Evaluation of Three Long-Term Remotely Sensed Precipitation Estimates for Meteorological Drought Monitoring over China

Round 1

Reviewer 1 Report

This study used the SPI as the meteorological drought index and evaluated the skills of three remotely sensed precipitation products in capturing meteorological drought. This study is of significance for meteorological monitoring and assessment in ungauged regions. My general feeling about this work is that it puts TOO MUCH content in results, leading to the key points being hard to grasp for me. Authors are advised to reorganize the paper and simplify the research content so that readers can grasp the key points to be expressed. Also, the manuscript needs to be read very carefully, there are several typos and wrong figure references. Many sentences need to be re-written, and this manuscript needs to be proofread. A moderated reversion is recommended.

 

Detailed comments are as follows:

[1] Check the typos in the abstract.

[2] L19: Why only emphasize the ability of the three RSPEs to capture long-term drought? How their performance for short-term drought?

[3] L76: “Gao, Zhang[35]”, revise the format of citation.

[4] L85: why the “reference” appeared here?

[5] L82-93: rephrase this sentence.

[6] L97-99: I don’t think this study is useful for improving the precipitation retrieval algorithm.

[7] L149: incomplete sentence.

[8] L163: What does “S” mean?

[9] Section 3.2.1: remove this section because most hydrology and climate communities are familiar with the MK test. Just mention it briefly in section 3.1.

[10] TOO MUCH performance statistics were used, resulting in a verbose statement for results. It is recommended to keep one or two (rBIAS and KGE) metrics for assessment.

[11] L192-208: shorten the section and only retain the key information for SPI. L192-199 can be deleted.

[12] Keep one categorical metric and put it in the section 3.2.2.

[13] Please use the most refined sentences to describe how to identify the drought characteristics based on the run theory.

[14] Fig. 4: this figure should map on the annual scale rather than the monthly scale. Also, for the CMA data, the presence of null values in Taiwan is understandable because precipitation observations there are not available. However, I cannot understand why null values of RSPEs still appear in Taiwan. Give me a explanation.

[15] Section 4.1.2: Only keep the results of relative bias and KGE.

[16] Section 4.2.1: remove Fig. 8 and Fig. 10. Rephrase the caption of Fig. 7 and Fig. 9. It is not the correlation coefficient between RSPES and CMA. It is the correlation coefficients of SPI estimated from the three RSPEs and CMA.

[17] Section 4.2.2: remove this section. Why didn’t the authors introduce SPI of other scales (e.g., SPI1, SPI3, and SPI6)? Figs. 11 and 12 cannot provide any useful information to readers.

[18] Figs 13 and 14: Only keep the result of one categorical skill.

[19] Delete section 4.4. There is already too much content in the results. I has been driven mad by too much information before I read this chapter. I really don’t have the courage and energy to read the following section. Please, please delete this chapter. More importantly, this section is not closely related to the topic.

[20] Shorten the conclusions and only provide the “take-home” information to readers.

Author Response

Dear reviewer,

Thank you so much for giving us guidance on our manuscript. According to your good suggestions, we have revised them one by one. In addition, the authors also checked the manuscript carefully several times to make sure no such mistakes, please see our revised manuscript in RED font for details. You can see the change in our revised manuscript and response to comments for details. Finally, please accept our sincere gratitude for the efforts you have made for our paper. We are looking forward to hearing from your early favorable reply.

Sincerely yours,

Yanzhong Li

On behalf of all authors

Author Response File: Author Response.pdf

Reviewer 2 Report

In my opinion it is a summary analysis, which is correct from the point of view of research methodology on the spatio-temporal evolution of the rainfall regarding monitoring of droughty meteorological phenomena, via three  RSPE_s, also based on the SPI. The result of the research are conclusive.

 

Author Response

Dear reviewers,

Thank you so much for giving us guidance on our manuscript. According to your good suggestions, we have revised them one by one. In addition, the authors also checked the manuscript carefully several times to make sure no such mistakes. Please see the attachment

of our revised manuscript in RED font for details. You can see the change in our revised manuscript and response to comments for details. Finally, please accept our sincere gratitude for the efforts you have made for our paper. We are looking forward to hearing from your early favorable reply.

