Assessment of Arctic Sea Ice Thickness Retrieval Ability of the Chinese HY-2B Radar Altimeter

Dong, Zhaoqing; Shi, Lijian; Lin, Mingsen; Zeng, Tao; Wu, Suhui

doi:https://doi.org/10.5194/egusphere-2022-870

Preprints

https://doi.org/10.5194/egusphere-2022-870

Preprints

21 Sep 2022

| 21 Sep 2022

Assessment of Arctic Sea Ice Thickness Retrieval Ability of the Chinese HY-2B Radar Altimeter

Zhaoqing Dong, Lijian Shi, Mingsen Lin, Tao Zeng, and Suhui Wu

Abstract. In the context of global warming, sea ice changes have received increasing attention as "indicators" and "amplifiers" of climate change. With the development of satellite altimeters, satellite altimeter technologies have been increasingly used to retrieve Arctic sea ice thicknesses and have achieved rapid development and application. At present, the CryoSat-2 radar altimeter and Ice, Cloud and land Elevation Satellite-2 (ICESat-2) laser altimeter are the main data sources used in Arctic sea ice thickness retrievals. With the continuous development of the China Ocean Dynamic Environment Satellite Series (HY-2), it is of great significance to explore the potential application of this dataset in Arctic sea ice thickness retrievals. In this study, we first estimated the Arctic radar freeboard and sea ice thickness values during two sea ice growing cycles (from October 2019 to April 2020 and from October 2020 to April 2021) using the China HY-2B radar altimeter and then compared the results with the Alfred Wegener Institute (AWI) CryoSat-2 sea ice freeboard and sea ice thickness products recorded during the same period. The accuracies of the HY-2B radar freeboard and sea ice thickness were then verified with the Operation IceBridge (OIB) airborne data and ICESat-2 laser altimeter data, and the random uncertainties in the HY-2B sea ice freeboard and sea ice thickness results were finally estimated. Although the spatial distributions of the HY-2B radar freeboard and sea ice thickness results agreed well with those of AWI CryoSat-2, the deviation between the HY-2B radar freeboard and CryoSat-2 radar freeboard data was within 2 cm, while the deviation between the HY-2B sea ice thickness data and CryoSat-2 sea ice thickness data was within 0.2 m. In addition, the growth trends of the HY-2B radar freeboard and sea ice thickness were slower than those of AWI CryoSat-2. This finding was related to the applied sea surface height anomaly (SSHA) extraction method. Comparisons with the OIB sea ice freeboard and sea ice thickness values recorded in April 2019 showed that the correlation between the HY-2B sea ice freeboard retrievals and OIB sea ice freeboard data was 0.58, the root mean square error (RMSE) was 0.17 m, and the mean absolute error (MAE) was 0.14 m. The correlation between the HY-2B sea ice thickness retrieval and OIB sea ice thickness data was 0.41, the RMSE was 2.05 m, and the MAE was 1.91 m. Based on the Gaussian error propagation theory, we estimated the uncertainties of the HY-2B sea ice freeboard and sea ice thickness data: the uncertainty of the former ranged from 8.5 cm to 12.0 cm, while the uncertainty of the latter ranged from 26.8 cm to 37.7 cm. Due to the influence of the SSHA uncertainty (σ_SSA) and the number of observation points inside the grid, the uncertainties in the HY-2B sea ice freeboard and sea ice thickness data were higher at low latitudes than at high latitudes.

Received: 02 Sep 2022 – Discussion started: 21 Sep 2022

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Journal article(s) based on this preprint

31 Mar 2023

Feasibility of retrieving Arctic sea ice thickness from the Chinese HY-2B Ku-band radar altimeter

Zhaoqing Dong, Lijian Shi, Mingsen Lin, Yongjun Jia, Tao Zeng, and Suhui Wu

The Cryosphere, 17, 1389–1410, https://doi.org/10.5194/tc-17-1389-2023,https://doi.org/10.5194/tc-17-1389-2023, 2023

Short summary

Zhaoqing Dong et al.

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2022-870', Anonymous Referee #1, 31 Oct 2022

The review is attached as a PDF.

Citation: https://doi.org/10.5194/egusphere-2022-870-RC1
- AC1: 'Reply on RC1', Zhaoqing Dong, 21 Dec 2022
  
  Dear Editors and Reviewers,
  
  Thank you for considering our manuscript, and the reviewers’ comments concerning our manuscript entitled Assessment of Arctic Sea Ice Thickness Retrieval Ability of the Chinese HY-2B Ku-band Radar Altimeter (manuscript ID: egusphere-2022-870). The comments are all valuable and very helpful for improving upon our paper. We have now carefully reviewed and addressed all of comments which we hope meet with approval, with revisions to the original manuscript shown in red. Please see Respone to RC1 for details.
  
  Best wishes,
  Zhaoqing Dong
  
  Citation: https://doi.org/10.5194/egusphere-2022-870-AC1
RC2:
'Comment on egusphere-2022-870', Anonymous Referee #2, 08 Nov 2022

Review of the MS: “Assessment of Arctic sea ice thickness retrieval ability of the Chinese HY-2B Radar altimeter” by Dong et al.

The HY-2B satellite is carrying a dual frequency Ku- and C- band radar altimeter. The data are used for deriving the sea ice thickness and it is compared to similar retrievals from CryoSat2 and airborne campaign data (Operation Ice Bridge). This is an urgent and welcome topic. However, important details are missing from the MS about the instrument and data and discussion of the processing steps and choices made. I did not see it stated clearly, but this study is not using the dual-frequency capability of HY-2B when deriving the freeboard? Only Ku-band? I think that the answers to these questions are important for evaluating the MS and the novelty of it.

