Interannual Variability of Winter Sea Levels Induced by Local Wind Stress in the Northeast Asian Marginal Seas: 1993–2017

Round 1

Reviewer 1 Report

Review jmse-925121 : Interannual variability of winter sea levels induced by local wind stress in the northeast Asian marginal seas: 1993–2017 by MyeongHee Han , SungHyun Nam , Yang-Ki Cho , Hyoun-Woo Kang , Kwang-Young Jeong , Eunil Lee

The authors investigate interannual changes in mean winter (November and December) regional sea level in the northeast Asian marginal seas of the order of 4 cm. They show qualitatively that anomalous Ekman currents in the inflow and outflow regions and related divergence/convergence in the marginal seas play a key role. The anomalous Ekman currents are related to local patterns of the east Asian winter monsoon and hence to the strength and the position of the Aleutian Low, remote forcing is of minor importance. They are able to predict the interannual winter sea levels from local wind stress anomalies and even from local SLP.

The paper is well and comprehensively written. It would be interesting to know whether the proposed mechanism is working only during November and December or also for other months. The authors show that there might be a connection to the North Pacific Gyre Oscillation as well. Did you try to include the NGPO-Index and the WNS-Index together in the regression? Are there steric changes in the Northeastern Pacific that correlate with the changes in the marginal seas?

I would recommend the publication of the paper with minor changes.

Minor Comments

- is there a special reason why you stop your analysis in 2017?

- could you elaborate why you use only data from November and December to define your winter sea level

- figure 7 lower panel: what’s the meaning of the dark grey boxes in the upper part of the figures?

- figure 10 caption: check NSI=WNSI?

- formulas 2 ,3 , 4: I would prefer to have conventional formulas with explanations and numbers given in the text, it is difficult to read this way

- p 14, 368-373 check sentences (missing verbs)

Author Response

Reviewer #1

Review jmse-925121 : Interannual variability of winter sea levels induced by local wind stress in the northeast Asian marginal seas: 1993–2017 by MyeongHee Han , SungHyun Nam , Yang-Ki Cho , Hyoun-Woo Kang , Kwang-Young Jeong , Eunil Lee

The authors investigate interannual changes in mean winter (November and December) regional sea level in the northeast Asian marginal seas of the order of 4 cm. They show qualitatively that anomalous Ekman currents in the inflow and outflow regions and related divergence/convergence in the marginal seas play a key role. The anomalous Ekman currents are related to local patterns of the east Asian winter monsoon and hence to the strength and the position of the Aleutian Low, remote forcing is of minor importance. They are able to predict the interannual winter sea levels from local wind stress anomalies and even from local SLP.

The paper is well and comprehensively written. It would be interesting to know whether the proposed mechanism is working only during November and December or also for other months. The authors show that there might be a connection to the North Pacific Gyre Oscillation as well. Did you try to include the NGPO-Index and the WNS-Index together in the regression? Are there steric changes in the Northeastern Pacific that correlate with the changes in the marginal seas?

(Response) Thank you very much for these important and constructive comments. Based on the inputs provided by your comments, we have now added the results of the multiple linear regression analysis to include both remote (NPGO) and local (WNSI) indices in the revised manuscript (Section 3.4 Atmospheric Pressure Disturbances and the Winter NEAMS Sea Level Index (WNSI)). The correlation coefficient for NPGO + WNSI is 0.78, which is higher than those for WNSI (0.62) and NPGO (0.41) as the interannual variability of the steric changes in the Northeastern Pacific is not totally irrelevant to the NEAMS mean sea level. In this study, however, our focus is on the sea level changes including wind-driven mass convergence/divergence and steric changes that are averaged over the NEAMS region, and not the Northeastern Pacific. Our results, as discussed in Section 4, indicate that the steric changes are relatively minor and the local wind-driven (but affected by large-scale atmospheric disturbance, e.g., the Aleutian Low) horizontal mass convergence/divergence is dominant in the NEAMS mean sea level.

I would recommend the publication of the paper with minor changes.

(Response) We thank you for your positive and encouraging comment.

Minor Comments

- is there a special reason why you stop your analysis in 2017?

(Response) We chose the data period (from 1993 to 2017) with no specific intention except for the fact that we wanted to use the most recent data. Inclusion of satellite altimeter data collected and processed for the year 2018 did not make any meaningful change to our conclusion.

- could you elaborate why you use only data from November and December to define your winter sea level

(Response) We compared the results for a few different definitions of winter; 1) December–January–February (DJF), 2) January–February–March (JFM), 3) December–January (DJ), 4) January–February (JF), and 5) November–December (ND). The reason we selected the definition of 5) in this paper is that the interannual variations of the NEAMS-mean sea level is large and it is most correlated with the local wind forcing that we analyzed for these two months. Following your and the other reviewers’ comments on this point, we have described these considerations in the revised manuscript in Section 2

- figure 7 lower panel: what’s the meaning of the dark grey boxes in the upper part of the figures?

(Response) It denotes the ice-covered area. The description was added to the figure caption based on your comment (Figure 6 of the revised version).

- figure 10 caption: check NSI=WNSI?

(Response) The typographical error was fixed in the revised version (Figure 9 of the revised manuscript).

