Influence of initial soil moisture in a regional climate model study over West Africa – Part 2: Impact on the climate extremes

Koné, Brahima; Diedhiou, Arona; Diawara, Adama; Anquetin, Sandrine; Touré, N'datchoh Evelyne; Bamba, Adama; Kobea, Arsene Toka

doi:https://doi.org/10.5194/hess-26-731-2022

Articles | Volume 26, issue 3

https://doi.org/10.5194/hess-26-731-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-26-731-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 26, issue 3

Research article

|

11 Feb 2022

Research article |

| 11 Feb 2022

Influence of initial soil moisture in a regional climate model study over West Africa – Part 2: Impact on the climate extremes

Brahima Koné, Arona Diedhiou, Adama Diawara, Sandrine Anquetin, N'datchoh Evelyne Touré, Adama Bamba, and Arsene Toka Kobea

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Final revised paper (published on 11 Feb 2022)
Preprint (discussion started on 08 May 2020)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC1: 'Reviewer Comments', Anonymous Referee #1, 17 Jun 2020
- AC1: 'Reply to the comments of the referee 1 for the manuscript hess-2020-113', Arona Diedhiou, 03 Sep 2020
RC2: 'Review of Part II', Anonymous Referee #2, 24 Jun 2020
- AC2: 'Reply to the comments of the reviewer 2 for the manuscript hess-2020-113', Arona Diedhiou, 03 Sep 2020

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Reconsider after major revisions (further review by editor and referees) (09 Sep 2020) by Shraddhanand Shukla

AR by Arona Diedhiou on behalf of the Authors (29 Sep 2020) Author's response Manuscript

ED: Referee Nomination & Report Request started (01 Oct 2020) by Shraddhanand Shukla

RR by Anonymous Referee #1 (03 Nov 2020)

Suggestions for revision or reasons for rejection

Review: HESS-113

Influence of initial soil moisture in a Regional Climate Model study over West Africa. Part 2: Impact on the climate extremes.

This is the second revision on "Influence of initial soil moisture in a Regional Climate Model study over West Africa. Part 2: Impact on the climate extremes." I found the manuscript to be improved from the first, and the authors provided context on the review comments noting their experiment design. Overall, I think the results will be helpful for the field. I think the manuscript still suffers from some organizational issues, and if the authors can improve the organization the manuscript will be greatly improved.
I recommend minor revisions mostly for organization and clarity. While I only have a few comments, I think comment 1 will take some time and care to respond to.

Major Comment(s):

1. This manuscript is attempting to show a large amount of comparisons. For instance, the authors use 2 observational datasets that are compared, the RegCM4 control run compared to observations, stratify the analysis based on the two extreme years, and provide results based on their idealized soil moisture experiments. I appreciate the authors summarizing the results from each of their indices because it helped a lot with clarity, but I think the authors could go a step further and make it more clear what the main goal and results of this study are. i.e., Are the authors trying to mainly show the ability of RegCM4 to represent the extreme indices, the differences between two extreme years, or the idealized experiments? It could be all of these, but if that's the case I think your main points get somewhat lost in the details. In addition, while I again appreciate the authors care in comparing two observational datasets, I think it adds unnecessary information to the manuscript, and it also doesn't make sense when the authors say things like "TRMM is biased compared to CHIRPS" because they have not provided any reasoning why one dataset is preferred over the other. To sum up this comment, I think the manuscript would benefit from the authors picking a clear goal.

2. I'm still having some issues/concerns with your significance tests. Almost the entire region is significantly different in most of your Figures, to the point where it would be easier to show areas where there is NO significant difference. You did use a 90% confidence level, perhaps this is too low given your datasets? Is your sample size too low to form a proper significance test?

Minor Comments:

1. As in your first manuscript, I strongly suggest very careful editing. I gave a large amount of examples in my first review, and I'm going to give 1 example here:
(Line 154) The statistically significant differences has been tested between the control and the sensitivity experiments, we perform the two-tailed of the student’s t-distribution at every grid points as did by Liu et al. (2014) in a similar work over Asia.

Can be rewritten to something similar to the following: Significance of differences was tested for the control vs. sensitivity experiments. We used a two-tailed Student's t-test at each grid point as in Liu et al. (2014).

2. Table 2: This is a lot of data to look at. Is there a way to highlight some of the values you want to draw the reader to? Such as using an asterisk, bolding, italics, etc.

3. Table 3: Same comment as above.

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RR by Anonymous Referee #2 (04 Nov 2020)

Suggestions for revision or reasons for rejection

The authors have not addressed my previous concerns. See below for portions of my original comment, followed by the author response, and my follow-up comment. I still have 4 concerns with the manuscript.

 1. Original comment: “Model evaluation: The authors need to either demonstrate that the model used can reproduce precipitation or temperature extremes in the study region or provide a citation demonstrating this otherwise this model may not be a good tool for this research question. It’s important that the evaluation be of precipitation extremes rather than the means or seasonal cycle (as in Koné et al. 2018) since that is what the authors are focusing on.