The snow data used in the processing are the same as the AWI snow depth (line 224). This is logical when HY-2B data are compared to AWI CS2 data. Are all the other processing steps and auxiliary data used in the processing identical to the AWI processing so that a proper comparison can be made? In line 24 it is mentioned that some of the differences were due to the applied sea surface height anomaly extraction method. Is it due to differences in the methodology or sensor specific differences? Please clarify.

A number of studies focused on Ku- and Ka-band radar altimeter applications from AltiKa and CryoSat and for preparation of the planned CRISTAL mission. This MS does not continue that discussion using C- and Ku-band radar altimetry for sea ice applications. Anyway, I think that some justification of the choices made in this paper are needed, for example, it is implicitly understood that radar scattering is at the snow-ice interface. Is that a good assumption? And how would that differ for Ku- and C-band. Would the different foot-print sizes at the two frequencies have an impact for the derived ice thickness?

The snow depth dataset is a strange combination of retrieved snow depth over first-year ice and snow depth climatology over multiyear ice and some smoothing and filtering. What does the different snow depths and ice densities in first-year ice and multiyear ice areas mean for the retrieved ice thickness? How does this compare to the variation in derived freeboards for the ice thickness variability? What is the impact of the fixed ice densities and the ice type classification with its different snow depths etc.? Is the snow depth needed at all? To me it seems that the snow data are massaged until the “right” ice thickness is achieved.

Some specific comments:

Line 13: “… it is of great significance…” this is a subjective statement without real justification. Please reformulate.

Line 14: delete “values”

Line 15: “… ice growing cycles” replace by “winters”.

Line 17: delete “recorded”.

Line 18: replace “verified” with “compared”.

Line 40: delete “effect”.

Around line 45: It is confusing and inaccurate what is written about AMOC. Please reformulate or delete.

Line 52: add “and extent” after “density”.

Line 57: use “derive” instead of “estimate”, also line 61.

Line 75: “few reports” please list these few reports as references.

Line 77: delete “as a supplementary means”

Line 79: delete sentence starting with “Therefore…”.

Line 90: Add some details about the HY-2B altimeter.

Line 91: delete “successfully”.

Line 168: “Snow depth” it is unclear which snow depth dataset is actually used. Please clarify this and explain if you are using AWI snow depths or IS-2/CS2 snow depths.

Line 224: delete “depth”.

Line 226: Eq. 3 units in meters? Please add units, sometimes [m] sometimes [cm]… use the same units throughout.

Line 230: Eq. 4, what is the sea water density? Sometimes units are [kgm-3] sometimes [kg/m3], stick to one form. Multiplication is sometimes a dot and sometimes x?

Line 322: I think that I know, but this is confusing: what is a “deviation”? standard deviation? or bias? Throughout the MS.

Line 324: replace ”independent” with “OIB”

Citation: https://doi.org/10.5194/egusphere-2022-870-RC2
- AC2: 'Reply on RC2', Zhaoqing Dong, 21 Dec 2022
  
  Dear Editors and Reviewers,
  
  Thank you for considering our manuscript, and the reviewers’ comments concerning our manuscript entitled Assessment of Arctic Sea Ice Thickness Retrieval Ability of the Chinese HY-2B Ku-band Radar Altimeter (manuscript ID: egusphere-2022-870). The comments are all valuable and helpful for improving upon our paper. We have now carefully reviewed and addressed all of comments which we hope meet with approval, with revisions to the original manuscript shown in red. Please see Respone to RC2 for details.
  
  Best wishes,
  Zhaoqing Dong
  
  Citation: https://doi.org/10.5194/egusphere-2022-870-AC2
RC3:
'Comment on egusphere-2022-870', Anonymous Referee #3, 23 Nov 2022

This manuscript introduces the retrieval of Arctic sea ice freeboard and thickness with the radar altimeter onboard HY-2B. The inclination angle of HY-2B allows the coverage of up to 82N, and the satellite potentially constitutes an important source of information for sea ice of both polar regions. Specifically in the manuscript, the authors focus on the processing of converting existing range (or elevation) product of HY-2B into radar/ice freeboard and thickness. I consider the data from HY2B and this submission a good contribution to the community, but I do have the following comments that in my opinion that should be addressed first.

The overall uncertainty analysis needs to be more clear and precise, especially in terms of the determination of freeboard uncertainty. First, the (claimed) uncertainty used for further analysis is sigma_SGDR, which is only 2cm and should be a lower bound of the actual range uncertainty. This uncertainty, in its true quantity, applies to both SSHA and individual freeboard. Since SGDR is the upstream dataset this work relies on, it is not necessary a quantity that needs much elaboration within this work. However, its value needs to be justified. For example, what is the gate resolution of HY-2B? Is the 2cm uncertainty due to the combination of several footprints (therefore smaller)? Furthermore, the authors state that Ricker et al. (2014) `believed’ the random uncertainty of radar freeboard to be determined by radar speckle noise. Is it possible to provide any other proof of how is the reference relevance to the treatment here?

Second, the uncertainty of SSH is computed as the standard deviation (SD) of SSH points (of the along-track 25km segment). I think this is a crude guess, and unfortunately, probably an underestimation of SSH-induced uncertainty. Because the along-track points that are not used for determining SSH share the same uncertainty caused by the same set of SSH points, and therefore the uncertainty of the retrieved freeboard samples on the same track is systematic (rather than random). Therefore, in Eq. (11) it should be averaged out and diminished much more slowly.

