Meteorological Drivers of Extreme Swells on the Peruvian Coast

Agurto, Gonzalo; Collazo, Soledad; García-Herrera, Ricardo

doi:10.5194/egusphere-2026-408

Preprints

https://doi.org/10.5194/egusphere-2026-408

Preprints

20 Feb 2026

| 20 Feb 2026

Meteorological Drivers of Extreme Swells on the Peruvian Coast

Gonzalo Agurto, Soledad Collazo, and Ricardo García-Herrera

Abstract. In this study, we analyze the meteorological configurations leading to extreme ocean swells along the Peruvian coast, which are frequently produced by remote Pacific storms from both hemispheres. Using extreme-swell warnings from the Peruvian Navy and ERA5 reanalysis, we examine five austral-winter Southern Hemisphere (SH) events (very strong, south-westerly) and six boreal-winter Northern Hemisphere (NH) events (strong, north-westerly). Event-centred composites are computed over lead windows guided by estimated swell travel times (3–4 days in the SH; 8–11 days in the NH). In both hemispheres, a deep extratropical cyclone becomes vertically aligned from sea-level pressure through 500 hPa to 250 hPa before coastal peak swell, while an upper-level jet core strengthens and organizes a persistent corridor of enhanced surface westerlies over the swell-generation region. In the SH, coherent surrounding ridging tightens the meridional pressure gradient and co-occurs with a strengthened, sharper polar-front jet. In the NH, preconditioning is dominated by a deep central–western North Pacific low with comparatively weak, localized ridging and a markedly intensified, more zonally extended subtropical jet, while the polar-front jet weakens. A flow-analogue framework suggests a recent strengthening of SH event-related surface winds consistent with increased large-scale pressure contrasts and a shift toward more positive Southern Annular Mode conditions, whereas NH events show no robust trend and attribution is obscured by strong interannual-to-decadal variability. These results can support earlier recognition of remote swell hazards affecting Peru and, consequently, can lead to an improvement of early warning systems.

Received: 23 Jan 2026 – Discussion started: 20 Feb 2026

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 paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.

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Journal article(s) based on this preprint

16 Sep 2026

Meteorological drivers of extreme swells on the Peruvian coast

Gonzalo Agurto Barragán, Soledad Collazo, and Ricardo García-Herrera

Weather Clim. Dynam., 7, 1779–1796, https://doi.org/10.5194/wcd-7-1779-2026,https://doi.org/10.5194/wcd-7-1779-2026, 2026

Short summary

Gonzalo Agurto, Soledad Collazo, and Ricardo García-Herrera

Interactive discussion

Status: closed

CC1:
'Comment on egusphere-2026-408', Momme Hell, 24 Feb 2026

At least one citation in the bibliography is incorrect (Hell et al., 2021) and lists the wrong co-authors.

This suggests the use of an LLM for citation generation.

Citation: https://doi.org/10.5194/egusphere-2026-408-CC1
- CC2: 'Reply on CC1', Soledad Maribel Collazo Inglesini, 24 Feb 2026
  
  Thank you for pointing this out. Upon careful inspection, we confirm that the co-authors in the Hell et al. (2021) citation were indeed listed incorrectly, while the title, journal, and DOI were correct. We apologize for this oversight, which occurred during the reformatting of references to comply with the journal's style requirements.
  We have thoroughly reviewed all references in the manuscript. The corrected citation reads:
  Hell, M. C., Ayet, A., & Chapron, B. Swell generation under extra-tropical storms. Journal of Geophysical Research: Oceans, 126, e2021JC017637. https://doi.org/10.1029/2021JC017637, 2021
  During this verification process, we also identified and corrected an error in the citation of Semedo et al. (2011). All remaining references have been thoroughly checked and confirmed to be accurate.
  
