Southern Ocean influence on Atlantic Meridional Overturning Circulation across climate states

Domain: earth_science
Published: 2025-10-17
Editorial outcome: major_revision

Abstract
Various proxy data agree on a shallow Atlantic Meridional Overturning Circulation (AMOC) during the last glacial maximum (LGM), extending down to 2000 m−2500 m depth, which is similar to the AMOC geometry projected by climate models over the 21st century with rising atmospheric CO2. The AMOC strength in the two climate states is insufficiently constrained. Here the Antarctic Bottom Water (AABW) and North Atlantic Deep Water (NADW) properties from proxy data and climate models are used to investigate their influences on the AMOC. It is primarily the AABW’s potential density that determines the AMOC depth in both the LGM and warming climate. Changes in the potential density of the AABW, and the density contrast between NADW and AABW affect the pathways via which NADW returns to the surface and provide a constraint on AMOC strength. This study emphasizes the importance of the Southern Ocean in the AMOC’s depth and strength across climate states.

Introduction
The AMOC is part of the global Meridional Overturning Circulation (MOC), which is a major component of the climate system. In a zonally averaged view, the MOC can be divided according to the region of deep-water formation into the North Atlantic Deep Water (NADW) cell characterised by northward flow in the upper ocean and southward flow in the deep ocean1, and the Antarctic Bottom Water (AABW) cell with northward flowing water in the abyssal ocean below the NADW cell. Changes in the MOC have a major influence on global and regional climate variability over a wide range of time scales by storing and transporting heat, freshwater, carbon and nutrients2–6.

The Last Glacial Maximum (LGM, ~21,000 years before present) is one of the best documented periods by paleoclimate archives and helpful for understanding past climate change and carbon cycle7. During the LGM, the AMOC was shallower relative to the present-day AMOC by about 1000–1500 m, which is a robust feature inferred from various types of tracers such as δ13C, Cd/Ca, PO4 and εNd8–13. The AMOC strength derived from proxy data, however, exhibits a large uncertainty, inhibiting a complete picture of the AMOC during the LGM. It remains highly controversial as to whether the glacial AMOC was stronger14, comparable15,16 or weaker17–22 relative to the present-day AMOC.

Paleoclimate modelling during the last several years attempted to reproduce the AMOC during the LGM constrained by proxy data23–26. Climate models generally agree on a stronger glacial AMOC relative to the present-day AMOC, yet disagree widely on the depth of the overturning cell26 (Supplementary Fig. 1) due to misrepresentations of various processes associated with surface-buoyancy forcing and mixing in the ocean interior27–29. These deficiencies lower the confidence in the climate models and contribute to the uncertainty regarding the AMOC projections over the 21st century with rising atmospheric CO2 30.

In this study, we evaluate the simulated properties of the NADW and AABW in climate models simulations against glacial reconstructions through direct model-data comparison. We also explore the influences of an improved AABW in the models on the AMOC geometry through a set of dedicated numerical experiments. As changes in the density of deep waters potentially affect the pathways via which deep water returns to the surface, this set of experiments permit to assess the dependence of AMOC strength on various overturning pathways across climate states, eventually allowing to constrain AMOC strength with observation-based estimates of the pathways in both the LGM and warming climate.

Results
Changes in the deep ocean revealed by proxies
Changes in the properties of the NADW and AABW influence the AMOC depth and strength31–34 and therefore became a central topic of paleoclimate modelling35. The potential density of seawater, which is a function of temperature, salinity and pressure, is a direct indicator for the properties of the NADW and AABW and hence could provide information about their influences on the AMOC36. We first discuss the mean temperature and salinity, and the climate-model biases relative to observations at Feni Drift, Bermuda Rise and Shona Rise (Fig. 1a) in pre-industrial simulations with the Kiel Climate Model (KCM, “Methods”) and climate models participating in the Paleoclimate Modelling Intercomparison Project (PMIP). Temperature and salinity at these locations reveal the approximate properties of the NADW and AABW36. Two pre-industrial simulations were conducted with the KCM: one (PI) is performed with the standard version and the other (PIres) with salinity in the deep Southern Ocean (south of 60°S and below 3250 m) relaxed to the Levitus’ salinity climatology (“Methods”, Supplementary Fig. 2). All simulations (KCM and PMIP) presented in this study are integrated for at least a few hundred years to reduce the effects of spin-up.