Third, although the authors treat the snow-induced uncertainty as random error (possibly a typo on line 400), it is hardly the case, despite that the snow depth is based on both climatology and PMI retrieval. A simple counter argument is that: the PMI product is based on C-band PMI onboard AMSR-E/2, which is at about 60km in resolution. Not to mention the 8-grid smoothing that is carried out over the snow depth retrieval. Then there exists large local correlation of the snow depth uncertainty, given that 25km grid is used in this study. Arguably more importantly, the climatology of snow depth from W99 plays a very important role in the snow-depth composite of AWI, which is evident in the respective technical report. Given that W99 is halved for the combined product, its induced uncertainty is still very large and will dominate the portion caused by snow in the uncertainty of the final ice thickness product. Therefore, I will be very cautions to treat the snow depth related uncertainty as random errors.

Finally, the density of snow and ice are also treated as random errors. This should be also a very `optimistic’ estimation, especially the effect on the final ice thickness uncertainty. Overall I suggest that the authors reconsider the uncertainty quantification process and divide into the random part and the systematic part, and be cautious about which category each term belongs to. Differentiation of the uncertainty also ensures fairer comparison with the AWI product, and the author seemed to have used the random error of it, which is much lower in may part of the basin (e.g., Beaufort Sea).

Another major issue I noticed is the limited data availability of HY-2B even in the later months of the winter. As shown in Figure 6 and 8, there are large areas with no valid radar freeboard on the monthly scale: on the Eurasia continental shelf, Beaufort Sea, etc. What is the cause of the missing data? Invalid waveforms. I suppose that at this latitude HY-2B should have better coverage than CS2.

Also, the authors mainly compared the HY-2B retrieval with CS2. However, Sentinel-3 and AltiKa have the same inclination angle as HY-2B, and especially Sentinel-3 satellites work on Ku-band (although they are of delay-Doppler type). Is it better to compare against Sentinel-3 retrievals? This is only a suggestion, out of my curiosity. The authors can decide whether this is an option or not.

The comparison against CS2-IS2 data contains inconsistencies in the methodology. The comparison of radar freeboard is inherently between two CS2 retrievals (one from AWI and the other one carried out by Kwok). Therefore it’s not a fair comparison, since the two products based on CS2 arises from the same source of information. So many issues are not present, such as limited representation by altimetry.

Minor issues:

Some figures contain maps that are too small to read, such as Fig. 6 and 8. Pls increase the font and maps accordingly.

For the third-party and auxiliary datasets, I suggest that the authors just introduce them, without too much comments on the specific advantages. For each product there are potentially uncertainties that are fully addressed. I think just stating the basic status quo of the products is already enough.

The reference list is not strictly ordered.

The language usage needs improvements. General suggestions include avoiding long sentences, and avoiding complex statements. Several typos are present. I suggest that the authors give an overhaul of the manuscript after the major issues are addressed.

Citation: https://doi.org/10.5194/egusphere-2022-870-RC3
- AC3: 'Reply on RC3', Zhaoqing Dong, 21 Dec 2022
  
  Dear Editors and Reviewers,
  
  Thank you for considering our manuscript, and the reviewers’ comments concerning our manuscript entitled Assessment of Arctic Sea Ice Thickness Retrieval Ability of the Chinese HY-2B Ku-band Radar Altimeter (manuscript ID: egusphere-2022-870). The comments are all valuable and helpful for improving upon our paper. We have now carefully reviewed and addressed all of comments which we hope meet with approval, with revisions to the original manuscript shown in red. Please see Respone to RC3 for details.
  
  Best wishes,
  Zhaoqing Dong
  
  Citation: https://doi.org/10.5194/egusphere-2022-870-AC3

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2022-870', Anonymous Referee #1, 31 Oct 2022

The review is attached as a PDF.

Citation: https://doi.org/10.5194/egusphere-2022-870-RC1
- AC1: 'Reply on RC1', Zhaoqing Dong, 21 Dec 2022
  
  Dear Editors and Reviewers,
  
  Thank you for considering our manuscript, and the reviewers’ comments concerning our manuscript entitled Assessment of Arctic Sea Ice Thickness Retrieval Ability of the Chinese HY-2B Ku-band Radar Altimeter (manuscript ID: egusphere-2022-870). The comments are all valuable and very helpful for improving upon our paper. We have now carefully reviewed and addressed all of comments which we hope meet with approval, with revisions to the original manuscript shown in red. Please see Respone to RC1 for details.
  
  Best wishes,
  Zhaoqing Dong
  
  Citation: https://doi.org/10.5194/egusphere-2022-870-AC1
RC2:
'Comment on egusphere-2022-870', Anonymous Referee #2, 08 Nov 2022

Review of the MS: “Assessment of Arctic sea ice thickness retrieval ability of the Chinese HY-2B Radar altimeter” by Dong et al.

The HY-2B satellite is carrying a dual frequency Ku- and C- band radar altimeter. The data are used for deriving the sea ice thickness and it is compared to similar retrievals from CryoSat2 and airborne campaign data (Operation Ice Bridge). This is an urgent and welcome topic. However, important details are missing from the MS about the instrument and data and discussion of the processing steps and choices made. I did not see it stated clearly, but this study is not using the dual-frequency capability of HY-2B when deriving the freeboard? Only Ku-band? I think that the answers to these questions are important for evaluating the MS and the novelty of it.

The snow data used in the processing are the same as the AWI snow depth (line 224). This is logical when HY-2B data are compared to AWI CS2 data. Are all the other processing steps and auxiliary data used in the processing identical to the AWI processing so that a proper comparison can be made? In line 24 it is mentioned that some of the differences were due to the applied sea surface height anomaly extraction method. Is it due to differences in the methodology or sensor specific differences? Please clarify.

