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Climate and Extreme Rainfall Events in the Mono River Basin (West Africa): Investigating Future Changes with Regional Climate Models

Water 2020, 12(3), 833; https://doi.org/10.3390/w12030833

by Ernest Amoussou^1,2,3,4,*, Hervé Awoye^5,6

, Henri S. Totin Vodounon^1,2, Salomon Obahoundje³

, Pierre Camberlin⁴

, Arona Diedhiou^3,7

, Kouakou Kouadio^3,8,9

, Gil Mahé¹⁰

, Constant Houndénou² and Michel Boko²

Reviewer 1: Anonymous

Reviewer 2: Anonymous

Reviewer 3: Anonymous

Reviewer 4: Anonymous

Water 2020, 12(3), 833; https://doi.org/10.3390/w12030833

Submission received: 28 November 2019 / Revised: 9 January 2020 / Accepted: 21 January 2020 / Published: 16 March 2020

(This article belongs to the Special Issue Multiscale Impacts of Anthropogenic and Climate Changes on Tropical and Mediterranean Hydrology)

Round 1

Reviewer 1 Report

A brief summary of the manuscript

The present manuscript tries to investigate and project the future changes in three key climate parameters (mean temperature and precipitation and extreme rainfalls) in the region of Mono river. In order to achieve this, four regional climate models are used, while observational data from several stations in the area are used as default. Additionally, a specific analysis for extreme rainfall events is presented using the GEV distribution, as well as for its return levels.

Broad comments

Generally, I believe that the present research is interesting, but it needs lots of improvements in order to be appropriate for publication. Consequently, I propose the present manuscript for publication after major revision.

Specific comments

Abstract

Line 28: Add the word “Daily” before Precipitation and temperature.

Line 30: The “Weibull-type GEV” that the authors use is not right as the Weibull distribution from the GEV distribution is not appropriate for extreme precipitation events because it is an upper bound distribution. So the authors use the simple Weibull distribution and not the GEV-type 3, in which the shape diagram is negative. So, I propose to delete the “Weibull” from the «Weibull-type GEV”

Line 31: Change the phrase “extreme events” with “extreme rainfalls”.

Introduction

The references should be added with the numbers 1,2,3… starting with the first in the manuscript, not alphabetically. Please correct it. The first paragraph of the introduction analyses the need for extremes analysis. There is no discussion or reference about the importance of average temperature and precipitation. However, the manuscript analysis these parameters. You should add a paragraph explaining to the readers the importance of the selected parameters.

Line 46: Add reference.

Line 56: Add reference.

Line 63: Add reference.

Line 65: Add reference.

Line 79: Start the paragraph with the goal not with the used data set.

Line 88: The authors should add a sentence about the novelty of the study. What is the new of this research and why is it helpful?

Lines 89-93: I propose to rewrite the paragraph using words like “Firstly”, “In the next session” etc or to delete it, as it is not well organized.

Materials and Methods

Line 129: The rainfall data came form 14 stations and the temperature from 14+2 or only from two? If it is the second, I believe that there is an important difference in the accuracy of the temperature and precipitation results.

Lines 138: The same steps were followed also for temperature? Please explain.

Lines 145: According to who the CRU data should be preferred from the ERA-Interim? Please add a reference.

Line 156: Why the authors chose the period 2000-2010?

Line 191: Why the authors select the 99^th for extreme rainfall events? Please add some studies that have also used this threshold.

Line 197: As the authors use the GEV distribution in the next sessions. a more extended analysis should be presented. For example the importance of the shape parameter, the fact that the different values of the shape parameter lead to different distributions etc. Additionally, there are some main , classic studies that are missing (e.g. Coles 2001).

Line 209: Add a reference for the definition of return level.

Line 212: With the “best GEV model” you mean the most appropriate distribution? (Gumbel, Weibull or Frechet) Please explain.

Results and Discussion

Despite the fact that the name of the session is results and discussion, there is almost no discussion in it. There are no references to other studies, no comparison of the results. I suggest to rename the session as “results” and to add the discussion in the next session “discussion and conclusion” where the authors should make a comparison with other studies. Otherwise, I propose to add studies and make a discussion in this session.

Lines 278: The models do not underestimate the projected rainfall amount, but they estimate a number lower that the default period. Please rephrase. Also correct the same analysis in other points in the manuscript.

Line 375: Add also the names of the authors not only the reference numbers.

Figure 14: I can’t see the line of historical data. Please make it more clear or with different color.

