The Global Patterns of Interannual and Intraseasonal Mass Variations in the Oceans from GRACE and GRACE Follow-On Records

Round 1

Reviewer 1 Report

The authors adopt the method described by Vejmelka et al. (2015), based on what they call “surrogate”, however to understand the method a reading of the Vejmelka et al. (2015) is necessary. So, I think that the authors have to spend more words in introducing the method.

The total variances of 23 components of the PCA is about equal to the 72% of the original variance and each component contribute with small values of variance as reported in Figure S1, where the maximum value is 6.4% of component #0. These values are really significative? When the authors compare each single component with different climate indices using the Pearson’s correlation index, in my opinion, this clusterization is not always confirmed. For instance in figure S5 panel (t) show a strong correlation with the zonal wind stress in an area covered by zone 8, 19, 11 and 17 (panel t and i), and panels t and i are very similar.

In Figure 3b, the authors report the auto-correlation but these values are not commented. What information do you think to get from those graphs?

Table 2: in the legend the sentence “In bold: significant correlation coefficient from the surrogate testing” is reported. Could you explain how the significativity has been tested?

Figure S3: the black dots are not clearly visible in the plots. I think that are not necessary because with he color scale the significant correlations are well shown.

Author Response

We thank the reviewer for his/her time, interest, and feedback on the manuscript. Please, see our reply in the attached pdf file.

Author Response File: Author Response.pdf

Reviewer 2 Report

Review report on “The Global Patterns of Interannual and Intraseasonal Mass Variations in the Oceans from GRACE and GRACE Follow-On Records” by Damien  Delforge et al.
In this study, grace and grace follow on data are used to analyze and sort out the mass variation of global temporal and spatial scales. Although it is only the basic statistical results, it is acceptable to publish it in the form of communication. The images in the manuscript are very attractive and are a good reference for future researchers. At present, there are only a few small problems to be solved in the manuscript, as follows:
1. Lines 20-21, 267-268: What kind of correlation? Positive correlation? Negative correlation?
2. Figure 1a: Please zoom in and add latitude and longitude coordinates.
3. Figure S2: What is the value and unit of the Y-axis?
4. Figure S3-S6: Add the latitude and longitude coordinates to the submap in the lower left corner.

Comments for author File: Comments.pdf

Author Response

We thank the reviewer for his/her time, interest, and feedback on the manuscript. Please, see our reply in the attached pdf file.

Author Response File: Author Response.pdf

Reviewer 3 Report

The authors present  the monthly global Ocean Bottom Pressure (OBP) from GRACE(-FO) mass 12 concentration solutions, extracting 23 significant regional modes of variability.

In my opinion, the work is original, well written and well structured. I like how the authors focus the problem, the methodology and the results. The analysis is correct, rigorous and the statistical PCA methodology is well known and applied.

I do not find any grammar or methodological errors as well.

Finally, I think that is a good job and I suggest the editor to publish the work in Remote Sensing. 

 

 

Author Response

In the absence of comments, we did not provide a reply file. We thank the reviewer for his time and feedback on the manuscript. 

Round 2

Reviewer 1 Report

Dear authors,

Thanks for having taken into account for my comments and specially for the improving in the description of the adopted method (Vejmelka et al., 2015).

Concerning my comment #3, with your PCA analysis you obtain 23 patters (Figure 1), but I wanted to observe that the comparison with the results obtained by the Pearson’s correlation index confirm partially this patters subdivision. I expected that the comparison with the different climatic indices would confirm this division into patterns, but probably the phenomena are more complex and combinations of effects can contribute to this division into patterns.