PCLM-D-24-00182

Intercomparison of satellite derived SST with logger data in the Caribbean – Implications for coral reef monitoring

PLOS Climate

Dear Dr. Margaritis,

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Liqiang Xu

Academic Editor

PLOS Climate

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Reviewers' comments:

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Comments to the Author

1. Does this manuscript meet PLOS Climate’s publication criteria? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The paper assesses the quality of two remote sensing SST products, namely ESA CCI and NOAA CoralTemp, and their capability to characterize the persistence of temperature conditions on coral reefs that can cause bleaching. That is an important topic and the authors discuss it in depth and with insight. The paper is very well written and it is very easy to follow. The results are in agreement with what is expected from previous assessment and from the known evolution of the SST products, particularly ESA CCI.

The paper can be accepted as is. I have however some minor comments that I think that should be addressed in the paper in order to improve it.

When presenting the in situ data, please clearly specify the logging time interval(s) of the HOBO temperature loggers. The expected standard deviation of the daily and monthly averages is going to be reduced by the square roott of the number of averaged observations, so that number of observations is relevant.

It is well known that globally there has been a stark change in the trend on SST since the ending of the 2015-2016 ENSO, and this is actually clearly reflected in some plots. This for sure affects the assessment of the trends. You could consider truncating the trend up to 2016 when possible, or to introduce a comment in the paper..

There is an error in the titles of figure 4, they should read as the two periods for which the difference between ESA CCI and CT are taken, and not as "ESA" and "CT".

Reviewer #2: This is a very useful analysis for those concerned about coral reefs and the use of satellite based temperature observations to monitor for thermal stresses. With minor corrections, I think it can be published. The conclusions should be revisited to express more clearly and positively what needs to be improved/changed to make coral monitoring better, I suggest, in order to make the conclusions as impactful as possible.

I have found no fundamental problems with any of the analysis or interpretation.

As a paper, I think it could be improved by making the reasons for each analysis clearer, with each clearly linked to a specific research questions. I question whether all of the plots shown need to be present in the main manuscript: having so many detracts from the really important plots which are about showing how product errors (assuming the loggers are right) lead misleading coral thermal stress and bleaching alert calculations.

I leave it to the authors to consider whether and how they can make the paper more compelling by signposting and making clear the research question behind each analysis; and also whether to trim some of the results that don't lead directly to the most significan conclusions.

The sort of thing I mean is considering the coral-stress metrics systematically, and organising the sequence of analyses presented around specific questions (e.g., "Do satellite products estimate the MMM well?" followed by analyses that answer that question, etc). That would be better than apparently meandering through analyses and leaving us to reverse engineer the relevance of each result to coral monitoring when we get to section 4.3. I realise it invovles a significant reorganisation. But I think more people would read reach the end of the paper.

Detailed comments

36. Differences in resolution between products cannot cause differences between a product and what a coral experiences. Please reword.

39. Better to use the short name for this product which the producers recommend in their data paper, throughout, given the number of SST datasets around. Product: SST CCI analysis. SSTs: CCI analysis SSTs.

40. It is better to stick with the data producer's name here too. Please replace CT with CoralTemp throughout.

48. Is "CRW" a useful keyword? Expand?

53. First SSTs from space were over 50 years ago, although they weren't very accuate.

60. Missing '.'

68. Some would call the microwave measurements "subskin", being a bit deeper than the thermal skin layer.

71. "Very thin" -- please quantify.

90. For complete clarity, worth inserting "geophysical" before "discrepancy"?

97. "is compared"? By whom? Overall, this sentence has too long a chain of concepts and isn't clear.

97. Make clear that both datasets are not only gridded, but are in fact gap-filled.

125. I think this needs to be referenced.

128. What the timescales are is important, so please quantify "over time".

132. and 136. Acronym used before long form is shown.

150. By "general" do you imply that all the products do so to the same degree?

154. We will be extremely lucky if it takes that long. Is this 2deg meant to be 2deg from now or 2deg from preindustrial, or pre-satellite ...?

205. The agreement here is far better than the accuracy stated above would lead us to expect. How can you get RMS of 0.028 from a sensor discretized at 0.2? From memory the standard deviation from discretization should be "resolution/root(12)", which is 0.06. Can this be explained? The mean agreement is also highly improbable if the stated accuracy is valid.

250. Glitch "and L4 Analysis products"?

297. Which of the listed things is "called standard uncertainty"?

323.-325. Took me ages to work out this sentence, which is trying to say too many things in few words. Use more words to make it all clearer.

