the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 20 Sep 2024
A consistent regional dataset of dissolved oxygen in the Western Mediterranean Sea (2004–2023): O2WMED
Abstract. A new dataset from oceanographic cruises in the Western Mediterranean Sea (WMED) was compiled to integrate the previously published regional data product about dissolved inorganic nutrients CNR-DIN-WMED about dissolved inorganic nutrients (https://doi.org/10.1594/PANGAEA.904172, Belgacem et al., 2019, 2020). The Mediterranean region is experiencing rapid changes, necessitating high-quality and reliable datasets. However, the scarcity of the in-situ observations hinders the understanding of these changes and their impact on biogeochemical cycles. Dissolved oxygen is a vital component of marine ecosystems and plays a fundamental role in governing nutrient and carbon cycles, underscoring the need for accurate and reliable data. To address this, a high resolution, regional-scale data product was developed to understand decadal variability and spatial/temporal patterns of the ventilation process in the WMED. This study presents an extensive collection of unpublished dissolved oxygen data from continuous sensors collected between 2004 and 2023, along with a description of the quality assurance procedures. The quality assurance process involves calibration of CTD measurements against Winkler analyses and the comparison of deep observations with reference datasets, using the crossover analysis. The resulting data product O2WMED can be used as reference for assessing oxygen sensors mounted on biogeochemical Argo (BGC-Argo) floats or Gliders and for regional model validation.
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RC1: 'Comment on essd-2024-365', Toste Tanhua, 28 Oct 2024
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The manuscript from Belgacem et al. is setting out to produce a data product focusing on consistent ocean oxygen values in the western Mediterranean Sea, with some important restrictions, such as only considering data collected on Italian vessels, and only considering the oxygen data from the CTD sonde. It is a well needed attempt to move toward a consistent set of ocean data, fit to determine variability and trends in oxygen in this particular area.
The abstract promises “The quality assurance process involves calibration of CTD measurements against Winkler analyses and the comparison of deep observations with reference datasets, using the crossover analysis”. However, I see only weak connections in the manuscript between Winkler and sonde (CTD) data. I recommend making the
The supplementary information is very short, only 2 tables. These are of interest and I suggest including this information in the main manuscript rather than having a SI. Maybe the information from table S1 could be included in tables 1, for instance. There are a lot of details on how the analysis of Winkler and CTD data is done that needs to be discussed in the manuscript. Table S1 has no information on any post-calibration of the CTD sensor: Was a “post-calibration” needed? If so, how was this done, and how large was the post-calibration?
There needs to be a discussion on the difference of this analysis, that uses CTD sensor data, vs. the Winkler data. It took me a while to understand that the manuscript is about the CTDO data, and not about the discrete bottle data, as is the case for CARIMED and GLODAP. Also, and importantly, if there was an adjustment applied to the CTDO data, was the same adjustment applied to the Winkler data for that cruise? And where is this documented, and where are the bottle data for those cruises? Actually, where are the bottle data for all of these cruises? This connection is particularly important for any future effort to make a data product of oxygen data in the Mediterranean Sea that is more universal, but based on bottle data.
The link to the temporary data set did not work, so I could not inspect the product. This in itself is a disqualifier for publication, that can only happen once the data is on a recognized repository.
Based on my assessment this manuscript is likely worthy of publication, but only after a major revision.
Minor issues:
Abstract: Quality assurance is the process of checking the data while doing the measurements, so that you can react and correct any issues you notice. What you have done here is quality control, not quality assurance.
Line 69: profiles
Line 38. Is that the end of the sentence? Add period.
Line 39: Oxygen is not leading to high productivity, but is the result of high (primary) productivity.
Line 41: OMZs are certainly important, but the OMZ in the Med is very weak, i.e. most areas of the (open) Med is well oxygenated. I suggest to note this in the text. OMZs cannot become “more frequent”, as they the term OMZ refer to an area, not an event. OMZ can become larger/smaller, more, or less, intense, but not more/less frequent. Low oxygen events can, however, become more frequent.
Line 69: Profiles
Table 1: Maybe add a column on which oxygen sensor was used, and if there was a post-calibration needed after comparison with Winkler data.
Lines 102-110: This paragraph probably belongs to the introduction rather than method section.
Line 123: A “cruises” too much?
Line 132: Similarly,
Lines 132-135: As Far as I know, the CARIMED data product is not published, or final. How can you be sure that the oxygen has “reference cruise” quality by simply stating that they were part of a non-ready product? Also, did you make a check on consistency between Winkler data and CTD data for the reference cruises as well, noting that CARIMED is only bottle data`
Would there be another, more objective, way of assigning reference cruises, such as using cruises that used CRMs or certified standards?
Lines 181-219, roughly. Most paragraphs is this section is only one sentence long. It makes it awkward to read. Consider modifying. Much of this information is probably better in a table.
Line 227: Why is this an issue for recent cruises?
Line 232: It seems very strange to average each cruise to one single profile. I cannot see how that can work, except for cruises with limited geographic extent. Why not make an average profile for each of your sub-regions instead, that might work out.
Line 232: Ferer to Figure 7a
Line 242: A 4% offset can be related to conversion between volumetric and gravimetric units, a difference that is close to 4%. Not saying that is the case, but could be worth checking.
Lines 247-249: Is it “between 1000-2000 meters”, or “below 1000 meter”? That is not the same.
Line 248: Capital “T”
Line 270. You might refer to Tanhua 2011 here.
Line 269: Section crossovers. I did not understand if you made a cross-over analysis of all cruises vs. each other, or only the cruises in the product vs. the reference cruises. The text is not clear on that.
Table 4 and Figure 8. The table states correction facto 1,039, whereas the offset in figure 8 is 0,957. That does not match. Why? This is confusing.
Section 4: I would strongly suggest to use coherent definitions, and standardized language for the description of the adjustments to each cruise. I would suggest to make sure the ms is consistent in using “offset” – this is the difference between a cruise and reference cruises: “correction” – this is the reciprocal of the offset and indicate what would need to be done to get consistency based on the determined off-sets – “Adjustment”- this is what you did to the cruise based on different lines of evidence.b Reading the text on each cruise, it is not always clear what you did to the cruise due to fluffy language. I would recommend not to to fancy on language, but be consistent and clear.
Line 427: Very fluffy language, and numbers. Why would an offset of 0.97 lead to an adjustment of 2% - it has to be 3%.
Line 443: Very fluffy – “We think an adjustment of …. “. Tell me what you did, not what you think.
There are many many figures to the section describing the individual cruises. Maybe having one or two cruises with many panels would be much easier to read .
Line 457: I do not understand this, what does this mean, and what is the adjustment in the end?
Line 473: An “%” too much?
Please add a table of applied adjustments! Maybe by adding a column to table 5.
Line 505: ? This paragraph do not really belong to the conclusion.
Line 522: The individual data are not a product, remove the word. The adjusted data product is not the “original”, suggest removing the word.
Citation: https://doi.org/10.5194/essd-2024-365-RC1
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