Author’s response: Thank you for your comment. The RegCM model is one of the most widely used models by the scientific community to reproduce mean and extreme climate a most anywhere in the world. In this study we evaluated its performance in West Africa for extreme climate. The model performs well in West Africa as well as in Asia in the representation of mean and extreme climate”

Follow up comment: Please provide a reference for this, particularly with respect to climate extremes. Replying to my comment by stating it in an author response without reference is inadequate and unsupported. I don’t mean to be stubborn, but the authors’ response is dismissive.

2. Statistical significance: The procedure for calculating statistical significance remains unclear. Do the authors pool all points in a given year into a single distribution to test significance of the test year against the reference? If so, this makes sense, but it does not make sense how they stipple point-wise statistical significance as in the bottom panels of Figure 2. With point-wise statistical significance the authors are apparently comparing the three model ensemble observations at each point against a single reference value? It’s not possible to do statistical significance using 3 observations. Using a student-t distribution with three values is not appropriate. Please clarify, how many observations are in the reference distribution at each point in space and how many observations are in the wet or dry experimental ensemble at each point in space. As I mentioned in my original comment, it’s okay if the authors simply remove the statistical significance.

3. Pattern correlation in Table 3: I understand that pattern correlation is a common statistical tool, but I don’t believe it’s appropriate to use the pattern correlation of absolute temperature values. It would be more appropriate to conduct a pattern correlation of anomalies of each variable rather than the absolute value.

4. My final comment was for Table 3. I believe the left columns in Table 3 should not read “TRMM_2003” but rather “EIN_2003” correct? This table is evaluating the daily temperature anomalies from the EIN reanalysis, not the TRMM observations

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ED: Publish subject to revisions (further review by editor and referees) (16 Nov 2020) by Shraddhanand Shukla

AR by Arona Diedhiou on behalf of the Authors (28 Dec 2020) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (10 Feb 2021) by Shraddhanand Shukla

RR by Anonymous Referee #2 (15 Feb 2021)

RR by Anonymous Referee #1 (26 Apr 2021)

Suggestions for revision or reasons for rejection

This is the third revision of HESS 113. Overall I find Part-II to be interesting, but I don't feel that the authors fully responded to my comments in my second revision. Also, as noted in my review of HESS 112, while I appreciate the authors sending the manuscript for editorial review, I think the authors still need to read over the paper for some missed edits, some of which are noted below. Overall my recommendation is minor revisions as again I think these are mostly cosmetic suggestions, but please note that the authors should carefully respond to each comment.

1. In my second review, comment 2, I stated: I'm still having some issues/concerns with your significance tests. Almost the entire region is significantly different in most of your Figures, to the point where it would be easier to show areas where there is NO significant difference. You did use a 90% confidence level, perhaps this is too low given your datasets? Is your sample size too low to form a proper significance test?

The authors response did not fully answer the questions posed. One could simply remove the significance test at this point, but if not, then do the authors feel that 90% CL is appropriate here, and why? In addition, I feel like your sample size is far too low to perform a proper significance test, but I'm unsure of the sample size used as I do not see it stated.

2. There is an exclamation point on line 156 after the word "neighboring"

3. Line 191: "The TRMM datasets underestimate..." Compared to CHIRPS?

4. Line 193 should read "The strongest underestimation was found over the central Sahel..."

5. Given the authors response to my note in my second review, comment 1, on the use of the two observational datasets TRMM and CHIRPS, I'm unsure why this comparison is indeed necessary for this particular manuscript. If in fact CHIRPS is considered more appropriate for extremes in West Africa with the given references, why re-assess it here? It may clarify things to remove this comparison, unless the authors think it is strictly necessary to include. If the authors do think that this comparison is necessary to include, then very clear reasoning should be provided.

6. Are there similar references that discuss the ability of the temperature datasets over West Africa? I could see this as a reason for including the comparison if there are no other references, but again this does not seem to be the focus of this particular manuscript.

7. As in Part-I, I suggest again noting that these experiments are done in a highly-idealized framework and are intended to show the potential impact of very strong soil moisture conditions on extremes, and should thus be used as a guide or first look at the influence of soil moisture on extremes.

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ED: Reconsider after major revisions (further review by editor and referees) (01 Jun 2021) by Shraddhanand Shukla

AR by Arona Diedhiou on behalf of the Authors (13 Jul 2021) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (03 Oct 2021) by Shraddhanand Shukla

RR by Anonymous Referee #3 (19 Nov 2021)

ED: Publish subject to minor revisions (review by editor) (03 Dec 2021) by Shraddhanand Shukla

AR by Arona Diedhiou on behalf of the Authors (12 Dec 2021) Author's response Author's tracked changes Manuscript

ED: Publish as is (20 Dec 2021) by Shraddhanand Shukla

AR by Arona Diedhiou on behalf of the Authors (26 Dec 2021) Manuscript

Short summary

The impact of initial soil moisture is more significant on temperature extremes than on precipitation extremes. A stronger impact is found on maximum temperature than on minimum temperature. The impact on extreme precipitation indices is homogeneous, especially over the Central Sahel, and dry (wet) experiments tend to decrease (increase) the number of precipitation extreme events but not their intensity.