The North Atlantic mean state in eddy-resolving coupled models: a multimodel study

Frigola, Amanda; Martin-Martinez, Eneko; Moreno-Chamarro, Eduardo; Samsó, Margarida; Loosvelt-Tomas, Saskia; Bretonnière, Pierre-Antoine; Kuznetsova, Daria; Lin, Xia; Ortega, Pablo

doi:10.5194/egusphere-2025-547

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https://doi.org/10.5194/egusphere-2025-547

Preprints

21 Feb 2025

| 21 Feb 2025

The North Atlantic mean state in eddy-resolving coupled models: a multimodel study

Amanda Frigola, Eneko Martin-Martinez, Eduardo Moreno-Chamarro, Margarida Samsó, Saskia Loosvelt-Tomas, Pierre-Antoine Bretonnière, Daria Kuznetsova, Xia Lin, and Pablo Ortega

Abstract. Ocean mesoscale structures, which are parameterized in standard resolution models, play an important role in featuring global ocean dynamics. Here we study the effects of increasing model ocean resolution to eddy-resolving scales on the representation of the North Atlantic mean state, by comparing an ensemble of four HighResMIP coupled historical simulations with nominal ocean resolutions of at least 1/10° – corresponding to the models CESM1-CAM5-SE-HR, EC-Earth3P-VHR, HadGEM3-GC31-HH, and MPI-ESM1-2-ER – to a baseline of 39 Coupled Model Intercomparison Project phase 6 (CMIP6) simulations at coarser resolution. Despite a warm and salty bias at the surface, we find generally improved vertical stratification in the Labrador (LS) and western Irminger Seas (IS) in the high resolution ensemble, leading to stronger deep water convection in that region, in closer agreement with observations. Both the overturning and barotropic circulations of the North Atlantic present significant improvements in the eddy-resolving models: the Atlantic Meridional Overturning Circulation (AMOC) is weaker than for lower resolution models and closer to RAPID observations; the paths, strength, and structure of the Gulf Stream (GS), North Atlantic Current (NAC), and subpolar gyre (SPG) are also improved, resulting into reduced surface temperature and salinity biases north of Cape Hatteras (NCH) and in the Central North Atlantic (CNA).

Received: 05 Feb 2025 – Discussion started: 21 Feb 2025

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Journal article(s) based on this preprint

15 Dec 2025

The North Atlantic mean state in mesoscale eddy-resolving coupled models: a multimodel study

Amanda Frigola, Eneko Martin-Martinez, Eduardo Moreno-Chamarro, Margarida Samsó, Saskia Loosvelt-Tomas, Pierre-Antoine Bretonnière, Daria Kuznetsova, Xia Lin, and Pablo Ortega

Ocean Sci., 21, 3507–3540, https://doi.org/10.5194/os-21-3507-2025,https://doi.org/10.5194/os-21-3507-2025, 2025

Short summary

Amanda Frigola, Eneko Martin-Martinez, Eduardo Moreno-Chamarro, Margarida Samsó, Saskia Loosvelt-Tomas, Pierre-Antoine Bretonnière, Daria Kuznetsova, Xia Lin, and Pablo Ortega

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2025-547', Anonymous Referee #1, 18 Mar 2025

The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-547/egusphere-2025-547-RC1-supplement.pdf

Citation: https://doi.org/10.5194/egusphere-2025-547-RC1
- AC2: 'response to referee#1', Amanda Frigola, 29 Jun 2025
  
  Thank you for your constructive comments. Please, find attached our response.
  