Sincerely yours,

Yanzhong Li

On behalf of all authors

Author Response File: Author Response.pdf

Reviewer 3 Report

PERSIANN, CHIRPS and MSWEP precipitation data are used for the estimation in the study. SPI12 values are calculated to assess drought variation. The subject is very important and the study is valuable in terms of climate change & drought forecasting but the novelty of the study is emphasized insufficiently. Some suggestions and comments to the authors are presented below:

1. Two more keywords as “drought characteristics” and “CMA” can be added to keywords.

2. Check the tenses in the paragraphs. For example, there are present and past tenses in a paragraph under “Abstract” …

3. There are some crucial and grammatical errors. Check them all.

4. Check the spaces between words as “MSWEPperformed” in line 20, “1000km” in Figure 1 …

5. Use passive sentences. Check the sentences started by “we”.

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

7. Very major editing of the language is needed.

8. Literature part is looking weak. Give new and last updated examples from literature about “drought characteristics (duration, severity, and intensity)” as

 

doi.org/10.1080/02626667.2021.1934473

 

doi.org/10.1016/j.jhydrol.2022.128097

 

9. The flow chart of the suggested methodology in Figure 2 can be developed with more branches in detail.

 

10. Additional statistical properties as coefficient of variation, confidence intervals, distribution characteristics, min and median, etc. of used data should be given in a table.

Additional Comments：

1. What is the novelty of the paper? It should be emphasized in the paper. Three popular (as mentioned in abstract) long-term RSPEs are used in the study.
2. The flow chart of the suggested methodology in Figure 2 can be developed with more branches in detail. E.g.: Is the methodology only valid for China and ten basins in datasets and Step 2?
3. In the study, some performance metrics as fRMSE, aBIAS, rBIAS and KGE are calculated. These are not statistical metrics, only performance metrics. Some statistical properties as coefficient of variation, confidence intervals, distribution characteristics, min and median, etc. of used data (SPI or precipitation data for each ten basins) should be given in a table. 4. Meteorological drought is investigated for short-term duration. Using long term data, hydrological or agricultural drought can be assessed by considering and calibrating hydrological data.

 

Author Response

Dear reviewer,

Thank you so much for giving us guidance on our manuscript. According to your good suggestions, we have revised them one by one. In addition, the authors also checked the manuscript carefully several times to make sure no such mistakes. Please see the attachment

of our revised manuscript in RED font for details. You can see the change in our revised manuscript and response to comments for details. Finally, please accept our sincere gratitude for the efforts you have made for our paper. We are looking forward to hearing from your early favorable reply.

Sincerely yours,

Yanzhong Li

On behalf of all authors

Author Response File: Author Response.pdf

Reviewer 4 Report

This manuscript reports on three long-term remotely sensed precipitation estimates for meteorological drought monitoring over China. The analysis of the article sounds reasonable. Though, I have the following issues that need to be addressed before it can be considered for publication.

-How MSWEP (version 2.0) was shifted to 0.25 degrees? There is no information. Please elaborate on it.

-Why analysis is only carried out for SPI12.

-Why specifically SPI 12, not SPEI? SPI may over or underestimate the dryness because of a single variable estimation.

-PERSIANN-CDR performance is very low which is already discussed in many studies. So what is the benefit to use this product?

-PDIR-NOW is the most recent data product in PERSIANN family. It is advised to run the same analysis for PDIR-NOW if authors want to check product suitability in the region.

 

-Why is the selection of these three products, and why GPM is absent?

Author Response

Dear reviewer,

Thank you so much for giving us guidance on our manuscript. According to your good suggestions, we have revised them one by one. In addition, the authors also checked the manuscript carefully several times to make sure no such mistakes. Please see the attachment

of our revised manuscript in RED font for details. You can see the change in our revised manuscript and response to comments for details. Finally, please accept our sincere gratitude for the efforts you have made for our paper. We are looking forward to hearing from your early favorable reply.

Sincerely yours,

Yanzhong Li

On behalf of all authors

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

I suggest accepting the manuscript.

Reviewer 4 Report

The authors have made significant changes to their manuscript. Still, need to work on some minor checks and edits. Authors could cite the below papers to enhance the readership.

-  https://doi.org/10.1016/j.jhydrol.2022.128543

 

-https://doi.org/10.1016/j.jhydrol.2021.127308

Good Luck!