  Citation: https://doi.org/10.5194/egusphere-2026-408-CC2
RC1:
'Comment on egusphere-2026-408', Anonymous Referee #1, 19 Apr 2026

This study uses extreme swell warnings issued by the Peruvian Navy and ERA5 reanalysis data to analyze the atmospheric circulation precursors of extreme swell events in the Southern Hemisphere (5 events) and Northern Hemisphere (6 events). It reveals the hemispherically differentiated configuration of the polar-front jet and the subtropical jet, and employs a flow-analogue approach to assess the impact of climate change on event intensity. The research topic has clear practical value, the methodology is relatively advanced, and the results are directly relevant to swell early warning along the Peruvian coast. The overall scientific quality is good; however, there are several methodological limitations and deficiencies in result interpretation. It is recommended that the manuscript be revised before acceptance. The specific suggestions are as follows:
1. Only five SH events and six NH events are included, spanning 17 years. The conclusions may be affected by interdecadal bias, raising doubts about their generalizability. It is recommended to extend the event selection period back to beyond 1980 (using earlier wave reanalysis or historical documentary records) to increase the number of events.
2. The study uses a fixed great-circle distance and a constant wave period (16–20 s), without considering nonlinear dissipation, refraction, diffraction, or background currents (e.g., equatorial currents) during wave propagation. The 8‑ to 11‑day composite window for NH events may incorporate substantial unrelated meteorological noise. It is recommended to use at least one wave hindcast model (e.g., WAVEWATCH III) to simulate one or two representative events (one from each hemisphere), validating the wave height, period, and travel time from the generation region to the Peruvian coast. If such modelling is not feasible, a sensitivity analysis should be added: recompute the travel-time window using different wave periods (14–22 s) and great-circle distances (±10%), and assess the sensitivity of the composite fields to window shifts.
3. For NH events, wind speeds weaken in E6–E8 but strengthen in E9–E11. Although modes such as PDO, ENSO, PNA, AO, and WP are listed, their influences are inconsistent across events, and no unified physical explanation or statistical model is provided. It is recommended to divide the NH events into two groups (E6–E8 vs. E9–E11) and perform separate composite and flow-analogue analyses for each group, comparing the phase distributions of modes such as PDO and ENSO between the two groups. In addition, multiple linear regression or random forest methods should be used to quantify the relative contributions of each climate mode to the 10‑m wind speed anomalies and to identify the dominant factors.
4. The flow-analogue method uses only SLP, Z500, and Z250, without including boundary conditions such as sea surface temperature (SST) or sea ice. This may mistakenly classify weather patterns that are dynamically similar but thermodynamically different as the same type, thereby introducing spurious climate change signals. It is recommended to add the SST field (e.g., monthly SST anomalies) as a fourth variable in the analogue similarity calculation, or at least to perform a sensitivity test: keep the existing three variables unchanged, but use the SST anomalies corresponding to the analogue dates as a posteriori diagnostic variable to test whether SST differs significantly between the earlier and later periods.
5. The study uses only the significant height of wind waves (SHWW) in the generation region as an indicator of swell generation, without providing measured wave height, period, or energy spectral data at the Peruvian coast. The causal chain between the source region and coastal impacts is therefore incomplete. It is recommended to use measured wave data from at least one coastal site in Peru (e.g., Callao, Miraflores, or Paita), which may come from wave buoys, tide gauge inversion, or ERA5 nearshore points, and to produce time-series plots for one or two typical events (e.g., E1 and E9) showing the evolution from SHWW anomalies in the source region to nearshore wave heights, thereby directly illustrating the wave evolution during propagation. If measured data are unavailable, significant wave height time series should be extracted from ERA5 nearshore points (within 50 km of the coast) and subjected to lagged correlation analysis with the SHWW anomalies in the generation region (with the lag time set to the estimated travel time) to quantitatively verify the causal relationship.

Citation: https://doi.org/10.5194/egusphere-2026-408-RC1
- AC1: 'Reply on RC1', Soledad Maribel Collazo Inglesini, 02 Jun 2026
  
  Thank you for taking the time to review our work and for your valuable suggestions, which enabled us to conduct a more thorough analysis. Please find our detailed responses in the attached document.
  