  Citation: https://doi.org/10.5194/egusphere-2025-547-AC2
RC2:
'Comment on egusphere-2025-547', Anonymous Referee #2, 01 Apr 2025

Thank you for the manuscript “The North Atlantic mean state in eddy-resolving coupled models: a multimodel study”. Understanding how increasing resolution improves the mean state is an important topic and I welcome this study. However, I have some major comments so have to recommend major revisions.
There are a lot of statements throughout about quantities being larger/smaller in the HR ensemble compared to the HR ensemble, however this isn’t really tested. It seems to be based on differences in the ensemble mean without taking into account the fact that the two ensembles are quite different in size and possibly quality. If 4 members were picked at random from the LR ensemble, what is the probability that they look like the HR ensemble? It should also be borne in mind that the CMIP6 ensemble includes some models which are a long way from the observations. The authors should statistically test their assertions – one way of doing this is by using single number metrics (for instance the AMOC strength, SST in the CNA etc) and testing whether the ensembles are statistically different by: randomly picking 4 members from the LR ensemble, calculating the ensemble mean, then repeating until you have a distribution from the LR ensemble. This will show whether the HR ensemble is really different from the LR ensemble, or whether there are some LR members which have similar properties.
My other concern is that the analysis here is quite basic and doesn’t really show much that is new. The authors could include more analysis of scatterplots of the metrics they analyse against each other and discuss the implications for how biases affect each other. There have been a number of studies looking at how resolution affects the North Atlantic. The novelty of this paper seems to be having multiple models at eddy-resolving rather than permitting resolution. What are the implications of going to eddy-resolving resolution?

Minor
L11 ‘important role in featuring global ocean dynamics’ – what does this mean?
L19 ‘weaker than for lower resolution models’ This is rather misleading – the way this is reported in the abstract suggests that it is a result of the resolution change. As the authors discuss, studies have shown that the impact of increased resolution varies from model to model. The result here that the AMOC is weaker in the LR ensemble is likely because of some very strong models in the LR ensemble.
L63 ‘to a’-> ‘with a’
L105 Include resolution in km to compare with other values.
L173 I can’t see the paper ‘in review’ though other studies (eg Marzocchi et al 2015) have suggested that this bias is because of the location of the NAC , rather than the strength.
L237 and Fig 6 Using correlation of profiles to assess the shape seems rather flawed – if one profile has twice the slope of a second profile then the correlation would be perfect. It would be better to assess the stratification itself.
L243 ‘expected to impact on’
Fig 6 What region are these for?
L256 ‘Its’ -> ‘The’
Fig 8 Might be clearer if you adjusted the scale
L287 I don’t really understand this sentence.
L305 It’s not entirely clear what you mean by methodological approach and what it affects – expand a little on this.
L331 ‘biases in NCH’
L347 ‘reduced cold and fresh biases’
L380-383 and Fig A1 Needs more discussion. The correlations in Fig 1a are certainly not significant so I’m not sure what it means that the correlation increases. Maybe instead discuss why there might be correlations and why the HR models might be outliers.
L384-386 Doesn’t really make sense – what is ‘it’?
L397 temperature signals are often damped by interactions with the atmosphere reducing the amplitude of the signal. This would explain why there are stronger correlations for salinity
L401-404 I don’t understand what the authors are getting at here – please explain more.
L410-418 Different definitions of MLD can give very different results. Do all the studies mentioned use the same density criteria? Also you don’t make it very clear that using monthly mean densities to calculate a MLD can give very different (and likely shallower) estimates than means of instantaneous profiles used by Yashayaev etc.
L463 ‘southward propagation of the MLD signal into the AMOC’ – what does this mean?

Citation: https://doi.org/10.5194/egusphere-2025-547-RC2
- AC1: 'response to referee#2', Amanda Frigola, 29 Jun 2025
  
  Thank you for your constructive comments. Please, find attached our response.
  
  Citation: https://doi.org/10.5194/egusphere-2025-547-AC1

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2025-547', Anonymous Referee #1, 18 Mar 2025

The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-547/egusphere-2025-547-RC1-supplement.pdf

Citation: https://doi.org/10.5194/egusphere-2025-547-RC1
- AC2: 'response to referee#1', Amanda Frigola, 29 Jun 2025
  
  Thank you for your constructive comments. Please, find attached our response.
  
