the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 07 Apr 2026
Regional Oceanographic Database (BaRDO) for the Argentine Continental Shelf
Abstract. The Regional Oceanographic Data Base (BaRDO) contains 25,845 quality-controlled oceanographic stations acquired by INIDEP research vessels in the Southwest Atlantic. This paper describes the operability of the data management system, the characteristics and accuracy of the dataset, the quality-control procedures, and the main errors detected and corrected during the flagging process. In addition, we present information on the geographical and temporal distribution of the data, the evolution of the dataset in response to technological advances, and recommendations for its use. BaRDO contains two main data types: quasi-continuous CTD profiles (conductivity, temperature, and depth) and discrete, low-resolution OSD (Ocean Station Data) profiles. The majority of observations comprise temperature and salinity, while fluorometry, oxygen, and turbidity are also available when measured. Cruise listings and data access covering the period up to 2012 are provided at https://catalogo.inidep.edu.ar/geonetwork/.
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Status: open (until 18 Jun 2026)
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RC1: 'Comment on essd-2025-841', Anonymous Referee #1, 18 May 2026
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AC1: 'Reply on RC1', Ana Graciela Baldoni, 21 May 2026
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We want to thank the Anonymous Referee #1 for the careful and detailed review of the manuscript. The comments and suggestions were extremely valuable, allowing us not only to correct several basic issues, such as missing information in tables and figures, but also to improve and enrich the overall quality and clarity of the paper. In the supplement file, we provide a detailed response to each of the comments raised.
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AC1: 'Reply on RC1', Ana Graciela Baldoni, 21 May 2026
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RC2: 'Comment on essd-2025-841', Alexey Mishonov, 29 May 2026
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The comment was uploaded in the form of a supplement: https://essd.copernicus.org/preprints/essd-2025-841/essd-2025-841-RC2-supplement.pdf
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AC2: 'Reply on RC2', Ana Graciela Baldoni, 03 Jun 2026
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We appreciate your positive feedback on the BaRDO database and its value as a regional contribution. We are particularly grateful for your appreciation of the considerable effort made by the INIDEP team in compiling, organizing, and documenting the information contained in this database.
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AC2: 'Reply on RC2', Ana Graciela Baldoni, 03 Jun 2026
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Data sets
Datos CTD - Campañas INIDEP 1984–2012 A. Baldoni https://doi.org/10.47193/ctd.inidep.1984-2012.v1
Datos discretos de temperatura y salinidad - 1969–2012 A. Baldoni https://doi.org/10.47193/bottle.temp-sal.1969-2012.v1
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- 1
This is an interesting paper, presenting the data archive of profiles collected by INIDEP and QCed in the BaRDO regional data base, mostly on the Southeastern shelves (and slopes) of South America (largely off Argentina and Uruguay). The majority of those are CTD profiles (with an early smaller set of OSD profiles). The paper deals mostly with T and S profiles, as a function of P (or z), and not on the other variables (most commonly fluorescence), which as far as I can tell, have not been paid too much attention. The paper is well structured, and usually rather clear.
My main comment is that it sometimes lacks relevant information (see the detailed comments after), and that the figures are not alwaysin a final form (vertical scales missing, difficult to distinguish different lines plotted, sometimes incomplete figure captions). I suspect that this can be relatively easily fixed by the authors.
List of comments.
l. 97 13% of the total dataset (I assume total refers to the 1981-2024, but as phrased the 13% is only for the data before 1993; whereas Fig. 3 suggests that it is the total number of ME data, that were collected in 1984-2000). Why separate this from the later period 1993-2010 (line 98, for which the 40% cited is only relative to the 1993-2010 data collection period). It would likely be wise to unify the way to report the data for each CTD type and period. Personally, I would cite ME CTD use for the total period 1984 to 2010.
On Fig. 4: I assume that the two profiles shown on each plot are for the up and down profiles respectively. They should be shown with different line sets (for example full and hyphened), as well as different colors for T and S. Actually, this raises the question on whether the profiles stored are only the downward profiles, or are both the downward and upward profiles stored (and if so separately?)
l. 140, add a reference to the mismatches for SBE19 data (it has been described in different papers, as well as ways to minimize it through signal processing). If I understand correctly, here the choice is made to flag the data (through the spikes, gradient and density inversion QC1), and not try to minimize the effect.
l. 174: ‘The structure of the database tables…’
In Fig. 6, last line of stations. I believe what is meant is TempScaleID
l. 190-192: interestingly, non SBE instrument data are also processed with the standard Sea-Bird data processing. Is there some specific choices that had to be made, which are dependent on each instrument?
Table 2 column ‘calibration date’. I am not sure that I fully understand what is reported. For example, SBE19, 1268 reported ‘Jan 1993-Dec 1997”. Does it mean that there were two calibration dates in jan 1993 and dec 1997. (in that case,probably title of column should be ‘Calibration dates’. For ME and NBIII/V, only year (or years) reported, not a month. Does it mean that there were no known months. Also, near the end, 6214/4687 or 6218/4684, no date (means that there was no calibration, even when the sensors were provided?)
l. 207: How are ‘outliers’ identified here? (and are they or not included when calculating Q1 and Q3 quartiles?)
In 3.2.1: these comparison of pairs of sensors are interesting. It would be probably even more useful to know whether some (small) systematic differences could be identified, and whether they could have been corrected. For example, on Fig. 7, one gets a sense (maybe wrong) that 4727 would tend to have positive T difference compared to other sensors. On the other hand, an information that is not provided in Fig. 7 and in the chapter, is how far in time were these comparisons of sensors done relative to when calibration is provided (of course, one can imagine that it is highly variable, but maybe it would be valuable to select in the comparisons only pairs of sensors that have not been recently been calibrated).
3.3 I am not 100% sure that the notion of spike is clearly defined. How does one define a spike (isolated data point relative to the average of what is below or above? Or a certain thickness…). I am aware that it is in the V1.5 version of the software used, but more explanations are needed. Otherwise, one does not understand which flag is activated, and why. Also, Figure 10 shows a huge number of flags in Temp in the spring-summer season (in particular November). What is it about? Seeing after on Figure 11, where flagged temperature points happen, I am tempted to say that I don’t think that in most cases there is something ‘wrong’ that would need to be flagged in this season. In the example plotted it seems to be temperature inversions or spikes in the thermocline, which can happen for a whole host of natural reasons. On the other hand, if not present in SBE9plus (or on XBT profiles in the same region), this raises a question on the quality of the SBE19 profiles (maybe the pressure-dependent averaging, or temperature-lag corrections?). I also wondered whether the difference in flagged levels mentioned between SBE19 and SBE9plus is for “=’Total’. It would be more instructive to have it reported separately for Temp and Sal data.
l. 328: I am not sure that I understand the last part of the sentence.
Fig. 10: labels missing on vertical scale (possibly,1 2, 3,…%), and is the scale the same for Sal and Temp marks?. What is meant by the black dots ‘Total’ that are sometimes less than the sum of Sal and Temp Marks (such as in Nov to May)
Table 4 : What is meant by Gradient in threshold (it should be in /bar or /dbar or /m?).