Analysis of the Potential Impact of Climate Change on Climatic Droughts, Snow Dynamics, and the Correlation between Them

Round 1

Reviewer 1 Report

Reviewer’s Report on the manuscript entitled:

Analysis of potential climate change impacts on climatic droughts, snow dynamics and their correlations

The authors assessed the climate change impacts on meteorological and hydrological droughts considering the snow cover area dynamics and analyzed the correlation between both types of droughts. Although the topic and results are interesting, the presentation and structure of the manuscript must be improved. Furthermore, I had a hard time providing comments because the line numbers were not provided.

I see many style/typo issues in this manuscript. I list below some of such issues but there are many more to be checked and corrected.

Line 10 in Abstract should be “multiple”.

Please remove all the square brackets [] from the Abstract.

Line one in third paragraph of page 2. It should be “…monitoring and analysis” Same paragraph, it should be “…appropriate analysis…requires” not “…analyse…require”

Please define SSCI, SCA, SPI, SPEI, etc. Please define all the acronyms the first time the appear and be consistent with their style. Always, use the capital letter for the first letters. Please also add an acronym table at the end of the manuscript listing all acronyms used.

Please restructure the manuscript as follow:

1. Introduction
2. Materials and Methods

     2.1 Study region

     2.2 Datasets and Preprocessing

     2.3 Methods

         2.3.1 Drought Indices

         2.3.2 Drought Statistics

         2.3.3 Future Drought Strategy

3. Results
4. Discussion
5. Conclusions

 

And then update the last paragraph of the Introduction.

 

Section 2.1: “…Note that ….future drought…” please remove the space after Note that..

On page 4. You have a section 2.1, then 2.1.1, then 2.1.1.1! You do not have section 2.1.1.2! Please avoid using too many subsubsections. Please follow the structure that I suggested above. Some of the formulas and indices listed in the article can be removed and be easily referred to by an appropriate reference instead.

Figures are generally produced poorly and require attention. For example, the legend in Figure 4 c should be placed in the bottom corner of the panel so it does not hide the points. Figure 5, the y-axis label, and unit must be inserted. The x-axis and y-axis values of Figures 3 to 12 should be enlarged. Please note that the font size of the numbers and texts in the figures are recommended to have a size like the font size of the figure captions. Finally, please ensure that the quality of the figures have a resolution of at least 300 dpi.

Section 4.1.1. It should be 1976-2005 not 976-2005.

Also, it is “e.g.,” not “e.g,” Please check and correct elsewhere.

Please explain why in panels (a),(b),(c),(e),(f) of Figure 6, there are some horizontal patterns of the datapoints. Is there some sort of a systematic error in the data?

Please check the references for the authors’ names, volume, page numbers, etc. and ensure that they follow the MDPI guidelines. Please ensure that they are properly cited in the manuscript. For example, in the first paragraph in Conclusion: It should be [81] not [810]. Or in page 25, the third paragraph, it should be [103,104,105] not [103.104.105].

The impact of climate change on vegetation, drought, and wildfires are rigorously analyzed via the least-squares spectral and cross-wavelet analyses using remote sensing and meteorological data:

https://doi.org/10.3390/rs12152446

The software package that comes with the article above is available at

https://geodesy.noaa.gov/gps-toolbox/JUST.htm

The least-squares cross-wavelet analysis described in the paper above investigate the coherency between the seasonal components of climate and vegetation time series in the time-frequency domain and provide the phase lag/lead information as well unlike the traditional correlation analysis that is time independent.  

Likewise, the Cross Wavelet Transform and Wavelet Coherence were also applied to investigate the relationship between the climate indices and drought/flood conditions in

https://doi.org/10.3390/atmos12111446

https://doi.org/10.3390/w14010026

The cross-wavelet analysis is considered a robust method that show how the components of the time series are coherent in the time-frequency domain and provides the phase information. Therefore, I suggest the authors to add a paragraph in the discussion section and discuss the use of the cross-wavelet analysis by referring to the four articles above. Places that this technique could potentially provide better results are in Figure 5, and on page 3 part (2) the coherency (instead of correlation) between meteorological and hydrological droughts. Also between climate and vegetation time series, etc. So, these should at least be mentioned in a paragraph.

