The Operational and Climate Land Surface Temperature Products from the Sea and Land Surface Temperature Radiometers on Sentinel-3A and 3B
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThis paper “The operational and climate land surface temperature products from the Sea and Land Surface Temperature Radiometer” aims to describe and validate the LST products from the Sentinel satellite series, which is an important earth observation satellite. Therefore, this article is crucial for the application of land surface temperature products. However, unfortunately, the paper suffers from poor readability due to its disorganized structure and redundant expressions. Consequently, the paper needs a thorough reorganization and language refinement. Detailed comments are as follows:
1. The Introduction section lacks depth. It does not adequately summarize relative retrieval algorithms, validation, and current research frontiers. The logic and structure of this section are unclear and need significant improvement.
2. The paper lacks essential quantitative figures and technical diagrams. For instance, in Section 2, it would be beneficial to include a technical flowchart of the methods and processes.
3. Section 2.1 (SLSTR LST Products): This section should be concise, clearly stating the advantages and features of the SLSTR LST products relative to other popular LST products. Currently, the writing lacks strong logical flow and clear structure, resembling a product or data documentation rather than a research paper.
4. In Cloud Clearing section, a technical flowchart of the processing steps should be provide to the detect process. Moreover, the explanation of how cloud detection accuracy is improved is not clearly articulated.
5. Page 11 (Product Consistency section): In the sentence “Product Consistency”, the findings related to the Sentinel are unclear. The previous paragraph's conclusion is not supported by specific data or comparative figures. The results seem to be based on literature review rather than robust evidence.
6. Many descriptions are not precise enough. For example, in the Method Section on Page 12, it is crucial to clearly state the degree of temporal and spatial matching between the in situ and satellite data. Given that land surface temperature is highly spatiotemporally heterogeneous, the paper should explain the range within which the differences are ensured to directly impact the reliability of the evaluation results.
In summary, while the paper addresses an important topic, substantial revisions are required to improve its clarity, organization, and adherence to the standards of a
Comments on the Quality of English LanguagePlease enhance the logical coherence and precision of the language.
Author Response
Please see the attachment
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsThis study provides an evaluation work for the sentinel LST products from Sentinel 3A and B. However, the manuscript is a little redundent and it looks like a report but not a research article.
1. The satellite information is better to be provided in the title.
2. From the introduction, it is not clear about the difference between SL_2_LST and LST_cci. The authors should be mention this more clearly. Meanwhile, why the comparison study is very important?
3. Instead of general introduction of the LST estimation algorithm and also the validation methods. the authors should be pay more attentions on the importance of the product.
4. As for the common information, it is not appropriate to show the details in the manuscript for the instrument but provide a basic introduction in the introduction section.
5. About the difference of the two product algorithms, the function is similar and only the auxiliary data is different. The comparison of the difference is better to be provided with a table.
6. For table 4, it is better to be provided as an appendix table.
7. For the product consistency analysis, how to explain the big difference as shown in Figure 2?
8. The basic rule for the selection of the in-situ data should be introduced in the text and also the basic methodology for the validation.
9. Some sub-sections are preferred in the results section to show the validation result with regard to different products?
10. From the comparison results, please verify the key contribution to the accuracy difference between LST_cci and SL_2_LST? The authors should clearly indicated the sources.
Comments on the Quality of English Language
The language is fine and some minor revisions should be done.
Author Response
Please see the attachment
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThis manuscript focuses on the introduction and validation of land surface temperature products from SLSTR instruments onboard Sentinel-3A and -3B. A detailed algorithm description, validation data, and validation results was presented in this paper. After careful reading, I have provided the following comments and suggestions.
(1) In section 2.2, the author provides definitions of precision and accuracy. I think it is necessary to add their calculation formulas.
(2) The LST uncertainty was detailed introduced, and the total uncertainty per pixel was presented in Figure 1. However, is the validation result (i.e. accuracy and precision) in the text consistent with the uncertainty of the temperature product? This comparison can better demonstrate the accuracy of the product and the accompanying pixel by pixel uncertainty information.