329. "hotter" -- it is not exactly wrong, but usually "hotter" is used when comparing things that are hot, whereas a neutral term, more appropriate here, is conventionally "warmer". If changed, do so elsewhere too.

337. Temporal correlation of what? It the "average uncertainty" mentioned a spatial average? Not clear.

Fig 2 -- I don't think this caption is adequate. "plus" should be "and" I think. What does "2*ESA2 uncertainty range" mean -- is it -2sigma to +2sigma? Explain "mean Caribean" (what domain and time stepping for the means?). Is "the confidence interval" = "2*ESA2 uncertainty"? The Bottom caption suggest data are only shown when the mean difference exceeds "the confidence interval", but I suspect that is not true, because there are lots of zeros.

355. "While ..." is not a complete sentence.

Fig 3. The problem with a daily plot like this with so many data points in the series is that visually we cannot discern the distribution properly because of finithe line thickness. Would be good to get a feel for how common are the outliers by seeing the corresponding difference distributions (perhaps could have histograms at one end of each timeseries panel?)

371. "increase 0.42 ± 0.13 °C larger ..." does not mean the same as "increase 0.42 ± 0.13 °C, larger" and I think the latter is intended.

388. But that is the global average stability? Can there be less good stability regionally?

Table 3 is not organised the most effective way for making comparisons site by site.

391. What are "joint confidence intervals"?

418. "Comaprisons" rather than "Intercomparison" I think?

426. Perhaps comment a bit more. For example, the greater SD of SST CCI compared to CoralTemp could be because the former is noisier, or because the former captures real skin-to-logger variability more faithfully, or some combination. Can you conclude on which it is?

Figure 9 -- I think these important timeseries needs to be spread across the full width of the page to improve legibility.

452. I think you need to motivate why this is done at the start of this paragraph.

Table 5 is not optimised for comparing products.

497. "sources of discrepancy" perhaps?

500. A "discrepancy" --> "real difference" I suggest, as discrepancy slightly implies that one is wrong.

510. This resolution-driven source of differences that are "real" (given the product definitions) but not pertinent to the application for the coral at a certain location is an important one. The solution can only be better spatial resolution for coral-reef focussed products from space. I think it is worth spelling that out and also mentioning that several new missions will greatly improve the situation by 2029, with 50 m SSTs quite frequently available. The development of coral products to exploit these sensors should be an important recommendation from the paper.

530. "homogeneous' -- could be good or bad depending what is mean. Do you mean consistent over time? Or do you mean "data with variability suppressed so that we get the same number everywhere:, which would be a bad meaning of homogeneous. Please carefully reword.

531. "at a time when diurnal stratification is at its minimum". Earlier it says 10.30 which represents the average of the diurnal cycle, rather than the minimum. CoralTemp, being nighttime, is morely likely to be dominated by the minimum of the diurnal cycle, I'd have thought.

554. I am slightly at a loss with this comment in comparison to what I have read from NOAA about how usefully predictive the satellite-based products of CRW are for bleaching. Perhaps "typically" is too vague here. I suggest qualify the statement with quantitative values (what fraction of week-long events is missed, for example).

579 -- Check all warming rates have the right units.

588 - 589. Need to sort out the commas (use two parenthetical commas or use none, but don't just use one.)

627. Consider (see earlier comment) whether the point and potential regarding high resolution sensors could be expanded a bit here. The new missions could (should) change the game if resources are put into exploiting them in this area.

634. I feel it is more clear to agencies that might potentially react to the conclusions of a study like this to give positive recommendations rather than negative conclusions -- eg., say what would have to change for SST CCI v3 to be usable for coral monitoring rather than saying that something currently prevents it.

In general, I invite the authors to consider whether their conclusion section is expressed optimally for making the paper impactful with agencies that might be able to respond.

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Reviewer #1: Yes: Antonio Turiel

Reviewer #2: No

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Intercomparison of satellite derived SST with logger data in the Caribbean – Implications for coral reef monitoring

PCLM-D-24-00182R1

Dear Dr Margaritis,

We are pleased to inform you that your manuscript 'Intercomparison of satellite derived SST with logger data in the Caribbean – Implications for coral reef monitoring' has been provisionally accepted for publication in PLOS Climate.

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Liqiang Xu

Academic Editor

PLOS Climate

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Additional Editor Comments (if provided):

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