Line 458: What does this means? Explain also what each parameter means for the distribution.

Figure 16: I propose to use different color for the bars of each model in order to be more clear the comparison.

Conclusions

I propose to rename it to “ discussion and conclusions” and compare the results of this study with others.

Author Response

Comments and Suggestions for Authors

A brief summary of the manuscript

Broad comments

Thank you for the comments and suggestions. We have revised the manuscript to make it more concise according to your recommendations. Bellow are the responses to your comments.

Specific comments

Abstract

Line 28: Add the word “Daily” before Precipitation and temperature. Thank you. Done.

Line 31: Change the phrase “extreme events” with “extreme rainfalls”. Done

Introduction

The references should be added with the numbers 1,2,3… starting with the first in the manuscript, not alphabetically. Please correct it. Addressed.

The first paragraph of the introduction analyses the need for extremes analysis. There is no discussion or reference about the importance of average temperature and precipitation. However, the manuscript analysis these parameters. You should add a paragraph explaining to the readers the importance of the selected parameters. Thank you for your suggestion. It has been considered.

Line 46: Add reference. (referenced in the following line). Addressed.

Line 56: Add reference. Addressed.

Line 63: Add reference. Addressed.

Line 65: Add reference. Addressed.

Line 79: Start the paragraph with the goal not with the used data set. Addressed.

Line 88: The authors should add a sentence about the novelty of the study. What is the new of this research and why is it helpful? Addressed.

Lines 89-93: I propose to rewrite the paragraph using words like “Firstly”, “In the next session” etc or to delete it, as it is not well organized. Addressed.

Materials and Methods

Line 129: The rainfall data came form 14 stations and the temperature from 14+2 or only from two? Temperature dataset comes only from two stations while rainfall comes from 14 rain gauges stations.

If it is the second, I believe that there is an important difference in the accuracy of the temperature and precipitation results. The temperature is available in only these two stations.

Lines 138: The same steps were followed also for temperature? Please explain. Thank you again for your time. The procedures are explained in the manuscript.

Lines 145: According to who the CRU data should be preferred from the ERA-Interim? Please add a reference. Addressed

Line 156: Why the authors chose the period 2000-2010? We are sorry for this mistake. Indeed, the 18-year period spanning 1988-2005 was used for the comparison of precipitation and air temperature RCMs data with observation (GPCP for precipitation and CRU for temperature) was considered for air temperature.

Line 191: Why the authors select the 99^th for extreme rainfall events? Please add some studies that have also used this threshold. Thank you for your interest. Some literature on the importance of 99^th in the extreme rainfall were added into the manuscript.

Line 197: As the authors use the GEV distribution in the next sessions. a more extended analysis should be presented. For example, the importance of the shape parameter, the fact that the different values of the shape parameter lead to different distributions etc. Additionally, there are some main, classic studies that are missing (e.g. Coles 2001). Addressed .

Line 209: Add a reference for the definition of return level. Addressed.

Line 212: With the “best GEV model” you mean the most appropriate distribution? (Gumbel, Weibull or Frechet) Please explain. Addressed.

Results and Discussion

Line 375: Add also the names of the authors not only the reference numbers. Addressed.

Figure 14: I can’t see the line of historical data. Please make it more clear or with different color.

Line 458: What does this means? Explain also what each parameter means for the distribution. Addressed in the manuscript.

Figure 16: I propose to use different color for the bars of each model in order to be more clear the comparison. Addressed

Conclusions

I propose to rename it to “discussion and conclusions” and compare the results of this study with others. Thank you for this suggestion. However, we prefer discussed our result rather to change the conclusion into conclusion and discussion.

All your concern was addressed to make the paper easy reading.

Comments and Suggestions for Authors

A brief summary of the manuscript

Broad comments

Thank you for the comments and suggestions. We have revised the manuscript to make it more concise according to your recommendations. Bellow are the responses to your comments.

Specific comments

Abstract

Line 28: Add the word “Daily” before Precipitation and temperature. Thank you. Done.

Line 31: Change the phrase “extreme events” with “extreme rainfalls”. Done

Introduction

The references should be added with the numbers 1,2,3… starting with the first in the manuscript, not alphabetically. Please correct it. Addressed.

Line 46: Add reference. (referenced in the following line). Addressed.

Line 56: Add reference. Addressed.

Line 63: Add reference. Addressed.

Line 65: Add reference. Addressed.

Line 79: Start the paragraph with the goal not with the used data set. Addressed.