A number of studies focused on Ku- and Ka-band radar altimeter applications from AltiKa and CryoSat and for preparation of the planned CRISTAL mission. This MS does not continue that discussion using C- and Ku-band radar altimetry for sea ice applications. Anyway, I think that some justification of the choices made in this paper are needed, for example, it is implicitly understood that radar scattering is at the snow-ice interface. Is that a good assumption? And how would that differ for Ku- and C-band. Would the different foot-print sizes at the two frequencies have an impact for the derived ice thickness?

The snow depth dataset is a strange combination of retrieved snow depth over first-year ice and snow depth climatology over multiyear ice and some smoothing and filtering. What does the different snow depths and ice densities in first-year ice and multiyear ice areas mean for the retrieved ice thickness? How does this compare to the variation in derived freeboards for the ice thickness variability? What is the impact of the fixed ice densities and the ice type classification with its different snow depths etc.? Is the snow depth needed at all? To me it seems that the snow data are massaged until the “right” ice thickness is achieved.

Some specific comments:

Line 13: “… it is of great significance…” this is a subjective statement without real justification. Please reformulate.

Line 14: delete “values”

Line 15: “… ice growing cycles” replace by “winters”.

Line 17: delete “recorded”.

Line 18: replace “verified” with “compared”.

Line 40: delete “effect”.

Around line 45: It is confusing and inaccurate what is written about AMOC. Please reformulate or delete.

Line 52: add “and extent” after “density”.

Line 57: use “derive” instead of “estimate”, also line 61.

Line 75: “few reports” please list these few reports as references.

Line 77: delete “as a supplementary means”

Line 79: delete sentence starting with “Therefore…”.

Line 90: Add some details about the HY-2B altimeter.

Line 91: delete “successfully”.

Line 168: “Snow depth” it is unclear which snow depth dataset is actually used. Please clarify this and explain if you are using AWI snow depths or IS-2/CS2 snow depths.

Line 224: delete “depth”.

Line 226: Eq. 3 units in meters? Please add units, sometimes [m] sometimes [cm]… use the same units throughout.

Line 230: Eq. 4, what is the sea water density? Sometimes units are [kgm-3] sometimes [kg/m3], stick to one form. Multiplication is sometimes a dot and sometimes x?

Line 322: I think that I know, but this is confusing: what is a “deviation”? standard deviation? or bias? Throughout the MS.

Line 324: replace ”independent” with “OIB”

Citation: https://doi.org/10.5194/egusphere-2022-870-RC2
- AC2: 'Reply on RC2', Zhaoqing Dong, 21 Dec 2022
  
  Dear Editors and Reviewers,
  
  Thank you for considering our manuscript, and the reviewers’ comments concerning our manuscript entitled Assessment of Arctic Sea Ice Thickness Retrieval Ability of the Chinese HY-2B Ku-band Radar Altimeter (manuscript ID: egusphere-2022-870). The comments are all valuable and helpful for improving upon our paper. We have now carefully reviewed and addressed all of comments which we hope meet with approval, with revisions to the original manuscript shown in red. Please see Respone to RC2 for details.
  
  Best wishes,
  Zhaoqing Dong
  
  Citation: https://doi.org/10.5194/egusphere-2022-870-AC2
RC3:
'Comment on egusphere-2022-870', Anonymous Referee #3, 23 Nov 2022

This manuscript introduces the retrieval of Arctic sea ice freeboard and thickness with the radar altimeter onboard HY-2B. The inclination angle of HY-2B allows the coverage of up to 82N, and the satellite potentially constitutes an important source of information for sea ice of both polar regions. Specifically in the manuscript, the authors focus on the processing of converting existing range (or elevation) product of HY-2B into radar/ice freeboard and thickness. I consider the data from HY2B and this submission a good contribution to the community, but I do have the following comments that in my opinion that should be addressed first.

The overall uncertainty analysis needs to be more clear and precise, especially in terms of the determination of freeboard uncertainty. First, the (claimed) uncertainty used for further analysis is sigma_SGDR, which is only 2cm and should be a lower bound of the actual range uncertainty. This uncertainty, in its true quantity, applies to both SSHA and individual freeboard. Since SGDR is the upstream dataset this work relies on, it is not necessary a quantity that needs much elaboration within this work. However, its value needs to be justified. For example, what is the gate resolution of HY-2B? Is the 2cm uncertainty due to the combination of several footprints (therefore smaller)? Furthermore, the authors state that Ricker et al. (2014) `believed’ the random uncertainty of radar freeboard to be determined by radar speckle noise. Is it possible to provide any other proof of how is the reference relevance to the treatment here?

Second, the uncertainty of SSH is computed as the standard deviation (SD) of SSH points (of the along-track 25km segment). I think this is a crude guess, and unfortunately, probably an underestimation of SSH-induced uncertainty. Because the along-track points that are not used for determining SSH share the same uncertainty caused by the same set of SSH points, and therefore the uncertainty of the retrieved freeboard samples on the same track is systematic (rather than random). Therefore, in Eq. (11) it should be averaged out and diminished much more slowly.

Third, although the authors treat the snow-induced uncertainty as random error (possibly a typo on line 400), it is hardly the case, despite that the snow depth is based on both climatology and PMI retrieval. A simple counter argument is that: the PMI product is based on C-band PMI onboard AMSR-E/2, which is at about 60km in resolution. Not to mention the 8-grid smoothing that is carried out over the snow depth retrieval. Then there exists large local correlation of the snow depth uncertainty, given that 25km grid is used in this study. Arguably more importantly, the climatology of snow depth from W99 plays a very important role in the snow-depth composite of AWI, which is evident in the respective technical report. Given that W99 is halved for the combined product, its induced uncertainty is still very large and will dominate the portion caused by snow in the uncertainty of the final ice thickness product. Therefore, I will be very cautions to treat the snow depth related uncertainty as random errors.