- formulas 2 ,3 , 4: I would prefer to have conventional formulas with explanations and numbers given in the text, it is difficult to read this way

(Response) Following your and other reviewers’ comments, we have changed the formulas to the conventional form with symbols/notations and added a table with numbers in the revised manuscript.

- p 14, 368-373 check sentences (missing verbs)

(Response) We have corrected the sentences based on your comment. 

Author Response File: Author Response.docx

Reviewer 2 Report

I found the manuscript interesting and the science is sound. I recommend acceptance after minor revision. My comments to the authors are the following (numbers refer to lines):

15: Please justify this particular choice of months. Why didn't the authors use December-January-February or January-February-March?

22-25: Try to join these two sentences to avoid "in other words".

39-42: The authors need to add references to this statement.

52-55: Please provide a reference.

58 (and others): Please check that this reference style is in agreement with the journal style. 

Figure 1: Please add the abbreviations of the water bodies, as they are used throughout the text instead of their names. Also, information about the bathymetry would help the reader.

122-124: How do you justify using climatological data, that removes interannual variations, in a study of interannual variability?

149-153: The meaning of this paragraph is not very clear. Are you saying that the winter (ND) mean sea level anomalies are more determinant to the annual values that those of the other months? Please clarify.

163: Why 0.019 m?

225-229 (and elsewhere): Please, remove the detailed calculations as they clutter the text and make it difficult to follow. If you wish to show the numerical parameters used, please use a table.

Eqs (2) and (4): Please use mathematical notation. If you wish, after the equation you can explain the meaning of the terms.

283-284. Here, the authors needs to substantiate this claim with more data, such as the correlation coefficient between SLA_NEAMS and these indices.

Author Response

Reviewer #2

I found the manuscript interesting and the science is sound. I recommend acceptance after minor revision.

(Response) We thank you for your positive and encouraging comment.

My comments to the authors are the following (numbers refer to lines):

15: Please justify this particular choice of months. Why didn't the authors use December-January-February or January-February-March?

(Response) We compared the results for a few different definitions of winter; 1) December–January–February (DJF), 2) January–February–March (JFM), 3) December–January (DJ), 4) January–February (JF), and 5) November–December (ND). The reason we selected the definition of 5) in this paper is that the interannual variations of the NEAMS-mean sea level is large and it is most correlated with the local wind forcing that we analyzed for these two months. Following your and the other reviewers’ comments on this point, we have described these considerations in the revised manuscript in Section 2.

22-25: Try to join these two sentences to avoid "in other words".

(Response) Based on your and other reviewers’ comments, we have rewritten the sentences in the revised manuscript.

39-42: The authors need to add references to this statement.

(Response) There were references [1, 2] at line 43 of the original manuscript (line 38 of the revised manuscript)

52-55: Please provide a reference.

(Response) The references were added to the sentence in the revised manuscript.

58 (and others): Please check that this reference style is in agreement with the journal style. 

(Response) We changed the reference style to match the journal style based on your comment.

Figure 1: Please add the abbreviations of the water bodies, as they are used throughout the text instead of their names. Also, information about the bathymetry would help the reader.

(Response) Based on your comment, we have added abbreviations of the water bodies and bathymetry (colors) to Fig. 1b in the revised manuscript.

122-124: How do you justify using climatological data, that removes interannual variations, in a study of interannual variability?

(Response) The climatological mean temperature and salinity data were used to estimate the thermal expansion coefficient as a function of temperature and salinity. Our intention is not to consider interannual variation of the thermal expansion coefficient but use the range of the interannual variability in the air–sea heat exchange resulting in the thermosteric sea level via the turbulent heat flux by using the coefficient. We have clarified this point in the revised manuscript.

149-153: The meaning of this paragraph is not very clear. Are you saying that the winter (ND) mean sea level anomalies are more determinant to the annual values that those of the other months? Please clarify.

(Response) Our intention is to better describe the relationship of the annual mean sea level anomalies with the winter mean sea level anomalies than with those of the other months. We clarified the sentences based on your comment.

163: Why 0.019 m?

(Response) The threshold was determined to arrive at equal number of years with positive and negative anomalies (at six years each).

225-229 (and elsewhere): Please, remove the detailed calculations as they clutter the text and make it difficult to follow. If you wish to show the numerical parameters used, please use a table.

(Response) Following your and other reviewers’ comments, we have changed the formulas to the conventional form with symbols/notations and added a table with numbers in the revised manuscript.

Eqs (2) and (4): Please use mathematical notation. If you wish, after the equation you can explain the meaning of the terms.

(Response) As mentioned above, we have changed the formulas to the conventional form with symbols/notations and added a table with numbers in the revised manuscript following your and other reviewers’ comments.

283-284. Here, the authors needs to substantiate this claim with more data, such as the correlation coefficient between SLA_NEAMS and these indices.

(Response) Following your and other reviewers’ comments, we have included the correlation coefficients of all the indices in the revised manuscript.

Author Response File: Author Response.docx

Reviewer 3 Report

I thank you the authors for such a pleasant reading.
The paper is well written, I agree with the methodological approach, I could see you really paid attention to the Figure editing and captions (they are clear).
Moreover, I feel the you did not spend much time to write the Introduction. It appears short and poor of adequate background. It must be improved to express the real importance of the study also in relation with the international scientific community finding.

You will find further suggestions in the attached file.