Line 88: The authors should add a sentence about the novelty of the study. What is the new of this research and why is it helpful? Addressed.

Lines 89-93: I propose to rewrite the paragraph using words like “Firstly”, “In the next session” etc or to delete it, as it is not well organized. Addressed.

Materials and Methods

Line 129: The rainfall data came form 14 stations and the temperature from 14+2 or only from two? Temperature dataset comes only from two stations while rainfall comes from 14 rain gauges stations.

If it is the second, I believe that there is an important difference in the accuracy of the temperature and precipitation results. The temperature is available in only these two stations.

Lines 138: The same steps were followed also for temperature? Please explain. Thank you again for your time. The procedures are explained in the manuscript.

Lines 145: According to who the CRU data should be preferred from the ERA-Interim? Please add a reference. Addressed

Line 209: Add a reference for the definition of return level. Addressed.

Line 212: With the “best GEV model” you mean the most appropriate distribution? (Gumbel, Weibull or Frechet) Please explain. Addressed.

Results and Discussion

Line 375: Add also the names of the authors not only the reference numbers. Addressed.

Figure 14: I can’t see the line of historical data. Please make it more clear or with different color.

Line 458: What does this means? Explain also what each parameter means for the distribution. Addressed in the manuscript.

Figure 16: I propose to use different color for the bars of each model in order to be more clear the comparison. Addressed

Conclusions

All your concern was addressed to make the paper easy reading.

Author Response File: Author Response.docx

Reviewer 2 Report

see file

Comments for author File: Comments.pdf

Author Response

Reviewer 2

Review of: Climate and extreme rainfall events in the Mono river basin …. By Amoussou et al.

This is a useful study of the regional climate of the Mono Basin using available data, global data and

regional climate models. Broadly the paper is well presented and conclusion well drawn. I think my

main comment is I found the inclusion of the CMIP5 and AMMA simulations a bit unclear (e.g. table

1 and figs 2 and 3. I think the authors need to be much clearer about the experimental design and

how the differing simulations fit into the narrative.

In detail

Thank you for the comments and suggestions. We have revised the manuscript to make it more concise according to your recommendations. Bellow are the responses to your comments.

Line Comment

38 What does ‘could trigger ecosystem services’ mean? The services that ecosystem could generate.

66 Caution not reserve. Addressed.

78 They not their. Addressed

123 More than what? . Addressed

149 Which are the ENSEMBLES RCMs? Addressed

Table 1 This is very confusing (see also my main comment). Need to be much clearer about

which models are used when. Thank you for your interest. We think this is the way to describe our data. Indeed, CORDEX as well as AMMA-ENSEMBLES data is made of RCM (Regional Climate Model) of a given institution driven by a GCM (Globall Climate Model) developed by a given institution. Only CMIP5 is made of a GCM of a given institution.

Fig 2 It would be clearer if areas getting wetter were blue and drier orange. Also replace

raw with row or, better, number a,b,c and d. Addressed.

Fig. 4 and 5 Are the bottom two a repeat of figure 2 on a different scale – confusing - explain

276 Where is table 2? The figures were combined to make things understandable

290 I couldn’t really see that there was no change in the MPI projection – it looks quit

yellow and orange ie negative? Yellow =excess, orange= deficit closer to zero

309-310 What does this mean? All the model project an increasing air temperature which could reach at least 1^oC whatever the model and the warmest prediction was from METO.

359 and 360 Plateau not sill. Addressed.

373-375 Not sure if I agree MPI and METO seem well off. MPI and METO are closer to the observation than SMH. However, ICT is the best.

All your concern was addressed to make the paper easy reading.

Author Response File: Author Response.docx

Reviewer 3 Report

Summary
The MS from Amoussou et al. used a set of GCMs and RCMs to project the future extreme rainfall events in the case of the Mono River basin. To approach this, the authors performed a set of simulations driven by selected RCMs and evaluated the future change by reasonable statistical metrics. Although the MS is informative and may be helpful for climatological studies, I found several places where substantial revisions are needed before being considered for publication.

Specific comments
-Major comments
1. Future projection of extreme events is quite an important research topic. As the author mentioned, there is a huge uncertain in precipitation projection by GCMs and RCMs due to lack of well representation and parameterization of the interactions between the land surface and the atmospheric boundary layer. There is no surprise that RCMs' projection varied a lot. Thus it is good to either demonstrate the different performances of models and related parameterizations or just analyze the general agreement of the models. But here the authors struggled a lot with detailed differences among models while just mentioned the sources of mismatch in the summary. This is not novel enough.