Finally, the density of snow and ice are also treated as random errors. This should be also a very `optimistic’ estimation, especially the effect on the final ice thickness uncertainty. Overall I suggest that the authors reconsider the uncertainty quantification process and divide into the random part and the systematic part, and be cautious about which category each term belongs to. Differentiation of the uncertainty also ensures fairer comparison with the AWI product, and the author seemed to have used the random error of it, which is much lower in may part of the basin (e.g., Beaufort Sea).

Another major issue I noticed is the limited data availability of HY-2B even in the later months of the winter. As shown in Figure 6 and 8, there are large areas with no valid radar freeboard on the monthly scale: on the Eurasia continental shelf, Beaufort Sea, etc. What is the cause of the missing data? Invalid waveforms. I suppose that at this latitude HY-2B should have better coverage than CS2.

Also, the authors mainly compared the HY-2B retrieval with CS2. However, Sentinel-3 and AltiKa have the same inclination angle as HY-2B, and especially Sentinel-3 satellites work on Ku-band (although they are of delay-Doppler type). Is it better to compare against Sentinel-3 retrievals? This is only a suggestion, out of my curiosity. The authors can decide whether this is an option or not.

The comparison against CS2-IS2 data contains inconsistencies in the methodology. The comparison of radar freeboard is inherently between two CS2 retrievals (one from AWI and the other one carried out by Kwok). Therefore it’s not a fair comparison, since the two products based on CS2 arises from the same source of information. So many issues are not present, such as limited representation by altimetry.

Minor issues:

Some figures contain maps that are too small to read, such as Fig. 6 and 8. Pls increase the font and maps accordingly.

For the third-party and auxiliary datasets, I suggest that the authors just introduce them, without too much comments on the specific advantages. For each product there are potentially uncertainties that are fully addressed. I think just stating the basic status quo of the products is already enough.

The reference list is not strictly ordered.

The language usage needs improvements. General suggestions include avoiding long sentences, and avoiding complex statements. Several typos are present. I suggest that the authors give an overhaul of the manuscript after the major issues are addressed.

Citation: https://doi.org/10.5194/egusphere-2022-870-RC3
- AC3: 'Reply on RC3', Zhaoqing Dong, 21 Dec 2022
  
  Dear Editors and Reviewers,
  
  Thank you for considering our manuscript, and the reviewers’ comments concerning our manuscript entitled Assessment of Arctic Sea Ice Thickness Retrieval Ability of the Chinese HY-2B Ku-band Radar Altimeter (manuscript ID: egusphere-2022-870). The comments are all valuable and helpful for improving upon our paper. We have now carefully reviewed and addressed all of comments which we hope meet with approval, with revisions to the original manuscript shown in red. Please see Respone to RC3 for details.
  
  Best wishes,
  Zhaoqing Dong
  
  Citation: https://doi.org/10.5194/egusphere-2022-870-AC3

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

ED: Reconsider after major revisions (further review by editor and referees) (21 Dec 2022) by Vishnu Nandan

AR by Zhaoqing Dong on behalf of the Authors (22 Dec 2022) Author's response Author's tracked changes

EF by Sarah Buchmann (02 Jan 2023) Manuscript

ED: Referee Nomination & Report Request started (02 Jan 2023) by Vishnu Nandan

RR by Anonymous Referee #2 (06 Jan 2023)

RR by Anonymous Referee #1 (18 Jan 2023)

Suggestions for revision or reasons for rejection

Review of:
“Assessment of Arctic Sea Ice Thickness Retrieval Ability of the Chinese HY-2B Ku-band Radar Altimeter”
By Dong et al.
# 2nd review

I’d like to thank the authors for the extensive edits, added work, and detailed response made to all the reviews. This is my second time reviewing this manuscript, so my comments will primarily focus on the edits made since the last review as well as the author’s response to the reviews, but I will also include some additional comments that I realized when reading it a second time. Unfortunately, even with the extensive edits and comments provided by the authors, I still have concerns that should be considered before publication.

-----------------

The authors have since the original submission changed the processing slightly to include not-a-number values when sea surface height anomalies (SSHA) were not available (instead of providing a value of 0), as well as used the 15 lowest (instead of 9) points within a 25-km segment as a measure of the sea level within leads (SSHA). This has improved their statistics when comparing with reference data (Operation IceBridge data) for both sea ice freeboard and sea ice thickness estimates. They have produced additional studies in response to reviews, where they have assessed waveform parameters/features to use for discriminating between leads/floes instead of their current methodology. However, this did not yield better results than their current methodology (and have therefore not been included in the manuscript). The authors have amended their uncertainty estimation, which now presents more feasible estimations, and provided a more extensive discussion on the limitations of their methodology and impacts hereof.

General comments

I am happy to see the positive impact that the change in processing has shown in your comparison with OIB, however the statistics are still not a positive for HY-2B freeboard nor thickness estimates as the CryoSat-2 estimates. This, again, tells me that the processing chain of AWI (lead/floe discrimination, TFMRA50 re-tracker) is likely the way forward even with the different footprint and altimeter specifications of HY-2B compared with CryoSat-2. I do recommend the authors to investigate using waveform parameters for lead/floe discrimination as well as applying a re-tracker commonly used for sea ice (such as TFMRA50), however I understand that it will require quite the effort. If this is not possible, I think it is crucial that the manuscript clearly reflects (and mentions) the limitations of the methods and data used in this study. Below I have mentioned some suggestions for implementing this.