(3) For Goodwin Creek site in Figure 4 and 5, what is the reason why the in-stu LST of many sample points is lower than the satellite LST? Can you provide necessary explanations like that made for the Bondville site.
(4) For the sentence " [16] further demonstrated the algorithm is particularly suited to instruments with low radiometric noise. " in section 4, the citation method in this description is not quite correct.
Overall, I think you’ve done a very thorough study on validation of the LST products from SLSTR instruments onboard Sentinel-3A and -3B. I hope these comments help.
Author Response
Please see the attachment
Author Response File: Author Response.pdf
Reviewer 4 Report
Comments and Suggestions for AuthorsThe manuscript presents an important contribution to the field of remote sensing and climate studies by evaluating the operational and climate land surface temperature (LST) products derived from the Sea and Land Surface Temperature Radiometer (SLSTR) instruments aboard Sentinel-3A and Sentinel-3B satellites. The study assesses the quality of two LST products: the Land Surface Temperature Climate Change Initiative (LST_cci) product and the Copernicus operational LST product (SL_2_LST) over a period spanning from 2018 to 2021.
A key strength of the paper is the validation of the LST products against ground-based observations from eleven well-established in situ stations. The authors report that the mean absolute differences between the satellite-derived LST and in situ measurements are 0.77 K and 0.50 K for daytime and nighttime, respectively, for SLSTR-A, and 0.91 K and 0.54 K for SLSTR-B, when using the LST_cci product. These values represent improvements over the corresponding statistics for the SL_2_LST product, which exhibit mean absolute differences of 1.45 K (daytime) and 0.76 K (nighttime) for SLSTR-A, and 1.29 K (daytime) and 0.77 K (nighttime) for SLSTR-B. The authors attribute these improvements primarily to the retrieval coefficients and the cloud masking algorithms.
There are some suggestions for improvement:
1. The methods section could benefit from a clearer description of the algorithms used for generating the LST products and the validation procedure. It would be helpful to include details about the retrieval coefficients and cloud masking methodologies to ensure transparency and reproducibility. It is recommended to add an overall technical flowchart in the methodology section.
2. A more detailed discussion of the limitations of the study would strengthen the paper. This could include factors affecting the accuracy of satellite-derived LST, such as atmospheric conditions, topography, and sensor calibration.
3. Comparisons with other LST products and studies would provide context and demonstrate the relative performance of the SLSTR instruments. This could involve a brief literature review or a discussion of how the results compare with previous findings.
4. Dissgussion of future research, such as potential improvements to the retrieval algorithms or the integration of additional data sources, would enhance the paper's value and relevance to the scientific community.
5. Some figure captions, notably those for figures 4, 5, 6, and 7, were found to be overly succinct. It is recommended that additional descriptive details be incorporated into these figure captions to enhance clarity.
6. Given the importance of clear and concise language in scientific communication, the manuscript would benefit from a thorough review and polish by a native English-speaking expert.
Overall, the study offers valuable insights into the capabilities and performance of the SLSTR instruments in generating high-quality LST products, contributing to our understanding of the Earth's radiative energy budget and climate dynamics. It is recommended to major revisivion before acceptance.
Comments on the Quality of English LanguageN/A
Author Response
Please see the attachment
Author Response File: Author Response.pdf
Reviewer 5 Report
Comments and Suggestions for AuthorsDear authors,
I've read the paper on "The operational and climate land surface temperature products from the Sea and Land Surface Temperature Radiometer ". The manuscript is interesting and well written, with an adequate number of figures and appropriate references.
However, I've some general comments that should be addressed, I've marked "minor revisions" but they are not too few:
1) Most of the work presented here is based on the validation with in situ data of LST. A description of the methods uses for the validation is necessary (see specific comment below).