Abstract:
• please avoid the adoption of acronyms, you may extensively use them in the Introduction.
• Try to clarify with different sentences the expressions between rows 22 and 30 (please avoid the adoption of expression like: "In other words").

Introduction:
• I found it quite short
• The importance of the study on sea level variation in basin/coastal scale is not sufficiently addressed and poor of references.
• I think you have space to add some words more on the geography of the study site
• 67-73 expand this part. explain better the work you have hardly performed.
• In general Nov Dec is a good representation of winter season?

Methods:
• If you want to use the form: "(not shown)", you should try to better convince the reader about such preliminary work you have performed. By the way I think you can add Appendix or supplementary material on this topic.Result:
• Could you convince the reader that considering for instance a subsample of 1993-2017 or including more years in the dataset the spread you are speaking about in figures 2 is effectively poor in January?
• In figure 2d, can you find a way to show all other years instead of showing only 2016 and 2017?
• We should be sure we can speak about "winter" when considering only ND. This problem of course is found all along the manuscript and I think it should addressed trying to better explain the scientific reasons of such choice and with a semantic approach. I think it is not sufficient, for me, to read for instance "....focusing on the winter (November and December; ND) ......... in which the interannual spread is relatively large."

Discussion & Conclusions:
• Ok, I provide specific suggestions on the attached manuscript_suggestions.

Comments for author File: Comments.pdf

Author Response

Reviewer #3

I thank you the authors for such a pleasant reading.
The paper is well written, I agree with the methodological approach, I could see you really paid attention to the Figure editing and captions (they are clear).
Moreover, I feel the you did not spend much time to write the Introduction. It appears short and poor of adequate background. It must be improved to express the real importance of the study also in relation with the international scientific community finding.

You will find further suggestions in the attached file.

Abstract:
• please avoid the adoption of acronyms, you may extensively use them in the Introduction.

(Response) Thank you very much for your encouragement, constructive comments, and great suggestions. Following your comments, we have modified the abstract and used only two acronyms (expanded in the abstract itself) to meet with the word limit prescribed for the abstract by the journal.

• Try to clarify with different sentences the expressions between rows 22 and 30 (please avoid the adoption of expression like: "In other words").

(Response) Following your and other reviewers’ comments, we have changed the abstract to clarify the meaning with separate sentences and avoided expressions like “In other words.”

Introduction:
• I found it quite short
• The importance of the study on sea level variation in basin/coastal scale is not sufficiently addressed and poor of references.

(Response) Following your and other reviewers’ comments, we have rewritten and highlighted the importance of this study and included more references in the revised manuscript.

• I think you have space to add some words more on the geography of the study site

(Response) Following your and other reviewers’ comments, we have included descriptions on the local geographical characteristics (and with information on bathymetry included in the new Figure 1b) in the revised manuscript.

• 67-73 expand this part. explain better the work you have hardly performed.

(Response) As mentioned above, we have rewritten the entire Section including these sentences and included more references in the revised manuscript.

• In general Nov Dec is a good representation of winter season?

(Response) We compared the results for a few different definitions of winter; 1) December–January–February (DJF), 2) January–February–March (JFM), 3) December–January (DJ), 4) January–February (JF), and 5) November–December (ND). The reason we selected the definition of 5) in this paper is that the interannual variations of the NEAMS-mean sea level is large and it is most correlated with the local wind forcing that we analyzed for these two months. Following your and the other reviewers’ comments on this point, we have described these considerations in the revised manuscript in Section 2.

Methods:
• If you want to use the form: "(not shown)", you should try to better convince the reader about such preliminary work you have performed. By the way I think you can add Appendix or supplementary material on this topic.

(Response) Following your comments, we have removed “not shown” and have included descriptions on the results of the sensitivity test in the revised manuscript.

Result:
• Could you convince the reader that considering for instance a subsample of 1993-2017 or including more years in the dataset the spread you are speaking about in figures 2 is effectively poor in January? 

(Response) Following your comments, we have added uncertainty bars to Figure 2d using the estimated standard deviations of the interannual spread from 25 different subsamples of a monthly series for a period of 24 years among the total study period of 25 years.

• In figure 2d, can you find a way to show all other years instead of showing only 2016 and 2017?

(Response) Following your comments, we have included plots of sea level anomalies for years other than 2016 and 2017 to Figure 2c, particularly for the two groups of Periods H and L.

• We should be sure we can speak about "winter" when considering only ND. This problem of course is found all along the manuscript and I think it should addressed trying to better explain the scientific reasons of such choice and with a semantic approach. I think it is not sufficient, for me, to read for instance "....focusing on the winter (November and December; ND) ......... in which the interannual spread is relatively large."

(Response) As mentioned above, we selected these two months (ND) to define winter in this paper as the interannual variations of the winter sea level with a relatively large variance were best correlated with the local index that we have developed (presenting what we can explain) as described in the revised manuscript.

Discussion & Conclusions:
• Ok, I provide specific suggestions on the attached manuscript_suggestions.

Before to move toward site/ocean description I would suggest to write some more information/references about :” increasing concern about the regional sea level variability”.

(Response) Following your and other reviewers’ comments, we have included more references and descriptions on previous findings in the revised manuscript.