  Citation: https://doi.org/10.5194/egusphere-2026-408-AC1
RC2:
'Comment on egusphere-2026-408', Anonymous Referee #2, 08 May 2026

Summary:
This manuscript examines a set of extreme swell events along the coast of Peru and connects them to jet characteristics in both the Southern and Northern Hemisphere. The recorded extreme swells coincide with strong wind events in either hemisphere. The circulation patterns are then related to a larger sample of events using an analogue approach with an accounting for the long-term changes in wind speed between the mid 20^th century and the more recent period. The connections between the remote drivers of extreme swell events is important for planning purposes and the current work is a nice addition to this understanding with some examination of the historical changes in these drivers that could inform potential future projections of extreme swell events. I have some broad suggestions related to the

Main comments:
There is a relatively small sample size of these events presented and presumably available from the Peruvian Navy records. Especially in the case of the Northern Hemisphere generated events, this introduces a very large degree of uncertainty in the types of events and the background conditions. There is discussion related to the PDO and IPO, but all the events are during 2010 or later, and thus are likely not sampling a representative range of the full variability associated with these modes or their trajectories. It’s not clear to me that the Southern Hemisphere analogue, where a climate change signal is detected, is representative of the swell events in general. Additional discussion related to these limitations could be added to the analogue analysis and discussion.

The authors do account for this somewhat with the flow analogues, but the primary novelty of the manuscript is the connection between extratropical cyclones or large-scale circulation patterns and the swells from this specific dataset. It would be ideal to make more of a connection between the analogues and the swell data where and if possible.

While the statistical tests suggest significance, the box plots for extreme events in Figure 2 and 5 are still within the spreads of the climatological boxplots in all cases. It is not clear that there is a distinction being made between the two groups and it does not necessarily highlight any of the jet metrics being examined. These figures require revisiting or expanded discussion to make their point. The authors could consider removing these figures because the primary conclusions would not be impacted.

Specific comments:
Table 1: The classifications for the Southern Hemisphere events are all “Very Strong” versus only “Strong” in the Northern Hemisphere. Can you provide more information on the definition of “extreme” and “strong” swells? Please make clear the distinction between the classifications taken from the Peruvian Navy records and those in the Northern Hemisphere.
Line 71-72: It wasn’t initially clear that the swells were generated in the Northern Hemisphere and registered along the Peruvian coast. Please make this clearer.

Equation 1: Nitpicking but could you make the g in G_g a subscript to make clearer it is group velocity not another gravitational constant.

Line 96-97: Were there any considerations for modifying the approach for characterizing jet stream characteristics when applying it to the Northern Hemisphere, since Collazo et al. (2024) was only focused on this Southern Hemisphere region near South America.

Line 196: Are you accounting for different numbers of samples in the MW and KS statistical tests? Qualitatively the extreme distribution doesn’t look like a distinct distribution from the climatology, though the tests suggest they are and I’m concerned that is due to sampling.

Line 205: How similar are the SLP patterns for the other events? The SLP patterns in Fig. 3 look quite different from those in Fig. 1, so I’m wondering how representative they are of the other events.

Line 216: Perhaps checking an Amundsen Sea Low index in addition to the SAM would be more targeted based on the composite patterns. It might not give substantially different interpretations, being highly correlated with the SAM, but might provide a more nuanced regional signal or predictive power.

Line 223: It would be good to introduce the counterfactual approach here in the text before discussing the results, rather than only in the figure caption.

Line 224-225: In addition to changes in the SAM, studies have shown strengthening of the Southern Hemisphere over the satellite period that are expected to continue in the future in response to anthropogenic forcing (Priestley and Catto, 2022).

Line 226: The timing of the SAM changes and their relationship with the stated external forcings is somewhat difficult to gauge given the time period available in this study. But an additional factor that might be interesting in this case is the rapid decline of sea ice cover beginning around 2016. Perhaps this exposed more ocean surface and increased fetch in the region.

