the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 23 Jul 2025
Emerging Climate Signals in Oxygen Minimum Zones
Abstract. The ocean is losing oxygen due to anthropogenic climate change. This loss is particularly worrying when it occurs in naturally low-oxygen regions, such as the Oxygen Minimum Zones (OMZs) found at mid-depth in tropical oceans, because the expansion of OMZs reduces habitable space for marine life and threatens oxygen-dependent ecosystems. However, detecting the emergence of climate-driven signals is challenging due to internal variability. Here, we isolate externally forced signals of OMZ volume change and regional deoxygenation, and determine their time of emergence using the IPSL-CM6A-LR Large Ensemble. We apply time of emergence analysis to identify when climate-driven signals become statistically distinguishable from natural variability. Our results show that OMZ edges consistently expand, with emergence occurring in the second half of the 20th century, which is in phase with regional mean deoxygenation in the tropical Pacific and tropical Atlantic. In contrast, we reveal a marked spatial asymmetry in the emergence of OMZ core and hypoxic volumes between the northern and southern parts of OMZs. While OMZ core volumes in the tropical North Pacific and hypoxic volumes in the tropical North Atlantic expand, their southern counterparts contract due to a sudden, ventilation-driven oxygen increase from the Southern Ocean at the start of the 21st century. Uncertainties in emergence timing range from 20 to 30 years across ensemble members, and increase substantially in regions influenced by abrupt changes in OMZ ventilation. By linking the emergence of regional deoxygenation to that of OMZ volume changes, climate-driven expansions of OMZ volumes are likely already beginning to emerge, with distinct dynamics between northern and southern tropical oceans.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2025-2805', Anonymous Referee #1, 14 Sep 2025
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AC1: 'Reply on RC1', Mathieu Delteil, 16 Feb 2026
REVIEWER #1
All suggestions were considered and the issues raised were addressed, which in our opinion led to increasing the clarity of the revised manuscript.
Below are the authors’ point-by-point responses to the comments. Reviewer comments are in bold and responses are in normal font. Changes to the manuscript are in italics. Line numbers mentioned below refer to the revised manuscript.
General Comment:
The manuscript "Emerging Climate Signals in Oxygen Minimum Zones" by Delteil et al provides an a comprehensive analysis of oxygen minimum zones across the worlds oceans within the IPSL large ensemble including both spatial and volumetric metrics, correlating mechanistic drivers such as solubility, nutrients, and age and multiple metrics of time of emergence of change. It is well written with only a few points requiring attention specified below. I recommend publication after attention to these technical issues.
The authors would like to thank Reviewer #1 for their useful comments.
Specific comments:
- 24 - This is also true in regions where temperature is high reducing solubility
Thank you for the comment. In this study, we focus exclusively on permanent subsurface open-ocean OMZs, whose persistence is maintained by weak ventilation in so-called “shadow zones” and by high oxygen consumption associated with eastern boundary upwelling systems (Pedlosky, 1983). Whereas coastal hypoxic zones are primarily driven by enhanced eutrophication and warming (Breitburg et al., 2018). To clarify, the definition of OMZs has been refined to explicitly define the regions of interest considered by this study. The sentence now reads as follows:
P1 L24-26: Permanent open-ocean OMZs are typically located in poorly ventilated regions of the ocean and beneath zones of high biological productivity, where oxygen consumption is elevated
- 55 - "dynamics" should be "dynamic"
Done
- 57-58 - suggest replacing "rise" with "emerge" and deleting ". The detectability thus becomes a signal to noise ratio problem, where emergence occurs"
Thank you for this comment. The sentence has been reworded accordingly:
P2 L58-59: For a forced signal to be detectable, the externally forced trend must persistently emerge above internal variability, which is considered as noise Hasselmann, 1993; Santer et al., 1994).
- 61 - suggest removing "the moment" as this is a retrospective statement of accumulated behavior rather than a single "moment"
We agree with this comment. The term as been removed from the revised manuscript.
- 65 - suggest replacing "this method" with "single simulation analysis"
The sentence has been reworded accordingly.
- 69-70 - suggest removing "performed with the same Earth system model" as the phrase seems unnecessarily specific and draws the criticism that multi-model analysis is even better as it captures structural uncertainty (Hawkins and Sutton, 2009)
We agree with this comment, and the corresponding text has been removed from the revised manuscript.
- 91-98 - This belongs in the discussion
Yes, we agree with the reviewer’s comment. The paragraph at Line 91-98 in the preprint manuscript was removed as its content was already included in the discussion section.