There are noticeable warm biases in the pre-industrial control integrations of a number of climate models amounting up to about 3°C in the temperatures at Feni Drift, Bermuda Rise and Shona Rise relative to the EN4.2.2 and WOA18 datasets (Fig. 1b–d). Yet the climatological mean salinity at the three sites is generally in good agreement with the observations (Fig. 1b–d). Overall, most PMIP models and the KCM reproduce reasonably well the potential density σ2 (contours in Fig. 1b–d), which is referenced to 2000 m depth, in the deep North Atlantic and Southern Ocean in the pre-industrial control integrations. Following the PMIP protocol, the LGM simulations with the KCM and the PMIP models are performed by implementing glacial boundary conditions including among others continental ice sheets, greenhouse gas concentrations and orbital parameters (Methods). The potential density σ2 in the LGM simulations is significantly underestimated compared to the proxy data at the three sites (Fig. 1e–g). At Feni Drift and Bermuda Rise, the bias in σ2 can be mainly attributed to a warm temperature and to a lesser extent fresh salinity bias. The biased potential density at Shona Rise is largely related to fresh salinity biases in the deep Southern Ocean. Fresh biases there exceed 1 practical salinity unit (psu) in the LGM simulations performed with the standard KCM (Methods) and the PMIP models. We note that the salinity bias at Shona Rise in FGOLAS-g2 and MIROC-ESM exceeds 2 psu. This is likely because these models do not fully implement the PMIP protocol and do not add 1 psu to the oceanic initial conditions of the LGM simulations. The two CESM2 models show relatively dense waters at Shona Rise, which may be due to the parameterisation of density-driven overflow that moves dense water from the shelves to the deep ocean without cascading37,38.

Southern Ocean controls the geometry of the AMOC
The σ2 of the NADW and AABW at their source regions is suggested to be a major factor controlling the AMOC in the LGM and modern climate26,28,39,40. We examine the relationship of the AMOC in the region 20°S-10°N to the σ2 of the NADW and AABW. Here the AMOC depth is defined as the depth at which the overturning stream function is zero. The density of the NADW and AABW is represented by the vertical and area-weighted mean from 800 m to 2800 m over 50°N-55°N and 50°W-10°W in the North Atlantic, and below 3000m over 50°S-55°S and 50°W-10°E in the South Atlantic, respectively (yellow rectangles in Fig. 1a). The AMOC depth exhibits a statistically significant correlation of 0.70 at the 95% confidence level with the σ2 contrast between NADW and AABW in the LGM simulations (Fig. 2a). The significance of correlation coefficient is tested using the p value approach. It is primarily the σ2 of the AABW that exhibits a strong relationship with the AMOC depth, with a correlation of −0.71 (Fig. 2b). The NADW hardly influences the AMOC depth, as illustrated by its small and insignificant correlation with σ2 (not shown). Clearly, the shoaling of the AMOC in the LGM relative to the pre-industrial simulations is linked to enhanced stratification due to the rather dense AABW in the deep ocean36.

The AMOC is projected to shoal under enhanced greenhouse-gas forcing in the models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6)30. We examine the influence of the AABW density on the AMOC geometry in 90 global warming simulations under the Shared Socioeconomic Pathway 5–8.5 (SSP5-8.5) from 25 CMIP6 ensembles41,42 (Table 1, Supplementary Fig. 3). The individual members in each ensemble start from different atmospheric and oceanic initial conditions covering a wide range of climate states. We compute from all available ensemble members the mean AMOC depth between 20°S-10°N and the σ2 of the NADW and AABW averaged over the years 2071-2100. Similar to the LGM, the density contrast between the NADW and AABW exhibits a statistically significant correlation with the AMOC depth under global warming, which, however, is smaller amounting to 0.46 (Fig. 2c). Again, the σ2 of the AABW is the dominating factor determining the AMOC depth with a correlation of −0.72 (Fig. 2d), while the correlation with the σ2 of the NADW is again small and insignificant (not shown).