Line 282: The 10m wind anomalies for the Northern Hemisphere composites occur behind the SHWW anomalies, but in the Southern Hemisphere it the opposite. Why causes this difference?

Lines 354-355: Looks like maybe the sentence got cut off around “intensifies”

References:
Priestley, M. D. K., and J. L. Catto. Future changes in the extratropical storm tracks and cyclone intensity, wind speed, and structure, Weather Clim. Dynam., 3, 337–360. 2022.

Citation: https://doi.org/10.5194/egusphere-2026-408-RC2
- AC2: 'Reply on RC2', Soledad Maribel Collazo Inglesini, 02 Jun 2026
  
  We appreciate the time and effort you devoted to reviewing our work. Your insightful suggestions helped us perform a more in-depth analysis. Please find our detailed responses in the attached document.
  
  Citation: https://doi.org/10.5194/egusphere-2026-408-AC2

Peer review completion

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

AR by Soledad Maribel Collazo Inglesini on behalf of the Authors (17 Jun 2026) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (18 Jun 2026) by Stephan Pfahl

RR by Anonymous Referee #1 (18 Jun 2026)

For final publication, the manuscript should be

accepted as is

accepted subject to technical corrections

accepted subject to minor revisions

reconsidered after major revisions

rejected

Were a revised manuscript to be sent for another round of reviews:

I would be willing to review the revised manuscript.

I would not be willing to review the revised manuscript.

Suggestions for revision or reasons for rejection

As a reviewer, after carefully evaluating the revised manuscript, the authors' responses, and the comments from the other reviewer, I find that while the authors have made noticeable efforts in incorporating statistical tests and expanding textual discussions, the core scientific and methodological flaws raised in the previous round remain unresolved. I completely share the reservations expressed by Reviewer 2; the current revisions appear to be statistical and rhetorical patchworks that gloss over fundamental vulnerabilities in the underlying physical mechanisms.

First, regarding the extremely limited sample size (5 events in the Southern Hemisphere and 6 in the Northern Hemisphere), the composite analysis is highly susceptible to the leverage of a single outlier event, as pointed out by Reviewer 2. Although the authors introduced statistical remedies such as balanced resampling and bootstrap testing, these methods cannot inherently eliminate the structural bias embedded in such a tiny dataset. Without quantitatively isolating the dominant impact of individual extreme events, these statistical adjustments fail to cure the Achilles' heel of a weak data foundation, leaving the robustness and representativeness of the conclusions highly questionable.

Second, the attribution mechanism for the Northern Hemisphere (NH) events suffers from a severe logical fracture, which further validates Reviewer 2's skepticism regarding the validity of the analogue analysis. Out of the 6 NH events, half show intensification under global warming while the other half show weakening. The authors attribute this divergence to the countervailing effects of internal modes like PDO and ENSO, ultimately sheltering their argument under the IPCC's "low confidence" conclusion. This line of reasoning precisely exposes the limitation of the proposed framework: if internal climate variability can so easily mask or reverse the global warming signal, the core thesis concerning the regulation of Peru's extreme swells by global warming lacks sufficient certainty and persuasion in the NH, failing to deliver a unified and lucid physical picture.

Finally, the dynamical link between large-scale circulation anomalies and actual coastal hazards remains fractured. The near-shore wave validation using ERA5 data, hastily added to the discussion section, is superficial. It fails to quantitatively resolve the complex physical processes—such as wave-current interactions and shallow-water deformation—that swells experience during their multi-thousand-kilometer propagation. The sensitivity experiments also stop short at merely proving that "timing inaccuracies do not matter," failing to establish a rigorous, closed dynamical chain from open-ocean generation to coastal transmission.

In summary, the scientific conclusions of the revised manuscript still rest upon highly uncertain derivations, and the critical deficiencies flagged by both reviewers persist.

