An Investigation into the Future Changes in Onset and Cessation of Rain and Their Variability over the Aswa Catchment, Uganda
Round 1
Reviewer 1 Report
Hi,
The manuscript has been greatly improved. All my questions and requests have been answered.
Nevertheless, there are still inconsistencies and problems of form: for example whole paragraphs that have the style of a title (chapter 2.4), the same graphics that sometimes have different legends (JAN vs. 01, in figures 12 and 13), or illegible abscissa axes (figure 15) etc...
But I leave it up to the editor to correct all these form problems with the authors.
Yours sincerely
Author Response
Response to the Reviewer1's comments
In the manuscript, the responses and other changes have been highlighted with track changes and using the line numbers
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Comment |
Response |
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Coment 1: All my questions and requests have been answered. Nevertheless, there are still inconsistencies and problems of form: for example whole paragraphs that have the style of a title (chapter 2.4), the same graphics that sometimes have different legends (JAN vs. 01, in figures 12 and 13), or illegible abscissa axes (figure 15) etc.. |
· The whole document has been checked and where necessary changes have been made
· Figures 12 and 13 legends have been harmonised. The months in figure 13 have been changed from numbers to text (e.g. 01 to Jan)
· The illegible abscissa axes for figure 4-11,14-16 have been edited and are now legible
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419-432
346-375, 433-435, 439-442, 446-447 |
Author Response File: 
Author Response.docx
Reviewer 2 Report
Dear Authors,
I found the manuscript improved under many aspects since the last revisions' iteration.
However, I believe that some work is still required before being suitable for publication.
More specifically,
- English should be improved throughout the paper;
- Evident editing flaws must be fixed (it should be done before submitting the manuscript);
- Figures (4-11) readability must be improved. x-axis tick labels are not interpretable.
Furthermore, please address also some comments that I reported throughout the manuscript identifying missing or unclear methodological steps description.
Best regards
Comments for author File: 
Comments.pdf
Author Response
Please see the attachment.
Author Response File: Author Response.docx
Reviewer 3 Report
Studies that use very specific regions of the Earth's surface must necessarily justify the reasons for using this region and what the meanings of these data and results are for the local, regional and global climate scenario.
The study has a region of 31,000 km2, the study area has a range of approx. 150km wide, according to the legend in figure 1. How to link this to TRMM data, if this satellite has a spatial resolution of 100km. I co-consider this crucial spatial relationship to be discussed and considered as statistical results in such peculiar areas.
I believe that when it comes to presentation, work can improve the quality and presentation of images and graphics. Especially in figure 1, the location map needs to be completely reformulated.
Author Response
Response to the Reviewer3's comments
In the manuscript, the responses and other changes have been highlighted with track changes and using the line numbers
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Comment |
Response |
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Coment 1: · Studies that use very specific regions of the Earth's surface must necessarily justify the reasons for using this region and what the meanings of these data and results are for the local, regional and global climate scenario.
· I believe that when it comes to presentation, work can improve the quality and presentation of images and graphics. Especially in figure 1, the location map needs to be completely reformulated.
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·The study area of Aswa catchment offers a typical Ugandan and African setting where the future socio-economic wellbeing of the community who mostly depend on agriculture is uncertain due to impacts of climate change. More than two million people, of which more than 70 % are peasants, live in Aswa catchment. The catchment is characterized by periodic and extended drought spells leading to chronic food insecurity and famine. With annual population growth rate of over 3 %, and within the context of climate change, the future is increasingly becoming more uncertain. A detailed research on variability in the future rainfall changes and their onset and cessation at the catchment and local level is, therefore, required for effective crop, environment and water resources planning and management
·The TRMM grid resolution is 32 by 32 Km, while for the GCMs used is within 290 by 435 km. The TRMM data can therefore be used for downscaling GCM data to a finer resolution.
· Figure 1 has been improved. A new figure has been inserted |
45-53, 93-95
114-122
107-109 |
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
In this paper, Tropical Rainfall Measuring Mission (TRMM) was considered to calibrate the Statistical Downscaling Model for downscaling of two General Circulation Models to simulate future changes in rainfall. The analysis was done in terms of trend, wet and dry conditions/variability; onset and cessations of rains using Mann Kendall, Standardized Precipitation Index (SPI) and cumulative percentage mean rainfall method respectively. Before publishing, the following key questions should be addressed.
