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Article
Peer-Review Record

Long-Term Ice Conditions in Yingkou, a Coastal Region Northeast of the Bohai Sea, between 1951/1952 and 2017/2018: Modeling and Observations

Remote Sens. 2022, 14(1), 182; https://doi.org/10.3390/rs14010182
by Yuxian Ma 1,2, Bin Cheng 3, Ning Xu 2, Shuai Yuan 2,*, Honghua Shi 4 and Wenqi Shi 2
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Reviewer 4: Anonymous
Remote Sens. 2022, 14(1), 182; https://doi.org/10.3390/rs14010182
Submission received: 13 December 2021 / Revised: 27 December 2021 / Accepted: 29 December 2021 / Published: 1 January 2022
(This article belongs to the Special Issue Remote Sensing of Sea Ice and Icebergs)

Round 1

Reviewer 1 Report

The authors have addressed all my comments satisfactory. 

Author Response

thank you.

Reviewer 2 Report

Dear authors,

thanks for this revised version. I am now fine with the manuscript being published.

Author Response

thank you.

Reviewer 3 Report

This paper used modeling approach to provide long-term ice conditions in Yingkou coastal region. The topic is of great interest and the method sounds workable. I suggest accepting this paper after taking serval minor revisions.

1. Lines 79-80, ‘Understanding changes in long-term ice conditions would require long-term, sustainable, in-situ observations, which is a big challenge in the Bohai Sea.’
Please give more details about why understanding the long term-ice conditions is a big challenge for this region, e.g. large uncertainties of modeling approach or clouds on remotes sensing images that hinder from monitoring sea ice changes routinely?

2. Many figures such as Figs. 2&3 are too blur to be easily read. Therefore, I believe a significant enhancement for those figures is necessary. 

Author Response

Dear Professor. the reply is in the attachment. Thank you.

Author Response File: Author Response.pdf

Reviewer 4 Report

The authors present an interesting long-term range of ice phenomena data for the Bohai Sea. I recommend the paper for publication after comments have been made.

Figure 1: Lack of location of in situ measurements.

 A major comment concerns the lack of reference of the results obtained to the influence of rivers on ice cover formation and destruction. The authors concentrate on climatic conditions (including macro-scale circulation), completely ignoring local factors. It should be noted that the Bohai Sea is semi-enclosed, influenced by factors such as rivers (especially Liaodong Bay). The inflow of river water with a different chemical composition than sea water, moreover, the energy associated with the inflow will significantly affect the course of the issue under analysis: the formation/decay of ice cover. How are the flow trends of the Daliao River shaped?

Another issue- how was the sea ice separated from the ice flowing in from the river?

Figure 7: The figure description does not start with "a". The same way "b" should be after the description

Figure 11: Similar to Figure 7.

Figure 9 is unreadable to the viewer. In the case of modeled seasonal average ice thicknesses, maybe it is worth using e.g. black colour?

Author Response

Dear Professor. the reply is in the attachment. Thank you.

Author Response File: Author Response.pdf

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

1)
There is no snowy data in the input value of Table 1.
Did the influence of snowy ignore?
Moreover, has the flow of water ignored in this computational model?
When these are disregarded, what is the reason?

2)
Only in the one period of 2017 to 2018, I think that examination of a calculated value is insufficient.
Please describe the idea about this point.

3)
Although the initial value of a calculated value is 5 cm, I think that this value is large.
Please describe this reason.

4)
The vertical axis of Fig. 11 is a minus display.
Please check, and please description of explanation of a figure.

5)
In Fig. 12, I think that the maximum and average value are reversed.
Please check.

Author Response

1. There is no snowy data in the input value of Table 1. Did the influence of snowy ignore? Moreover, has the flow of water ignored in this computational model? When these are disregarded, what is the reason?

The HIGHTSI model is entitled as “High-resolution Thermodynamic Snow and Ice model”, so snow thermodynamics is an important component of HIGHTSI (e.g., Launiainen and Cheng, 1998, Cheng et al., 2003 and 2008). However, for this case study, snow was not considered. Because snow was very thin on top of the Bohai Sea ice. Therefore, we didn’t add snow physics in Table1.

“The flow of water” was parameterized as the oceanic heat flux (Fw). So, no, we didn’t ignore this factor. In this study we assumed it as 2W/m2 and it was mentioned in the Table 1.

