How do extreme ENSO events affect Antarctic surface mass balance?

Macha, Jessica M. A.; Mackintosh, Andrew N.; Mccormack, Felicity S.; Henley, Benjamin J.; McGregor, Helen V.; van Dalum, Christiaan T.; Purich, Ariaan

doi:https://doi.org/10.5194/egusphere-2024-3425

Preprints

https://doi.org/10.5194/egusphere-2024-3425

Preprints

13 Nov 2024

| 13 Nov 2024

How do extreme ENSO events affect Antarctic surface mass balance?

Jessica M. A. Macha, Andrew N. Mackintosh, Felicity S. Mccormack, Benjamin J. Henley, Helen V. McGregor, Christiaan T. van Dalum, and Ariaan Purich

Abstract. Extreme El Niño-Southern Oscillation (ENSO) events have far-reaching impacts globally, yet their impacts on Antarctica are poorly understood. In particular, how extreme ENSO events influence Antarctica's mass balance remains uncertain, with few studies considering how extreme events could differ from moderate events. Here, we examine the impacts of past extreme El Niño and strong La Niña events over the period 1979–2018 on surface mass balance of Antarctica using a reanalysis-forced regional climate model. We find that Antarctic surface mass balance does not vary significantly during most of the simulated extreme events. Regional impacts differ between individual events and cannot be generalized across all extreme events. Enderby Land is an exception: significant increases in surface mass balance – approximately 32 % of the regional annual average – occur during all extreme El Niño events. Furthermore, during the 2015/16 extreme El Niño event, widespread and significant surface mass balance changes occurred across East and West Antarctic catchments. These changes are remarkable, extending outside the respective catchments' 5th and 95th probability distributions for September-November period. Our results suggest that future extreme ENSO events may continue to cause significant impacts in Antarctic surface mass balance. However, the magnitude and polarity of the potential impacts cannot be inferred from the limited information available on extremes contained in four decades of historical data. Further investigations using ice core data and large ensemble model simulations are needed to better understand the drivers of the spatial and temporal variability in this system.

Received: 04 Nov 2024 – Discussion started: 13 Nov 2024

Competing interests: At least one of the (co-)authors is a member of the editorial board of The Cryosphere. The peer-review process was guided by an independent editor, and the authors also have no other competing interests to declare.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.

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Journal article(s) based on this preprint

19 May 2025

How do extreme ENSO events affect Antarctic surface mass balance?

Jessica M. A. Macha, Andrew N. Mackintosh, Felicity S. McCormack, Benjamin J. Henley, Helen V. McGregor, Christiaan T. van Dalum, and Ariaan Purich

The Cryosphere, 19, 1915–1935, https://doi.org/10.5194/tc-19-1915-2025,https://doi.org/10.5194/tc-19-1915-2025, 2025

Short summary

Jessica M. A. Macha, Andrew N. Mackintosh, Felicity S. Mccormack, Benjamin J. Henley, Helen V. McGregor, Christiaan T. van Dalum, and Ariaan Purich

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2024-3425', Anonymous Referee #1, 27 Nov 2024
General comment
This study uses a regional atmospheric model to investigate the impact of extreme ENSO events on the surface mass balance (SMB) of the Antarctic ice sheet. The detailed SMB change in many subregions and catchments is described quantitatively about the simulated results. While such information is of great value, the robustness of the conclusion is rather limited due to the smallness of the sample size (as the authors are well aware). More specifically, the conclusion drawn from the composite analysis of only three samples (for El Nino) is not highly convincing. Such a weakness of statistical power can be augmented by revealing the mechanism: why each ENSO event has a differing impact. Is the SMB difference between cases due to the difference in ENSO itself (and its teleconnection) or the effect of other internal variabilities near Antarctica? Neither the effect of other internal variabilities nor the difference of each ENSO event is analyzed in depth. I think the analysis needs to be strengthened to provide more robust insight into interpreting the results.
Specific comment
Abstract, L.8-9: It is unclear how much of the observed anomaly is due to the ENSO during 2015/16. Other modes of variability can affect the SMB, and thus the result may not necessarily represent the ENSO response alone. Therefore, I am not sure if the statement of L.11-12 has its evidence within the manuscript.

Conclusion, L.413-414: I did not understand that “SMB changes differ greatly between the ENSO events” on the one hand and “numerous catchments exhibit similar SMB responses when comparing the impacts of extreme and moderate ENSO events” on the other. How are they consistent? Does this indicate that the observed feature does not represent ENSO response? It is misleading to conclude that the SMB response (signal) to extreme and moderate ENSO events is similar if noise and noise are compared (or if the signals are embedded by noise due to the small sample size).