The web address of HadCM3 and CanESM2 should be provided in the manuscript. In lines 105-106, standard homogeneity test was performed. Why this test was performed? How it was performed? In lines 114-115, highest correlation was considered as super predictor. Are the correlations statistically significant? In equation 1, line 117, correlation coefficient is shown as RI. However, in line 121, it was put as R1. Please make them consistent. Table 2 is not explained properly. Why there are four partial correlation coefficients (P.r). For some variables, the four values of the P.r is shown but for some only one, why? It was claimed that the 2nd and 3rd…… variables were selected based on smallest PRP. However, it is not supported by Table 2. Please clarify. In lines 135-136, why different time-steps data were selected for Had3 and CanESM2? In line 224, symbol for standard deviation is missing. In tables 5 and 6, why 9 months results have been shown?
There are also researches on rainfall prediction based on linear and non-linear modelling approaches using the climate indices. Some of them shown below should be included in the literature review.
Hossain, I., Rasel H.M., Imteaz, M.A., and Mekanik, F., 2019. Long‑term seasonal rainfall forecasting using linear and non‑linear modelling approaches: a case study for Western Australia, Meteorology and Atmospheric Physics, DOI: https://doi.org/10.1007/s00703-019-00679-4.
Abbot and J. Marohasy, "Skilful rainfall forecasts from artificial neural networks with long duration series and single-month optimization," Atmospheric Research, vol. 197, pp. 289-299, Nov 2017.
Author Response
Please see attachment below
Author Response File: Author Response.doc
Reviewer 2 Report
In this study are presented current and future changes in rainfall patterns, trends, extreme occurrences, onset and cessation of rainfall over Aswa catchment using several statistical methods. Projections from downscaled global climate models for the near future (2006 2035), midterm (2036 to 2065) and long term (2066 to 2100) future periods are considered coupled to pseudo-observed product TRMM.
This study represents an attractive research subject. Future precipitation pattern changes regarding typically agriculture-based communities take on extreme importance.
The statistical approaches' spectrum presented to assess changes in rainfall in the considered area, are enough consistent and suitably applied. The results are relevant even if poorly described in some section of the manuscript. Conclusions section is completely missed even if a poor summary of the results is presented in the Discussion section.
It follows some point-by-point remarks for the Authors.
Line 20 please introduce CV acronym.
Line 61 the research field and the main concept regarding the statistical downscaling is poorly introduced and described. I suggest to provide some more introduction detail regarding statistical post-processing (i.e., statistical bias correction and statistical downscaling) in climate services. Also should be mentioned that the statistical post processing of the climate model simulations can affect the original climate change signal which in turn can alter the impact model results.
Some reference:
Maraun, D. Bias Correcting Climate Change Simulations - a Critical Review. Curr. Clim. Chang. Reports 2016, 1–10.
Sangelantoni, L.; Russo, A.; Gennaretti, F. Impact of bias correction and downscaling through quantile mapping on simulated climate change signal: a case study over Central Italy. Theor. Appl. Climatol. 2019, 135, 725–740.
Maraun, D.; Shepherd, T.G.; Widmann, M.; Zappa, G.; Walton, D.; Gutiérrez, J.M.; Hagemann, S.; Richter, I.; Soares, P.M.M.; Hall, A.; et al. Towards process-informed bias correction of climate change simulations. Nat. Clim. Chang. 2017, 7, 764–773.
Line 80 correct latitude-longitude.
Line 136 Is not clear how do you generate 20 ensembles. Please specify this important point.
Line 210 PDF and CDF can not be defined parameters. Please correct and make clearer this passage.
Line 221 To me is not clear how we shift from a Gamma to a Gaussian-Normal PDF. Please clarify.
Line 243 Figure 2 linear regression interpolation in not visible in white color.
Lines 265-268 Trends result section is rather poorly described. Please argument Mann Kendall test results and also specify which of the results present a statistical significance in function of the p_value. I would also suggest splitting Table 4 (is not sufficiently clear in my opinion) in two tables, one for the Homogeneity SNHT test and the second one for the Mann Kendal Statistics.