- 103 - suggest replacing "used in of" with "contributing to"
Done
- 173 - Why is "Core" capitalized - If it is a special definition, that should be made explicit, and for "Oxygen Minimum Zones" either use previously defined acronym instead of writing it out or redefine it by adding "(OMZ)"
Thank you for your comment. OMZ core, hypoxic volumes, and low-oxygen volumes are defined using the three oxygen thresholds of interest: 20 µmol kg−1, 60 µmol kg−1, 120 µmol kg−1, respectively. For consistency, the term “OMZ core” has been uncapitalised throughout the revised manuscript. The OMZ acronym defined before has been used to refer to the Oxygen Minimum Zone.
- 175 - Why is "Low" capitalized? If it is a special definition, that should be made explicit.
As for OMZ core, low-oxygen volumes has been uncapitalised throughout the revised manuscript.
- 185 - How much is PO4 underestimated? This should be explicit - and what about solubility and the other physical mechanisms? Are the waters biased cold? That would be another explanation? Are they overventilated with respect to CFC’s or 14C? I recognize that these are treated as trends later on, but a more comprehensive discussion of the mean state biases is warranted here.
In this study, we focus on oxygen concentration biases, as they directly affect the definition of OMZ volumes. A comprehensive evaluation of biogeochemical variables in IPSL-CM6A-LR has been provided by Séférian et al. (2020). In the tropical Pacific, IPSL underestimates nutrient concentrations by approximately 2 µmol L−1 (Séférian et al., 2020).
The tropical Pacific is overventilated in the model, partly due to excessively strong deep convection in the Southern Ocean (Boucher et al., 2020). To assess large-scale ventilation, we compare age since surface contact at the end of the piControl simulation (years 3840–3850) with two data-driven inverse models: the Total Matrix Intercomparison (TMI) and the Ocean Circulation Inverse Model (OCIM) (Millet et al., 2025). The IPSL simulation reproduces shadow zones in the tropical regions of interest, indicating the representation of large-scale physical ventilation of tropical regions (Figure A5).
We have reworded and further detailed the discussion of IPSL-CM6A-LR biogeochemical biases. As suggested by Reviewer #2, this paragraph has been moved to Section 4.5 (Limitations).
P25 L560-567: The IPSL-CM6A-LR model exhibits a positive bias in dissolved oxygen concentrations, particularly in the OMZ regions. This oxygen overestimation in tropical OMZs is linked to the IPSL-CM6A-LR coarse spatial resolution, which leads to weaker equatorial currents Busecke et al., 2019; Calil, 2023). We compare age since surface contact at the end of the piControl simulation (years 3840–3850) with two data-driven inverse models: the Total Matrix Intercomparison (TMI) and the Ocean Circulation Inverse Model (OCIM) (Millet et al., 2025). The IPSL model reproduces shadow zones in the tropical regions of interest, indicating the representation of large-scale physical ventilation of tropical regions (Figure A5). The oxygen overestimation is then also linked to too strong deep convection in the Southern Ocean (Boucher et al., 2020).
- 185 - The weakness of the undercurrent oxygen transport is also a resolution issue (Busecke, J. J., Resplandy, L., & Dunne, J. P. (2019). The equatorial undercurrent and the oxygen minimum zone in the Pacific. Geophysical Research Letters, 46(12), 6716-6725.) such that even if the physical transport is correct, the oxygen supply is underestimated - but this would tend to go in the other direction, suggesting that the model would be even more biased in oxygen if the undercurrent oxygen transport were correct.
Thank you for this insightful comment. The IPSL model uses at a coarse spatial resolution. Busecke et al. (2019); Calil (2023) have shown that eddy-non-resolving models weaken the equatorial undercurrent in the tropical Pacific and the equatorial zonal currents in the tropical Atlantic. In both basins, such models also fail to adequately represent countercurrents that limit the vertical and lateral transport of dissolved oxygen. As a result, coarse-resolution models tend to simulate higher dissolved oxygen concentrations in the western basins and smaller OMZs in the eastern tropical basins. The impact of model resolution has been added to the discussion of OMZ biases and moved to the section 4.5 (Limitations), as suggested by Reviewer #2. The revised text now reads as follows:
P25 L560-567: The IPSL-CM6A-LR model exhibits a positive bias in dissolved oxygen concentrations, particularly in the OMZ regions. This oxygen overestimation in tropical OMZs is linked to the IPSL-CM6A-LR coarse spatial resolution, which leads to weaker equatorial currents Busecke et al., 2019; Calil, 2023). To assess large-scale physical ventilation, we compare age since surface contact at the end of the piControl simulation (years 3840–3850) with two data-driven inverse models: the Total Matrix Intercomparison (TMI) and the Ocean Circulation Inverse Model (OCIM) (Millet et al., 2025). The IPSL model reproduces shadow zones in the tropical regions of interest, indicating the representation of large-scale physical ventilation of tropical regions (Figure A5). The oxygen overestimation is then also linked to too strong deep convection in the Southern Ocean (Boucher et al., 2020).