I think it is important to highlight that this study is a feasibility study. What I mean, is that you are in fact not truly assessing the retrieval ability of HY-2B for Arctic sea ice thickness, since you are not using re-trackers commonly used, or designed, for sea ice – in fact, you use observations provided by an ocean-preferred re-tracker. As such, your results are also limited by this. I therefore propose you change the title of your manuscript to reflect this. Suggestions could be: “Feasibility of retrieving Arctic sea ice thickness from the Chinese HY-2B Ku-band radar altimeter” or “Assessment of Arctic sea ice thickness retrieval ability of the Chinese HY-2B Ku-band radar altimeter: a feasibility study”. Also, I think it is crucial that you state the purpose of this study in the end of the introduction, highlighting that you are aiming to investigate whether HY-2B can be used for sea ice, but that you are limited to already provided higher-level products, and that it is not within the scope of the study to derive a freeboard product using your own re-tracker from the HY-2B product.

I’m happy to see a study using the waveforms and classifying the waveforms using pulse peakiness (PP), however slightly confused to see that it was in fact not satisfactory. Based on your response, I see some aspects that could potentially explain this: (1) PP can be calculated in different ways (that is to say, sometimes they are tweaked in different studies). I cannot see how you have calculated PP, but I do find it exceptionally odd that HY-2B is not able to use it to classify by – whereas all other radar altimeters have in fact successfully used this. Therefore, it may be due to how you have calculated PP; (2) For HY-2B we do not yet know which PP thresholds to use. You have tried several PP thresholds (not sure what the selection of thresholds were based on) but choosing high PP’s (which would normally yield a classification as lead) resulted in almost no lead observations. This might be a result of the already low data coverage, which you also suggest, but I do propose that for the next time you look at this, that instead of pre-defined PP’s, you choose a selection of waveforms and make a statistical analysis to derive the PP thresholds. I am aware that you state this is work for future studies, however it will unfortunately be those studies that have the true value then.

There is very little data available by HY-2B. Why is that? It is based on the selected re-tracker where some restrictions/flags are applied? There must be applied some post-processing steps that remove the data. Could you provide paragraph explaining when in the processing this data is removed, and why it was removed? Surely, this should not be the case when a more appropriate re-tracker is used. Could you also provide a measure of how much coverage HY-2B has compared with CryoSat-2? (e.g., how many points within each grid cell when gridding).

Your method of using 25 km segments and choosing leads based on the lowest 15 points within a segment still hasn’t fully convinced me. As mentioned, several times throughout your study, this will have different impacts: higher freeboards during freeze-up, lower freeboards during spring, and a difference across first-year ice (FYI) and multi-year ice (MYI). So, essentially, you have a known bias due to your choice of methodology that you are not accounting for. I think it would be necessary to provide a measure (average, modal, median – take your pick) of how often this is the case, e.g., by providing a statistical value of how many points you usually have within a 25 km segment, as well as the standard deviation of this (or min-max range, quantiles – again, take your pick) to understand the variability. In truth, we do not know how often it is the case that your method will be impacted using the 15 lowest points.

Furthermore, your method ensures a lead point every 25 km (if 15 points within a segment). Is this ‘enough’? Here, I am considering the fact that HY-2B’s footprint is 1.9 km across-track. In the study of Tilling et al. (2019), they compared CryoSat-2 and EnviSat, and saw that a lead-to-floe echo distance for EnviSat ranged from 0-20 km (average 11.3 km) – a satellite with a larger footprint, whereas for CryoSat-2 it ranged 0-4 km (mean of 1.0 km) – a satellite with comparable footprint. Somehow one lead observation every 25 km seems low.

Figure 1 in response to Reviewer#1 suggests that something odd is going on due to the limited lead observations identified using the selected PP threshold, since you are simply using a nearest neighbor interpolation – which makes me wonder; how come you use this interpolation? Many other studies use either linear or cubic interpolations, making the interpolation dependent on several points rather than just one. Furthermore, do you have a limit on how far away points are allowed to be from a lead observation, e.g., 200 km, which other studies have required.
In response to GC2 for Reviewer#1, you present a comparison with TFMRA50 product – which is not available in the SGDR product. How come you have not used this sea-ice specific re-tracker for the study instead of the SGDR? Please provide some justification/explanation for the choice of this re-tracker in the manuscript.

In response to GC2 from Reviewer#2, you conclude that the assumption of Ku-band penetrating to the snow-ice interface still holds based on former studies. However, more recent studies (Stroeve et al. 2020, 2022; Nab et al. 2022) have questioned this (with good reason). Since we do not currently have methods that can take into account this change of scattering horizon within the snowpack, I’d say the assumption is fair (and still widely used), however I do think that the topic warrants a discussion which is currently not given in the manuscript.

Also, based on several review comments, the uncertainty estimation procedure has been refined, and the results look more promising. However, when comparing with other studies (Ricker et al. 2014, Landy et al. 2020), the uncertainties estimated in this study (for both CS-2 and HY-2B) are in the lower range, which warrants a discussion. Also, consider separating your uncertainty estimates into ranges for MYI and FYI (like Ricker et al., 2014), since you also mention that you see different results depending on ice type.

Finally, I tried retrieving the data again. It was indeed necessary to create an account to access the FTP server, so I was not able to look at the data used for this study without creating a user (the user was not activated within deadline of this review). I suggest you write, in the data availability section, how to properly retrieve the data as you wrote in the response to reviews (especially since the website is not available with an English translation, thus limiting the potential user pool) to help other users get a hold of this data.

Please check again that all references are properly written. E.g., line 144 (new manuscript) should be ‘Tonboe et al. (2016)’ not ‘Rasmus et al. (2016)’.

Specific comments (references to line numbers in the new manuscript)

I highly encourage the authors to look over the text again. With the introduction of a several new paragraphs, there are several places where it could benefit from some proofreading.