2. The DEV model is not well introduced, but its related parameters are studied later in Sect. 4.6. Please introduce the DEV model and the scientific implications of those parameters. Moreover, please use the Greek letter italic font instead of English expression (e.g., sigma).

3. We know bias exists in model projections. It is reasonable to use the initial outputs for qualification of the trend but not quantification. There are a lot of approaches available for bias correction of GCM outputs (e.g., Vrac et al. 2016: 10.1002/2015JD024511). It is better to correct known bias before quantify the magnitudes of changes.

4. Seem the uncertainties of predicted temperature (Fig. 10) is much larger than the projected changes. Can we trust the simulated trends?

5. The Sect. 5 seems like a discussion, not a summary. The summary should be short and provide take away messages what we learned from this study. I suggest the authors rename it as Discussion and add a summary, or, if the journal allows, name Sect. 5 as "Discussion & Summary".

6. The quality of the figures should be substantially revised. Detailed comments are listed below.

-Minor comments
- Figure 2: It's better to revise the color bar of the right panel (red negative and blue positive) to keep uniform with the left one. The same case as in Figure 4. The tiles can be improved by using the mathematical expression, e.g. P_hist, P_rcp85 - P_hist, etc. Then readers can fast understand the contents.

- Figure 4: use (first/second column) instead of (top/bottom) to keep uniform as Fig. 2 and 3.

- Figure 5: Why not use the same color palette as the one in Figure 3? Then they are comparable.

- Figure 2-5: The CORDEX plots in Fig. 2/3 are the same as Fig. 4/5, right? Why not assemble Fig. 2 and 4; Figure 3 and 5 together?

-Section 4.1 and 4.2 can be combined together.

-Figure 18: I cannot fully understand the content with few explanations. It seems a comparison of modeled and simulated CDF. If so, perhaps qqplot is more suitable.

-Figure 19: What are the two blue curves represent? Perhaps I overlooked something, but please explain it as legend or in the caption to make the manuscript be reader-friendly.

Author Response

Reviewer 3

Review Report Form

Open Review

(x) I would not like to sign my review report
( ) I would like to sign my review report

English language and style

( ) Extensive editing of English language and style required
( ) Moderate English changes required
( ) English language and style are fine/minor spell check required
(x) I don't feel qualified to judge about the English language and style

	Yes	Can be improved	Must be improved	Not applicable
Does the introduction provide sufficient background and include all relevant references?	( )	( )	(x)	( )
Is the research design appropriate?	( )	(x)	( )	( )
Are the methods adequately described?	( )	( )	(x)	( )
Are the results clearly presented?	( )	( )	(x)	( )
Are the conclusions supported by the results?	( )	(x)	( )	( )

Comments and Suggestions for Authors

Thank you for the comments and suggestions. We have revised the manuscript to make it more concise according to your recommendations. Bellow are the responses to your comments.

The DEV model is not well introduced, but its related parameters are studied later in Sect. 4.6. Please introduce the DEV model and the scientific implications of those parameters. Moreover, please use the Greek letter italic font instead of English expression (e.g., sigma). Addressed. We know bias exists in model projections. It is reasonable to use the initial outputs for qualification of the trend but not quantification. There are a lot of approaches available for bias correction of GCM outputs (e.g., Vrac et al. 2016: 10.1002/2015JD024511). It is better to correct known bias before quantify the magnitudes of changes. Thank you for this suggestion. We appreciate it, but this is not the aim of this present work. It will be considered in our next work. Seem the uncertainties of predicted temperature (Fig. 10) is much larger than the projected changes. Can we trust the simulated trends? This is the reason why we try to compare the reanalysis data (CRU) with the models and the best or the closest model to the observation is selected for the next step. The Sect. 5 seems like a discussion, not a summary. The summary should be short and provide take away messages what we learned from this study. I suggest the authors rename it as Discussion and add a summary, or, if the journal allows, name Sect. 5 as "Discussion & Summary". Thank you again for your suggestion. We have discussed our result to make our work comparable to existed studies. The quality of the figures should be substantially revised. Detailed comments are listed below. Addressed.

- Figure 4: use (first/second column) instead of (top/bottom) to keep uniform as Fig. 2 and 3. Addressed.

- Figure 5: Why not use the same color palette as the one in Figure 3? Then they are comparable. Addressed.

