Evaluation of CMIP6 Models and Multi-Model Ensemble for Extreme Precipitation over Arid Central Asia

Round 1

Reviewer 1 Report

The study presents a well-designed and technically sound analysis of simulated historical extreme precipitation using CMIP6 models and ETCCDI indices in arid Central Asia. The results show that the models have a certain ability to simulate the spatial distribution of extreme precipitation, but there are some deficiencies in capturing the spatial bias of consecutive wet days. The authors also compare four multi-model ensemble approaches and find that the IWM approach has the most reliable simulations. However, I would like to see the authors emphasize the novelty of their study more clearly. Additionally, the authors should discuss the limitations and deficiencies of their research in the Discussion section. I am curious as to why the authors chose to use the GPCC dataset instead of local high-precision observational data, which is available through the China Meteorological Administration. Additionally, it would be helpful for readers to understand how the authors selected the 33 GCMs used in the study, given that there are over 100 models in the CMIP6 project. Finally, the authors should provide some physical explanations for the differences in performance among the models. Overall, the manuscript presents valuable insights into the application of GCMs in arid Central Asia and its sub-regions. I believe that this study will contribute to reducing uncertainties in future climate change projections and improving the reliability of such projections through the use of optimal multi-model ensemble methods.

Author Response

We have submitted a document with comments in response. Please write down "Please see the attachment."

Author Response File: Author Response.docx

Reviewer 2 Report

The manuscript focuses on an interesting topic but needs further improvement. The paper needs the below-mentioned editing and revision before it is considered for publication in the Journal.

 

ü In the keyword, Global Climate Model should be considered.

ü A series of similar studies have already been carried out, what’s new in your study, please specify.

ü Please provide effectiveness for the GPCC datasets used in this study by providing references already used these datasets for validation.

ü In the 2.1 section, please add some major information focusing on the climatology (annual average temperature, wind, precipitation, evapotranspiration) of the study region.

ü I would suggest to use a methodological flowchart.

ü The discussion of this paper needs to be improved. It should highlight the insights and the applicability of your findings/results for further work. There is a lack of justifications and reasoning behind the changes. Most importantly, need in-depth and more concrete discussion regarding why different models and indices perform differently, five distinct regions show varying attribution, and how climate change/global warming influences the process.

ü Please mention some shortcomings in this research; uncertainties involved with data and methods.

 

 

Author Response

We have submitted a document with review comments. Please see the attachment

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

I'm glad to see that the author has made revisions to the manuscript based on the comments. However, unfortunately, some issues have not been given enough attention, and substantive changes have not been made to address these problems.

Regarding the innovation of the article, it is the biggest issue. What are the unique features and contributions of this study compared to previous research? Similar articles can easily be found through simple searches, and some of them are presented in a better format with similar data, research areas, and methods. It is meaningless to repeat similar work, and it does not have the potential to be published in this journal.

1.         Guo H, Bao A, Chen T, et al. Assessment of CMIP6 in simulating precipitation over arid Central Asia[J]. Atmospheric Research, 2021, 252: 105451.

2.        Zhang J, Wang F. Future changes in extreme precipitation in central Asia with 1.5–4° C global warming based on Coupled Model Intercomparison Project Phase 6 simulations[J]. International Journal of Climatology, 2022.

3.         Dike V N, Lin Z, Fei K, et al. Evaluation and multimodel projection of seasonal precipitation extremes over central Asia based on CMIP6 simulations[J]. International Journal of Climatology, 2022, 42(14): 7228-7251.

4.        Dong T, Dong W. Evaluation of extreme precipitation over Asia in CMIP6 models[J]. Climate Dynamics, 2021, 57(7-8): 1751-1769.

5.        Liu Z, Huang J, Xiao X, et al. The capability of CMIP6 models on seasonal precipitation extremes over Central Asia[J]. Atmospheric Research, 2022, 278: 106364.

6.        Zhang X, Chen Y, Fang G, et al. Future changes in extreme precipitation from 1.0° C more warming in the Tienshan Mountains, Central Asia[J]. Journal of Hydrology, 2022, 612: 128269.

7.         Guo H, Bao A, Chen T, et al. Assessment of CMIP6 in simulating precipitation over arid Central Asia[J]. Atmospheric Research, 2021, 252: 105451.

In the fourth section, what is needed is not a broad, non-specific discussion. The author should focus on discussing current limitations, uncertainties, and other aspects of this study in separate sections and provide supporting data and graphs as much as possible.

Please provide statistical results on significant levels related to Table 3.

Author Response

Thank you very much for your comments which will be very helpful to the improvement of this article. We have made modifications according to the opinions, please see the attachment for details.

Author Response File: Author Response.docx

Reviewer 2 Report

The authors satisfactorily revised the manuscript considering all of my suggested comments which certainly improved the quality of the paper. I would suggest to accept this paper to publish in the journal.

Author Response

Thank you very much for your comments which will be very helpful to the improvement of this article. Thank you again for taking the time and effort to review this manuscript. I wish you all the best.