I think You can remove this filename

(Response) We removed this file name according to your comment.

what kind of sensitivity test? try to quantify “rather robust interannual variability”. Quantify, for instance, percentage of stations indicating such variability

(Response) Following your comments, we have detailed the sensitivity test in the revised manuscript.

why ND is defined Winter? how you can assert that 2 months are representative of the winter season?

(Response) We added more explanation on the definition of winter in this study in Section 2 of the revised manuscript.

spread are large in ND only referred to 2016 and 2017?  Not clear! I think no (as displayed in figure 2d)

(Response) Following your and other reviewers’ comments, we have detailed the interannual spreads with new Figures 2c and 2d in the revised manuscript.

In figure 2d could you find a wide spread also in January? For instance, considering a subsample of 1993-2017 or including more years in the dataset.

the point is, we should be sure we can speak about winter time, considering only ND.

(Response) As mentioned above, we have added uncertainty bars to Figure 2d using standard deviations of interannual spread from 25 different subsamples of a monthly series for a period of 24 years among the total period of 25 years based on your comments.

please explain how you chose this value 0.019 to identify H and L? Explain what is the best way to chose this value (can you cites approaches?)

(Response) The threshold was determined to arrive at equal number of years with positive and negative anomalies (at six years each).

The winter season described in figure 4 is an ND winter? This is not clear to me looking at the text and figure caption.

(Response) Yes, winter is defined as ND in this study and it is described as ND winter throughout the manuscript for the same reason mentioned above.

Errors of symbols and equations.

(Response) We rewrote the symbols and equations according to your comment.

I do not like the way you chose to write equation 2. I believe you can find a different way to explain/show such content.

(Response) Following your and other reviewers’ comments, we have changed the formulas to the conventional form with symbols/notations and we have added a table with numbers in the revised manuscript.

I am not really familiar with climatic Indices computation. If I correctly understood WNSI, computed using information of the ND period, is more powerful in terms of predictability than some of the other climate indices.

(Response) The climate indices used in this study to represent remote forcing instead of the local forcing. Our conclusion is that the local wind forcing represented by the WNSI we developed provides better prediction than any known remote forcing (climate indices).

Some of the indices you cited are derived by entire annual dataset of information (e.g. SST from Jan. to Dec). On the light of this, could you clarify how you can compare them to WNSI? You may also include, for instance, a table where you declare the “insignificant correlation” you are speaking about.

(Response) Following your and other reviewers’ comments, we have detailed the climate indices (providing all correlation coefficients for annual mean and ND winter mean in Table 2) in the revised manuscript.

I do not enjoy (not readeable) the way you chose to write equation 4. However if you want keep it, i would suggest to reduce font dimension and space between lines.

(Response) Following your and other reviewers’ comments, we have changed the formulas to the conventional form with symbols/notations and a table with numbers was added in the revised manuscript.

Please, think to reformulate clearly the sentence

(Response) We rewrote the sentence according to your comment.

Author Response File: Author Response.docx

Reviewer 4 Report

The present paper is devoted to the analysis of sea level variability over the period 1993-2017 for two months of each year (November and December) and the influence of wind stress on this variability. The analysis was based on the daily mean satellite altimetry data from the Copernicus database, as well as atmospheric data from the ERA-Interim database. Despite the high interest in the features of sea level variability in the northeastern Asian seas, this paper contains a number of significant shortcomings to be eliminated before publishing the paper in the JMSE.

The main drawback of this study is weak argumentation of novelty and importance of the results obtained. In the manuscript, the authors point out the incompleteness of knowledge on the processes responsible for sea level variability, particularly in the northeastern Asian seas including the Yellow, East China and Japan/East seas. The introduction provides a too brief overview of investigations of sea level variability in these seas. Wind stress is indicated as one of the main factors of this variability. However, in a number of papers not presented in the introduction (Choi et al. 2004, Gordon et al. 2004; Kang 2005; Moon et al. 2016; Ohshima 1994; Wang et al. 2009) it is indicated that, for example, for the Japan/East Sea basin, sea level variability is significantly contributed by its steric component, which is not considered in the present study. In a number of investigations, it has been established that the circulation and, accordingly, sea level changes in the Asian seas are strongly influenced by Kuroshio, or rather, changes in its mass transport. This factor was also ignored. As well, there are a number of papers where comprehensive studies of sea level variability in the Asian seas have been carried out, not limited to only two months. It is not clear from the manuscript what new results were obtained in comparison with those presented in these works.

Minor disadvantages.

L118-120

Indicate how the wind stress was estimated. Is the sea surface current velocity taken into account?

L134-144

When analyzing sea level trends, it is necessary to take into account their spatial heterogeneity. It is not clear from the assessment which trend is observed in the Yellow and East China Seas, and which in the Japan/East Sea. How far do these trends deviate from what was obtained by averaging over all these seas?

L149-153

In the study, a high correlation has been found between variations in the sea level averaged over all seas in winter and annual mean anomalies. Does such a high correlation stays between winter and annual mean variations in each of the seas?

L162-184

The authors argue that the reason for high and low sea level anomalies in the region of interest is related to the position of the Aleutian minimum. However, the authors did not consider as a possible reason, in particular, the change in mass transport through the straits of the Japan/East Sea, which are associated with the variability of the Kuroshio mass transport. What is the contribution of the latter to the identified periods of high and low levels in the Japan/East, East China and Yellow Seas?

