Drought Evaluation with CMORPH Satellite Precipitation Data in the Yellow River Basin by Using Gridded Standardized Precipitation Evapotranspiration Index
Round 1
Reviewer 1 Report
This paper uses a set of reconstructed high-resolution maps of surface hydrological variables to compute a newly defined drought index for the Yellow River Basin. The seasonal cycle and trends of the drought index are also analyzed. This is a very substantial work that synthesizes multiple sources of observations (particularly latest satellite measurements) of hydrological variables. In the context of climate monitoring, this work is among the latest attempts to push drought monitoring to higher spatial and temporal resolution; The dataset used in this paper has a horizontal resolution finer than 10 km, compared to previous well-established datasets of drought indices. (For example, the Dai-Palmer global drought index data has a spatial resolution coarser than 100 km.) The authors also use the new dataset to uncover the spatial and temporal structures of droughts in the Yellow River Basin. The findings could potentially be used for statistical predictions of droughts in that region. Overall, I find the results of this work useful and worth publishing. I have a few relatively minor comments:
(1) The authors claim that the CMORPH dataset has a temporal resolution of 0.5 hour and spatial resolution of 8 km, but the effective resolution (as supported by real observations) is likely coarser. For example, the 0.5 hour resolution in time is likely possible only for along-track data from the periods when there is a satellite fly-by overhead. After interpolation in space and time, the data would not have that resolution. In the context of the key analysis of this paper, it would be useful to state a more realistic effective resolution for precipitation and evaporation for the dataset.
(2) Many figures in the paper have a large number of panels. While the details in those panels are useful, the way they are presented/arranged sometimes make the figures hard to read. An example is Fig. 6. Perhaps due to the choice of the color scheme (the colors for the areas with upward and downward trends are not too different), I find it hard to discern the detailed structures of the trends in those small panels. In particular, the areas with the most significant trends (i.e., those with red or green color) are barely visible. If it is possible, I would suggest making the panels bigger to improve the clarity of presentation.
(3) Related to point (1) and (2), in Fig. 6 there appear to be very small red or green “dots” that represent the locations with a highly significant downward or upward trend. Some of those “dots” seem to be of the size of just one or a few pixels. This raises the question as to whether such a fine resolution is supported by the effective resolution of the original observations (that were used to construct the CMORPH data). In other words, whether those very small-scale trends shown in Fig. 6 are real. (If not, then perhaps it’s more meaningful to first perform a spatial averaging on the data before determining the trends.)
Author Response
Response to Reviewer 1
Manuscript No.: 438630
Title: Drought evaluation with CMORPH satellite precipitation data in the Yellow River basin by using Gridded Standardized Precipitation Evapotranspiration Index
Authors: Fei Wang, Haibo Yang*, Zongmin Wang, Zezhong Zhang, Zhenhong Li
Dear Reviewer #1:
We quite appreciate your favorite consideration and insightful comment. In particular, we welcome and note your comment “Overall, I find the results of this work useful and worth publishing”. Now we have revised the manuscript exactly according to your suggestions, and found these suggestions are very helpful to improve our paper. The revised portions were marked in red color in the revised manuscript. All changes were marked via “Track Changes” option.
We hope that these clarifications and revisions will now enable the paper to be accepted for publication in “Remote Sensing”, and look forward to hearing from you soon.
Yours sincerely,
Haibo Yang (on behalf of all the authors)
School of water conservancy and environment
Zhengzhou University
E-mail address: [email protected]
Author Response File: Author Response.pdf
Reviewer 2 Report
In this paper authors tried to assess based on CMORPH satellite precipitation data over the study are but there are some points that needs to be considered as following:
1. The main point that is not mentioned in this paper including title, abstract and conclusion that how the authors related the ground-based meteorological parameters to different temporal and spatial resolution remote sensing-based data. It is not clear that the authors how connected those parameters to each other or if they applied any geo-spatial method and what the rational of selection of that method. And how authors assessed the accuracy of implemented geo-statistical method. This part also would be a big portion of materials and methods that totally missed in this paper.
2. It’s not clear that how the authors dealt with uncertainty caused by using different RS data with different spatial and temporal scales. And if any homogeneity test has been done before using different datasets.
3. The authors indicated that used M-K method in their research but the there is no neither explanations about this method’s assumptions nor pre-processing required statistical tests for this method e.g. non-stationarity, seasonality etc. I recommend that the authors should add a separate section and discuss in detail about implemented M-K method and its assumptions and required statistical tests. This part will be the main part of materials and methods of this manuscript.
4. For better results in comparison with other grid-based data, I suggest that authors consider cluster analysis to show if this index has better results over the particular group of grids that may have similar condition in terms of agro-climatological conditions.
Author Response
Response to Reviewer 2
Manuscript No.: 438630
Title: Drought evaluation with CMORPH satellite precipitation data in the Yellow River basin by using Gridded Standardized Precipitation Evapotranspiration Index
Authors: Fei Wang, Haibo Yang*, Zongmin Wang, Zezhong Zhang, Zhenhong Li
Dear Reviewer #2:
We quite appreciate your favorite consideration and insightful comment. These comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches. According to your comments and suggestions, we have already revised our paper point by point. The revised portions were marked in red color in the revised manuscript. All changes were marked via “Track Changes” option. And we enclosed a revised version.
We hope that these clarifications and revisions will now enable the paper to be accepted for publication in “Remote Sensing”, and look forward to hearing from you soon.
Yours sincerely,
Haibo Yang (on behalf of all the authors)
School of water conservancy and environment
Zhengzhou University
E-mail address: [email protected]
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
I recommend this paper for publishing in present form.