- 206 - Why show the three sets of numbers both as long term change and annual change? One presentation method would seem sufficient. Given the importance of the annual change in the next paragraph, I think that would be the superior approach.
This section provides the only opportunity to compare the global decrease of oxygen of the global oceans. We chose to present both the long-term changes, which can be compared to the historical observational decrease of ∼2 %, and the dissolved oxygen trends required for the computation of the time of emergence in this study.
- 260 - It is not clear if this analysis accounts for WOA underestimating hypoxic volumes Bianchi, D., Dunne, J. P., Sarmiento, J. L., & Galbraith, E. D. (2012). Data-based estimates of suboxia, denitrification, and N2O production in the ocean and their sensitivities to dissolved O2. Global Biogeochemical Cycles, 26(2).
Thank you for this insightful comment. In this study, WOA18 is used as the observational reference to define OMZs in the model. This approach does not explicitly account for biases inherent to the WOA18 dataset. (Bianchi et al., 2012) showed that the World Ocean Atlas underestimates hypoxic volumes, which may lead to an underestimation of the volume percentiles used to define OMZ volumes in the IPSL-CM6A-LR Large Ensemble. (Kwiecinski and Babbin, 2021) used high-frequency oxygen measurements to characterise oxygen-deficient zones, allowing them to resolve the fine-scale vertical and horizontal structure of these regions that is not captured in gridded climatologies such as WOA18. They further showed that products such as WOA18 misplace both the upper boundary and the vertical extent of hypoxic volumes. To account for these uncertainties, we evaluate the sensitivity of our results to alternative OMZ definitions (fixed-threshold versus fixed-percentile), such that the resulting range of responses encompasses uncertainties inherent to IPSL oxygen overestimation and WOA18 underestimation of OMZ volumes.
The biases of the World Ocean Atlas are now discussed in Section 4.5 (Limitations).
P25 L568-572: However, the fixed-percentile approach does not correct for biases inherent to WOA18, which is known to underestimate hypoxic volumes (Bianchi et al., 2012; Kwiecinski and Babbin, 2021).
To account for these uncertainties, we evaluate the sensitivity of our results to alternative OMZ definitions (fixed-threshold versus fixed-percentile), such that the resulting range of responses encompasses uncertainties from IPSL oxygen overestimation and WOA18 underestimation of OMZ volumes (Figure A6).
- 347 - "the" belongs between "in" and "tropical"
Done
- 351 - Does "variability" meaning one standard deviation?
"Variability" referred here to one Large Ensemble standard deviation. Accordingly, we reworded the sentence. It now reads as follows:
P16 L342-344: The tropical Atlantic shows the lowest Large Ensemble standard deviation, thus the lowest internal variability, with hypoxic and low-oxygen volumes varying by 2.3 ×1013 m3 and 1.2 ×1014 m3, respectively.
- 377-378 - Does "twice the magnitude of time-dependant internal variability" mean 2 standard deviations, or 95% confidence?
Here, internal variability is measured using the Large Ensemble standard deviation. Accordingly, internal variability refers to the ensemble standard deviation throughout the manuscript. An emergence beyond twice the standard deviation also corresponds to a 95% confidence interval for the time of emergence. This has been clarified in the revised version.
P17 L376-378: We also examine the time of emergence of these climate-driven signals, defined as the year when the forced signal exceeds twice the magnitude of time-dependent internal variability, quantified here as the Large Ensemble standard deviation (Figure 7, Table 3).
- 400 - "signal" should be "signals"
Done
- 425 - suggest deleting "an annual increase of"
Done
- 504 - suggest "shown in" or "exhibited by" in place of "show by"
Yes. We modified the text accordingly as follows:
P23 L506-508 This oxygenation trend in the tropical South Atlantic basin is also exhibited by CMIP6 multi-model mean over the present-day period in Takano et al., 2023 and by the end of the 21st century over SSP1-2.6 and SSP5-8.5 in Kwiatkowski et al., 2020.
- 507 - Why assume that the model is wrong on the trend emergence in the North Indian? Is this just because of the model mean state bias, or is there observational evidence to the contrary?