Line 15-17. Your methodology has yet to be described, yet you mention specifics about how it is done. I suggest generalizing this sentence.
Line 17-20. Could you include a short sentence of how CryoSat-2 compare with OIB, for a perspective?
Line 22. I’m happy to see that the abstract has been shortened. Perhaps, you could include a short line on future work or current limitations for your work with HY-2B observations.
Line 59. “corrections” -> “processing steps”
Line 67. “The overall difference (…) AWI data is ” -> “They noted the average difference (…) AWI data to be ”
Line 69. “The radar freeboards are generally higher for HY-2B than CS-2” -> “They generally observed higher radar freeboards for HY-2B than CS-2”.
Line 70. “(…), the HY-2B satellite can be used to observe polar sea ice” -> “(…), the feasibility of using the HY-2B satellite to map the polar sea ice must be explored”. Please, also present limitations of your study (using already provided and re-tracked data rather than applying your own re-tracker etc.).
Line 84-85. Is “take into account the observations of sea ice” part of its main mission? I suggest rephrasing this sentence for clarity.
Line 88. Please provide a description of which stage the satellite is currently at and when the stages have started/ended.
Line 90. Waveforms have not been mentioned yet. Consider rephrasing this for clarity.
Line 96-97. Are the tracking modes named after the different re-trackers (OCOG, SMLE) or does HY-2B have to tracking modes based on surface, that tracks with different re-trackers? Consider rephrasing this, while also including a reference to what the “Brown” model is.
Line 114. Include which version (baseline) of ESA CryoSat-2 product you are using.
Line 196. MSS defined (by acronym) later than first used (used in MSS data section).
Line 199. You mention residual error – be careful with terms like error/uncertainties. Consider using a different term. Also, this is the first time you are mentioning anything about this residual “error”. Could you describe it more?
Line 207. Has SSHA been defined yet?
Line 209-210. “Since the (…)” -> consider rephrasing this or write the limitations in the introduction already, and then highlighting here, that you are simply using already provided elevations in the SGDR product.
Line 232 (Section 3.2). Aren’t these results? Consider moving them to the result section.
Line 241-242. “(…), which may have been caused by the fact that not all points within the 25 km segment are leads” -> “(…), which may have been caused by the fact that not all points used to estimate the SSHA within the 25 km segments originate from leads”.
Line 248. “totally overlapped” -> “fully coincident”
Line 249. Could you provide the exact time difference and overall spatial difference? If the difference is significant (in hours), perhaps a measure of drift might be provided as well, to imply how big of an impact drift may have in this comparison.
Line 308-310. Consider combining these two sentences (“Except (…)”) in the sentence starting in line 307: “The HY2-B sea ice thicknesses are thicker (…)” for clarity. Also, throughout the text, be aware of too many repetitions of practically the same text.
Line 331. What underestimation? It can be seen on the figures but has not been described in the text so far. Please include it.
Line 334. “The majority of the spread” -> “The majority of the spread (shown by RMSE or MAE)” – or however you see this spread, but link to it.
Line 339. The IS-2 snow freeboard is not subtracted from the AWI snow depths to obtain the sea ice freeboard. The AWI snow depths are subtracted from the IS-2 snow freeboards to obtain the sea ice freeboard. Please correct.
Line 342. Add which section this slower wave propagation correction has already been explained in, in the end of the sentence -> “(see Section …).
Line 348. “In addition (…)” – consider rephrasing this sentence for clarity.
Line 367. What is meant by a “larger” SSHA? I suggest rephrasing for clarity.
Line 434. Similar to the changes for the abstract, consider generalizing this sentence since you are talking specifics about a methodology that has not been described in your conclusion yet.

References
Landy, J. C., Petty, A. A., Tsamados, M., & Stroeve, J. C. (2020). Sea ice roughness overlooked as a key source of uncertainty in CryoSat-2 ice freeboard retrievals. Journal of Geophysical Research: Oceans, 125, e2019JC015820. https://doi.org/10.1029/2019JC015820
Nab, C., Mallett, R., Gregory, W., Landy, J., Lawrence, I., Willatt, R., et al. (2023). Synoptic variability in satellite altimeter-derived radar freeboard of Arctic sea ice. Geophysical Research Letters, 50, e2022GL100696. https://doi.org/10.1029/2022GL100696
Ricker, R., Hendricks, S., Helm, V., Skourup, H., and Davidson, M.: Sensitivity of CryoSat-2 Arctic sea-ice freeboard and thickness on radar-waveform interpretation, The Cryosphere, 8, 1607–1622, https://doi.org/10.5194/tc-8-1607-2014, 2014.
Stroeve, J., Nandan, V., Willatt, R., Dadic, R., Rostosky, P., Gallagher, M., Mallett, R., Barrett, A., Hendricks, S., Tonboe, R., McCrystall, M., Serreze, M., Thielke, L., Spreen, G., Newman, T., Yackel, J., Ricker, R., Tsamados, M., Macfarlane, A., Hannula, H.-R., and Schneebeli, M.: Rain on snow (ROS) understudied in sea ice remote sensing: a multi-sensor analysis of ROS during MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate), The Cryosphere, 16, 4223–4250, https://doi.org/10.5194/tc-16-4223-2022, 2022.
Stroeve, J., Nandan, V., Willatt, R., Tonboe, R., Hendricks, S., Ricker, R., Mead, J., Mallett, R., Huntemann, M., Itkin, P., Schneebeli, M., Krampe, D., Spreen, G., Wilkinson, J., Matero, I., Hoppmann, M., and Tsamados, M.: Surface-based Ku- and Ka-band polarimetric radar for sea ice studies , The Cryosphere, 14, 4405–4426, https://doi.org/10.5194/tc-14-4405-2020, 2020.
Tilling, R., Ridout, A., & Shepherd, A. (2019). Assessing the impact of lead and floe sampling on Arctic sea ice thickness estimates from Envisat and CryoSat-2. Journal of Geophysical Research: Oceans, 124, 7473– 7485. https://doi.org/10.1029/2019JC015232

