the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 10 Jun 2026
Influence of Sea Surface Temperature on the Columnar Water Vapor Content and Cloud Fraction, Based on Monthly-Averaged MODIS Data at 1° by 1° Resolution
Abstract. Satellite data on global sea surface temperature (SST), water vapor and cloud fraction are analyzed to provide direct relationships on these parameters. Increase in SST elevates the water vapor pressure at the surface following the Clausius-Clayperon (exponential) form, and this effect persists to increase the columnar water vapor up to SST of approximately 300 K, at the 1° by 1°, monthly-averaged scale. Beyond SST of 300 K, a steeper slope for the columnar water vapor is observed. A similar transitional relationship is observed between cloud fraction (CF) and SST, except that a negative slope is found up to SST of 300 K. Then, a reversal occurs at SST of approximately 300 K where CF increases quadratically as a function of SST. Parameterization of water vapor and CF is provided as a function of SST for 1° by 1° spatial resolution and monthly-averaged time scale.
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RC1: 'Comment on egusphere-2026-1234', Anonymous Referee #1, 24 Jun 2026
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The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-1234/egusphere-2026-1234-RC1-supplement.pdfReplyCitation: https://doi.org/
10.5194/egusphere-2026-1234-RC1 -
RC2: 'Comment on egusphere-2026-1234', Anonymous Referee #2, 26 Jun 2026
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General comments
In this study, the authors investigate the relationships among sea surface temperature (SST), column water vapor (CWV), and cloud fraction (CF) using monthly averaged 1° × 1° MODIS observations. They find a universal relationship between SST and CWV, as well as between SST and CF. In both relationships, the dependence on SST changes around 300 K.
The motivation for this study is understandable, as it addresses a classic problem in atmospheric science, and it is well known that both CWV and CF are primarily dependent on SST. However, it is also well known that they are not solely determined by SST. For example, Kanamaru and Masunaga (2013) introduced the water vapor scale height and found that the relationship between CWV and SST varies systematically with this parameter. Such studies have shown that the dependence of CWV or CF can be further refined by considering additional key parameters in addition to SST.
It is not clear why the authors chose to use the MODIS dataset. CWV is not directly retrieved from MODIS observations, and SST retrieval from MODIS is inherently limited in cloudy regions. Several more reliable and widely used datasets are available for both CWV and SST.
For the above reasons, I find that the present analysis is too simplistic to provide a comprehensive understanding of how CWV or CF is determined. A more thorough investigation should incorporate multiple observational datasets and consider additional controlling factors beyond SST.
Therefore, I do not recommend publication of the manuscript in its present form. The authors should substantially reconsider the approach; employing more appropriate datasets and more comprehensive analyses would be required
Specific comments
L47-48, “The atmospheric optical depth and cloud fraction are close correlated (Engstrom and Ekman, 2010; Gryspeerdt et. al, 2014).”: These literatures focus on the aerosol optical depth. It is not relevant to the present study.
L60-62, “Waliser (1996) investigated the SST-atmosphere interaction by examining thermodynamic and convection dynamic variables, suggesting that there is a feedback mechanism to suppress locally high SST.: “Waliser (1990)” is not listed in the reference. The feedback mechanism is not relevant to the present context.
L66, “vertical gradients”: It is unclear what quantity the authors are referring to. Please specify the variable whose vertical gradient is being discussed.
L79-80, “However, detailed and accurate simulations of entire global circulation are intrinsically difficult and time-consuming”: This statement is no longer appropriate, as detailed and accurate representations of the global atmospheric circulation are now readily available from high-resolution reanalysis datasets, such as ERA5.
L106-108, “Detailed descriptions of the data and processing methods are discussed by various authors of the MODIS data set (https://modis.gsfc.nasa.gov/data/).”: The authors should review scientific papers on the MODIS data set and find their limitations and the rationale for using it in the present analysis.
L120, Figure 1: Which domain on the Earth is analyzed here? The CWV-SST relationship should be analyzed separately in the tropics and extratropics.
L121, “a Clausius-Claperyon (CC) form of exponential dependence on SST is observed up to SST of approximately 300 K.”: To discuss deviations from the Clausius–Clapeyron (CC) relationship, the authors should explicitly compare the observed relationship with that predicted by the CC relationship. For example, they could produce a scatter plot of the theoretical CC scaling against the observational results to quantitatively assess deviations.
L131-133, “During some months, the data are bifurcated for SST < 285 K, with upper branch exhibiting higher WV than the lower CC branch. These months are also associated with larger scatter in the data, in Figure 1.”: The authors should demonstrate this evidence.
L143-145, “Data plotted in Figure 1 indicate that the water vapor content is “over-saturated”, higher than the water vapor pressure at the corresponding SST, SST of of approximately 300 K.”: It is unclear from Figure 1 how the authors reached the conclusions described in the text. The authors should provide additional analyses and supporting figures that directly demonstrate these findings.
L160-163, “The physical mechanism for this reversal and increase in CF above the threshold temperature (Tc) may again be attributed to the increased upward convection at high SST, distributing the water vapor to higher altitude resulting in more vapor available for condensation and cloud formation.”: The reversal in the CF relationship is one of the most interesting findings of the present study and deserves a more in-depth investigation. The authors should explore the underlying physical mechanism by analyzing additional meteorological fields (e.g., reanalysis data), such as convection, large-scale circulation, and humidity.