The misrepresentation of the trend emergence for the OMZ core primarily arises from its mislocation in the model. In IPSL-CM6A-LR, the OMZ core is simulated in the Bay of Bengal rather than in the Arabian Sea. In addition, the historical trend of dissolved oxygen in the tropical North Indian Ocean is biased in the model, which fails to reproduce the oxygenation–deoxygenation dipole reported by Ditkovsky et al. (2023). However, no observational dataset is sufficiently resolved to detect the emergence of OMZ volumes. We can therefore only compare trends in dissolved oxygen. In the North Indian Ocean, the model shows an emergence of deoxygenation in the early 21st century at 10°S-30°S (Figure A3), whereas Tan et al. (2026) report no detectable emergence of deoxygenation in observations prior to 2023.
References
Bianchi, D., Dunne, J. P., Sarmiento, J. L., and Galbraith, E. D.: Data-based estimates of suboxia, denitrification, and N2 O production in the ocean and their sensitivities to dissolved O2, Global Biogeochemical Cycles, 26, 2011GB004 209, https://doi.org/10.1029/2011GB004209, 2012.
Boucher, O., Servonnat, J., Albright, A. L., Aumont, O., Balkanski, Y., Bastrikov, V., Bekki, S., Bonnet, R., Bony, S., Bopp, L., Braconnot, P., Brockmann, P., Cadule, P., Caubel, A., Cheruy, F., Codron, F., Cozic, A., Cugnet, D., D’Andrea, F., Davini, P., de Lavergne, C., Denvil, S., Deshayes, J., Devilliers, M., Ducharne, A., Dufresne, J.-L., Dupont, E., Éthé, C., Fairhead, L., Falletti, L., Flavoni, S., Foujols, M.-A., Gardoll, S., Gastineau, G., Ghattas, J., Grandpeix, J.-Y., Guenet, B., Guez, E., L., Guilyardi, E., Guimberteau, M., Hauglustaine, D., Hourdin, F., Idelkadi, A., Joussaume, S., Kageyama, M., Khodri, M., Krinner, G., Lebas, N., Levavasseur, G., Lévy, C., Li, L., Lott, F., Lurton, T., Luyssaert, S., Madec, G., Madeleine, J.-B., Maignan, F., Marchand, M., Marti, O., Mellul, L., Meurdesoif, Y., Mignot, J., Musat, I., Ottlé, C., Peylin, P., Planton, Y., Polcher, J., Rio, C., Rochetin, N., Rousset, C., Sepulchre, P., Sima, A., Swingedouw, D., Thiéblemont, R., Traore, A. K., Vancoppenolle, M., Vial, J., Vialard, J., Viovy, N., and Vuichard, N.: Presentation and Evaluation of the IPSL-CM6A-LR Climate Model, Journal of Advances in Modeling Earth Systems, 12, e2019MS002 010, https://doi.org/10.1029/2019MS002010, 2020.
Breitburg, D., Levin, L. A., Oschlies, A., Grégoire, M., Chavez, F. P., Conley, D. J., Garçon, V., Gilbert, D., Gutiérrez, D., Isensee, K., Jacinto, G. S., Limburg, K. E., Montes, I., Naqvi, S. W. A., Pitcher, G. C., Rabalais, N. N., Roman, M. R., Rose, K. A., Seibel, B. A., Telszewski, M., Yasuhara, M., and Zhang, J.: Declining oxygen in the global ocean and coastal waters, Science, 359, eaam7240, https://doi.org/10.1126/science.aam7240, 2018.
Busecke, J. J. M., Resplandy, L., and Dunne, J. P.: The Equatorial Undercurrent and the Oxygen Minimum Zone in the Pacific, Geophysical Research Letters, 46, 6716–6725, https://doi.org/10.1029/2019GL082692, 2019.
Calil, P. H. R.: High-Resolution, Basin-Scale Simulations Reveal the Impact of Intermediate Zonal Jets on the Atlantic Oxygen Minimum Zones, Journal of Advances in Modeling Earth Systems, 15, e2022MS003 158, https://doi.org/10.1029/2022MS003158, 2023.
Ditkovsky, S., Resplandy, L., and Busecke, J.: Unique ocean circulation pathways reshape the Indian Ocean oxygen minimum zone with warming, Biogeosciences, 20, 4711–4736, https://doi.org/10.5194/bg-20-4711-2023, 2023.
Kwiecinski, J. V. and Babbin, A. R.: A High-Resolution Atlas of the Eastern Tropical Pacific Oxygen Deficient Zones, Global Biogeochemical Cycles, 35, e2021GB007 001, https://doi.org/10.1029/2021GB007001, 2021.
