the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Subsurface manifestation of Marine Heatwaves in the South West Indian Ocean
Abstract. Marine heatwaves (MHW) are extreme events of prolonged, anomalously warm ocean temperatures. Globally, marine heatwaves are increasing in frequency and intensity and are responsible for long-term impacts on marine ecosystems, which have devastating socio-economic consequences. A key gap in our understanding of MHWs is how they manifest in the subsurface. This paper uses satellite sea surface temperature (SST) data and in situ subsurface temperature observations from Expendable Bathythermographs (XBTs) to investigate the anomalous water temperature characteristics associated with surface identified MHWs in the South West Indian Ocean (SWIO) and how they progress through the water column. We find that the SWIO, which is dominated by the presence of mostly warm anticyclonic eddies, is characterised by moderate MHWs, and that the frequency, duration and intensity of these events are largely associated with mesoscale activity. Surface-detected MHW case studies demonstrated a strong subsurface temperature anomaly signal, with maximum intensity below the mixed layer depth. The spatial distribution of anticyclonic, warm-core eddies closely matched the distribution of the MHWs. This provides a possible mechanism for the deep extent of these surface MHWs. Improving our understanding of the interaction between mesoscale features and subsurface MHW characteristics will benefit prediction of MHWs and management of the regions’ biodiversity.
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Status: open (until 25 Nov 2024)
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RC1: 'Comment on egusphere-2024-2210', Anonymous Referee #1, 03 Sep 2024
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General comments:
The paper focuses on the characterization of Marine Heat Waves (MHW) at the surface and subsurface in the Southwest Indian Ocean region and the role that mesoscale eddies might play in their generation. The results are relevant in terms of addressing knowledge gaps on the vertical extent of temperature extremes and for regional impacts on biodiversity and fisheries. The paper is well-written, and the methods are sound overall. However, the link between EKE, SST and MHW metrics present in Fig 3 is quite qualitative. Adding a spatial correlation analysis, for example, would strengthen the suggested links between eddies and MHW activity. It is also unclear why MHW total days (annual total of extreme days) and maximum intensity metrics were omitted from the analysis. Finally, the analysis time periods of SST, subsurface temperature and SLA, currents data are not consistent without a clear justification (see details in specific comments below). The authors need to address these points and the specific comments below.
Specific comments:
Line 16: Explain what is meant by moderate MHW. Are they moderate in intensity or have moderate occurrences, ...?
Line 53: add ‘the’ before focus
Line 53-54: Can also add that the SWIO is one of the main 6 hotspots of global marine biodiversity (Ramirez et al. 2017; https://www.science.org/doi/10.1126/sciadv.1601198), which makes assessing MHW in this region even more crucial and urgent.
Line 96 section 2.1: Why the study time period was restricted to 1993-2022 when the satellite SST record extend from 1982 to 2023 (as full years)?
Line 102-103: What’s the exact climatological period used in from what year to what year. Please specify.
Line 104-106: Why Total Days (annual total of extreme days) and maximum intensity metrics were omitted? Is there a specific reason?
Lines 128-129: Why just 20 years period only from 1993-2012. Please explain the choice of not using an SLA time period that extends to the end of the subsurface or surface temperature data (2022) when the aim is to examine the influence of eddies on MHWs?
Figure 2e title and caption: Do you mean “mean intensity”? If so, please update accordingly.
Figure 2 panels titles: To avoid confusion between SST and MHW metrics, please update the title as follows: b) SST standard deviation, c) MHW Frequency, d) MHW Duration, e) MHW Mean Intensity, f) MHW Cumulative Intensity
Line 144-145: How were the seasonal MHW derived?
Line 163: true but excluding MHW frequency.
Lines 191-195: This fits better in Discussion.
Line 204-205: The dates in Figure 4 captions do not always match those in panels titles. Correct accordingly.
Citation: https://doi.org/10.5194/egusphere-2024-2210-RC1 -
RC2: 'Comment on egusphere-2024-2210', Anonymous Referee #2, 18 Nov 2024
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The paper presents a study of subsurface characterization of MHWs, which in the past have received more attention in terms of surface properties. The study is performed in the South West Indian Ocean, whose choice is well motivated both in terms of available datasets (a dense and recurrent array of XBTs), regional dynamics, and potential impacts of subsurface warm anomalies. The paper has two main claims: that MHWs have strong subsurface warm anomalies below the mixed layer and that these are mainly associated to the presence of eddies. In general, I found the paper well written, with pertinent bibliographic references, clear figures, and solid structure. Together with some very minor issues listed at the end, there is however in my view a critical issue that prevents the paper to be acceptable in the present form.
A statistical, robust identification of subsurface warm anomalies associated to surface MHWs is the key result that the reader waits for, and the pillar over which the entire paper could stand or fall. Nevertheless, this part is developed only in terms of a visual inspection of four case studies (Fig. 4). These case studies are well described and useful, because they show concretely the type of events encountered and the datasets. However, a consolidation of this part by a statistical analysis is necessary. This in fact is somehow announced, as the authors write “For each day where subsurface data was available and a MHW signal was present over the XBT transect, the surface MHW intensity was compared to daily subsurface temperature and anomaly profiles.” (L199-200). For some reasons, the result of this comparison beyond the case studies is not shown (the Result Section ends with the case study analysis). The paper has largely the space for an in-depth extra analysis, having at the moment only 4 figures, with 2 of them serving for the context.
In conclusion, the paper should provide a statistically robust analysis based on the ensemble of the XBT dataset presented, if the authors want to support quantitatively the two main claims namely, (i) the presence of subsurface warm anomalies associated to surface MHWs, and (ii) the association of these anomalies to the presence of mesoscale eddies. Without this additional analyses (i.e., at least two extra figures) in my view the paper is not strong enough for publication.
Minor issues
I find the paper overall very well organized and very well written. I have only one minor suggestions for the text: Fig. 2C: If I understand correctly, what is shown is the N of events/year. Please modify “events” in “events/year” to be consistent.
References
In general I find the reference list complete and well discussed. I found just one more recent paper that also studied the subsurface signal of MHWs in the South Indian Ocean:
Azarian, C. et al. Marine heatwaves and global warming impacts on winter waters in the Southern Indian Ocean. Journal of Marine Systems 243, 103962 (2024).
The authors may (or may not) want to discuss their findings in its respect.
Citation: https://doi.org/10.5194/egusphere-2024-2210-RC2
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