Hide

RR by Anonymous Referee #2 (08 Jul 2026)

RR by Vikki Thompson (08 Jul 2026)

For final publication, the manuscript should be

accepted as is

accepted subject to technical corrections

accepted subject to minor revisions

reconsidered after major revisions

rejected

Were a revised manuscript to be sent for another round of reviews:

I would be willing to review the revised manuscript.

I would not be willing to review the revised manuscript.

Suggestions for revision or reasons for rejection

The paper presents an assessment of the dynamics causing extreme swell along the Peruvian coast. It uses the flow analogue method to investigate if the atmospheric circulation patterns have changed through time.

1. I would like to highlight that analogues from observations/reanalysis alone cannot be used to attribute changes to anthropogenic climate change. I quote from my own paper (https://www.sciencedirect.com/science/article/pii/S2212094726000496):

It is important to note that differences between past and present composites are not necessarily caused by forced changes, such as anthropogenic greenhouse gas forcings. The differences may be due to internal variability, land-use or aerosol changes, or could be statistical artefacts due to the small sample size or a lack of good analogues. We cannot attribute the changes from these results alone, but they can be used to support attribution statements derived from other methods.

Therefore I would suggest that conclusions point 4 is rewritten to account for this. It would be beneficial to also reframe Line 435, though the inclusion of 'partly' does already help. Perhaps it could be highlighted that further work including flow analogues in GCMs of the past and future could lead to an attribution of the changes.

2. For SH 'very strong' observed events are used, whereas for NH there are only 'strong' events. I understand this is simply what is in the observational record. It would be interesting to see the analogue assessment repeated for the 'strong' SH events to see if less conclusive findings are shown (as in the NH). Alternatively, a comment in the discussion on the difference in results from SH and NH and how that could be linked with the very strong / strong event types would be useful.

Hide

ED: Publish subject to minor revisions (review by editor) (08 Jul 2026) by Stephan Pfahl

AR by Soledad Maribel Collazo Inglesini on behalf of the Authors (01 Sep 2026) Author's response Author's tracked changes Manuscript

ED: Publish as is (02 Sep 2026) by Stephan Pfahl

AR by Soledad Maribel Collazo Inglesini on behalf of the Authors (04 Sep 2026) Manuscript

Interactive discussion

Status: closed

CC1:
'Comment on egusphere-2026-408', Momme Hell, 24 Feb 2026

At least one citation in the bibliography is incorrect (Hell et al., 2021) and lists the wrong co-authors.

This suggests the use of an LLM for citation generation.

Citation: https://doi.org/10.5194/egusphere-2026-408-CC1
- CC2: 'Reply on CC1', Soledad Maribel Collazo Inglesini, 24 Feb 2026
  
  Thank you for pointing this out. Upon careful inspection, we confirm that the co-authors in the Hell et al. (2021) citation were indeed listed incorrectly, while the title, journal, and DOI were correct. We apologize for this oversight, which occurred during the reformatting of references to comply with the journal's style requirements.
  We have thoroughly reviewed all references in the manuscript. The corrected citation reads:
  Hell, M. C., Ayet, A., & Chapron, B. Swell generation under extra-tropical storms. Journal of Geophysical Research: Oceans, 126, e2021JC017637. https://doi.org/10.1029/2021JC017637, 2021
  During this verification process, we also identified and corrected an error in the citation of Semedo et al. (2011). All remaining references have been thoroughly checked and confirmed to be accurate.
  
