Warming Trend and Cloud Responses over the Indochina Peninsula during Monsoon Transition

Round 1

Reviewer 1 Report

Using remote sensing data, the authors investigated the seasonal and interannual variations of the surface air temperature (SAT) and cloud properties over the Indochina Peninsula in the summer monsoon transition months. The results are meaningful for a better understanding of the monsoon transitional process by revealing the cloud changes in May. I suggest to accept this paper for publication after revisions. My detailed comments are as follows.

 

1. The warming trend in the title obviously indicates the long-term trend of the SAT. However, in Figure 3, the long-term trend of Tmax does not seem evident. At least, the correlation coefficient between the interannual Tmax anomaly and the time is not shown in the analyses. Therefore, the temporal distribution of the warm and cold cases might be not used to represent the local long-term warming trend.

 

2. L276-275. Are he differences between the warm and cold years enough to indicate the interdecadal changes associated with the warming trend?

 

3. Most of the results are based on the comparisons between the warm and cold cases using the composite analysis. The direct differences and the statistical significance levels may be additionally addressed in the results.

 

4. The Figures are relatively small, and they should be enlarged properly.

 

5. The ICP precipitation during the monsoon transition can affect the local soil mositure, which would in turn influence the East Asian summer monsoon and remote climate (J. Climate, 2020, 33, 10055-10072; Climate Dyn., 2020, 54, 3845–3861; J. Climate, 2020, 33, 7063-7082; J. Climate, 2021, 34, 5971-5984; Climate Dyn., 2021, 56, 2651-2665). The discussions would highlight the importance of this work.

 

Other comments:

L12. …exhibits…

 

Figure 2. The units are missing in the picture and the caption.

 

L214-215. Are they correlation coefficients of Tmax with precipitation, cloud fraction, and zonal wind?

 

L267-268. This sentence is confusing. How could the differences in SAT indicate the development states of monsoon?

 

L569-570. The warming trend in the SAT needs to be clarified based on the results in Figure 3.

 

L657-658. “…reaches…, and decreases …with increases…”. Anyway, maybe it would be better to rewrite this sentence.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

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Comments for author File: Comments.pdf

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

The general discussion is reasonable, the writing is smooth, and some of the content needs to be improved, which is suitable for this journal. Some comments:

1) MODIS has a fixed transit time, and the daily of the CPC Global Temperature dataset and the Global Unified Precipitation dataset matches in time, whether it has an impact on the analysis and conclusions;

2) The COT and CER of the cloud with diurnal changes of MOIDS are only fixed during the day, and the diurnal situation is analyzed in this paper, whether it will have an impact on the results of the mechanism analysis;

3) In the analysis, it is recommended to increase the consideration of low tropospheric stability parameters;

4) The analysis is mainly liquid water clouds, but the classification has high cirrus clouds in it, whether it is reasonable?

Kind regards,

 

Author Response

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Author Response File: Author Response.pdf

Reviewer 4 Report

The paper analyses the long-term relationship between surface temperature and precipitation during the summer monsoon transition, including the climatology of cloud properties using MODIS data.

A year is marked as a warm or cold year if Tmax is one standard deviation above or below the 43-year mean. As there is a warming trend, there are fewer cold than warm years, which can lead to noisy statistics. Indeed the small number of even cold years means that all results are noisy, and the differences between warm and cold have further noise.

The differences in properties (especially cloud properties) between warm and cold years are not shown to be statistically significant.

The figure captions explain in detail how each result is computed. While this can be seen as openness, it can also mean that the captions are exceptionally long. Detailed information on diagrams is part of the analysis method and should either appear in the text or be assumed when normal practice is followed. In general much of the information in the captions is repeated in the text.

Several figures have detail that can only be seen by magnifying the figure greatly.

The English could be improved, but the meaning of text is generally very clear.

 

Specific comments

l8. What is meant by ‘exacerbated precipitation-temperature relationship’?

L85. Could ‘exacerbated negative precipitation-SAT relationship’ be perhaps an enhanced or exaggerated or stronger relationship?

L276. It is not clear how composites (ie averages over the whole period) can reveal information on trends during that period. In any case, both composites are noisy so that even differences between them are hard to demonstrate as being statistically significant.

Figure 5. The colour bar in 5a does not well demonstrate the magnitude of probability; a colour bar with a tone gradient would be much more effective. In fact it is not clear that 5a is needed; 5b seems to summarise the key points well. Indeed 5c is just a different representation of the summary figure 5b. Both 5a and 5c could be removed, and so keep a focus on the key results.

Figure 6 has the same information in two different plots, and a caption that is far too long.

L451. It is not at all clear that the differences in drop size distribution between warm and cold years are statistically significant.

Again with figure 7 it is not clear that any differences in time in the relationship between COT and CER are statistically significant.

In Figure 8, where does the overall mean iso-height lie for each level (Figure 3)? Once again, we are unsure of the overall variability of these heights.

L528. Figure 3a does not show CTP.

Figure 9. Are the differences significant? In fact the unexpected changes on the BoB suggests the changes are in the noise.

In table 2, if the bold numbers are statistically significant at some level, then this should be stated in the caption.

L565. The reduction in correlation between ENSO and Tmax and Tmin is likely associated with global warming, as the warming continues independently of internal climate factors.

Figure 10 e and f. Are the distributions of the initial elevation of each set of back trajectories? The relevant time or period needs to be stated (rather than much of the present detail that could be assumed or found in the text).

L604. What is meant by “the specific humidity carried by the backward trajectories”? Is it the humidity at the start or end or average?

L607. What is meant by “Both the specific humidity and temperature exhibit statistical patterns of decreasing with heights”? They are both likely to decrease with height.

L609. How is the temperature of a trajectory computed?

 

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Thank you for answering my questions about the role played by the water vapor feedback over the three involved regions. According to the new Figure 10 enhanced convective processes occur during warm years over ICP and SCS regions. Over BoB the high value of CAPE makes the contrast between warm and cold years less clear, although the feedback seems to be reversed.

The article is interesting and can be published as it is.

Reviewer 3 Report

The authors have addressed to all comments. 

Reviewer 4 Report

The authors have responded to my queries.  In partiular, they have considered the statistical significance of some of their results