2. Only in the one period of 2017 to 2018, I think that examination of a calculated value is insufficient. Please describe the idea about this point.

The ice winter season (2017/2018) was simulated, and the results were compared with various in situ observations. This seasonal ice mass balance simulation was used to validate HIGHTSI model before making multi-decadal (67 winter seasons) simulations. This model validation period is much longer than typical model validation modelling experiment which usually last for only a few weeks (e.g., Launiainen and Cheng, 1998) or even less (Cheng et al., 2008). Thus, we think one seasonal validation is sufficient for model validation.

3.Although the initial value of a calculated value is 5 cm, I think that this value is large. Please describe this reason.

We applied a model initialization procedure. The initial ice thickness (5cm in this case) is an assumption for model calculation to start with. In some seasons, even in the beginning of December, the weather condition may not be favorable for ice formation, so this initial 5 cm ice may subject to melting and if this is happened, we will resume ice to be 5cm again. The initial ice formation is defined as when ice thickness starts to growth continuously and only from that moment the ice freezing-up date is defined. This procedure allows ice simulation to be started in any time before ice freezing up season and has been used before for lake and sea ice conditions (Yang et al., 2012, Zhai, et a., 2021). Another reason for us to use 5 cm is that since the dynamic impact on ice thickness was large due to wave/tide and wind in the Bohai Sea, the ice thickness is rarely sustainable below 5 cm.

Before large areas of sea ice freeze in Liaodong Bay, thinner sea ice is easily broken under the influence of wind, current and waves, so the initial value is calculated using 5cm.

4. The vertical axis of Fig. 11 is a minus display.
Please check, and please description of explanation of a figure.

Corrected.

5. In Fig. 12, I think that the maximum and average value are reversed. Please check.

Yes, indeed, we made correction accordingly.

Author Response File: Author Response.pdf

Reviewer 2 Report

The discussion and conclusions should be seperated, and english writing should be improved.

Author Response

Thank you for your assessment on our manuscript. We have carried out a major revision to improve the clarity of result and conclusions. The manuscript has been checked by professional language service

Reviewer 3 Report

Review

 

The manuscript models the sea ice growth and extend in the Bohai sea. The manuscript is clearly structured and reasonably well written. It could benefit from a few less figures to bring home the main message.

Major changes

Figure 5. Perhaps R2 values could be added to the figures, or the linear relationship for the line be added?

Are there any in-situ data that could be added to the figure 7 or to the analysis that would corroborate the freeze-up date? It would add strength to the analysis.

Figure 12. The maximum sea ice thickness is lower than the mean thickness, this seems very strange. Please check this figure to confirm that it is correct.

Perhaps you can combine figures 13 and 15 as they are very complementary to each other. Or for Figure 13 show the combined results but also show the results for, e.g., the 1950s and the 2000 to illustrate any changes between the different time eras. Overall consider if all of figures 13-15 are necessary or if they in fact show similar information and hence some of them can be removed.

The results correspond to some degree to those presented in [37], are those results also modelling based or are they in-situ data based? This could be further discussed in the discussion section, or at least be made clearer to the reader. Further connections to changes of length of season in other parts of the world could perhaps also be mentioned in the discussion section, e.g., work by e.g., Muckenhuber et al (2016) and Johansson et al (2020) investigated changes in timing of sea ice freeze-up and melt onset in Svalbard fjords where sea ice only exists for part of the year.

Minor changes

P1R13-14. For how many years were the model validated?

P1R22-23. Unclear sentence please revise.

P1R22-24. Unclear sentence please revise.

P1R24- …level ice is delayed…

P1R29. YingKou Sea, shouldn’t this be the Bohai Sea?

P2R68. A recent study…

Change Radar to radar throughout the manuscript

P5R173. Talk -> take

P6R19. Down -> done

P7R231 deformation -> deform

P7R244. Highest/lowest instead of most?

P8R266. Sea ice growth / extent?

P9R277. Change hardly to not likely

Table 5. It’s unclear if 14th of January was the timing of onset for both 1990s and 2000s. Please add date for both time periods even if they are the same to avoid confusion.