Finally, please very carefully proofread the manuscript.

Thank you for your contribution

Regards,

Author Response

Thank you to the Reviewer for the comments that helped to improve the paper and for recognizing the interest of the topic and results. We apologize for not including line numbers in the previous version. The new version includes it.

I see many style/typo issues in this manuscript. I list below some of such issues but there are many more to be checked and corrected.

Line 10 in Abstract should be “multiple”.

Please remove all the square brackets [] from the Abstract.

Line one in third paragraph of page 2. It should be “…monitoring and analysis” Same paragraph, it should be “…appropriate analysis…requires” not “…analyse…require”

Certainly we detected several typo/style issue mistakes in the text. The manuscript has been carefully revised to correct these mistakes. These changes were marked with “Track Changes” in Word file.

Please restructure the manuscript as follow:

Introduction
Materials and Methods
     2.1 Study region

     2.2 Datasets and Preprocessing

     2.3 Methods

         2.3.1 Drought Indices

         2.3.2 Drought Statistics

         2.3.3 Future Drought Strategy

Results
Discussion
Conclusions
 

And then update the last paragraph of the Introduction.

 

The manuscript structure has been modified following the proposed structure in the review:

1. Introduction
   2. Materials and Methods
   2.1 Study region
   
   2.2 Datasets and Preprocessing
   
        2.3 Methods
   
            2.3.1 Drought Indices
   
            2.3.2 Drought Statistics
   
            2.3.3 Future Drought Strategy
   
   3. Results
   4. Discussion
   5. Conclusions
   
   

And we change the last paragraph of the introduction. See the modified paragraph below:

“This article is organized as follows: Section 2 describes the case study and available data and presents the methodology used to assess potential climate change impacts and its uncertainty in droughts. Section 3 displays the results analysis. Section 4 discusses main study aspects. Section 5 presents main conclusions.”

 

Please define SSCI, SCA, SPI, SPEI, etc. Please define all the acronyms the first time the appear and be consistent with their style. Always, use the capital letter for the first letters. Please also add an acronym table at the end of the manuscript listing all acronyms used.

The acronyms have been defined the first time that they are used (SCA, SSCI, etc.) and a list with all the acronyms defined in the text has been included at the end.

 

Some of the formulas and indices listed in the article can be removed and be easily referred to by an appropriate reference instead.

We have also reduced considerably the number of equations. We have made reference to other articles, in which the calculation procedure of eliminated equations was developed.

 

Figures are generally produced poorly and require attention. For example, the legend in Figure 4 c should be placed in the bottom corner of the panel so it does not hide the points. Figure 5, the y-axis label, and unit must be inserted. The x-axis and y-axis values of Figures 3 to 12 should be enlarged. Please note that the font size of the numbers and texts in the figures are recommended to have a size like the font size of the figure captions. Finally, please ensure that the quality of the figures have a resolution of at least 300 dpi.

We inserted the y-axis label in Figure 5, as well we changed the location of the legend when it will necessary. All figures have been modified by enlarging the font size on the x-axis and y-axis, as well we modified the numbers size in figures. We also ensured that the quality of the figures have a resolution of at least 300 dpi.

The cross-wavelet analysis is considered a robust method that show how the components of the time series are coherent in the time-frequency domain and provides the phase information. Therefore, I suggest the authors to add a paragraph in the discussion section and discuss the use of the cross-wavelet analysis by referring to the four articles above.

 

 We added a comment in discussion about the usefulness of cross-wavelet analysis as a method to study the relationship between meteorological and hydrological drought and cited the literature suggested by the Reviewer. See the modified paragraph below:

“Another possible option will be to use the cross-wavelet analysis, which is a robust method that show how the components of the time series are coherent in the time-frequency domain and provides the phase lag information. The cross-wavelet analysis has been used in other researches to study the coherency between the seasonal components of climate and vegetation time series and provide the phase lag [106,107], and investigate the relationship between the climate indices and drought/flood conditions [108,109], among others.”