Author Response

Reviewer #4

The present paper is devoted to the analysis of sea level variability over the period 1993-2017 for two months of each year (November and December) and the influence of wind stress on this variability. The analysis was based on the daily mean satellite altimetry data from the Copernicus database, as well as atmospheric data from the ERA-Interim database. Despite the high interest in the features of sea level variability in the northeastern Asian seas, this paper contains a number of significant shortcomings to be eliminated before publishing the paper in the JMSE.

The main drawback of this study is weak argumentation of novelty and importance of the results obtained. In the manuscript, the authors point out the incompleteness of knowledge on the processes responsible for sea level variability, particularly in the northeastern Asian seas including the Yellow, East China and Japan/East seas. The introduction provides a too brief overview of investigations of sea level variability in these seas. Wind stress is indicated as one of the main factors of this variability. However, in a number of papers not presented in the introduction (Choi et al. 2004, Gordon et al. 2004; Kang 2005; Moon et al. 2016; Ohshima 1994; Wang et al. 2009) it is indicated that, for example, for the Japan/East Sea basin, sea level variability is significantly contributed by its steric component, which is not considered in the present study. In a number of investigations, it has been established that the circulation and, accordingly, sea level changes in the Asian seas are strongly influenced by Kuroshio, or rather, changes in its mass transport. This factor was also ignored. As well, there are a number of papers where comprehensive studies of sea level variability in the Asian seas have been carried out, not limited to only two months. It is not clear from the manuscript what new results were obtained in comparison with those presented in these works.

(Response) Thank you very much for your many comments that have contributed toward the improvement of this paper. Following your and other reviewers’ comments, we have rewritten Section 1 Introduction to include more references and highlight the importance of this study.

Minor disadvantages.

L118-120

Indicate how the wind stress was estimated. Is the sea surface current velocity taken into account?

(Response) We did not use wind data to estimate wind stress, but we downloaded wind stress data directly from the ECMWF. Based on your comment, we found that the sea surface current velocity was not considered in their estimation of wind stress and we have described this in the revised manuscript.

L134-144

When analyzing sea level trends, it is necessary to take into account their spatial heterogeneity. It is not clear from the assessment which trend is observed in the Yellow and East China Seas, and which in the Japan/East Sea. How far do these trends deviate from what was obtained by averaging over all these seas?

(Response) That is true for studying spatial changes in long-term sea level rise in the regional seas. Our focus, however, is not the long-term sea level rise in the YS or ECS or ES, but interannual variability of the winter NEAMS-mean sea level after removing the long-term trend of the sea level averaged over the NEAMS area. We have clarified the study objectives more clearly in Section 1 Introduction of the revised manuscript.

L149-153

In the study, a high correlation has been found between variations in the sea level averaged over all seas in winter and annual mean anomalies. Does such a high correlation stays between winter and annual mean variations in each of the seas?

(Response) This is an interesting question that can be taken up in a future study. However, we have focused on the interannual variations of the NEAMS-mean sea level as a whole system, not at the sea level in specific parts of the NEAMS or on individual seas in this study.

L162-184

The authors argue that the reason for high and low sea level anomalies in the region of interest is related to the position of the Aleutian minimum. However, the authors did not consider as a possible reason, in particular, the change in mass transport through the straits of the Japan/East Sea, which are associated with the variability of the Kuroshio mass transport. What is the contribution of the latter to the identified periods of high and low levels in the Japan/East, East China and Yellow Seas?

(Response) In the revised manuscript, we have provided results of multiple linear regression analysis of both local (WNSI) and remote (NPGO) forcing that show slightly higher correlation coefficients than those of the individual indices (WNSI or NPGO), which implies that remote forcing is not irrelevant to the NEAMS-mean sea level. Since the thermosteric part in interannual variations of the winter NEAMS-mean sea level is relatively small as discussed in Section 4, we believe that it is more likely linked to atmospheric teleconnection between the open Pacific Ocean and the NEAMS. We have added discussions on this point in the revised manuscript.

Author Response File: Author Response.docx

Reviewer 5 Report

This manuscript explores causes of winter sea-level variability in the northeast Asian marginal seas and uses the results to deduce a simple index based on large-scale atmospheric circulation that can be used as a proxy for sea level variability.

General comments

This is a good paper with some solid and useful data analysis. However, sometimes the choices the authors make are not clear or well explained (see specific comments).

I’m also wondering if the authors could make a bit more use of the tide gauge data to also look at the pre-satellite era.  Tide gauge data is introduced but somehow discarded and not further commented on in the remainder of the manuscript.

Many acronyms are used in the manuscript. I suggest including a table with their definitions to make it easier for the reader to keep an overview.

Specific comments

Abstract:

Many acronyms are already used in the abstract which makes it tedious to read. I recommend keeping acronyms in the abstract to a minimum as you do introduce them in the main text again.

Line 15-16: I would remove “after being de-trended in the regional sea level”. You already mention that you are focusing on interannual variability.

Line 19: Here, and in the following, consider giving only two digits when you state trends in mm/yr. You could also use cm instead of m - it would make the manuscript easier to read.

Line 39: What do you mean by “horizontal mass and volume exchanges”? The land ice contribution?

Line 43-45: I’m not sure what you mean by “regional variability” here. Regional sea level rise is some kind of regional variability as well, yet you mention them separately. Please clarify. Are you talking about interannual variability in sea level? Or differences between or within regions?

