-dive sectors across both the Envisat and CryoSat-2 eras (Figure 7 for sea-ice freeboard, with the corresponding radar freeboard time series in Appendix C: Monthly Time Series of Radar Freeboard in Three Representative Sectors). Each panel shows the May to October monthly means for every winter, with per-year line segmentation that preserves the seasonal data structure and avoids implying continuous evolution across the November to April observational gaps. The inter-product range envelope is similarly segmented by year. This addresses your concern about seasonal evolution comparison.
  
  Figure 3: I would consider to present scatter plots instead (including the numbers presented here). This adds more information than just the bare numbers for bias, correlation and RMSE. For example, how do they intercompare over thin/thick ice? Are there differences?
  The revised manuscript now presents inter-product scatter plots for sea-ice freeboard in the main body (Figure 8), with corresponding scatter plots for radar freeboard (Figure D1) and the snow propagation-speed correction (Figure D2) in Appendix D: Inter-Product Scatter of Radar Freeboard and Snow Propagation-Speed Correction. Each scatter plot shows monthly sector-mean values for the three deep-dive sectors, allowing direct visual inspection of the inter-product agreement across the freeboard range. The thin-ice versus thick-ice comparison you suggested is visible in the contrast between the Indian Ocean panels (thinner ice) and the Western Weddell Sea panels (thicker ice), and we discuss this contrast in Section 4.2 Implications for Sea-Ice Thickness Retrieval and Section 4.3 Ku-Band Penetration, Flooding and Snow-Ice Formation.
  
  We thank the reviewer again for the rigorous engagement that has materially shaped the revised manuscript. We hope the analytical extensions and the format change to a full Research Article address the substantive concerns of your original review.
  Yours sincerely,
  Xinlong Liu, on behalf of the author team:
  Rachel L. Tilling, Stuart P. Corney, Alexander D. Fraser, and Petra Heil.
  
  References
  Fons, S. W., Kurtz, N. T., and Bagnardi, M. (2023). A decade-plus of Antarctic sea ice thickness and volume estimates from CryoSat-2 using a physical model and waveform fitting. The Cryosphere, 17(6):2487–2508.
  Kurtz, N. T. and Markus, T. (2012). Satellite observations of Antarctic sea ice thickness and volume. Journal of Geophysical Research: Oceans, 117(C8).
  
  Citation: https://doi.org/10.5194/egusphere-2026-662-AC3
EC1:
'Comment on egusphere-2026-662', Ted Maksym, 08 May 2026

Based on the suggestions of the reviewers, I will be recommending that the authors submit a revised, full length article for their revision, rather than as a Brief Communication. This will allow space for a more in depth analysis as suggested by the reviewers. The Journal has been alerted, and the submission category will be changed accordingly upon submission of the revised manuscript.

Citation: https://doi.org/10.5194/egusphere-2026-662-EC1
- AC1: 'Reply on EC1', Xinlong Liu, 09 May 2026
  
  Dear Dr. Maksym,
  We thank you for your editorial guidance throughout the open-discussion phase of our manuscript and for confirming that the Journal will reclassify the submission as a full Research Article upon upload of the revised manuscript. We are grateful for your willingness to facilitate this format change, which allows us to address both reviewers' substantive suggestions through expanded analysis rather than through condensation into the constrained Brief Communication format.
  We agree with your assessment, drawing on the recommendations of both reviewers, that a full-length article provides the appropriate framework for the depth of analysis the manuscript requires. Reviewer 1 explicitly recommended expansion to a stronger regular-length paper to fully explore the differences between the products, and Reviewer 2 noted that the analytical depth required for a meaningful Antarctic freeboard comparison cannot be accommodated within the Brief Communication format. We have used the open-discussion period to substantially extend the manuscript along the directions both reviewers identified.
  The principal extensions in the revised Research Article are summarised in the accompanying cover letter and addressed in detail in our point-by-point responses to each reviewer below. The most consequential revisions are the introduction of a controlled snow-harmonisation experimental framework based on a two-by-two factorial design over snow thickness and snow density, the addition of year-level bootstrap confidence intervals on every reported quantitative claim, the extension of the time period from 2013 to 2018 to the full Envisat-CryoSat-2 record from 2003 to 2018, the inclusion of all six circumpolar Antarctic sectors in the main body, and a substantially expanded discussion of product-level retrieval methodology including snow-density parameterisations, retracking algorithms, and flooding and snow-ice formation processes. We have also added Alexander D. Fraser as a co-author in recognition of his substantive contributions to the experimental design of the snow-harmonisation framework.
  We confirm that we will follow the procedural sequence you outlined in your follow-up correspondence: this response document is uploaded to the system first, you will then close the discussion phase administratively, and we will subsequently upload the revised Research Article. Petra Heil, a co-author on this manuscript and a member of the Cryosphere editorial board, has not been and will not be involved in the editorial handling of this submission, as declared in the Competing Interests statement of the manuscript.
  We are grateful for the constructive engagement of both reviewers and for the time you have invested in resolving the procedural mechanics of this format change. We look forward to the further review of the revised Research Article.
  With kind regards,
  Xinlong Liu, on behalf of the author team: Rachel L. Tilling, Stuart P. Corney, Alexander D. Fraser, and Petra Heil.
  
  Citation: https://doi.org/10.5194/egusphere-2026-662-AC1

Xinlong Liu, Stuart Paul Corney, Rachel Louise Tilling, and Petra Heil

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Short summary

Antarctic sea-ice thickness from satellites depends on how snow is treated. We compared four widely used CryoSat-2 radar products for winters 2013–2018 on the same map grid. All show similar large-scale patterns, but each gives systematically higher or lower values, with the biggest differences in the snowier western Weddell Sea. Year-to-year changes are similar across products, yet these offsets can shift thickness estimates, so users should account for product choice and snow assumptions.


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