2) No investigation on the seasonality of the bias is given. I think, since you use 3 years of data that it should be important to see if the bias you find at different station has a seasonal behavior.
3) Any effect of the detectors temperature variation or of any other instrumental variation in this three years? What about stability (I know it is not a long time range but possibly something can be seen)
4) It is difficult to discriminate if parameters calculation or cloud masking has a major effect on the improvement of CCI data with respect to the operational ones. Is it possible to apply the same cloud mask used in the operational analysis to the CCI data?
Specific comments
The manuscript does not have any line numbers so I indicate with page numbers and paragraph incipit the points where corrections/suggestions apply.
Pag 2- The SLSTR instrument measures sea : I will move the description of SLTR before the paragraph about validation
Pag 3 2.1. SLSTR LST Products Overview : Personally I will move te section about the data after the description of algorithm, ADF and cloud clearing etc ...
Pag. 5 eq 1: what are v and s in the coefficients? I think vegetation and soil but please esplicitate this.
Pag 8 Cloud Clearing: BDT only the 11 and 12 um channels are used here?
Pag 9 Eq.4: this should be dR/dTCWV not dR/df again
Pag 8-9-10: Uncertainties: As far as I understand the uncertainties in the Eqs are calculated not at pixel level, but possible per coefficient scenario? please explain.
Pag 11 Following the investigation into the differences : Touch of the data in tables 2 and 3 do you refer?
Pag 13: it would be nice to have a map with the location of the stations just to investigate they distribution on the globe
Pag 14: I think something is missing here, a chapter in methods with the description of the coincidence criteria you used for the validation (time delay from overpass, distance around the station), any filtering of match up with low coverage due to cloud presence? Does the radius around the stations you consider for the comparison have an effect on the bias you find? Do you consider only the data after the tandem phase?
Pag 14 figure 4: captions are too small
Pag14: any effect due to aerosol presence in addition to clouds?
Pag 16: failures in the cloud masking : This is quite generic, have you investigated that further in any specific case?
Table 7: now Desert rock is ok, why if before this was due to illumination?
Any seasonality in these bias? It would be important to point it out
Have you tried to validate the tandem phase S3A and S3B products against in situ data?
Author Response
Please see the attachment
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
Comments and Suggestions for AuthorsThe manuscript has obvious improvements. However, some minor revisions are still required.
1. About the key influencing factors for the two products, I think the authors can indicate them more clearly in the abstract section.
2. For the influence from cloud masking, I think it is not the factor influencing the accuracy becasue the validation should be conducted at complete cloud-free pixels. But for the shortcoming of the two products, you can indicate that the SL-2_LST product has poor cloud masking ability.
3. It is not appropriate to show references in the conclusions section. The accuracy requirement can be provided in advance in the introduction.
Author Response
We thank the reviewer for working through the revisions in the first round, and suggesting the following further edits.
- About the key influencing factors for the two products, I think the authors can indicate them more clearly in the abstract section.
We agree, and we have amended the abstract to emphasize these more clearly.
- For the influence from cloud masking, I think it is not the factor influencing the accuracy becasue the validation should be conducted at complete cloud-free pixels. But for the shortcoming of the two products, you can indicate that the SL-2_LST product has poor cloud masking ability.
The validation pixels are indeed masked for cloud prior to the validation against in situ, although the poor cloud making ability of the SL_2_LST product has let too many cloud contaminated pixels through to the validation. We have emphasized further the poor cloud masking of the SL_2_LST product.
- It is not appropriate to show references in the conclusions section. The accuracy requirement can be provided in advance in the introduction.
The references have now been removed from the conclusions and only now appear earlier in the manuscript.
Reviewer 4 Report
Comments and Suggestions for Authors The manuscript has been sufficiently improved and suggest to accept. Comments on the Quality of English LanguageN/A
Author Response
We thank the reviewer for working through the revisions in the first round, and suggesting acceptance. We have made some minor edits to ensure the overall clear presentation of the key points