Methods

I suggest you call this section Data and Methods.

Is there a particular reason for why you use absolute dynamic topography? If I’m not mistaken CMEMS provides sea level anomalies as well and since you are interested in interannual variability that should be fine. I don’t mean to say that ADT is not suitable - I’m just wondering whether the details about the MDT computation are necessary.

Tide gauges: please specify whether you use the same time period for the tide gauge-derived NEAMS sea level as for altimetry data (i.e. 1993-2017). Would it be possible to go further back in time with the tide gauge data?

Line 125: So, tide gauge data is not used in this analysis? Why not?

Results

Line 134-136: I’m not sure I understand this sentence. Do you mean that NEAMS sea level derived from tide gauges agrees well the sea level derived from altimetry?

Line 138-139: It is interesting that the trend in winter sea level from tide gauges is a lot larger than the trend derived from annual data, while there is almost no difference in the altimeter derived sea level between winter and annual data. Do you have an explanation?

Line 140-141: Why do you focus on altimetry-derived sea level here (and in Figure 2c and 2d)? The same is true for sea level derived from tide gauges, isn’t it?

Line 149-150: Does this apply to the altimeter sea level or to tide gauges?

Line 152: How was this correlation coefficient computed: between annual data and data averaged over all months except ND? This is not clear from the text. I suggest you either remove the numbers or clearly state where they come from.

Line 162-165: How did you choose the threshold of +/-0.019m?

Line 169: I think you want to refer to Figure 5a here (instead of Figure 4), which shows the general atmospheric circulation during 1993-2017.

Figure 4: Would you consider showing pressure and wind stress anomalies here, i.e. deviations from the mean circulation shown in Figure 5a? That way, the anomalous wind stresses and pressures are easier to identify. I also think it makes more sense to show Figure 5a before you introduce Figure 4.

Line 207-210: How exactly did you choose WA and WB? Why rectangles and not just the areas with a correlation coefficient above a certain threshold?

Line 215: SE should be a subscript.

Line 215: I’m not sure I understand: do you mean that the composite southeast wind stress over Period H and averaged over WB is 0.047 N/m2 (and the same for Period L, WA etc)? I would not call that an increase, but an anomalously high wind stress in certain years.

Line 225ff: I appreciate that you walk the reader through the equation, but this makes the paragraph very tedious to read. I suggest you clean up a bit. Also make sure to use superscripts correctly. For example, it took me a while to figure out that O(104m) was supposed to mean O(10km).

Equation 2 should be introduced at the beginning of the paragraph.

Equation 3: I would like to see a more rigorous assessment of this multiple linear regression. What are the uncertainties of the coefficients? Have you tried a simple linear regression first (wind stress over WA or WB only) and then looked at whether the skill of Equation 3 is significantly improved adding a predictor? I assume that the wind stresses in WA and WB are correlated with each other? You could also use a leave-one out cross validation to quantify uncertainties. Also, I’m wondering whether you could extend your time series to before 1993 by using tide gauge data instead of altimetry. In any case, you need to provide some kind of uncertainty analysis with respect to Equation 3.

Line 278-281: It is not clear to me how the WNSI came about. How was the choice of the area motivated? Did you compute correlation maps between sea level pressure and NEAMS sea level? Why not rather use the difference between the high- and low-pressure centers (similarly to the NAO) to represent the pressure gradient? Please elaborate a bit.

Figure 10b: In the Figure and the caption you mention the NSI while in the text you use the acronym WNSI. Please be consistent.

Discussion

Could you also comment on how the WNSI is useful for practical applications for example with respect to future NEAMS sea level variability?

Author Response

Reviewer #5

This manuscript explores causes of winter sea-level variability in the northeast Asian marginal seas and uses the results to deduce a simple index based on large-scale atmospheric circulation that can be used as a proxy for sea level variability. 

General comments

This is a good paper with some solid and useful data analysis. However, sometimes the choices the authors make are not clear or well explained (see specific comments).

I’m also wondering if the authors could make a bit more use of the tide gauge data to also look at the pre-satellite era.  Tide gauge data is introduced but somehow discarded and not further commented on in the remainder of the manuscript.

Many acronyms are used in the manuscript. I suggest including a table with their definitions to make it easier for the reader to keep an overview.

(Response) Thank you very much for the constructive comments, great suggestions, and encouragement. Following your comments, we have revised the manuscript as detailed below and believe that the revised version meets the requirements of the journal for the publication of our paper.

Specific comments

Abstract:

Many acronyms are already used in the abstract which makes it tedious to read. I recommend keeping acronyms in the abstract to a minimum as you do introduce them in the main text again.

(Response) Following your comments, we have modified the abstract and used only two acronyms (expanded in the abstract itself) to meet with the word limit prescribed for the abstract by the journal.

Line 15-16: I would remove “after being de-trended in the regional sea level”. You already mention that you are focusing on interannual variability.

(Response) We have removed the words according to your comments.

Line 19: Here, and in the following, consider giving only two digits when you state trends in mm/yr. You could also use cm instead of m - it would make the manuscript easier to read.

(Response) We rewrote those numbers with only two digits, and we have also used cm instead of m according to your comments.

Line 39: What do you mean by “horizontal mass and volume exchanges”? The land ice contribution?