Millet, B., De Lavergne, C., Gray, W. R., Éthé, C., Madec, G., Holzer, M., DeVries, T., Gebbie, G., and Roche, D. M.: Deep Ocean Ventilation: A Comparison Between a General Circulation Model and Data-Constrained Inverse Models, Journal of Advances in Modeling Earth Systems, 17, e2024MS004 914, https://doi.org/10.1029/2024MS004914, 2025.
Pedlosky, J.: Eastern Boundary Ventilation and the Structure of the Thermocline, Journal of Physical Oceanography, 13, 2038–2044, https://doi.org/10.1175/1520-0485(1983)013%3C2038:EBVATS%3E2.0.CO;2, 1983.
Séférian, R., Berthet, S., Yool, A., Palmiéri, J., Bopp, L., Tagliabue, A., Kwiatkowski, L., Aumont, O., Christian, J., Dunne, J., Gehlen, M., Ilyina, T., John, J. G., Li, H., Long, M. C., Luo, J. Y., Nakano, H., Romanou, A., Schwinger, J., Stock, C., Santana-Falcón, Y., Takano, Y., Tjiputra, J., Tsujino, H., Watanabe, M., Wu, T., Wu, F., and Yamamoto, A.: Tracking Improvement in Simulated Marine Biogeochemistry Between CMIP5 and CMIP6, Current Climate Change Reports, 6, 95–119, https://doi.org/10.1007/s40641-020-00160-0, 2020.
Tan, Z., Von Schuckmann, K., Speich, S., Bopp, L., Zhu, J., and Cheng, L.: Observed large- scale and deep-reaching compound ocean state changes over the past 60 years, Nature Climate Change, 16, 58–68, https://doi.org/10.1038/s41558-025-02484-x, 2026.
Citation: https://doi.org/10.5194/egusphere-2025-2805-AC1
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AC1: 'Reply on RC1', Mathieu Delteil, 16 Feb 2026
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CC1: 'Comment on egusphere-2025-2805', Sam J. Ditkovsky, 14 Oct 2025
Dear authors,
Thank you for the interesting study. It’s great to see that the oxygen water mass framework is inspiring new work. However, there are some key ways in which the methodology in Section 2.3 of this manuscript differs from that of Ditkovsky and Resplandy (2025; hereafter D&R25) regarding regional bias correction. That is not to say that the methods of the present study are incorrect in any way, but they perhaps need justifications beyond references to D&R25.
Key differences in the methods of the present study compared to D&R25 are the regional constraints on OMZs and the direct mapping of simulated oxygen concentrations onto observed concentrations. (1) In D&R25, the oxygen-percentile framework is applied to the global ocean, but in the present study it is applied to local OMZ regions. When the oxygen-percentile framework is applied to constrained regions with open horizontal and vertical boundaries rather than to the global ocean, some key generalities are lost. For example, one can no longer assume that mixing-driven and redistribution-driven changes will sum to zero. (2) The present study goes beyond the scope of D&R25 by directly mapping modeled oxygen concentrations onto observed concentrations. This is a salient extension of the methodology, especially given the extreme biases in the IPSL model that are being corrected. Given both of these considerations, the approach of the present study feels much closer to a quantile-mapping bias correction (as used in e.g. precipitation studies) rather than a water mass framework. The authors may want to consult some papers dedicated to these approaches (e.g. Cannon et al., 2015, Journal of Climate) for some variations on this approach and the strengths and weaknesses of such approaches.
In my interpretation, an oxygen-based bias correction is sound if the biases in the IPSL model can be attributed primarily to biogeochemical processes, rather than physical processes. An oxygen-based coordinate system is meant to capture the behavior of physical pathways, taking advantage of the fact that remineralization differentiates waters along ventilation pathways. If the model simulates realistic ventilation pathways, then even unrealistic remineralization rates will differentiate waters along that pathway in oxygen-percentile space. However, if the model does not simulate realistic ventilation pathways– for example, if there is no effective shadow zone in the model– then the mapping of simulated regimes onto observations seems to me to have little physical significance. So, if the authors can support the claim that the oxygen biases in the IPSL model come primarily from biogeochemical processes, I believe that would strengthen the study significantly. One approach to this (but certainly not the only) could be evaluating temperature and salinity distributions in oxygen-percentile space for each region.
As a final note, the terms “geographic-space” and “ventilation-space” coined in D&R25 seem to be used incorrectly in the methods (Section 2.3) of the present study. To clarify, a result in geographic space is any distribution which uses latitude, longitude and depth as coordinates. So, both oxygen and oxygen-percentiles are represented in geographic space when shown on a map or section. Meanwhile, a result in ventilation-space is any distribution that uses an oxygen-based (or some other non-conservative) tracer coordinate. The frequency distribution of oxygen concentration values (as used in Busecke et al. 2022) and the oxygen-percentile relation are both examples of distributions in ventilation space.