  Citation: https://doi.org/10.5194/egusphere-2025-547-AC2
RC2:
'Comment on egusphere-2025-547', Anonymous Referee #2, 01 Apr 2025

Thank you for the manuscript “The North Atlantic mean state in eddy-resolving coupled models: a multimodel study”. Understanding how increasing resolution improves the mean state is an important topic and I welcome this study. However, I have some major comments so have to recommend major revisions.
There are a lot of statements throughout about quantities being larger/smaller in the HR ensemble compared to the HR ensemble, however this isn’t really tested. It seems to be based on differences in the ensemble mean without taking into account the fact that the two ensembles are quite different in size and possibly quality. If 4 members were picked at random from the LR ensemble, what is the probability that they look like the HR ensemble? It should also be borne in mind that the CMIP6 ensemble includes some models which are a long way from the observations. The authors should statistically test their assertions – one way of doing this is by using single number metrics (for instance the AMOC strength, SST in the CNA etc) and testing whether the ensembles are statistically different by: randomly picking 4 members from the LR ensemble, calculating the ensemble mean, then repeating until you have a distribution from the LR ensemble. This will show whether the HR ensemble is really different from the LR ensemble, or whether there are some LR members which have similar properties.
My other concern is that the analysis here is quite basic and doesn’t really show much that is new. The authors could include more analysis of scatterplots of the metrics they analyse against each other and discuss the implications for how biases affect each other. There have been a number of studies looking at how resolution affects the North Atlantic. The novelty of this paper seems to be having multiple models at eddy-resolving rather than permitting resolution. What are the implications of going to eddy-resolving resolution?

Minor
L11 ‘important role in featuring global ocean dynamics’ – what does this mean?
L19 ‘weaker than for lower resolution models’ This is rather misleading – the way this is reported in the abstract suggests that it is a result of the resolution change. As the authors discuss, studies have shown that the impact of increased resolution varies from model to model. The result here that the AMOC is weaker in the LR ensemble is likely because of some very strong models in the LR ensemble.
L63 ‘to a’-> ‘with a’
L105 Include resolution in km to compare with other values.
L173 I can’t see the paper ‘in review’ though other studies (eg Marzocchi et al 2015) have suggested that this bias is because of the location of the NAC , rather than the strength.
L237 and Fig 6 Using correlation of profiles to assess the shape seems rather flawed – if one profile has twice the slope of a second profile then the correlation would be perfect. It would be better to assess the stratification itself.
L243 ‘expected to impact on’
Fig 6 What region are these for?
L256 ‘Its’ -> ‘The’
Fig 8 Might be clearer if you adjusted the scale
L287 I don’t really understand this sentence.
L305 It’s not entirely clear what you mean by methodological approach and what it affects – expand a little on this.
L331 ‘biases in NCH’
L347 ‘reduced cold and fresh biases’
L380-383 and Fig A1 Needs more discussion. The correlations in Fig 1a are certainly not significant so I’m not sure what it means that the correlation increases. Maybe instead discuss why there might be correlations and why the HR models might be outliers.
L384-386 Doesn’t really make sense – what is ‘it’?
L397 temperature signals are often damped by interactions with the atmosphere reducing the amplitude of the signal. This would explain why there are stronger correlations for salinity
L401-404 I don’t understand what the authors are getting at here – please explain more.
L410-418 Different definitions of MLD can give very different results. Do all the studies mentioned use the same density criteria? Also you don’t make it very clear that using monthly mean densities to calculate a MLD can give very different (and likely shallower) estimates than means of instantaneous profiles used by Yashayaev etc.
L463 ‘southward propagation of the MLD signal into the AMOC’ – what does this mean?

Citation: https://doi.org/10.5194/egusphere-2025-547-RC2
- AC1: 'response to referee#2', Amanda Frigola, 29 Jun 2025
  
  Thank you for your constructive comments. Please, find attached our response.
  
  Citation: https://doi.org/10.5194/egusphere-2025-547-AC1

Peer review completion

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

AR by Amanda Frigola on behalf of the Authors (07 Sep 2025) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (08 Sep 2025) by Karen J. Heywood

RR by Anonymous Referee #2 (26 Sep 2025)

Suggestions for revision or reasons for rejection

Thank you for the revised manuscript “The North Atlantic mean state in mesoscale eddy-resolving coupled models: a multimodel study”. The paper is well written and much improved on the previous version. Though there are no major new findings, it is a useful reference for impacts of resolution, particularly for mesoscale eddy-resolving, which hasn’t been covered by many studies. I have a few minor comments.