(Response) Larger volume of inflow transport from than outflow transport into the Mediterranean Sea leads to higher sea level due to net convergence. We have revised the words to “horizontal volume exchanges” to clarify the meaning.

Line 43-45: I’m not sure what you mean by “regional variability” here. Regional sea level rise is some kind of regional variability as well, yet you mention them separately. Please clarify. Are you talking about interannual variability in sea level? Or differences between or within regions?

(Response) The focus of this study is interannual variability in sea level that is spatially averaged over the NEAMS region, and not spatial differences between or within the regions. We have clarified this point in the sentence in the revised manuscript.

Methods

I suggest you call this section Data and Methods.

(Response) We changed the section title to Data and Methods according to your comments.

Is there a particular reason for why you use absolute dynamic topography? If I’m not mistaken CMEMS provides sea level anomalies as well and since you are interested in interannual variability that should be fine. I don’t mean to say that ADT is not suitable - I’m just wondering whether the details about the MDT computation are necessary.

(Response) We used ADT to consider the mean as well as varying components of transports into and out of the NEAMS due to the sea level difference inside and outside the NEAMS. Outflow from the NEAMS or ES into the SO or Pacific Ocean through the SS and TS can be reduced/enhanced, but it would be hardly the inflow into the NEAMS or ES through the straits.

Tide gauges: please specify whether you use the same time period for the tide gauge-derived NEAMS sea level as for altimetry data (i.e. 1993-2017). Would it be possible to go further back in time with the tide gauge data?

(Response) As described in the original as well as in the revised manuscript, the tide gauge data that we have used were constructed from the observations for the same period (1993–2017) as that of the satellite altimetry data. As commented, the tide gauge data at many stations are available for the period before 1993. However, we used the tide gauge data only for the inter-comparison of NEAMS-mean sea level in this study rather than for extracting information on the interannual variability.

Line 125: So, tide gauge data is not used in this analysis? Why not?

(Response) Tide gauge stations in the NEAMS are not evenly distributed over the region and vertical displacements of the ground for only a few stations can be corrected. Therefore, we believe that the sea level averaged over the tide gauge stations hardly represents the NEAMS-mean sea level compared to the spatially even and consistently corrected satellite altimetry-derived sea level averaged over the NEAMS.

Results

Line 134-136: I’m not sure I understand this sentence. Do you mean that NEAMS sea level derived from tide gauges agrees well the sea level derived from altimetry?

(Response) Yes, our intention is to describe the consistency of the NEAMS-mean sea level derived from two independent observations even though that derived from the tide gauge was not to be used here for the reason mentioned above. We have clarified the meaning of these sentences in the revised manuscript.

Line 138-139: It is interesting that the trend in winter sea level from tide gauges is a lot larger than the trend derived from annual data, while there is almost no difference in the altimeter derived sea level between winter and annual data. Do you have an explanation?

(Response) As mentioned above, the tide-gauge stations are not evenly distributed over the NEAMS region and the correction for vertical ground displacements is available for only few selected stations among the 86 stations in total. Therefore, we had to conduct the sensitivity test of the NEAMS-mean sea level derived from tide gauge data to tens of different sets of stations using spatial averaging. Our selection of 15, 21, 33, and 47 tide gauge stations showed a consistency (not 65 and 85 stations as they were too biased) in the long-term rising trend of NEAMS-mean sea level within a few tenths of a mm/yr and not few mm/yr. In the revised manuscript, we have detailed the sensitivity tests following your and other reviewers’ comments.

Line 140-141: Why do you focus on altimetry-derived sea level here (and in Figure 2c and 2d)? The same is true for sea level derived from tide gauges, isn’t it?

(Response) As explained above, the NEAMS-mean sea level estimated from the tide-gauge observations might be biased depending on the way of averaging and selection of the stations.

Line 149-150: Does this apply to the altimeter sea level or to tide gauges?

(Response) In this study, we apply all the processing/analyses to the satellite altimetry data only except for inter-comparison.

Line 152: How was this correlation coefficient computed: between annual data and data averaged over all months except ND? This is not clear from the text. I suggest you either remove the numbers or clearly state where they come from.

(Response) Yes, we have clarified the methods in the revised manuscript according to your comment.

Line 162-165: How did you choose the threshold of +/-0.019m?

(Response) The threshold was determined to arrive at equal number of years with positive and negative anomalies (at six years each).

Line 169: I think you want to refer to Figure 5a here (instead of Figure 4), which shows the general atmospheric circulation during 1993-2017.

(Response) This is correct. Our intention is to refer to Figure 5a of the original manuscript. We have now merged Figures 4 and 5 into one figure (Figure 4 in the revised manuscript) and revised the referencing figure (Figure 4a of the revised manuscript) in the revised manuscript following your comments.

Figure 4: Would you consider showing pressure and wind stress anomalies here, i.e. deviations from the mean circulation shown in Figure 5a? That way, the anomalous wind stresses and pressures are easier to identify. I also think it makes more sense to show Figure 5a before you introduce Figure 4.

(Response) As mentioned above, we have merged the Figures 4 and 5 into Figure 4 of the revised manuscript, and present Figure 5a of the original manuscript as Figure 4a of the revised manuscript based on your comments.

Line 207-210: How exactly did you choose WA and WB? Why rectangles and not just the areas with a correlation coefficient above a certain threshold?

