Spatial and Temporal Variability of Upwelling in the West-Central South China Sea and Its Relationship with the Wind Field
Round 1
Reviewer 1 Report
No
Author Response
Thank you very much for your comment work, we really appreciate it! We made some minor adjustments to the grammar of the entire manuscript to ensure that it meets the standards of scientific writing.
Reviewer 2 Report
The authors have explored the spatial and temporal characteristics of upwelling in the west-central South China Sea and combined wind field data to investigate the effects of wind direction and speed on upwelling using the sea surface temperature (SST) satellite data from 2000-2018, providing valuable insights. The findings are useful for understanding the mechanisms driving the variability of upwelling in this region and for improving the prediction of upwelling events, and the work is quite worthy to be published to the community. Before the paper is due to be published, I would expect some minor revisions:
It would be clearer if the introduction section can describe more on the previous investigations about the correlations between wind field characteristics with annual mean SST and upwelling center coordinates.
It would be better if the section of 2.2.3 Wind-based upwelling Index algorithm can be more clearly described. From my view, in this paper, well understanding and applying the formula (2) is crucial for understanding the correlation in the latter section, please clarify its application in this section.
I would expect the figure 4 can be improved to better fit the explanation.
Author Response
Referee: 2
Comments to the Author
The authors have explored the spatial and temporal characteristics of upwelling in the west-central South China Sea and combined wind field data to investigate the effects of wind direction and speed on upwelling using the sea surface temperature (SST) satellite data from 2000-2018, providing valuable insights. The findings are useful for understanding the mechanisms driving the variability of upwelling in this region and for improving the prediction of upwelling events, and the work is quite worthy to be published to the community. Before the paper is due to be published, I would expect some minor revisions:
- It would be clearer if the introduction section can describe more on the previous investigations about the correlations between wind field characteristics with annual mean SST and upwelling center coordinates.
Response 1：As suggested by the reviewer, we have included an analysis of previous research on the correlations between wind field characteristics with annual mean SST, and upwelling center coordinates in the introduction section. (Please see lines 69-77).
- It would be better if the section of 2.2.3 Wind-based upwelling Index algorithm can be more clearly described. From my view, in this paper, well understanding and applying the formula (2) is crucial for understanding the correlation in the latter section, please clarify its application in this section.
Response 2：As suggested by the reviewer, for the section 2.2.3 on upwelling index algorithm, we have added the principle of Ekman transport that the algorithm is based on. We have also included a detailed explanation of and including how they are calculated and the physical meanings of the specific parameters. In addition, we have cited research papers on wind-based upwelling index. (Please see lines 114-153).
- I would expect the figure 4 can be improved to better fit the explanation.
Response 3：As suggested by the reviewer, we have removed the original Figure 4 and directly presented the calculated results in the content for better clarity. The new Figure 4 shows the results of the EOF analysis. Additionally, we have thoroughly checked all the figures in the manuscript to minimize the chance of errors. (Please see lines 229-233).
Author Response File: 
Author Response.docx
Reviewer 3 Report
This is an interesting research work about the prediction of the relation of weather variables with the upwelling in the South China Sea. To reach this objectives statistical analysis of data from satellite data from 200 to 2018 and field data. From this, an empirical orthogonal function decomposition of monthly data is employed. It was obtained that wind direction is associated with the movement of the centre of upwelling.
As it was explained before, it is an original work showing interesting relations between weather and the objective ( upwelling place). Despite this, some improvements are possible and recommended (maybe for future research work)
1. It was not done a previous study of the data. If this is parametric data some type of statistical studies can be done, In this sense, variance analysis may let the authors evaluate if wind intensity, direction, temperature or many other variables could be associated.
2. the reason why monthly data was selected is not described and this is a possible origin of interference at the time to associate variables. In an adequate scientific methodology, the sampling frequency must be adjusted t the variable objective of the study and, once related to the objective values, it could be analysed. For instance, maybe short winds or their changes in direction are associated with a movement of upwelling centres ( it is just a supposition) and this cannot be identified with monthly data.
3. For a higher sampling frequency may be of interest to employ artificial intelligence that let us adjust future sensors and control systems to identify in real time the place of the upwelling ( it is a proposal for future research works).
The paper format is adequate and the English style is good. There are some mistakes like in line 143 Kg must be with lowercases. In general terms, the paper is of adequate quality and only some explanations must be added.
Author Response
- It was not done a previous study of the data. If this is parametric data some type of statistical studies can be done, In this sense, variance analysis may let the authors evaluate if wind intensity, direction, temperature or many other variables could be associated.
Response 1：We thank the reviewer for raising this question. In the dataset used in this study, there have been previous analyses conducted by other researchers to evaluate data quality and analyze various environmental variables. Therefore, I did not perform data preprocessing analysis. I acknowledge that the reviewer's suggestion on exploring this area is a valuable direction for future research. I have added a reference to the analysis paper of the data used in this study in the manuscript (Please see lines 107-108).
- the reason why monthly data was selected is not described and this is a possible origin of interference at the time to associate variables. In an adequate scientific methodology, the sampling frequency must be adjusted t the variable objective of the study and, once related to the objective values, it could be analysed. For instance, maybe short winds or their changes in direction are associated with a movement of upwelling centres ( it is just a supposition) and this cannot be identified with monthly data.
Response 2：We thank the reviewer for raising this question. As suggested by the reviewer, we have added the reason for selecting monthly data for analysis. (Please see lines 171-174). The suggestion focuses on eliminating the interference of correlated variables in low spatial and temporal resolution data, analyzing the lifecycle of upwelling events in local areas over a short period of time, and paying attention to the detailed changes in upwelling events within a short time. This suggestion is in line with recent hot research topics. I believe that in future research, we can focus on the reviewer's opinion.The original SST data in this study is daily data, and the original wind field data is data every 6 hours. However, when studying the upwelling phenomenon of upwelling events in this article, monthly average data is used to show the overall change of upwelling events in the central and western South China Sea on a large time scale. At this time, the analysis results of monthly data have some representativeness, which allows us to understand the seasonal variation process of the overall upwelling events in the central and western South China Sea. Meanwhile, in the subsequent sections on the frequency of upwelling events and the impact of wind fields on upwelling events, we use daily data for processing and research.
- For a higher sampling frequency may be of interest to employ artificial intelligence that let us adjust future sensors and control systems to identify in real time the place of the upwelling ( it is a proposal for future research works).
Response 3：We thank the reviewer for raising this question. This is a very worthwhile research topic, and I have a strong willingness to consider the reviewer's suggestions in my subsequent research. At the same time, I will incorporate the reviewer's suggestions for future work into the conclusion of the paper. (Please see lines 422-425).
- The paper format is adequate and the English style is good. There are some mistakes like in line 143 Kg must be with lowercases. In general terms, the paper is of adequate quality and only some explanations must be added.
Response 4：We thank the reviewer for raising this question. As suggested by the reviewer, We have corrected a writing error in line 143, and we have also standardized the overall writing format of the article. (Please see lines 153)
Author Response File: Author Response.docx
Round 2
Reviewer 3 Report
After several changes, the paper is now adequate for publication.