Improved North Atlantic surface climate due to reduced salinity bias in the Southern Ocean
The KCM suffers from systematic model biases in the North Atlantic as other PMIP models (Supplementary Fig. 4). To alleviate the impact of systematic biases, we compute the simulated SST responses in the LGM simulations relative to the pre-industrial experiment. The KCM’s response of sea surface temperature (SST) over the North Atlantic benefits from the reduced σ2 bias in the Southern Ocean. The late-winter mean (January-March, JFM) SST changes during the LGM from MARGO46, which is a proxy-based reconstruction for the glacial ocean conditions, depict a cooling pattern relative to the modern climate over the eastern North Atlantic, which extends from 60°N to 40°N (Fig. 4a). In comparison to MARGO, the standard KCM simulates a weaker response of cooling in the eastern North Atlantic that is restricted to north of 50°N from 35°W to 5°W (Fig. 4b). Correcting the salinity bias in the deep Southern Ocean in the experiment LGMres20, not only improves the AMOC but also broadens the meridional extent of the cooling in the eastern North Atlantic (Fig. 4c). Relative to MARGO, the root-mean-square-error averaged over 40°N-60°N and 35°W-5°W reduces from 5.32°C to 3.87°C in the restoring experiment. Consistently, the restoring experiment exhibits improvements in the simulated JFM mean SST compared to MARGO (Supplementary Fig. 5). We note that there are still some significant discrepancies in the SST-cooling response between MARGO and the salinity-restoring experiment, which may partly arise from the mean-state biases over the North Atlantic associated with deficiencies in the dynamical processes in the pre-industrial simulation with the KCM47. There is an eastward expansion of the sea ice associated with the cooling over the North Atlantic in LGMres20 (Fig. 4d–f), which reduces the local surface-heat flux and wind-driven oceanic salt transport29. As a result, the deep oceanic convection, as measured by the JFM mean mixed layer depth, is weakened south of Iceland in LGMres20 relative to the standard LGM simulation (Fig. 4g–i). We note that LGMres10 and LGMres15 show similar but smaller changes as LGMres20.

Dependence of changes in the glacial AMOC on the overturning pathways
One remaining issue is the strength of the glacial AMOC. As proxy data disagree on the changes in the AMOC strength during the LGM, we seek to constrain the AMOC changes using present-day observations, which is similar to the concept of emergent constraints48. This approach assumes that despite major differences among the climate models, relationships between the present-day and glacial climate are implicit within the model solutions of the partial differential equations governing the physical processes and parameterisations. Thus, the relationship between the present-day constraint variable (x) and glacial change in AMOC (y) can be expressed as y=f(x)+ε where ε represents a negligible deviation from function f. The function f can be obtained through analysis of a diverse model ensemble with varying resolution and parameterisations, such as the PMIP/CMIP ensembles. This allows us to establish a relationship between the glacial AMOC changes and the pre-industrial overturning pathways, where the pathways are quantified by the overturning streamfunction, which stands for the zonally integrated volume transport that returns the NADW to the surface (Methods).

In latitude-depth space, the AMOC can be regarded as a superposition of the shallower adiabatic cell and the deeper diabatic cell separated in the Atlantic and the Indo-Pacific basin. An acceleration (deceleration) of either cell strengthens (weakens) the AMOC. As suggested by Cessi (2019)49, about half of the volume of the modern NADW returns adiabatically to the surface through the wind-driven upwelling pathway in the Southern Ocean50 (SO_Windtotal). The remaining half of the NADW completes its circulation diabetically via diffusive upwelling in the Atlantic (Atdiffu) and Indo-Pacific51 (IPdiffu).

There is compelling evidence from modern hydrography that ageostrophic inter-basin transport connects the Atlantic with the Indo-Pacific, resulting from differences in the isopycnal depth on the order of 100 m between the two basins52. Specifically, analysis of water mass properties shows that the NADW rising to the surface of the Southern Ocean is transformed into AABW and then transported to the bottom of the Indo-Pacific. These dense waters are upwelled through diapycnal mixing and eventually return to the Atlantic1.