- Figure 2-5: The CORDEX plots in Fig. 2/3 are the same as Fig. 4/5, right? Why not assemble Fig. 2 and 4; Figure 3 and 5 together? Addressed.

-Section 4.1 and 4.2 can be combined together. Thank you for your suggestion. We sorry to considered this suggestion. Indeed, the section 4.1 deals with all the three dataset (CMIP5, AMMA-ENSEMBLES and CORDEX) while the section 4.2 deals with the most realistic dataset which is AMMA-ENSEMBLES.

-Figure 18: I cannot fully understand the content with few explanations. It seems a comparison of modeled and simulated CDF. If so, perhaps qqplot is more suitable. Addressed

-Figure 19: What are the two blue curves represent? Perhaps I overlooked something, but please explain it as legend or in the caption to make the manuscript be reader-friendly. It was addressed. Indeed, the blue curves refer to the confidence level.

All your concern was addressed to make the paper easy reading.

Author Response File: Author Response.docx

Reviewer 4 Report

Review of “Climate and extreme rainfall events in the Mono river basin (West Africa): investigating future changes with regional climate models” by Amoussou et al.

General comments

The manuscript aims at investigating future changes in rainfall and air temperature by using weather projection outputs from different regional climate models (RCMs). The weather outputs from the selected RCMs refer to a scenario period that is assumed to be the period 2028-2050 and a reference period from 1988-2010.

Observed data of rainfall and air temperature are analyzed as well. About this point, in the Results and Discussion Section, I would suggest to compare the observed weather data with the weather outputs from RCMs in a more systematic way: for instance, by adding panels in Figure 6 and 8 with an average error.

For the remaining parts of the manuscript, I think that the paper extensively explains the data and the outcomes and critically illustrates the limits of the study. The referencing is appropriate and exhaustive.

Overall, the study is interesting and the authors are encouraged to consider some very minor comments that follow for improvement.

Specific comments

Line 28: correct “flooding inundation” with “flood inundation” Lines 220-223: please give some quantification (the same for lines 246-249) Lines 224-227: please avoid the repletion of the same concepts (the same for lines 250-253) Lines 264-265: I do not see any clear and explicative comparison among observed data and RCMs outputs for the reference period. Please provide an additional panel in Figure 6 with a statistic for the comparison (the same for Figure 8, but for air temperature some data for comparison are already given).

Author Response

Reviewer 4

Open Review

(x) I would not like to sign my review report
( ) I would like to sign my review report

English language and style

	Yes	Can be improved	Must be improved	Not applicable
Does the introduction provide sufficient background and include all relevant references?	(x)	( )	( )	( )
Is the research design appropriate?	( )	(x)	( )	( )
Are the methods adequately described?	(x)	( )	( )	( )
Are the results clearly presented?	( )	(x)	( )	( )
Are the conclusions supported by the results?	( )	(x)	( )	( )

Comments and Suggestions for Authors

Review of “Climate and extreme rainfall events in the Mono river basin (West Africa): investigating future changes with regional climate models” by Amoussou et al.

Thank you for the comments and suggestions. We have revised the manuscript to make it more concise according to your recommendations. Bellow are the responses to your comments.

General comments

Observed data of rainfall and air temperature are analyzed as well. About this point, in the Results and Discussion Section, I would suggest comparing the observed weather data with the weather outputs from RCMs in a more systematic way: for instance, by adding panels in Figure 6 and 8 with an average error. Addressed.

Overall, the study is interesting and the authors are encouraged to consider some very minor comments that follow for improvement. Thank you again.

Specific comments

Line 28: correct “flooding inundation” with “flood inundation” Lines 220-223: please give some quantification (the same for lines 246-249). Addressed.

Lines 224-227: please avoid the repletion of the same concepts (the same for lines 250-253). Addressed.

Lines 264-265: I do not see any clear and explicative comparison among observed data and RCMs outputs for the reference period. Please provide an additional panel in Figure 6 with a statistic for the comparison (the same for Figure 8, but for air temperature some data for comparison are already given). Thank you for your suggestion. They have been considered while editing the manuscript.

All your concern was addressed to make the paper easy reading.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

The authors have answered to my questions and have adressed my suggestions. Concequently, I beleive that the manuscript is appropriate for publication.

Reviewer 3 Report

The manuscript was improved a lot. All my comments are well addressed or replied. I would suggest to accept it.

