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Evaluation of Spatial and Temporal Variations in the Difference between Soil and Air Temperatures on the Qinghai–Tibetan Plateau Using Reanalysis Data Products
 
 
Article
Peer-Review Record

Dynamic Effects of Atmosphere over and around the Tibetan Plateau on the Sustained Drought in Southwest China from 2009 to 2014

Remote Sens. 2023, 15(8), 2198; https://doi.org/10.3390/rs15082198
by Yiwei Ye 1,2, Rongxiang Tian 1,* and Zhan Jin 1
Reviewer 1: Anonymous
Reviewer 2:
Reviewer 3:
Remote Sens. 2023, 15(8), 2198; https://doi.org/10.3390/rs15082198
Submission received: 28 February 2023 / Revised: 11 April 2023 / Accepted: 19 April 2023 / Published: 21 April 2023

Round 1

Reviewer 1 Report

The reviewer is really grateful to the authors for such an outstanding and vital research and article about dynamic effects of the Tibetan Plateau on the sustained drought in Southwest China from 2009 to 2014 since the two westerly branches around the Tibetan Plateau have a significant impact on the climate downstream and continuous drought event in Southwest China during the winter of 2009 to the spring of 2014 caused huge economic losses. The authors focused on the dynamic field anomalies over the Tibetan Plateau during this event using statistical analysis, attempts to decipher its mechanism on drought in Southwest China, and provided a regression model. The authors revealed that the anticyclone and downdraft over the Tibetan Plateau were weaker than usual during the drought, which would reduce the southward cold airflow on the northeast of the Tibetan Plateau and strengthen the west wind from dry central Asia on the south of the plateau. As a result, a larger area of the southwest region in China was controlled by the warm and dry air mass, which was acting against precipitation. The conclusion and regression model is of reference value to the drought forecast for Southwest China, and also encourage further research about how the Tibetan Plateau influence the climate downstream. 

The authors use reanalysis data and Empirical Orthogonal Function (EOF) method of analyzing the structural features of matrices and extracting the characteristic quantities of major data. 

So the main question addressed by the research is the dynamic effects of the Tibetan Plateau on the sustained drought in Southwest China from 2009 to 2014. The considered topic is original, relevant and very significant in the field. The conclusion is consistent with the evidence and arguments presented and do address the main question posed. The references are appropriate.

Author Response

Thanks very much for your comments and advice. Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

EOF methodology is used for the decomposition and analysis of big dataset in the study. 2009-2014 period is evaluated and Tibetan Plateau is selected for the application in the paper. The subject is very important and the study is valuable in terms of climate change & drought forecasting but the flowchart of the methodology is missing. Some suggestions and comments to the authors are presented below:

1. A basic flowchart of the suggested methodology should be presented in the paper. Thus, the readers can easily follow the application procedures.

2. Literature part is looking weak. Give new and last updated examples from literature about “drought characteristics” as

doi.org/10.1080/02626667.2021.1934473

doi.org/10.3390/rs15051297

3. The performance metrics are missing in the paper. Some metrics can be calculated to evaluate the application results.

4. Some statistical properties as coefficient of variation, confidence intervals, distribution characteristics, min and median, etc. of used dataset should be given in a table.

5. Spatial efficiency metric (SPAEF) can be used to compare two raster maps for different cases.

6. Conclusions part can be improved in the paper. Here is presented in a general concept.

 

7. What is the novelty of the paper? It should be emphasized in the paper.

Author Response

Thanks very much for your comments and advice. Please see the attachment.

Author Response File: Author Response.docx

Reviewer 3 Report

See in Attachment

Comments for author File: Comments.pdf

Author Response

Thanks very much for your comments and advice. Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

Thanks to the authors for trying to improve their manuscript by revision and considering our comments and suggestions. But, I believe there are still some points that need to be corrected.

 

From the first round,

 

Reply to Comment 1: “We have added a paragraph in the beginning of Section 2 to introduce our data and methods as follows…”

A basic flowchart about methodology is expected here, not a detailed explanation in a paragraph.

 

Reply to Comment 2: “Thanks for your comment and kind advice. We have read these two papers carefully. Finally, according to the Chinese official drought rating standard GBT20481-2017 (Administration, 2017) ([23] in the manuscript), we classify drought into four levels…”

I see the official standard for drought classification. But, I mean that the paper is still missing in terms of updated studies on drought indices. Suggested papers should be discussed in the paper.

 

Reply to Comments 3 & 5: As I mentioned in the first round, performance metrics as SPAEF can be used in the paper to evaluate application results. Other statistical metrics as NSE, RMSE, etc. can be also used. If you want to use SPAEF metric to compare temperature vs. precipitation distribution, you can discuss the data characteristics. It's not mandatory, but I recommend adding this part (figures with a paragraph) of the article to the discussion section.

 

Reply to Comment 4: “Thanks for your comment and advice. You mean the processing of precipitation data? We only calculated the seasonal mean of precipitation data from 1960 to 2019 and from 2009-2014. The precipitation data used is ‘Dataset of monthly climate data from Chinese surface stations’. The dataset is from the website of the China Meteorological Administration (http://101.200.76.197:93/data/cdcdetail/dataCode/SURF_CLI_CHN_MUL_MON.html). The data is quality-controlled  according to the website description …”

Thank you for your detailed information about the data here. But, it would be better if you add this information to the 2.1 Data section in the article. Because the readers will not see the comments & responses document.

 

 

Reply to Comments 6 & 7: OK & Thank you. I believe that these additional and detailed sentences increased the quality of the paper.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 3 Report

In this form

Author Response

Please see the attachment.

Author Response File: Author Response.docx

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