References

Muckenhuber S, Nilsen F, Korosov A and Sandven S (2016) Sea ice cover in Isfjorden and Hornsund, Svalbard (2000–2014) from remote sensing data. The Cryosphere 10, 149–158. doi: 10.5194/tc-10-149-2016

Johansson AM, Malnes E, Gerland S, Cristea A, Doulgeris AP, Divine DV, Pavlova O, Lauknes TR (2020). Consistent ice and open water classification combining historical synthetic aperture radar satellite images from ERS-1/2, Envisat ASAR, RADARSAT-2 and Sentinel-1A/B. Annals of Glaciology 1–11. Doi: 10.1017/ aog.2019.52

Author Response

1.Figure 5. Perhaps R2 values could be added to the figures, or the linear relationship for the line be added?

This figure tells the time series of investigated parameters rather than comparison between two time series. We included the linear trends.

2.Are there any in-situ data that could be added to the figure 7 or to the analysis that would corroborate the freeze-up date? It would add strength to the analysis.

Unfortunately, the initial ice freezing up was not observed. In early winter, the local coastal sea ice often experienced freezing up and thawing breakup cycle. We have added some analyses.

3.Figure 12. The maximum sea ice thickness is lower than the mean thickness, this seems very strange. Please check this figure to confirm that it is correct.

This was a technical mistake in figure legend, and the error was corrected.

4.Perhaps you can combine figures 13 and 15 as they are very complementary to each other. Or for Figure 13 show the combined results but also show the results for, e.g., the 1950s and the 2000 to illustrate any changes between the different time eras. Overall consider if all of figures 13-15 are necessary or if they in fact show similar information and hence some of them can be removed.

Those figures tell difference results, and we would prefer to keep them but, we reorganized them and merged them together for compactness and better clarity.

5.The results correspond to some degree to those presented in [37], are those results also modelling based or are they in-situ data based? This could be further discussed in the discussion section, or at least be made clearer to the reader. Further connections to changes of length of season in other parts of the world could perhaps also be mentioned in the discussion section, e.g., work by e.g., Muckenhuber et al (2016) and Johansson et al (2020) investigated changes in timing of sea ice freeze-up and melt onset in Svalbard fjords where sea ice only exists for part of the year.

Thank you for your suggestion, we have added discussions and compared our results with those previously studies.

Minor changes

P1R13-14. For how many years were the model validated?

The validation was made for one season and the results were compared with various in situ observations. This seasonal ice mass balance simulation was used to validate HIGHTSI model before making multi-decadal (67 winter seasons) simulations. This model validation period is much longer than typical model validation modelling experiment which usually last for only a few weeks (e.g., Launiainen and Cheng, 1998) or even less (Cheng et al., 2008). Thus, we think one seasonal validation is sufficient for model validation.

P1R22-23. Unclear sentence please revise.

The sentence was reformulated

P1R22-24. Unclear sentence please revise.

The sentence was reformulated

P1R24- …level ice is delayed…

Modified.

P1R29. YingKou Sea, shouldn’t this be the Bohai Sea?

Changed to Yingkou region of the Bohai Sea.

P2R68. A recent study…

Modified.

Change Radar to radar throughout the manuscript

Updated accordingly.

P5R173. Talk -> take

Done.

P6R19. Down -> done

Corrected.

P7R231 deformation -> deform

Done.

P7R244. Highest/lowest instead of most?

Done.

P8R266. Sea ice growth / extent?

A total 67 winters sea ice mass balance were simulated

P9R277. Change hardly to not likely

Changed.

Table 5. It’s unclear if 14th of January was the timing of onset for both 1990s and 2000s. Please add date for both time periods even if they are the same to avoid confusion.

Yes, it is, we updated the table layout for better clarity

Author Response File: Author Response.pdf

Reviewer 4 Report

Dear authors,

thank you for your submission. I have compiled my comments in the attached PDF.

Comments for author File: Comments.pdf

Author Response

Thank you for your assessment on our manuscript. We have carried out a major revision.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

This paper became useful by suitable correction.
Thank you.

Reviewer 2 Report

The authors have answered all of the questions and comments raised by the reviews and English language  and style of the manuscript have been improved.

Reviewer 4 Report

Dear authors, thanks for submitting this revised version. I have again collected my comments in the attached PDF.

Comments for author File: Comments.pdf

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