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

The subject of the paper is interesting both for scientific community and policy makers in the study region provided it is clearly treated, the results are well presented and clearly explained, and the conclusions are sound.

First of all, the author have to correct the title of the paper to fit with the content of manuscript in terms of simulation data used in their research. The title mentions “CORDEX regional climate models” while in the section 3 Materials and Methods, data description refers to the RCM simulations developed in the framework of ENSEMBLES EU FP7 project.

Further on I will make specific comments and suggest some clarifications to be done.

- The Abstract could be improved to clearly emphasise the changes between the characteristics of future projection compared to the reference period.

Material and Methods:

3.1 Observational climate data set:

Please, clarify

- 1) If you have used only 14 rainfall stations to create the gridded data, why did you first mentioned 34 rainfall stations (line 128-129) ?

- 2) Please, specify the spatial resolution of obs data you have created out of these 14 rainfall stations

- 3) Please, comment on the difference between rainfall (blue triangles) and hydrometric stations (red dots) in Figure 2

-4) How about the temperature stations? How have you managed with the comparison between simulated and observed temperature?

-5) The selection of the “reference” period for the simulations 1980-1999 ??? (Line 168). Is that correct?

-6) If you have selected the reference period 1988-2010 this means that your evaluation period overlaps the period 2000-2010 during which the RCM simulations are conducted under A1B scenario. In such case, and the comparison of the simulation with observations is not correct provided you use evaluation runs where the RCMs are driven by reanalysis. If you did so, please, clarify these things in the paper.

-7) Lines 170-171: It is not clear which simulated data (precip and/or temp) have been spatially averaged and then compared to observation data, and at which time scale.

-8) Please, provide more information on discharge data (time scale, how many series). The analysis of discharge series is not provided in the paper.

3.3 Statistical methods

1) Lines 177-179: “seasonal average maps ..over the 1988-2010 reference period “ – comparison between simulations and observations to validate the RCMs are missing in section 4 “Results and discussion” where the comparison is presented for annual mean of precipitation. However, the evaluation of model simulation against observations needs more clarifications.

2) line 184 – How do you define the average frequency? Was the frequency calculated in each grid point and the averaged over the domain?

3) line 187 : Using “deciles” and “percentiles” may induce confusion. Please, decide and make due clarifications.

4) were the percentiles calculated in each grid point and then averaged?

5) What discharge data have you used? Please, describe these data in section 3.2

4 Results and discussions

4.1 Spatial distribution of the averaged annual precipitation and temperature

1) In order to make a spatial comparison between simulations and observation data, you should have regridded first the data to a common grid and then compared them as difference (for temperature) and percentace (for precip) between simulation and observation. This step was not described in section 3.

2) Please, describe how have you calculated the change in Fig. 4 and Fig 5? It seems in Fig 6 that the change should be the difference in degree not %.

3) The annual cycle of precipitation and temperature presented in Fig 7 shows large biases of the RCM simulations compared to the observations. The RCM simulations should have been bias corrected at daily time scale before the calculation of frequency distributions, percentiles and applying the GEV model. The results you would have got were different.

4) In all figure captions where the comparison between simulations and observation is presented, please specify the observation dataset used.

5) Line 283: The Fig 8 does not present patterns but the annual cycle

6) Line 311: section 3.3 should be 4.3

7) Please, describe in section 3 or here how have you calculated the empirical cumulative distribution of daily precip. Figure 10 seems to show aggregated curves over the domain.

8) Is the 99^th percentile value in Table 3 calculated at annual scale? It shows large biases of RCM simulations compared to the observations. This is one more argument for bias correction before dealing with statistics of daily data.

9) Figure 12 shows large biases in the monthly distribution of the 99^th percentile. The fact that the models present similar distributions of extreme precip both in the reference and projection periods demonstrates that they must be bias corrected before the statistics of extremes is applied.

Given the above comments and suggestions, I would strongly encourage the authors to reorganize their research on the proposed topic and take into consideration the suggestions intended to improve the scientific quality of the paper and make the presentation of the results and conclusions more clear.

Author Response

Reviewer , thank you for their contribution to the improvement of the scientific quality of the article.

Author Response File: Author Response.pdf

Reviewer 2 Report

see attached file

Comments for author File: Comments.pdf

Author Response

Dear Reviewer

Thank you for this contribution to the improvement of the scientific quality of the article.

Author Response File: Author Response.pdf

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Climate and Extreme Rainfall Events in the Mono River Basin (West Africa): Investigating Future Changes with Regional Climate Models

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