  Citation: https://doi.org/10.5194/egusphere-2026-408-CC2
RC1:
'Comment on egusphere-2026-408', Anonymous Referee #1, 19 Apr 2026

This study uses extreme swell warnings issued by the Peruvian Navy and ERA5 reanalysis data to analyze the atmospheric circulation precursors of extreme swell events in the Southern Hemisphere (5 events) and Northern Hemisphere (6 events). It reveals the hemispherically differentiated configuration of the polar-front jet and the subtropical jet, and employs a flow-analogue approach to assess the impact of climate change on event intensity. The research topic has clear practical value, the methodology is relatively advanced, and the results are directly relevant to swell early warning along the Peruvian coast. The overall scientific quality is good; however, there are several methodological limitations and deficiencies in result interpretation. It is recommended that the manuscript be revised before acceptance. The specific suggestions are as follows:
1. Only five SH events and six NH events are included, spanning 17 years. The conclusions may be affected by interdecadal bias, raising doubts about their generalizability. It is recommended to extend the event selection period back to beyond 1980 (using earlier wave reanalysis or historical documentary records) to increase the number of events.
2. The study uses a fixed great-circle distance and a constant wave period (16–20 s), without considering nonlinear dissipation, refraction, diffraction, or background currents (e.g., equatorial currents) during wave propagation. The 8‑ to 11‑day composite window for NH events may incorporate substantial unrelated meteorological noise. It is recommended to use at least one wave hindcast model (e.g., WAVEWATCH III) to simulate one or two representative events (one from each hemisphere), validating the wave height, period, and travel time from the generation region to the Peruvian coast. If such modelling is not feasible, a sensitivity analysis should be added: recompute the travel-time window using different wave periods (14–22 s) and great-circle distances (±10%), and assess the sensitivity of the composite fields to window shifts.
3. For NH events, wind speeds weaken in E6–E8 but strengthen in E9–E11. Although modes such as PDO, ENSO, PNA, AO, and WP are listed, their influences are inconsistent across events, and no unified physical explanation or statistical model is provided. It is recommended to divide the NH events into two groups (E6–E8 vs. E9–E11) and perform separate composite and flow-analogue analyses for each group, comparing the phase distributions of modes such as PDO and ENSO between the two groups. In addition, multiple linear regression or random forest methods should be used to quantify the relative contributions of each climate mode to the 10‑m wind speed anomalies and to identify the dominant factors.
4. The flow-analogue method uses only SLP, Z500, and Z250, without including boundary conditions such as sea surface temperature (SST) or sea ice. This may mistakenly classify weather patterns that are dynamically similar but thermodynamically different as the same type, thereby introducing spurious climate change signals. It is recommended to add the SST field (e.g., monthly SST anomalies) as a fourth variable in the analogue similarity calculation, or at least to perform a sensitivity test: keep the existing three variables unchanged, but use the SST anomalies corresponding to the analogue dates as a posteriori diagnostic variable to test whether SST differs significantly between the earlier and later periods.
5. The study uses only the significant height of wind waves (SHWW) in the generation region as an indicator of swell generation, without providing measured wave height, period, or energy spectral data at the Peruvian coast. The causal chain between the source region and coastal impacts is therefore incomplete. It is recommended to use measured wave data from at least one coastal site in Peru (e.g., Callao, Miraflores, or Paita), which may come from wave buoys, tide gauge inversion, or ERA5 nearshore points, and to produce time-series plots for one or two typical events (e.g., E1 and E9) showing the evolution from SHWW anomalies in the source region to nearshore wave heights, thereby directly illustrating the wave evolution during propagation. If measured data are unavailable, significant wave height time series should be extracted from ERA5 nearshore points (within 50 km of the coast) and subjected to lagged correlation analysis with the SHWW anomalies in the generation region (with the lag time set to the estimated travel time) to quantitatively verify the causal relationship.

Citation: https://doi.org/10.5194/egusphere-2026-408-RC1
- AC1: 'Reply on RC1', Soledad Maribel Collazo Inglesini, 02 Jun 2026
  
  Thank you for taking the time to review our work and for your valuable suggestions, which enabled us to conduct a more thorough analysis. Please find our detailed responses in the attached document.
  