I hope this is helpful, and good luck with the manuscript!
Best wishes,
Sam Ditkovsky
Cannon, A. J., Sobie, S. R., & Murdock, T. Q. (2015). Bias correction of GCM precipitation by quantile mapping: how well do methods preserve changes in quantiles and extremes?. Journal of Climate, 28(17), 6938-6959.
Citation: https://doi.org/10.5194/egusphere-2025-2805-CC1 -
RC2: 'Comment on egusphere-2025-2805', Anonymous Referee #2, 15 Jan 2026
First let me congratulate the authors on a generally well-written paper. The are a few minor quirks with the English, but on the whole it is very good.
I have a few main conceptual points and long list of minor quibbles.
(1) The subarctic Pacific (SAP) is largely ignored, and possibly the title and Abstract should be altered to better reflect the exclusive focus on tropical and subtropical latitudes. There is a strong OMZ in the subarctic Pacific, which generally ESMs do a poor job of reproducing (Figure 2). It is ignored in the subsequent analysis (Figure 5), yet the casual reader of the title and Abstract could easily infer that the analysis is global. In Figure 5, data outside the boxes are included for the observations but not the model, and the caption does not explain why or make any mention of it.
(2) The exact method or criterion for choosing variable intervals along the piControl is not explained (118). The interval varies between 20 and 40 years and there is no explanation of how the specific years were chosen. Possibly this is explained in Bonnet et al 2021, but a brief summary of the core conceptual approach is warranted here.
(3) 20 umol/kg seems high for a choice of threshold to define the OMZ core, and is similarly not explained. I think the assertion that nitrous oxide is produced in <20 uM is a misreading of Ji et al.. Possibly there is some enhancement of N2O production from nitrification in this concentration range, but there is little or no denitrification above 6 uM (e.g., Devol 2008, 10.1016/B978-0-12-372522-6.00006-2). I think that almost all of the net N2O production in OMZs occurs below 6 uM.
(4) I often counsel authors to try alternate methods of data presentation such as histograms or scatterplots, rather than relying solely on visual comparison of colour maps. This seems like an obvious case. A statement like "Across all regions, the IPSL simulations systematically overestimate oxygen concentrations compared to observations" (190-191) seems made for such an analysis. If some histograms and/or scatterplots were included as Supplementary figures the reader could more easily and quantitatively evaluate this bias. (Note also that this passage makes no mention of the SAP.)
On 344 we have "Internal variability of OMZ volumes remains stable throughout the SSP2-4.5 scenario (Figure 6)" This may be true but it's not clear that the reader can verify it from the figure. Another possible example of where additional Supplementary figures with different data-presentation approaches could be useful.
(5) I was also surprised not to see any reference to the data product of Kwiecinski and Babbin (10.1029/2021GB007001). I think this is not a 'gridded' data product in the sense that WOA uses optimal interpolation to produce a continuous field, but it does address some of the deficiencies of the WOA in the ETNP and ETSP (see 150-151). I don't want to call for major new analysis at this stage, but it would nice if it were at least mentioned in the Discussion (e.g., what are the implications of alleviation of these biases for the paper's conclusions?)
(6) The methodology for emergence of individual ensemble members is not really explained (Figure 9). Because the ensemble mean has fairly low internal variability, its emergence from the envelope is usually monotonic. But individual ensemble members are more likely to meander in and out of the envelope for some time, and the text should clearly state whether it is the first or the last crossing of the envelope upper/lower bound that is recorded as ToE. Also on 456-457 it states that "They are members with either stronger forced trends or lower internal variability". Does this make sense? I think it does not. Why would one ensemble member have a stronger forced signal than another? Is not the whole premise of the experiment that the forced signal is common to all members? Some reconsideration of the wording is warranted here. Also what does it mean to say that the ensemble mean 'underestimates' ToE vs the median (460)? How do we know which is 'right'? Wouldn't it be better to just say that one is generally earlier/later?
(7) The Conclusion states that "extratropical ventilation pathways play a key role in maintaining oxygen levels". But this paper does not directly address ventilation pathways or mechanisms. It examines regional mean values of AOU and water age to infer that the ventilation pathways or mechanisms identified in some of the cited literature are important. There's nothing wrong with this but I would suggest that the Abstract and Conclusion be reworded to reflect what was actually done. Other than this the Discussion and Conclusions are generally good, although I find section 4.3 a bit vague and confusing (what does 'dispersion' mean in this context?), and 4.5 a bit repetitive. A little effort here could makes these both shorter and clearer.