Line 353 Also Tables 5 and 6 could be better described. Which is the role of the TRMM in this analysis. Does the CV originated from TRMM for the first historical segment and then from the GCM the future time segments? Here the confusion, in my opinion comes from associate two different kinds of data (pseudo-observations and simulations) in the same line of the Table. Please underline the distinction between the results coming from the two different kind of data.
383 Please make discussions section more comprehensive stressing the connection between the different statistical analyses performed. Finally, add a conclusive summary.
Author Response
Please see the attachment
Author Response File: Author Response.doc
Reviewer 3 Report
This manuscript presents an investigation into the future changes in onset and cessation of rains and their variability over Aswa catchment in Uganda. This study could be interesting if it were improved in depth. In my opinion, this study can only be accepted with major corrections.
Major comments (without correction of all these elements, I will not be able to accept the manuscript in the end of the review process) :
1) Before drawing any results on the future evolution of precipitation using the Can and HadC models, a study of their results over the current period must be carried out to answer the following questions:
a) how do the precipitations of these two models behave over the last 30 years?
b) What are the differences/biais with the observations?
If these two models already indicate differences in the present, it is logical that these differences persist in the future and in this case your conclusions are no longer correct.
2) Why did you choose these two models? You must absolutely justify your choice.
3) When analysing the evolution of the SPI index, you conclude "these values increase as we move towards the end of the century". It may seem clear to you, but it's not clear to me. What is the trend? What is the statistical significance of this trend? You must absolutely justify this sentence in a robust way.
4) Section "4. Discussion" is not a discussion section, it is a conclusion section. I think that your paper must absolutely have a real discussion section to discuss your results. Perhaps by going to look for half-discussions in the result section, but these discussions need to be increased and the results obtained more critically.
General comments :
5) A map of the general location of the catchment would be interesting.
6) Section "2.4 Downscalling and projection of future rainfall" is not clear. I think this section needs to be rewritten more clearly. I think there's a confusion between "predictors" and "predictand". The latter is not clearly stated. And the RI in the formula are not the same that the R1 in the text.
7) As with the corresponding text, Table 2 is not clear. For example, why didn't you choose "specific humidity at 500hPa" as the third predictor since it has the same score as the one chosen?
8) In Figure 2, the correlation may be good, but what about the error? Error that is greater than 50mm on average?
9) For all Figures, I ask the authors to check if they have all the units and a detailed legend. Indeed, the legend must be self-consistent with the text.
10) The results of Figures 4-11 should be pointed to a map. This would improve the results and conclusions of this article.
11) The "coefficient of variation" is not clear to me. The authors should specify, further detail and show the implication of this index.
12) Between lines 345 and 351, the authors use examples that are not at all comparable to their study area, nor comparable in terms of climate, soil or agricultural practices. This paragraph needs to be reviewed.
Minors comments :
13) Throughout the text, there are double spaces or lack of spaces between two words, or lack of spaces between a point or comma and a word. I think the text needs to be carefully reviewed.
14) The map is far too large for the information it provides. I think the authors can reduce its size and increase the font of toponyms.
Author Response
Please see the attachment
Author Response File: Author Response.doc
Round 2
Reviewer 1 Report
The authors have fulfilled my comments.
Reviewer 3 Report
Concerning the remark n°1 :
The authors use GCMs, General Circulation Models. These models do NOT represent the recent climate, these models only represent the AVERAGE of the recent climate. So it is nonsense to compare only a few years.
In this study, the authors compare between 2 and 12 years for calibration and validation but this is a scientific heresy.
The authors must ABSOLUTELY compare a long climatic series, i.e. a period of 25 to 30 years.
Without this kind of comparison, all future analyses are invalid.
Concerning the remark n°3 :
I realize that the authors highlight the results that interest them. Indeed, they use Kaabong values to justify an increase in IPS. But when you look at Kitgum's values, the results are much less clear, especially with "Extremely Wet 1.12 --> 0.00--> 4.41". What I would have liked to see in this study are regressions or other forms of trend studies over time of these indices. In addition, it is not known how other stations behave. In the end, the explanations provided by the authors do not convince me.
As I wrote in my first review, these two points were among the 4 crucial points where authors are obliged to answer otherwise I will not be able to accept the manuscript. As the authors did not convince me, I am obliged to reject this manuscript as it stands.