  Citation: https://doi.org/10.5194/egusphere-2026-408-AC1
RC2:
'Comment on egusphere-2026-408', Anonymous Referee #2, 08 May 2026

Summary:
This manuscript examines a set of extreme swell events along the coast of Peru and connects them to jet characteristics in both the Southern and Northern Hemisphere. The recorded extreme swells coincide with strong wind events in either hemisphere. The circulation patterns are then related to a larger sample of events using an analogue approach with an accounting for the long-term changes in wind speed between the mid 20^th century and the more recent period. The connections between the remote drivers of extreme swell events is important for planning purposes and the current work is a nice addition to this understanding with some examination of the historical changes in these drivers that could inform potential future projections of extreme swell events. I have some broad suggestions related to the

Main comments:
There is a relatively small sample size of these events presented and presumably available from the Peruvian Navy records. Especially in the case of the Northern Hemisphere generated events, this introduces a very large degree of uncertainty in the types of events and the background conditions. There is discussion related to the PDO and IPO, but all the events are during 2010 or later, and thus are likely not sampling a representative range of the full variability associated with these modes or their trajectories. It’s not clear to me that the Southern Hemisphere analogue, where a climate change signal is detected, is representative of the swell events in general. Additional discussion related to these limitations could be added to the analogue analysis and discussion.

The authors do account for this somewhat with the flow analogues, but the primary novelty of the manuscript is the connection between extratropical cyclones or large-scale circulation patterns and the swells from this specific dataset. It would be ideal to make more of a connection between the analogues and the swell data where and if possible.

While the statistical tests suggest significance, the box plots for extreme events in Figure 2 and 5 are still within the spreads of the climatological boxplots in all cases. It is not clear that there is a distinction being made between the two groups and it does not necessarily highlight any of the jet metrics being examined. These figures require revisiting or expanded discussion to make their point. The authors could consider removing these figures because the primary conclusions would not be impacted.

Specific comments:
Table 1: The classifications for the Southern Hemisphere events are all “Very Strong” versus only “Strong” in the Northern Hemisphere. Can you provide more information on the definition of “extreme” and “strong” swells? Please make clear the distinction between the classifications taken from the Peruvian Navy records and those in the Northern Hemisphere.
Line 71-72: It wasn’t initially clear that the swells were generated in the Northern Hemisphere and registered along the Peruvian coast. Please make this clearer.

Equation 1: Nitpicking but could you make the g in G_g a subscript to make clearer it is group velocity not another gravitational constant.

Line 96-97: Were there any considerations for modifying the approach for characterizing jet stream characteristics when applying it to the Northern Hemisphere, since Collazo et al. (2024) was only focused on this Southern Hemisphere region near South America.

Line 196: Are you accounting for different numbers of samples in the MW and KS statistical tests? Qualitatively the extreme distribution doesn’t look like a distinct distribution from the climatology, though the tests suggest they are and I’m concerned that is due to sampling.

Line 205: How similar are the SLP patterns for the other events? The SLP patterns in Fig. 3 look quite different from those in Fig. 1, so I’m wondering how representative they are of the other events.

Line 216: Perhaps checking an Amundsen Sea Low index in addition to the SAM would be more targeted based on the composite patterns. It might not give substantially different interpretations, being highly correlated with the SAM, but might provide a more nuanced regional signal or predictive power.

Line 223: It would be good to introduce the counterfactual approach here in the text before discussing the results, rather than only in the figure caption.

Line 224-225: In addition to changes in the SAM, studies have shown strengthening of the Southern Hemisphere over the satellite period that are expected to continue in the future in response to anthropogenic forcing (Priestley and Catto, 2022).

Line 226: The timing of the SAM changes and their relationship with the stated external forcings is somewhat difficult to gauge given the time period available in this study. But an additional factor that might be interesting in this case is the rapid decline of sea ice cover beginning around 2016. Perhaps this exposed more ocean surface and increased fetch in the region.

Line 282: The 10m wind anomalies for the Northern Hemisphere composites occur behind the SHWW anomalies, but in the Southern Hemisphere it the opposite. Why causes this difference?