Without the presented mechanism, it is unclear whether the differences between ENSO events are due to the diversity of ENSO itself or whether they are affected by other internal modes of variability. It would be helpful to present wave trains from the tropics to the Antarctic so that the link to each ENSO event becomes more visible. Then, whether the observed difference in the SMB anomaly arises from the difference in ENSO influences or the local variability may become clearer. There might be other ways to distinguish.

In Fig. 3, the SLP anomaly appears different for each extreme ENSO. It would be helpful to show moisture fluxes and explain why the SMB anomaly in Enderby Land is the same for all three cases despite different SLP responses. It was only explained by noting that the location is in the center of the action.

It is unclear what the benefit of using the regional model is. If the authors draw Figs 3 and 4 from the ERA5 dataset, are they very different? The authors should state the advantages of using the regional model. In particular, the resolutions of both models are not so much different (0.25 degrees vs. 27 km), and the SMB seems to be controlled primarily by moisture transport specified by the boundary conditions.

Figures 3 (and 4): Please stress the meaning of statistical significance here. How should one interpret the statistical significance of a single event when each ENSO-induced SMB is so different (including signs in some places) from the others? Or note that the anomaly is significantly different from the baseline but it does not necessarily represent the ENSO response (alone).
Citation: https://doi.org/10.5194/egusphere-2024-3425-RC1
- AC1: 'Reply on RC1', Jessica Macha, 21 Jan 2025
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-3425/egusphere-2024-3425-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2024-3425-AC1
RC2:
'Comment on egusphere-2024-3425', Christoph Kittel, 19 Dec 2024

Macha et al., 2024 investigates the effect of extreme ENSO events on the Antarctic surface mass balance using a RCM (RACMO). They found that Antarctic surface mass balance generally does not vary significantly during most extreme ENSO events, though regional differences exist especially over Enderby land (increase in snowfall and SMB); or during the extreme 2015/15 El Niño events.

Overall, I find the text well supported by the results where the authors also use robust statistical tests. The figures are clear, and personally I find figure 5 very well done. In this type of study, it's difficult to balance between an overly detailed analysis by region, which risks losing readers, or something too simple. I sometimes had a little trouble remembering the most important points, even if the balance seems good. I would encourage the authors to summarize the main results at the end of each section to help the reader follow the flow of the manuscript; (and if the results were more coherent for each event, to make a summary graph or table).

Although the authors point this out, I think that the too-small number of events qualifying as extreme reduces the robustness of the analysis. Perhaps it would be possible to use a wider range based on SST distribution percentiles, by varying the threshold defining an extreme event. It might also be the opportunity of using something more statistically-robust than arbitrary of +2 and then -1.5 “because -2 is too limiting for El-Nina events”.

I also had to reread several times to understand why the manuscript concentrates essentially on the SON period, while all the other periods are somewhat left to the reader's analysis. Even in the supplement, I'd suggest that the authors add a few explanatory lines on what they think is important for the other periods.

Finally, I have little to reproach this study. The method seems robust to me, the paper remains quite understandable and it's a good piece of work. The only rather annoying limitation comes more from the lack of events, and I would really encourage the authors to try to increase the samples in one way or another; while taking advantage of the review to further improve the clarity of the paper.

Best regards,
C. Kittel

PS: there are two missing spaces L47 and 49.

Citation: https://doi.org/10.5194/egusphere-2024-3425-RC2
- AC1: 'Reply on RC1', Jessica Macha, 21 Jan 2025
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-3425/egusphere-2024-3425-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2024-3425-AC1

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2024-3425', Anonymous Referee #1, 27 Nov 2024
General comment
This study uses a regional atmospheric model to investigate the impact of extreme ENSO events on the surface mass balance (SMB) of the Antarctic ice sheet. The detailed SMB change in many subregions and catchments is described quantitatively about the simulated results. While such information is of great value, the robustness of the conclusion is rather limited due to the smallness of the sample size (as the authors are well aware). More specifically, the conclusion drawn from the composite analysis of only three samples (for El Nino) is not highly convincing. Such a weakness of statistical power can be augmented by revealing the mechanism: why each ENSO event has a differing impact. Is the SMB difference between cases due to the difference in ENSO itself (and its teleconnection) or the effect of other internal variabilities near Antarctica? Neither the effect of other internal variabilities nor the difference of each ENSO event is analyzed in depth. I think the analysis needs to be strengthened to provide more robust insight into interpreting the results.
Specific comment
Abstract, L.8-9: It is unclear how much of the observed anomaly is due to the ENSO during 2015/16. Other modes of variability can affect the SMB, and thus the result may not necessarily represent the ENSO response alone. Therefore, I am not sure if the statement of L.11-12 has its evidence within the manuscript.