 

Please explain why in panels (a),(b),(c),(e),(f) of Figure 6, there are some horizontal patterns of the datapoints. Is there some sort of a systematic error in the data?

In response to question concerning Figure 6 (about the correlation between SPI-SPEI). There isn´t a systematic error in data. The horizontal pattern present in figures is due to the fact that SPEI (y-axis) does not present values below -1.5 when we made the analysis in 3 and 6 months aggregation time scales. On the other hand, SPI (x-axis) does reach lower values ​​(up to -3). For this reason, when we do a scatter-plotting, a horizontal line is observed in 3 and 6 months temporal aggregation scales, since SPEI values ​​(values ​​close to -1) are associated with SPI values ​​ranging from -3 to 0. We clarified in the new version of the manuscript:

“Note that SPEI and SPI have different minimum values (see the horizontal patterns of the data points in Figure 6. a, b, c, e and f). However the maximum values are similar.”

 

Thank you for your support,

Regards.

Author Response File: Author Response.docx

Reviewer 2 Report

This paper presents a very interesting and promising study on drought assessment in the context of climate chance scenario in alpine region. The key factor and the point of novelty of this work is the the adoption of SCA as proxy of hydrological droughts intensity. Specifically,  the adoption of  multiple climatic and SCA series generation by using a SWG  has allowed to study the correlation between  SCA droughts and meteorological droughts in the context of climate change. I think that this work is suitable for publication after some minor revisions.

 

Please add some proper reference to support the statement: “Despite the fact that drought is a phenomenon that can occur in any world region, droughts analysis in arid and semi-arid regions is of vital importance, since they are areas with water resources scarcity where the adverse effects may be greater due to climate change”

 

I think that (RCP 835) should be (RCP 85)

 

Eq. 1. for sake of completeness, could the authors specify what “x” stands for?

 

If I have understood correctly, the SSCI index in computed as the SPI but by using the SCA as independent variable?

Could you add a paragraph on “SSCI” in section 2.1.1?

 

I think that some comment on SCA and MODIS reliability should be done in the introduction. This the supporting literature review

“Di Marco, N.; Righetti, M.; Avesani, D.; Zaramella, M.; Notarnicola, C.; Borga, M. Comparison of MODIS and Model-Derived Snow-Covered Areas: Impact of Land Use and Solar Illumination Conditions. Geosciences 2020, 10, 134. https://doi.org/10.3390/geosciences10040134 ”

 

Parajka, J.; Holko, L.; Kostka, Z.; Blöschl, G. MODIS snow cover mapping accuracy in a small mountain catchment–comparison between open and forest sites. Hydrol. Earth Syst. Sci. 2012, 16, 2365–2377

 

“Forsythe, Nathan & Fowler, Hayley & Kilsby, Chris & Archer, David. (2011). Opportunities from Remote Sensing for Supporting Water Resources Management in Village/Valley Scale Catchments in the Upper Indus Basin. Water Resources Management. 26. 10.1007/s11269-011-9933-8. ”

 

Could specify in figure 1 that also future scenario of SCA are generated? Have I understood correctly?

 

Author Response

Thank you to the Reviewer for the comments that helped to improve the paper and for recognizing the interest and novelty of the work.

 

I think that (RCP 835) should be (RCP 85)

 

The manuscript contained several mistakes (in addition to the commented “RCP 835” by “RCP 8.5” that have been corrected. This changes in typo/style issue could be consult in the manuscript (“Track Changes in Word”).

 

I think that some comment on SCA and MODIS reliability should be done in the introduction. This the supporting literature review

About SCA and MODIS comment. I'm sorry, but when I revised the submitted manuscript I noticed that I made a mistake. SCA data “historical and future” used in this study are not from MODIS. SCA data provide from a cellular automata model previously developed in another investigation. We have included a short paragraph explaining the methodology used in this work and we have cited it. See the modified paragraph below:

“In this study we used a CA model based on one developed by Pardo- Igúzquiza et al. [63,64] to simulate SCA using climatic indices (precipitation and temperature) as descriptive variables and a series of parameters (threshold precipitation, threshold temperature and threshold in the number of neighbor cells that produce a change in the cell state) This model uses a series of transition rules that allows to determine the absence or presence of snow. It has proven to be a useful tool for accurately simulating SCA dynamics [61,63,64].”