Terminology/formatting
There are a few quirks about the way that numbers and units are represented, like not leaving a space between a number and its unit (e.g., 1000m), or using a . instead of space (e.g., mol.kg-1). Both of these occur numerous times.
O2 and AOU are usually italicized and should not be.
The sign convention is confusing. AOU is usually expressed as positive, i.e., if I say that AOU is 40 uM it is implicitly understood that O2sat>O2. There are numerous places in this MS where e.g., AOU is said to have decreased by -X uM (e.g., 407-410), which really means that it increased by X uM, which is the opposite of what is intended (see also e.g., 206-207, 226, 229, 381-382, 442-445, 449).
The number of significant figures is sometimes inconsistent and sometimes excessive. Generally it is good practice to use a consistent number of sf rather than of decimal places (e.g., 2.5+/-0.90). For example, on 225-229 some numbers have 2sf, some 3 and some 4. I think 2 is all that is justified by the actual precision of the data. On e.g., 291 the number of sf seems excessive. On 320-342 most numbers have 3sf, some have 2. I think 2 is all that is really justified or necessary here. Same for 381-386 and 408-415. On 426-449 some numbers have 4sf and some 3. 3 might be justifiable but 2 is probably adequate, and most of these numbers don't really require scientific notation, e.g., one could write 32.57e-1 as 3.3 or 3.78e-2 as 0.038.
There are quite a lot of cases where an unnecessary 's' is tacked onto a word (e.g., confuses singular and plural subject), or where there should be an 's' but it is missing (e.g., 55, 219, 295, 364, 365, 370, 373, 513, 526, 562).
There are quite a few "microparagraphs" consisting of single sentence (e.g., 237, 283, 362). Consider joining these to the preceding paragraph.
There are several figures where the subpanels are numbered abcde… but these are not mentioned in the caption (Figs 4, 5, 6, 7, 8, 9). The subpanels are referenced in the text, and in general there is no ambiguity. I don't know if this journal has a policy on this, but generally if you are going to number the subplots it is usual to define the labels in the caption.
The phrase, "In contrast" appears 13 times. I prefer, "By contrast", but I question whether all of the uses of this phrase are necessary at all. On 96 for example, I think it could be deleted without losing anything important. I would recommend to excise as many as possible.
On 382 for example, we have "These losses are stronger than those observed in their southern counterparts" I find this terminology vague and I think it would be easier on the reader to say e.g., "These losses are greater in the northern hemisphere OMZs than in the southern hemisphere OMZs of the same basin". Large gain in clarity for small number of extra words. (see also 389, 429, 485, 493, 523, 525).
On 178 and elsewhere: don't use 'significant' as a generalized term of emphasis (12 total occurrences; not all are necessarily inappropriate but some are)
Some details
15 "likely already beginning" is this consistent with IPCC-approved use of "likely" or more colloquial?
24-25 I am supportive of citing seminal historical papers like Luyten. The ur-reference on this topic is Wyrtki 1962 (Deep Sea Res 9: 11), which could possibly be included here.
35 change "severity" to "intensity"
42 "parameterization" misspelled
44 delete "the" before "Phase 5"
72 change "extract" to "identify"
105, 109 change "oceanic" to "ocean"
110 change "at 1/3" to "to 1/3"
123 change "then" to "and"
125 and "ensemble" after "IPSL-CM6A-LR"
127 and elsewhere "inter-member" strikes me as an unnecessary jargon term that could be avoided (~20 total occurrences). " Large Ensemble inter-member mean" could just be "Large Ensemble mean" and "the inter-member spread" could be "the spread among members".
182-183 change "the IPSL Hypoxic waters account for only 10% of the observed Hypoxic waters" to "in the IPSL model the volume of Hypoxic water is only 10% of that in the observational data product"
184-186 this sort of speculation properly belongs in the Discussion
189 "it fails" unclear antecedent
193-194 "CMIP6 models fail to capture OMZ core waters in the North Indian Ocean, with an oxygen minimum in the Arabian Sea rather than in the Bay of Bengal" appears to have the place names reversed
203 and elsewhere "Storch and Swiers 1999" both authors' names are misspelled. Zwiers is spelled with a "Z" and von Storch's surname is "von Storch"
203-204 "A 90% confidence interval is applied, accounting for the reduction in degrees of freedom" A vague and essentially meaningless statement. Reword and explain clearly what methods were used and what assumptions were made.
221 "fail to reproduce the observed dipole" "dipole is a jargony word that is probably unnecessary, and it isn't really clear what it refers to here
249 Equation (2): The text below the integral signs is not a limit of integration as is usual practice. It might be better to just drop the equation and explain this in words: V is the total volume of water with O2<O2*. I don't think the equation adds much value.