Conclusion, L.413-414: I did not understand that “SMB changes differ greatly between the ENSO events” on the one hand and “numerous catchments exhibit similar SMB responses when comparing the impacts of extreme and moderate ENSO events” on the other. How are they consistent? Does this indicate that the observed feature does not represent ENSO response? It is misleading to conclude that the SMB response (signal) to extreme and moderate ENSO events is similar if noise and noise are compared (or if the signals are embedded by noise due to the small sample size).

Without the presented mechanism, it is unclear whether the differences between ENSO events are due to the diversity of ENSO itself or whether they are affected by other internal modes of variability. It would be helpful to present wave trains from the tropics to the Antarctic so that the link to each ENSO event becomes more visible. Then, whether the observed difference in the SMB anomaly arises from the difference in ENSO influences or the local variability may become clearer. There might be other ways to distinguish.

In Fig. 3, the SLP anomaly appears different for each extreme ENSO. It would be helpful to show moisture fluxes and explain why the SMB anomaly in Enderby Land is the same for all three cases despite different SLP responses. It was only explained by noting that the location is in the center of the action.

It is unclear what the benefit of using the regional model is. If the authors draw Figs 3 and 4 from the ERA5 dataset, are they very different? The authors should state the advantages of using the regional model. In particular, the resolutions of both models are not so much different (0.25 degrees vs. 27 km), and the SMB seems to be controlled primarily by moisture transport specified by the boundary conditions.

Figures 3 (and 4): Please stress the meaning of statistical significance here. How should one interpret the statistical significance of a single event when each ENSO-induced SMB is so different (including signs in some places) from the others? Or note that the anomaly is significantly different from the baseline but it does not necessarily represent the ENSO response (alone).
Citation: https://doi.org/10.5194/egusphere-2024-3425-RC1
- AC1: 'Reply on RC1', Jessica Macha, 21 Jan 2025
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-3425/egusphere-2024-3425-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2024-3425-AC1
RC2:
'Comment on egusphere-2024-3425', Christoph Kittel, 19 Dec 2024

Macha et al., 2024 investigates the effect of extreme ENSO events on the Antarctic surface mass balance using a RCM (RACMO). They found that Antarctic surface mass balance generally does not vary significantly during most extreme ENSO events, though regional differences exist especially over Enderby land (increase in snowfall and SMB); or during the extreme 2015/15 El Niño events.

Overall, I find the text well supported by the results where the authors also use robust statistical tests. The figures are clear, and personally I find figure 5 very well done. In this type of study, it's difficult to balance between an overly detailed analysis by region, which risks losing readers, or something too simple. I sometimes had a little trouble remembering the most important points, even if the balance seems good. I would encourage the authors to summarize the main results at the end of each section to help the reader follow the flow of the manuscript; (and if the results were more coherent for each event, to make a summary graph or table).

Although the authors point this out, I think that the too-small number of events qualifying as extreme reduces the robustness of the analysis. Perhaps it would be possible to use a wider range based on SST distribution percentiles, by varying the threshold defining an extreme event. It might also be the opportunity of using something more statistically-robust than arbitrary of +2 and then -1.5 “because -2 is too limiting for El-Nina events”.

I also had to reread several times to understand why the manuscript concentrates essentially on the SON period, while all the other periods are somewhat left to the reader's analysis. Even in the supplement, I'd suggest that the authors add a few explanatory lines on what they think is important for the other periods.

Finally, I have little to reproach this study. The method seems robust to me, the paper remains quite understandable and it's a good piece of work. The only rather annoying limitation comes more from the lack of events, and I would really encourage the authors to try to increase the samples in one way or another; while taking advantage of the review to further improve the clarity of the paper.

Best regards,
C. Kittel

PS: there are two missing spaces L47 and 49.

Citation: https://doi.org/10.5194/egusphere-2024-3425-RC2
- AC1: 'Reply on RC1', Jessica Macha, 21 Jan 2025
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-3425/egusphere-2024-3425-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2024-3425-AC1

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

ED: Reconsider after major revisions (further review by editor and referees) (24 Jan 2025) by Masashi Niwano

AR by Jessica Macha on behalf of the Authors (24 Jan 2025) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (27 Jan 2025) by Masashi Niwano

RR by Anonymous Referee #1 (31 Jan 2025)

Suggestions for revision or reasons for rejection

I appreciate the authors’ great effort in improving the manuscript in response to my earlier comments. In particular, the careful writing and reserved attribution of the SMB anomaly to ENSO, taking other possibilities into account. The analysis of Rossby wave trains is also useful to identify where the differences originate. I still have two comments, of which the first one is important.

