Multiple Sea Ice Type Retrieval Using the HaiYang-2B Scatterometer in the Arctic
Round 1
Reviewer 1 Report (Previous Reviewer 1)
see attached document
Comments for author File: 
Comments.pdf
Author Response
Thank you very much for your constructive comments.Please see the attachment.
Author Response File: 
Author Response.docx
Reviewer 2 Report (Previous Reviewer 3)
Review on “Refinement classification of Arctic sea ice based on HaiYang-2B scatterometer”, by Lu Han, Haihua Chen, Lei Guan and Lele Li, submitted for publication in Remote Sensing.
General comments :
The paper develops a method to retrieve sea ice type using remote sensing scatterometer onboard the HaiYang-2B satellite. Previous studies focused on distinguishing between first-year ice (FYI) and multi-year ice (MYI) only, whereas the present work expands the approach to identify Nilas, Young Ice, and Fast Ice. The retrieval algorithm relies on methods developed in the field of machine learning.
The results show user accuracies of 70.28%, 77.69%, and 67.44% for Nilas, Young Ice, and Fast Ice, respectively over the test period from October 2021 to April 2022. Compared against OSI-SAF ice type product, the method proposed in the present paper (Stacking-HY2B) seems to be better at distinguishing FYI from MYI for at least one case shown (2022-03-01). However, on average over the period from November 2021 to March 2022, OSI-SAF outperforms the Stacking-HY2B algorithm. The verification against EM-Bird contains mainly old, thick ice, which cannot assess the accuracy of Stacking-HY2B with respect to the classification of Nilas and Young Ice.
Since it is the first publication of an automated method refining the ice type (refining here means more different ice types, not necessarily better classification), there is no other study to compare with. So it land a benchmark for the classification of ice type like Nilas, Young Ice, and Fast Ice. It is not clear if the results obtained in this study for Nilas, Young Ice, and Fast Ice could be useful, given the relatively low accuracy (between 67% to 77%).
The manuscript has improved from the first version. Below you will find some more suggestions to further improve the paper.
Specific comments :
Line 51: “σ0” should be “σ0” like on line 53.
Line 73: “bright temperature” should be “brightness temperature”.
Line 78: “scattermeters” should be “scatterometers”.
Line 79: Final dot “.” is missing.
Line 103: “October 2021 to April 2021” should probably be “October 2021 to April 2022”. Also, the final dot “.” is missing.
Line 147: (NISIDC) should be (NSIDC).
Line 153: Final dot “.” is missing.
Line 164: “it include” should be “it includes”.
Lines 163-167: “MOSAiC” is defined in 2 different ways in this paragraph. Please use only one.
Figure 1: Is “Fast Ice” also included in one of the other categories, or is “Fast Ice” a separate category ?
Line 248: “the σ0 has always between…” should be something like “the σ0 is always between…”
Line 279: “Figure 3,” should be “Figure 3.” since that is the end of the sentence.
Figure 7: This figure needs better resolution. The characters are very small, and when zoomed to be able to read them, they are blurred.
Table 3: “Nials” should be “Nilas”. Also the title does not seem to match the content of the table.
Lines 420, 421, 502: “Nials” should be “Nilas”.
Figure 13: The first part of the caption does not belong there. Please remove.
Author Response
Thank you very much for your constructive comments.Please see the attachment.
Author Response File: Author Response.docx
This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.
Round 1
Reviewer 1 Report
see attached document
Comments for author File: Comments.pdf
Reviewer 2 Report
In this paper, the Arctic refined sea ice type is retrieved using the scatterometer data onboard HY2B satellite. The algorithm is innovative, and the following suggestions are proposed to be modified and improved:
1. Topic: it is suggested to delete ‘satellite’.
2. The stacking model in this paper is an innovation. It is recommended to introduce it in detail.
3. CMEMS SAR product is used for the algorithm validation, but the area of the datasete is limited and not representative enough. It is recommended to add some validation data of other regions in the Arctic.
4. The refined sea ice classification results are recommended to be validate by ship or buoy data.
5. For HY2B scatterometer data in 2.1.1, it should add a reference.
6. The title of Section 3 is suggested to be modified to ‘process and result’, otherwise it is the same as the title of section 3.6.
7. References need to be improved, for example, the name of the sixth literature conference is wrong.
Reviewer 3 Report
Review on “Refinement classification of Arctic sea ice based on HaiYang-2B satellite scatterometer”, by Lu Han, Haihua Chen, Lei Guan and Lele Li, submitted for publication in Remote Sensing.
General comments :
The paper develops a method to retrieve sea ice type using remote sensing scatterometer onboard the HaiYang-2B satellite. Previous studies focused on distinguishing between first-year ice (FYI) and multi-year ice (MYI) only, whereas the present work expands the approach to include Nilas, Young Ice, and Fast Ice. The retrieval algorithm relies on methods developed in the field of machine learning. The verification focuses mainly on FYI and MYI.
One of the weaknesses of the study is that it includes Fast Ice into the MYI category when only FYI and MYI are available in the verification dataset. I think Fast Ice should be discarded in this case.
The other aspect that could be improved is the verification of the new ice types that are considered in this study, namely Fast Ice, Nilas, and Young Ice. So all five ice type categories could be included in the verification using the AARI dataset. Only an example for October 23, 2020 is shown (Figure 7) but that data was already included in the training set. The verification should be shown on independent data (2021-2022 AARI data set). In addition, Young Ice, FYI, and MYI could be evaluated using the CMEMS dataset.
Specific comments :
Line 79: Should that be CMIP6 instead of CIMP6 ?
Line 97: The references in the text do not match those found in the references section. For example, OSI-SAF has tag [17] in the text but it should be [16]. Please carefully revise all references in the text to make sure they match the list in the references section.
Figure 1: What is “Normalized Height” ? Is the backscatter VV or HH ?
Figure 2: The legend shows “Ice Type Diff”. What does mean the “Diff” ?
Lines 251-253: The description of the polarization for MYI in the text does not seem to match what it can be seen in Figure 3 for Old Ice. The polarization difference is always negative and (VV+HH) is distributed between -26 and -18 dB. Please explain.
Line 267: The paper of Haarpaintner should be tagged [24], not [25] (or change the numbering in the references section).
Figure 10: Area b is the result that Fast Ice was misclassified as MYI. Actually, Fast Ice can be FYI in some places like that, while in other places Fast Ice is MYI. I think it would be better to remove Fast Ice from the comparison against OSI-SAF.
Line 442: The time series are shown in Figure 12, not 11.
Figure 12: Please change “presicion” to “precision” in the title of the graph and on the y-axis. In the text, ”accuracy” is described while the figure shows “precision”. Please use consistent nomenclature to avoid confusion.
Line 463: What is “SIA” ? I Think it means Sea Ice Age, but that should be clarify in the text.
Lines 504-505: I don’t think that this affirmation is fully supported by the results shown in this paper. The “refined” aspect of the analysis was to include more ice types, i.e. Nilas, Young Ice and Fast Ice, which were generally not included in other studies. The verification is lacking for these ice types in the paper.