Lines 354-355: Looks like maybe the sentence got cut off around “intensifies”

References:
Priestley, M. D. K., and J. L. Catto. Future changes in the extratropical storm tracks and cyclone intensity, wind speed, and structure, Weather Clim. Dynam., 3, 337–360. 2022.

Citation: https://doi.org/10.5194/egusphere-2026-408-RC2
- AC2: 'Reply on RC2', Soledad Maribel Collazo Inglesini, 02 Jun 2026
  
  We appreciate the time and effort you devoted to reviewing our work. Your insightful suggestions helped us perform a more in-depth analysis. Please find our detailed responses in the attached document.
  
  Citation: https://doi.org/10.5194/egusphere-2026-408-AC2

Peer review completion

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

AR by Soledad Maribel Collazo Inglesini on behalf of the Authors (17 Jun 2026) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (18 Jun 2026) by Stephan Pfahl

RR by Anonymous Referee #1 (18 Jun 2026)

For final publication, the manuscript should be

accepted as is

accepted subject to technical corrections

accepted subject to minor revisions

reconsidered after major revisions

rejected

Were a revised manuscript to be sent for another round of reviews:

I would be willing to review the revised manuscript.

I would not be willing to review the revised manuscript.

Suggestions for revision or reasons for rejection

Hide

RR by Anonymous Referee #2 (08 Jul 2026)

RR by Vikki Thompson (08 Jul 2026)

For final publication, the manuscript should be

accepted as is

accepted subject to technical corrections

accepted subject to minor revisions

reconsidered after major revisions

rejected

Were a revised manuscript to be sent for another round of reviews:

I would be willing to review the revised manuscript.

I would not be willing to review the revised manuscript.

Suggestions for revision or reasons for rejection

Hide

ED: Publish subject to minor revisions (review by editor) (08 Jul 2026) by Stephan Pfahl

AR by Soledad Maribel Collazo Inglesini on behalf of the Authors (01 Sep 2026) Author's response Author's tracked changes Manuscript

ED: Publish as is (02 Sep 2026) by Stephan Pfahl

AR by Soledad Maribel Collazo Inglesini on behalf of the Authors (04 Sep 2026) Manuscript

Journal article(s) based on this preprint

16 Sep 2026

Meteorological drivers of extreme swells on the Peruvian coast

Gonzalo Agurto Barragán, Soledad Collazo, and Ricardo García-Herrera

Weather Clim. Dynam., 7, 1779–1796, https://doi.org/10.5194/wcd-7-1779-2026,https://doi.org/10.5194/wcd-7-1779-2026, 2026

Short summary

Gonzalo Agurto, Soledad Collazo, and Ricardo García-Herrera

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https://doi.org/10.5194/egusphere-2026-408-supplement

Gonzalo Agurto, Soledad Collazo, and Ricardo García-Herrera

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Feb 2026	324	130	48	502
Mar 2026	313	139	27	479
Apr 2026	86	60	6	152
May 2026	51	41	3	95
Jun 2026	26	13	4	43
Jul 2026	20	12	1	33
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Cumulative views and downloads (calculated since 20 Feb 2026)

Month	HTML	PDF	XML	Total
Feb 2026	324	130	48	502
Mar 2026	313	139	27	479
Apr 2026	86	60	6	152
May 2026	51	41	3	95
Jun 2026	26	13	4	43
Jul 2026	20	12	1	33
Aug 2026	17	35	3	55
Sep 2026	97	68	9	174
Oct 2026	23	15	8	46

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Total article views: 1,562 (including HTML, PDF, and XML) Thereof 1,562 with geography defined and 0 with unknown origin.

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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

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Large swells can travel thousands of kilometers and impact the Peruvian coast. Using Peruvian Navy warnings and ERA5 reanalysis, we compared extreme swells from the Southern and Northern Hemispheres. In both cases, a deep Pacific storm aligned with a strengthened jet stream sustained strong winds over swell-generation regions, directing wave energy toward Peru. Southern Hemisphere events reach higher intensity, and show a recent wind strengthening, unlike the North Pacific.


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