(Response) Following your comments, we checked the results using the wind stress averaged over the areas of amplitude of correlation coefficients exceeding 0.50 (threshold) instead of the rectangular areas of WA and WB. The results yield three correlation coefficients with NEAMS-mean sea level of wind stresses in WA and WB, and multiple linear regressed wind stresses (WA+WB) of −0.62, +0.57, and +0.67. Corresponding correlation coefficients for the case of the rectangular areas described in the (both original and revised) manuscript are −0.67, +0.57, and +0.70. Since the results are not significantly different from the new definition of the WA and WB areas, we have retained the previous definition in the revised manuscript.

Line 215: SE should be a subscript.

(Response) We modified this and other similar errors throughout the manuscript according to your comments.

Line 215: I’m not sure I understand: do you mean that the composite southeast wind stress over Period H and averaged over WB is 0.047 N/m2 (and the same for Period L, WA etc)? I would not call that an increase, but an anomalously high wind stress in certain years.

(Response) Following your comments, we have clarified the sentence by revising the ‘increase/decrease’ to ‘higher/lower.’

Line 225ff: I appreciate that you walk the reader through the equation, but this makes the paragraph very tedious to read. I suggest you clean up a bit. Also make sure to use superscripts correctly. For example, it took me a while to figure out that O(104m) was supposed to mean O(10km).

(Response) Following your and other reviewers’ comments, we have changed the formulas to the conventional form with symbols/notations and added a table with numbers in the revised manuscript. The errors in the superscripts and subscripts were corrected throughout the manuscript.

Equation 2 should be introduced at the beginning of the paragraph.

(Response) We have moved the Equation (2) to the previous paragraph according to your comments.

Equation 3: I would like to see a more rigorous assessment of this multiple linear regression. What are the uncertainties of the coefficients? Have you tried a simple linear regression first (wind stress over WA or WB only) and then looked at whether the skill of Equation 3 is significantly improved adding a predictor? I assume that the wind stresses in WA and WB are correlated with each other? You could also use a leave-one out cross validation to quantify uncertainties. Also, I’m wondering whether you could extend your time series to before 1993 by using tide gauge data instead of altimetry. In any case, you need to provide some kind of uncertainty analysis with respect to Equation 3.

(Response) We have inserted the correlation coefficients of the NEAMS-mean sea level with south-eastward wind stresses averaged over the WA and WB individually and then compared them with that with the multiple linear regression (WA + WB). Combining wind stress at both areas slightly improves the results, yielding time series closer to the observed winter NEAMS-mean sea level. In the revised manuscript, we have inserted more discussions on the results following your comments, but we did not use the tide gauge data in this study for the NEAMS-mean sea level variability due to the issues described above.

Line 278-281: It is not clear to me how the WNSI came about. How was the choice of the area motivated? Did you compute correlation maps between sea level pressure and NEAMS sea level? Why not rather use the difference between the high- and low-pressure centers (similarly to the NAO) to represent the pressure gradient? Please elaborate a bit.

(Response) Yes, the WNSI was derived from the atmospheric pressure anomaly in the specific area around the SS. The area was determined from the pattern of atmospheric pressure variations. Since the area of maximum southwestward gradient in atmospheric pressure corresponds to that of the strongest winter monsoonal wind, we targeted the area around the SS. Therefore, positive atmospheric pressure anomaly corresponds to strong northwesterly wind in the southern SO (rather than southern ES) and positive sea level anomaly in winter NEAMS-mean sea level. Following your comments, we have clarified this point in the revised manuscript.

Figure 10b: In the Figure and the caption you mention the NSI while in the text you use the acronym WNSI. Please be consistent.

(Response) We have corrected the word in the revised manuscript following your and other reviewers’ comments.

 Discussion

Could you also comment on how the WNSI is useful for practical applications for example with respect to future NEAMS sea level variability?

(Response) Following your and other reviewers’ comments, we have added more discussions on the predictive skills of WNSI and NPGO as climate indices, and the multiple linear regression of the two (local and remote; WNSI+NPGO) in Section 4 Discussion of the revised manuscript.

Author Response File: Author Response.docx

Round 2

Reviewer 4 Report

A great work is done by the authors on revising the manuscript. Nevertheless, there are some items, which could be further improved. The reviewer insists on the importance of investigating the sea level trends in the three separate seas, rather than in joint system, since it could be more interesting and correct from the scientific point of view. As well, contribution of steric effects has been left without detailed analysis, despite the inclusion of indirect estimations in the manuscript.

By the reviewer's opinion, investigation of these two items (three separate seas and steric effects) should be performed, and the results should be added in the article. However, if the authors argue that these features are subjects of additional investigation, as well as other reviewers approve the paper for publication, I would not object against it.

Author Response

Thank you very much again for your great comments again. It is important and extremely interesting to investigate the long-term trends and variability of sea level in the three separate seas and to compare the results with those of this study. Although this study focuses on the interannual variability of the NEAMS-mean sea level in winter, those in other time scales or other seasons are also of concern. Finally, the steric effects on the long-term trends and multi-scale variability of the NEAMS-mean sea level and sea levels averaged over the three separate seas need to be investigated in the future. We are now well aware of the limitations of this study and what should be investigated in the future considering the scientific viewpoints this reviewer pointed out. We deeply appreciate this reviewer's constructive suggestions/comments.