L53 ‘it has’ -> have
L279-288 Do models also generally have the same SST and SSS biases in regions outside the LS?
L340 ‘in consistency’ -> consistent
L341-345 I think the discussion about MLD datasets in the discussion should be moved here. At the moment you start by saying that HR MLD is in better agreement with EN4 than LR. I think you need to say that the observations of MLD vary a lot (probably because of differences in methodology – this could probably be shortened). Then either say that you can’t assess because of the wide range of observations, or make an argument than EN4 is most like the models (because you’re using the same methodology) and then compare to the models.
L355 For this ‘distinct stripe’, is there any evidence whether it’s real or an artifact of the method/data? Is it discussed in other studies?
Fig 12 I know from looking at the BSF in CMIP6 models that the way they are often calculated means that there is a large offset from integrating from the Southern Ocean northwards. You should comment on this somewhere and how you removed this offset since it affect the zero line.
L573-576 Fig 14a shows a huge amount of vertical scatter and, by eye, does not look significant to me. Could you please check the correlation and p value for this relationship? Also you quote a correlation from another study. Comparing correlations is pretty meaningless unless you take into account the number of data points. P values are more meaningful to compare.
L577 ‘in consistence’ -> consistent
Section 3.8 It would also be good somewhere to discuss observational agreement – ie that models can have good agreement with multiple metrics at once. E.g. Models with no LS SSS bias can have no AMOC bias etc. A previous study (Danabasoglu, 2014 https://doi.org/10.1016/j.ocemod.2013.10.005 ) found that although there was a correlation between AMOC and MLD, that models could only agree with one or the other observational constraint.
L661 ‘overly weak NAC’ – you haven’t measured NAC strength only position. Why do you say it is weak?
L689-693 Some studies also suggest that the NAC position is important for LS biases – see Jackson et al 2023, Marzocchi et al 2015, Treguier et al 2005 https://doi.org/10.1175/JPO2720.1 This seems relevant here since you’ve shown the NAC position improves at higher resolution
L761 Should this be ‘western continental boundaries’? I don’t think it includes those in the east Atlantic.
L775-780 This paragraph does not seem relevant to the mean state (the subject of the paper). There might be impacts on the variability/forced evolution, however there are many other studies that would also be relevant then.

Hide

RR by Anonymous Referee #1 (12 Oct 2025)

ED: Publish subject to minor revisions (review by editor) (12 Oct 2025) by Karen J. Heywood

AR by Amanda Frigola on behalf of the Authors (03 Nov 2025) Author's response Author's tracked changes Manuscript

ED: Publish as is (05 Nov 2025) by Karen J. Heywood

AR by Amanda Frigola on behalf of the Authors (20 Nov 2025)

Journal article(s) based on this preprint

15 Dec 2025

The North Atlantic mean state in mesoscale eddy-resolving coupled models: a multimodel study

Amanda Frigola, Eneko Martin-Martinez, Eduardo Moreno-Chamarro, Margarida Samsó, Saskia Loosvelt-Tomas, Pierre-Antoine Bretonnière, Daria Kuznetsova, Xia Lin, and Pablo Ortega

Ocean Sci., 21, 3507–3540, https://doi.org/10.5194/os-21-3507-2025,https://doi.org/10.5194/os-21-3507-2025, 2025

Short summary

Amanda Frigola, Eneko Martin-Martinez, Eduardo Moreno-Chamarro, Margarida Samsó, Saskia Loosvelt-Tomas, Pierre-Antoine Bretonnière, Daria Kuznetsova, Xia Lin, and Pablo Ortega

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We examine the performance of coupled climate models at unprecedented resolutions, capable of resolving ocean eddies in extensive areas of the North Atlantic. Eddy-resolving models present more realistic density profiles and stronger deep water convection in the subpolar North Atlantic. The strength and structure of the Gulf Stream, North Atlantic Current, and subpolar gyre are also improved at high resolution, and so is the Atlantic Meridional Overturning Circulation.


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