255 change "29st" to "29th" (I think French does not have this unfortunate quirk, it's just 'e' across the board)
269 should this specify OMZ core? (Figure 2)
297, 378, 488 "dependent" misspelled (https://www.grammarly.com/commonly-confused-words/dependant-vs-dependent)
297 "prevents underestimating variability" vague; reword
309 add "with" after "along"
321 "the tropical North Pacific shows the fastest growth" I'm not sure this is a meaningful comparison, as the volumes in the preindustrial climate vary. If it is the largest to begin with, does comparing rates of expansion in m^3/y really indicate the "fastest growth"?
333 add "about" before "2004"? I'm not sure this number is known this precisely. (see also 422)
349 "OMZ Core volumes being smaller" not clear if this refers to the mean or the variance
351 "relative variability of North Atlantic Hypoxic volume is the highest across all regions" appears to contradict the statement on 477 that "earlier emergence is not due to faster expansion, but rather to lower internal variability of the tropical Atlantic Low-oxygen volumes"; possibly these do not refer to the same [O2] ranges
363 , should be a ; (after "simulation")
375 elsewhere O2sat does not have a comma
381 "dissolved" misspelled
392 missing . after parenthesis
398 "increases in the tropical South Pacific and the tropical South Pacific" ???
400 "decrease signal" is another unnecessary bit of jargon where clarity could be increased with only a small amount of rewording. For example, what if they reworded "In all regions, the O2sat decrease signal emerges after the deoxygenation signal (Figure 7, Table 3). These signal decline gradually until 2000, after which it accelerates sharply" as "In all regions, O2sat emerges after deoxygenation (Figure 7, Table 3). Both O2 and O2sat decline gradually until about 2000, after which the decline accelerates sharply"
402 "the decline rate increases by a factor 10" Another assertion that is probably true but the reader can not necessarily verify from the plot. Possibly include a Supplemental table that would present the actual statistics.
404 and elsewhere I'm not sure any of the uses of "inflection point" (or "inflections" on 465) are valid or necessary. This term has a specific meaning in mathematics, i.e., the point at which d2X/dt2 changes sign (e.g., if supralinear growth become sublinear)
431 Figure 8 b, d, e should be d, h, j?
488-490 "Moreover, Northern Hemisphere ecosystems may face earlier and more intense disruptions from expanding low-oxygen volumes, while Southern Hemisphere systems may experience more gradual but persistent changes." Vague; reword
499 delete "such as the future ocean,"
500 delete "through"
501 "via the Agulhas Current" could use a literature ref
504 change "show" to "shown"
505 delete "showed"
507 add "Ocean" after "Indian"
508 add "model" after "IPSL"
512 according to the title, Schmidt et al., 2021 is about CMIP5 models. I'm not sure this is useful as a basis for generalizing about the present ensemble. Some CMIP5 models (notably IPSL-CM5A-LR) had very coarse resolution (ORCA2) and very weak ventilation of some intermediate ocean areas. In my experience the difference between ORCA2 and ORCA1 in terms of ventilation processes is large.
608 Code availability section not completed
660 Ditkovsky reference incomplete
Figure 1 caption delete "millennial polynomial"
Figure 3 the boxes referenced in the caption are not visible on the maps
Table 1 why not show values for the WOA as well?
Figure 6 consider using different y axes for different panels; also "The time of emergence …b occurs when (solid line) the ensemble mean exceeds (coloured area) the standard deviation over the Large Ensemble" may be true but it's not clear how the reader verifies this, as the envelope of preindustrial variability is not shown on the plots.
Table 2 change "has not emerged from twice the ensemble standard deviation" to "has not emerged at the level of twice the ensemble standard deviation"; change "absence of OMZ volume" to "absence of OMZ core"
Table 3 2986 should be 1986?
Figure 8 caption seems to imply that the criterion for emergence is 1sd rather than 2
Figure 10 For the North Atlantic, the dark blue star is not visible. The text states that O2 emerges before OMZ volume (521) but it appears they are concurrent in this case.
Citation: https://doi.org/10.5194/egusphere-2025-2805-RC2
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- 1
The manuscript "Emerging Climate Signals in Oxygen Minimum Zones" by Delteil et al provides an a comprehensive analysis of oxygen minimum zones across the worlds oceans within the IPSL large ensemble including both spatial and volumetric metrics, correlating mechanistic drivers such as solubility, nutrients, and age and multiple metrics of time of emergence of change. It is well written with only a few points requiring attention specified below. I recommend publication after attention to these technical issues.
Specific comments:
24 - This is also true in regions where temperature is high reducing solubility