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CEC1: 'Comment on egusphere-2026-1234 - No compliance with the policy of the journal', Juan Antonio Añel, 26 Jun 2026
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Dear authors,
Unfortunately, after checking your manuscript, it has come to our attention that it does not comply with our "Code and Data Policy".
https://www.geoscientific-model-development.net/policies/code_and_data_policy.html
In the link that you provide in the "Code and Data Availability" section of your manuscript you do not provide the data, but a code. Also, it is not clear if you provide the code used in your work. Given this, your manuscript should have not been accepted for Discussions in the journal.
The GMD review and publication process depends on reviewers and community commentators being able to access, during the discussion phase, the code and data on which a manuscript depends, and on ensuring the provenance of replicability of the published papers for years after their publication. Please, therefore, publish your code and data in one of the appropriate repositories and reply to this comment with the relevant information (link and a permanent identifier for it (e.g. DOI)) as soon as possible. We cannot have manuscripts under discussion that do not comply with our policy.
Later, if the Topical Editor decides to continue with the review or publication process of your manuscript and you are requested to upload a new version of it, then The 'Code and Data Availability’ section of your manuscript must also be modified to cite the new repository locations, and corresponding references added to the bibliography.
Additionally, your manuscript has been submitted to the journal as a "Model Description Paper". However, your work does not seem to describe a model according to the Manuscript Types of the journal. Please, check them here:
https://www.geoscientific-model-development.net/about/manuscript_types.html#item1
Also, it does not seem to fit any of the categories for manuscript types that we have and accept in the journal. If you disagree, please, reply to this comment with the reasoning for it.
I must note that if you do not fix this problem, we cannot continue with the peer-review process or accept your manuscript for publication in GMD.
Juan A. Añel
Geosci. Model Dev. Executive EditorCitation: https://doi.org/10.5194/egusphere-2026-1234-CEC1 -
RC3: 'Comment on egusphere-2026-1234', Anonymous Referee #3, 26 Jun 2026
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General Comments
The manuscript presents an empirical analysis and parameterization of the relationships between Sea Surface Temperature (SST), column Water Vapor (WV), and Cloud Fraction (CF) based on monthly averaged MODIS satellite data with a spatial resolution of 1°×1°. The authors identify a transitional bifurcation point at an SST of ~300 K, proposing a concept of two statistically formalized regimes (exponential and quadratic dependencies). Such a conceptual division represents an interesting idea that could potentially be useful for simplified climate models.
The manuscript is well-structured, easy to read, and follows a logical narrative. The authors provide a good literature review, relying on classic works and clearly distinguishing the current analysis from their previous 2022 research.
However, despite the high-quality technical execution and good data traceability, the manuscript has shortcomings and issues related to its validity and scope of application.
First of all, the paper is purely a visual and statistical analysis. The authors merely fit curves to the existing MODIS data. The manuscript does not address the core issues covered by the journal's scope and falls outside its thematic focus.
Secondly, the physical interpretation and the final conclusions drawn from the data are overly categorical and are not fully supported by the massive scatter present in the observational data.
Specific Comments
1. The study does not address relevant scientific modeling issues within the journal's scope, offering instead a mere statistical approximation of a function using satellite data as arguments. The authors should consider submitting this work to a journal focused on observations or Earth remote sensing.
2. The visual scatter of data in the plots is enormous. Although the authors indicate a variance of 5-25%, the data visually resemble noise from which it is difficult to extract a reliable physical signal, although a general trend is discernible. To better substantiate the findings of the study, the authors are recommended to consider other datasets of the considered parameters (e.g., datasets from other satellite systems such as AVHRR, or reanalyses), which would partially help separate data errors from the actual physical relationship between the parameters. It is also recommended to support their conclusions with statistical criteria; the R-squared value, for instance, would help strengthen the drawn conclusions.
3. Overly categorical conclusions
3.1 Due to such a high level of uncertainty, the conclusion formulated in the final remarks — "SST can be used as the main determining factor for the resulting atmospheric variables (WV and CF)" — is too strong and poorly substantiated. Cloud fraction and water vapor content are highly complex variables influenced by numerous factors: aerosols, atmospheric stability, etc.; they cannot be determined exclusively by SST, although they can be largely driven by it.
3.2 The authors should revise the statement "exact inversion" and clarify that this is merely a visual expert comparison of normalized trends, as the authors do not provide numerical statistical criteria to support this claim.
3.3 The authors also explain the sharp increase in CF above 300 K by "supersaturation" and enhanced ascending convection. While this is physically plausible, the monthly averaging at a 1°×1° resolution used in this study smooths out localized short-term convective events. The authors should elaborate on this point in the discussion, clarifying that monthly large-scale averaging may obscure the actual dynamic convective processes (which are mentioned in the manuscript text) that drive cloud formation at such high SSTs.
The conclusions must be significantly toned down given this level of analysis.
Technical Corrections
Terminology/Spelling: The name of the thermodynamic equation is misspelled several times throughout the text (e.g., lines 23, 51, 121, 249). It should be correctly written as "Clausius-Clapeyron", not "Clausius-Clayperon" or "Clasius-Claperyon".
Line 274-275: Typo in the abbreviation: "...resulting atmospheric variables (WF and CF)..." should be "WV and CF".
Citation: https://doi.org/10.5194/egusphere-2026-1234-RC3
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