Analyzing the Effects of Sea Surface Temperature (SST) on Soil Moisture (SM) in Coastal Areas of Eastern China

Round 1

Reviewer 1 Report

The authors have addressed all of my concerns from the previous submission. I recommend accept in present form.

Reviewer 2 Report

Dear authors,

Thank you for your careful additions and revisions.

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

Review for:

Analyzing the effect of sea surface temperature (SST) on soil

moisture (SM) in coastal areas

Summary: The paper presents an interesting study examining the relationship between soil moisture and sea surface temperature in the Eastern China Sea. To my knowledge this is the first study, on such a regional scale, looking at the issue. Overall, the primary conclusion is that there is a direct correlation between soil moisture and SST, but that the relationship is also seasonally dependent.  Other results include changes in overall trends. Overall SST showed warming trend, while soil moisture showed a drying trend.

Strengths: The work itself is very interesting, perhaps leading to more questions than answers.

The problem identified is extremely important  and could lead to a better understanding of the Earth’s Water Cycle.

Weaknesses: The connection to remote sensing is through the Global Land Data Assimilation System (GLDAS).  The authors need to describe in more detail the assimilated products or the connection to remote sensing is very weak.  This leads to what I believe is the weakness in the article. This has the potential of being a very strong paper if the authors could compare their results with some of the newer satellite data products. For example, can they use soil moisture data from SMOS? Can they use any of the satellite derived SST products that overlap with the study period?  This would, additionally, provide more validation for the results.

Can they also give any plausible explanations (or perhaps for future work) for some of the results. For example the differences in correlations depending on the season. This seems counter intuitive, as does the  trend towards increasing SST, but decreasing soil moisture. This is also where integrating some of the satellite derived products could be very useful.

Minor comments:

Line 127: add “a”. The main climate in this area is  “a”.

Remove spacing between “temperature” and °C.

Please put units on all the figures. Eg: Figure 4 add degrees Celsius to the y-axis.

Line 360: Please use “South China”.  When referreing to a specific part of China go ahead and capitalize “East”, “South”, etc.

Figure 19: Move the legend from the xaxis.

Overall, I recommend publication, but after a major revision.

Reviewer 2 Report

Dear authors

The use of remote sensing data as auxiliary evidence to identify a natural rule or the relationship between two human life significant impact natural factors should be encouraged to carry out, particularly in the field of disaster early warning and management. The manuscript which was written by Liu et al. entitled “Analyzing the effect of sea surface temperature (SST) on soil moisture (SM) in coastal areas” here is one of work like that. However, in order to ensure that the rule and/or the relationship you aimed to identify or prove is reliable, the remote sensing data should be validated and proved appropriating for the practical case of your study area.

The study described in this manuscript used traditional methods of statistical analysis such as standard z-score, Manner-Kendall trend test, regional correlation analysis and time series analysis to identify the relationship between the sea surface temperature (SST) and soil moisture (SM) over the Eastern China region. In which, SST data were obtained from the COBE-SST data of the Japan Meteorological Agency and SM data obtained from LDAS (Land Data Assimilation Systems). These two datasets usually used for the global observation purpose and should be validated when using at the regional scale.

In this case, the authors should use the in situ data from the national ground station system to validate these two data sources before using for the analysis. Without any assurance that these datasets exactly reflect the real condition/environment of Eastern China, all the obtained results from the analyses are not assured/reliable.

Therefore, I highly recommend the authors to validate the remote sensing data first and then discuss on the analysed results.