Each overturning pathway exhibits a large spread among the PMIP and CMIP models. Motivated by the influence of deep waters on the AMOC, we investigate relationships of the overturning pathways with the potential density of the NADW and AABW (Fig. 5). The Southern Ocean wind-driven pathway is positively correlated to the potential density contrast between the NADW and AABW in the LGM simulations (Fig. 5a). The correlation coefficient amounts to 0.62, which is significant at the 95% confidence level. Consistent with the LGM simulations, the potential density contrast between the NADW and AABW is associated with the magnitude of the Southern Ocean wind-driven pathway under global warming in CMIP simulations, with a correlation of 0.42 that is significant at the 95% confidence level (Fig. 5c).

The Indo-Pacific diffusive pathway exhibits no significant dependence on the potential density of the NADW and AABW in the LGM simulations with the PMIP models (blue lines Fig. 5b). Salinity-restoring experiments with the KCM suggest that enhanced potential density in the Atlantic basin tends to weaken the Indo-Pacific pathway (green lines in Fig. 5b). In contrast, global warming simulations with the CMIP6 models exhibits a positive correlation of the Indo-Pacific diffusive pathway with the potential density of the AABW, amounting to 0.53 which is significant at the 99% confidence level (Fig. 5d). Differences in the influence of the AABW on the Indo-Pacific diffusive pathway across the glacial and warming climate states are likely associated with the boundary conditions, particularly in the Northern Hemisphere. In summary, the two overturning pathways exhibit a significant relationship to the potential density of the AABW and NADW in the models across climate states.

Then each of the two pathways is examined with respect to the response of the AMOC strength, defined as the change in the LGM simulation relative to the pre-industrial simulation. Models with strong pre-industrial Southern Ocean wind-driven pathway tend to exhibit strengthened glacial AMOC driven by intensified westerly winds (Supplementary Fig 6), as indicated by the positive correlation (r=0.58), explaining about one third of the total variance among the models (PMIP and KCM, Fig. 6a). PMIP models with a stronger pre-industrial Indo-Pacific diffusive pathway are sensitive to the reduced inter-basin transport, which is affected by the glacial ocean stratification and depict an opposite relationship with the glacial AMOC response (r=−0.54; PMIP and KCM, Fig. 6b). Furthermore, the Indo-Pacific diffusive pathway is highly correlated with the glacial AMOC response (r=0.8, PMIP and KCM; Supplementary Fig 7c), consistent with previous studies53–55.

The above results suggest that the Southern Ocean wind-driven and the Indo-Pacific diffusive pathway can be used as a constraint on the glacial AMOC response. This hypothesis is tested using 110 global warming simulations from 12 CMIP5 (Table 2, Supplementary Fig 8) and 25 CMIP6 ensembles (Table 1, Supplementary Fig 3) employing the SSP5-8.5 scenario. The ensemble mean is computed using all available members and the model data are averaged over the years 2071–2100. Consistent with the LGM simulations, the weakening of the AMOC under global warming is dependent on the magnitude of the Southern Ocean wind-driven and Indo-Pacific diffusive pathways in the pre-industrial simulations (Fig. 6c, d). In particular, the Indo-Pacific diffusive pathway plays a dominant role in the AMOC response to global warming, explaining about 50% of the variance among the CMIP models (Fig. 6d). The weakening of the AMOC under global warming is largely attributed to the restricted Indian Ocean inflow induced by the shoaling of the AMOC56 and compensated by the Southern Ocean pathway driven by the intensified westerly winds (Supplementary Fig 6). We note that the CMIP6 models exhibit a stronger dependence of the AMOC response on the pre-industrial pathways than the CMIP5 models. This could be due to improvements in ocean stratification and abyssal circulation in the CMIP6 models57.