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ED: Reconsider after major revisions (further review by editor and referees) (18 Jan 2023) by Vishnu Nandan

AR by Zhaoqing Dong on behalf of the Authors (22 Feb 2023) Author's response Author's tracked changes Manuscript

ED: Publish subject to revisions (further review by editor and referees) (22 Feb 2023) by Vishnu Nandan

ED: Referee Nomination & Report Request started (24 Feb 2023) by Vishnu Nandan

RR by Anonymous Referee #1 (05 Mar 2023)

Suggestions for revision or reasons for rejection

I’d once again like to thank the authors for their diligent response to all the reviews. This is my third time reviewing this paper, and I am happy to see that many of my concerns have been addressed in the current version of the manuscript.

The authors have now included statistics (cumulative probability) on how many points are used pr grid cell, clearly highlighting the limited coverage of HY-2B with the re-tracker provided in higher level products. They have also provided statistics (cumulative probability) on how often 25 km segments include 15 points or more. They have also included a discussion on their uncertainty estimates in relation to other studies, as well as provided a distinction in uncertainty estimates from multi-year ice and first-year ice.

Overall, I am happy with the changes that the authors have made based on my comments and within the scope of their study. I have a few comments, which are minor, but nonetheless should be considered by the authors to strengthen their publication in comparison to recently published studies.

General comments
During the review process of this paper, it has come to my attention that a new paper (Jiang et al., 2023) with similar motivation/objectives and with a, to a large degree, similar processing chain has been published, although they have included more products in their comparison. I think this study now requires a short section or paragraph on how this study differs from the already published study. Here, I especially encourage a discussion on how they use the lowest 3 points in their study to estimate the SSHA with the argumentation that one other study on Envisat observation has been published using this and how this is often applied to laser altimetry, as well as their use of a different re-tracker and geophysical corrections (maybe, the results on DTU21 MSS represented in an earlier response to the reviewers of this study could be included to aid this discussion). You might want to have a look at their reviewer reports/response, where this has also been questioned. However, I believe it is imperative that the authors clearly highlight the differences, and present why the results of this study are still relevant.

The authors mention in response to the reviewers, that their estimation method of 15 points within the segment yielding one lead point does not necessitate that there is only one lead along the segment. This is inherently clear, however that was not the concern raised in that question. What is important here – especially considering that the interpolation of lead points into floes are done by nearest neighbor – is the accuracy of that lead estimation point every 25 km segment. This has already been partly discussed with the cumulative probability statistics and the analysis you made with using a combination of numbers of points used to estimate SSHA. But, what was questioned previously was: is one point pr. 25 km enough to represent the SSHA, especially if that point could be affected by floe points in the estimation? Showing the distance between leads identified for other missions was to feed into the discussion of whether the estimation method of SSHA seems reasonable, and whether one SSHA pr. 25 km (since this is your estimation method) is accurate enough. I’ll leave it up to the authors to consider if more discussion is relevant here, but I strongly suggest the authors to reflect upon this – especially in relation to the recently published study, that used 3 points along the segment.

With the introduction of new sentences, there are several places where a read-through would be beneficial. I am aware that this comment was also given the last time, but it is simply to ensure the readability of the manuscript, and since there have been a significant number of new/edited sentences, I encourage the authors to have a look at them again and see if they can improve on this.

Specific comments
Line 24: “we will …” -> I suggest rephrasing this sentence. Somehow it sounds like your not happy with your results. Perhaps mention that future work will include reprocessing the data with a dedicated sea ice re-tracker, and that a further investigation of using the radar waveforms directly to identify leads will be the next steps.

Line 254: In the review comments you mention that the satellites passes with about 3 hour difference, but the way it is written here sounds like almost 2 weeks of difference. Could you please clarify that you are comparison two instances, and that for each date denote the time differences between HY-2B and CS-2 acquisition.

References
Jiang, M.; Zhong, W.; Xu, K.; Jia, Y. Estimation of Arctic Sea Ice Thickness from Chinese HY-2B Radar Altimetry Data. Remote Sens. 2023, 15, 1180. https://doi.org/10.3390/rs15051180

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ED: Publish subject to minor revisions (review by editor) (05 Mar 2023) by Vishnu Nandan

AR by Zhaoqing Dong on behalf of the Authors (09 Mar 2023) Author's response Author's tracked changes Manuscript

ED: Publish as is (09 Mar 2023) by Vishnu Nandan

AR by Zhaoqing Dong on behalf of the Authors (10 Mar 2023) Manuscript

Journal article(s) based on this preprint

31 Mar 2023

Feasibility of retrieving Arctic sea ice thickness from the Chinese HY-2B Ku-band radar altimeter

Zhaoqing Dong, Lijian Shi, Mingsen Lin, Yongjun Jia, Tao Zeng, and Suhui Wu

The Cryosphere, 17, 1389–1410, https://doi.org/10.5194/tc-17-1389-2023,https://doi.org/10.5194/tc-17-1389-2023, 2023

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Zhaoqing Dong et al.

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With the development of satellite altimeters, satellite altimeter technologies have been increasingly used to retrieve Arctic sea ice thicknesses and have achieved rapid application. However, few reports have explored the retrieval of sea ice thickness by Chinese altimeters among recent studies. Therefore, it is of great significance to obtain reliable Arctic sea ice thickness products based on the China HY-2B radar altimeter to provide data support for the study of long-term changes in sea ice.


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