Global Drought-Wetness Conditions Monitoring Based on Multi-Source Remote Sensing Data

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Review

1- In the summary, the sentence "There has been a pattern in the spatial distribution of global drought and moisture conditions over the past 20 years (2001-2020): Centered on extreme drought, with areas of moderate drought, mild drought and no drought expanding outwards in a circular pattern" is confusing. Try to rewrite it in a more understandable way.

2- The authors need to highlight the period of analysis, preferably in the last paragraph of the introduction, along with the questions they intend to answer. Add references that show studies on the influence of dry and wet periods in certain regions of the planet and their return periods.

3- The authors need to establish a clearer connection between the data analyzed, for example, the information from the SPEI and scPDSI drought indices are from 2001 to 2020, crop yelds from 2001 to 2016, while land cover types, only from 2015. How will all this be interconnected to prove that the SDDI is a more powerful stand-alone tool for monitoring drought/moisture than other existing methods?

4- There are no references for the SDDI thresholds shown in Table 4?

5- The PCI takes into account precipitation estimated via remote sensing by GPM-IMERG. Since precipitation is the raw material, or main input, for indices such as SPEI and scPDSI, won't the insertion of PCI lead to an effect similar to multicollinearity, i.e. won't we have inserted data into the SDDI formula that will force a good approximation between SDDI and indices such as SPEI and scPDSI?

6- If we have global monitoring products like the SPEI, why use the SDDI? The authors need to demonstrate more clearly in the manuscript the great advantage of adopting this index over others that are already freely available for global monitoring of dry and wet conditions.

7- Wouldn't Figure 1 actually be a table?

8- In Figure 2, in the legends (a), (b) and (c), use the versus symbol (x) instead of the minus symbol (-), as this could give the impression that the SDDI and the indices have been subtracted, instead of calculating the correlation.

9- Were the global land surface percentages of 85.5%, 87.3% and 85.1% for areas with correlations greater than 0? What is the exact correlation threshold considered to classify areas as consistent between SDDI and SPEI and scPDSI values? Was the critical correlation threshold based on any statistical test taken into account? Was this for the entire period 2001 to 2020 (if so, this needs to be made clear in the manuscript)? The authors do not show the physical reasons for the areas with low correlations observed on the continents, limiting themselves to stating that "The small inconsistencies in these areas do not affect the ability of SDDI to monitor global drought-wetness conditions, because these inconsistent regions are scattered and not without geographical variability." It doesn't seem to me that these areas are so scattered and small, as in the case of much of the Amazon region, part of northern Europe and Asia and North America. It is known that one of the limitations of precipitation estimated by satellites, such as the GPM-IMERG, is the difficulty of estimating the precipitation of some types of clouds, such as the hot Amazonian clouds. This needs to be better discussed (see and reference the manuscript: https://www.mdpi.com/2225-1154/11/12/241.).

10- Were the results shown in Figure 9 regarding trends statistically significant? Which test was used? For what level of significance? This was mentioned superficially at the end of topic 3.2.3, but needs to be explored further and should be highlighted in the results.

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

The article presented is very interesting, and useful in providing a long-term view of global drought events. Some parts still need to be improved:

Line 113-114: It is necessary to add an explanation, of why the drought monitoring index studied by the authors in this paper must cover the entire world, not specific to one or a group of countries.

L 116: It is necessary to explain further why the authors prefer to use SDDI to describe worldwide drought-wetness. Add a citation about using the SDDI.

L 180: spatial resolution 0.5Deg should also include the equivalent in km

L211: There is at least one citation regarding the classification of global drought-wetness. Where does the terminology used in Table 4 come from? (referring to which reference?)

L214-215: why is SDDI not compared with actual drought events?

L 296: Be careful when using the term “large scale”. For example, a 1:1000 scale is larger than a 1:5000 scale

L 514: Conclusion is different from summary. The conclusion should be made more concise referring to the results obtained.

Comments on the Quality of English Language

Moderate editing of the English is still required.

Author Response

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Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors made the suggested corrections and satisfactorily answered all the questions that were raised. Therefore, I thank the authors for their efforts in significantly improving the manuscript.