Nevertheless the cellular automata approach used MODIS data for calibration and validation. As suggested by the reviewer, we included a short paragraph about MODIS reliability and cited the literature suggested. See the modified paragraph below:

“With regard to SCA, it can be obtained from satellite data (e.g., NOAA satellite data or MODIS satellite data) or models. MODIS provides a good accuracy to SCA data [29,30], but in presence of a forest canopy dense the uncertainty in the MODIS SCA data increase [31], which reduces the accuracy.”

 

If I have understood correctly, the SSCI index in computed as the SPI but by using the SCA as independent variable?

Could you add a paragraph on “SSCI” in section 2.1.1?

 

In response to your question about SSCI. Yes, we calculated SSCI following the same procedure described for SPI, it only changes the input variable (SCA instead of precipitation). In the manuscript, we add a comment in section 2.3 in brackets: “(applying the same methodology as for SPI using SCA data as input)”.

 

Could specify in figure 1 that also future scenario of SCA are generated? Have I understood correctly?

Historical and multiple future SCA series comes from a previous work (Collados-Lara et al. (2019)). We modified Figure 1 to include it. We also included a short paragraph to explain the methodology used in this work.

 

Thank you for your support,

Regards

Round 2

Reviewer 1 Report

I would like to thank the authors for addressing my comments. The manuscript is significantly improved. Please find below a few more minor suggestions:

Figures 2 and 12. For time lag 0 and 3 months, the R^2 values are on the y-axis. I suggest expanding the x-axis slightly so that those points fall inside the panels for better visualization.   

Line 94-95. Please define the acronyms NOAA, MODIS, etc. Please note that all the acronyms must be defined the first time they appear in the manuscript.

Line 174. It should be 2.2.2

Line 184. It should be 2.2.3

Line 190. It should be 2.2.4

Line 198. It should be 2.2.5

Line 210. Style issue. Please remove the dot between 3 and b in Figure 3.b, please check and correct everywhere else, like lines 211, 213, 215, etc.

Finally please carefully proofread the entire manuscript before publication if accepted by the editor.

Thank you for your contribution

Regards,

Author Response

Thank you for your comments that it allows to improve this paper. Firstly, It´s possible you note that the composition of the manuscript changed because we have send it to a native English to improve the text.

Figures 2 and 12. For time lag 0 and 3 months, the R^2 values are on the y-axis. I suggest expanding the x-axis slightly so that those points fall inside the panels for better visualization. 

I think you make an error in the comment, because figure 2 is a location map. I think you refer to figure 4. I have changed x-axis (expanding the x-axis) in figures 4 and 12. Moreover, I also expanding the y-axis in figure 4.

Line 94-95. Please define the acronyms NOAA, MODIS, etc. Please note that all the acronyms must be defined the first time they appear in the manuscript.

I define the acronyms NOAA and MODIS in the manuscript. I also include these acronyms in the acronyms list and I add its definition next.

Line 174. It should be 2.2.2

Line 184. It should be 2.2.3

Line 190. It should be 2.2.4

Line 198. It should be 2.2.5

I changed the subsections like you indicate in the comment:

“2.2.1.1. “ by “2.2.2.”

“2.2.1.2.” by “2.2.3.”

“2.2.1.3.” by “2.2.4.”

“2.2.1.4.” by “2.2.5.”

Line 210. Style issue. Please remove the dot between 3 and b in Figure 3.b, please check and correct everywhere else, like lines 211, 213, 215, etc.

I correct all the style issues when I call the subfigures in the manuscript. In this way, I remove all dots between the numbers of the figures “3, 7, 8, etc.” and the subsections of the figures “b, c, a, etc.”. I also correct the number of the figures so that they appear from least to greatest in the manuscript.

 

Thank you for your support,

Regards.

Author Response File: Author Response.docx