Multi-Site Statistical Downscaling Method Using GCM-Based Monthly Data for Daily Precipitation Generation
Round 1
Reviewer 1 Report
The authors proposed a multi-site downscaling method based on the CLIGEN model and the modified shuffle procedure. The proposed statistical downscaling method was applied to the Huangfuchuan Basin to demonstrate its feasibility. First, I agree that it is crucial to address the spatial correlation of inter-station precipitation sequences. And I believe that the proposed methodology will be of great interests to readers. Second, this paper is well written and easy to follow. Nevertheless, some key points need to be elaborated with additional explanations and discussions to improve the quality of this paper. Therefore, I think this paper can be considered for publication after the authors address all my comments and suggestions raised below.
L82: “daily precipitation data so generated…” Please rephrase.
L116: Why did you choose only one GCM as there were many CMIP5 GCMs available? Only a single GCM (the CMCC-CM model) is unacceptable indeed. How did you deal with the uncertainty?
L120: Why did you use the IDW interpolation method to obtain GCM data for each precipitation station? Did you perform any assessment on various interpolation methods?
L122: The statement of “With spatial interpolation, the number of wet days would be inflated artificially” is confusing. Please explicitly explain.
L124: Why did you choose the climate scenario RCP4.5? Please justify.
L127: I do not understand why RCP4.5 has a higher priority than RCP6.0. Please explain. Also, what about RCP8.5?
L196: Please change “Where” to “where”.
L477: Discussion – I agree that it is necessary to take into account the spatial correlation of precipitation time series independently generated at multiple weather stations. Nevertheless, why not generate the catchment-scale precipitation data through dynamical downscaling? The grid-based precipitation data generated through dynamical downscaling is able to better characterize the spatial pattern of precipitation and convection processes at a catchment scale. Please refer to the recently published articles for the related studies (doi.org/10.1007/s00382-019-04702-7; doi.org/10.1029/2019JD030686). I know that the computational cost of dynamical downscaling is relatively high, but the computing power should not be considered as a big challenge nowadays. At least some discussions about physically-based dynamical downscaling should be added in this section.
Author Response
Please see the attachment.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
The article is interesting, and the subject is worthy of research. However, the execution of the article and the research as well as presentation itself requires some important improvements to proceed with its publication in the journal in my opinion. For this I advise a major revision to the authors in the following points:
There are many oversights and mismatches with the format of the journal in the material execution. Here are some of them: non-MDPI format of all bibliographic references, formulation of incorrect bibliographical references, unjustified typography changes, missing authors contribution, etc.
In a number of cases, you had facts, information, ideas or methods that were not your own, which had no in-text citation. It is very important to stick a reference at the end of the paragraph. I noticed, in many lines or paragraphs there are no references cited, for example in lines 90-93, 478-485).
It is unclear to me what is the significance and innovation of the work discussed in the paper, compared to other similar works. Is it only the fact that this is the first study addressing possibilities of preserving a spatial correlation at the daily scale? If yes than this part is not later addressed in conclusions.
In the figure 1 I miss a general area representation. I advise to add one general figure representing the described area within a bigger perspective as not all international readers might be familiar with the Huangfuchaun basin or local city names only. Additionally some parts of figures miss a scale bar.
The methodology section appears to be well prepared. Though I miss some more explanation about decisions of some methods used for analysis. For example have only IDW method was used or you tested some other interpolation possibilities. Additionally no validation aspects have been presented.
The results sections appears to be too long and hard to read. For better clarity authors could reduce some subsections and present more logical sequence. Additionally I also miss more results that will underline the main paper aim presented in the introduction. Furthermore the projection period results (2021-2070) is not sufficiently described.
Finally the discussion and conclusions are the weakest part of the manuscript. Actually it appears there is no discussion at all. Presenting statement saying “many scholars have tried” without citations does not sound like discussion. Please rewrite this part and present a discussion of your results in the light of literature of subject. Similarly the conclusion part sounds like selected sentences form Result section. Please specify what are the biggest advantages of the methodology you used. Additionally please emphasize here the main aim of your research was achieved and how can it influence future analysis.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
I appreciate that the authors have made great efforts to address my comments and suggestions. The quality of the revised manuscript has been largely improved. Therefore, I think the revised manuscipt can be accepted for publication.
Reviewer 2 Report
Congratulation for authors.
I really appreciate introduced changes. Authors prepared them carefully and anvsered all issues.