1. Throughout the text, the authors use the term “impacts of El Niño”. As the authors now agree, what is shown is not necessarily the impact of El Niño alone. It is the SMB anomaly during the El Niño event. For example, it says in the abstract (L.6) that “Regional impacts differ between individual events and cannot be generalized across all extreme events.” More accurately, this should be “regional anomalies”, rather than “regional impacts”, as the causality is not demonstrated. I notice similar usage of “impacts” throughout the text. I suggest re-examining each use of the term “impacts”.

While I partially understand the authors’ intention, I think the following statements are too strong and can be misleading: “The impacts of extreme El Niño events in Antarctica therefore cannot be generalised; the extreme El Niño composite results miss key regional differences in impacts during events (Figure 3a-d). Extreme El Niño event impacts therefore need to be compared on a case-by-case basis.”

By these statements, the authors implicitly attribute the observed anomalies to the extreme El Niño events. As the authors now carefully phrased in places throughout the text, the differences are not attributable to El Niño alone. Therefore, there is no evidence that “El Niño event impacts need to be compared on a case-by-case basis”.

The composite analysis (or arithmetic average) is a powerful statistical tool to generalize the phenomena but has little meaning with a few samples. I think “The impacts of extreme El Niño events in Antarctica” can “be generalized” if there are enough samples. This is not what we have learned from this study but is supported by the textbook. Therefore, there is no convincing evidence that “The impacts of extreme El Niño events in Antarctica therefore cannot be generalized”. I also disagree with the point written in the response that “a key finding of our analysis is that the composite analysis cannot be used to generalize the behaviour of extreme El Nino or La Nina events.” This is not necessarily a finding from this study but may be a statistical limitation.

It is safe to argue that the individual extreme events are statistically different from the baseline (because that is what the extremes are), but it is difficult to make a statistical statement about commonality or dis-commonality among the three samples. In my opinion, this is a very valuable study consisting of three individual cases, but not more than that.

2. Could the author check whether the following statement is accurate? “RACMO is more appropriate than ERA5 for addressing SMB impacts due to its finer spatial resolution…” The ERA5 dataset is provided at 0.25x0.25 resolution (not the same as the original numerical model resolution), and 0.25 degree is about 27 km at the equator (same as RACMO). If one goes to polar regions, the zonal resolution becomes much finer. This is the reason why I originally asked the author if RACMO has the advantage of simulating moisture transport in the polar region than ERA5.

Hide

ED: Publish subject to minor revisions (review by editor) (10 Feb 2025) by Masashi Niwano

AR by Jessica Macha on behalf of the Authors (14 Feb 2025) Author's response Author's tracked changes Manuscript

ED: Publish as is (21 Feb 2025) by Masashi Niwano

AR by Jessica Macha on behalf of the Authors (24 Feb 2025) Manuscript

Journal article(s) based on this preprint

19 May 2025

How do extreme ENSO events affect Antarctic surface mass balance?

Jessica M. A. Macha, Andrew N. Mackintosh, Felicity S. McCormack, Benjamin J. Henley, Helen V. McGregor, Christiaan T. van Dalum, and Ariaan Purich

The Cryosphere, 19, 1915–1935, https://doi.org/10.5194/tc-19-1915-2025,https://doi.org/10.5194/tc-19-1915-2025, 2025

Short summary

Jessica M. A. Macha, Andrew N. Mackintosh, Felicity S. Mccormack, Benjamin J. Henley, Helen V. McGregor, Christiaan T. van Dalum, and Ariaan Purich

Supplement

https://doi.org/10.5194/egusphere-2024-3425-supplement

Jessica M. A. Macha, Andrew N. Mackintosh, Felicity S. Mccormack, Benjamin J. Henley, Helen V. McGregor, Christiaan T. van Dalum, and Ariaan Purich

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Extreme El Niño-Southern Oscillation (ENSO) events have global impacts but their Antarctic impacts are poorly understood. Examining Antarctic snow accumulation impacts of past observed extreme ENSO events, we show that accumulation changes differ between events & are unsignificant during most events. Remarkable changes occur during 2015/16 & in Enderby Land during all extreme El Niños. Historical data limits conclusions but future greater extremes could cause Antarctic accumulation changes.


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