Stronger glacial AMOC revealed by observational-based estimates
Since the responses of glacial AMOC in the models exhibits a dependence on the pre-industrial Southern Ocean wind-driven as well as Indo-Pacific diffusive pathway, we use this dependence, as represented by linear regression, to estimate the glacial AMOC strength (Fig. 6a, b). Two global ocean-reanalysis systems employing state-of-the-art data assimilation are used to compute the present-day constraining variables: GloRanV1458 and ECCOv459. As shown in Fig. 6a, the dependence of the glacial AMOC response (y) on the pre-industrial Southern Ocean wind-driven pathway (x) can be simplified as y=0.85*x−3.31 using linear regression (green lines in Fig. 6a). The transport by the Southern Ocean wind-driven pathway amounts to 7.6 Sv (GloRanV14) and 14.0 Sv (ECCOv4). Substituting estimates for the Southern Ocean wind-driven pathway in the above constraint relationship, we obtain positive changes of the glacial AMOC amounting to 3.2 Sv (GloRanV14) and 8.6 Sv (ECCOv4). Both reanalysis datasets suggest a stronger glacial AMOC relative to the pre-industrial state (Fig. 6a). Similarly, regression analysis in Fig. 6b shows the constraint relationship between changes in the glacial AMOC and the present-day Indo-Pacific diffusive pathway as y=−0.82*x+9.13 (green lines in Fig. 6b). The transport by the Indo-Pacific diffusive pathway in GloRanV14 amounts to 8.1 Sv averaged over the years 2000–2021. In ECCOv4, the transport is 0.0 Sv60 averaged over the years 1992–2015. Both datasets reveal a stronger glacial AMOC relative to its pre-industrial state, with a large uncertainty ranging from 2.5 Sv (GloRanV14) to 9.1 Sv (ECCOv4) (Fig. 6b). A stronger glacial AMOC is consistent with enhanced surface-buoyancy forcing27,61,62 over the oceanic deep convection regions63 and also with previous studies employing isotope modelling64.

Methods
Observational datasets and proxy reconstruction
To quantify the temperature and salinity biases of NADW and AABW in modern and glacial simulations, model results are compared to the present-day observations and to palaeoceanographic reconstructions, respectively. To obtain the mean-state salinity and temperature biases in pre-industrial simulations, the monthly version of EN4.2.2 objectively analysed temperature and salinity with bias corrections using the method of Cowley et al.79 is used as reference. Cowley et al. analyses and compares the ocean temperature profiles measured by some 4100 side-by-side deployed expendable bathythermographs and conductivity–temperature–depths such that the measurement biases in ocean temperature can be separated from those in depth. Biases in ocean temperature and salinity relative to the climatology from Volume I and Volume II of the World Ocean Atlas80,81 (WOA18) are considered as well. The temperature and salinity climatology of EN4.2.2 and WOA18 are both averaged over the period 1975–2004. The temperature and salinity biases during the LGM are mainly estimated by comparing the model data to proxy reconstructions at two sites from Ocean Drilling Program by Adkins et al.36.

Two reanalysis datasets, ECCOv4 and GloRanV14, are used here. Forced by the ERA-Interim data over the period 1992–2015, ECCOv4 uses a general circulation model (MITgcm) and assimilates most of available satellite and in-situ data. The data includes satellite sea surface height, ocean bottom pressure, sea surface temperature, sea surface salinity, in-situ temperature and salinity and sea-ice measurements from satellite and in-situ observations. The state estimation uses the adjoint method to iteratively minimise the squared sum of weighted model data misfits and control adjustments. The horizontal resolution varies from 22 km to 110 km, with the highest resolution in high latitudes and lowest resolution in mid latitudes.

GloRanV14 uses the eddy-permitting (1/4° horizontal resolution) Nucleus for European Modelling of the Ocean (NEMO) model, driven with atmospheric forcing from ERA-Interim over the period 1993–2021. Satellite sea surface height, sea surface temperature, sea-ice concentrations and in situ temperature and salinity are assimilated.

We choose the Multiproxy Approach for the Reconstruction of the Glacial Ocean Surface Project (MARGO) to estimate the sea surface temperature biases over the North Atlantic during the LGM46. The MARGO synthesis compiles and integrates 696 reconstructions of SSTs based on four microfossil (i.e. planktonic foraminifera, diatom, dinoflagellate cyst and radiolarian abundances) and two geochemical (alkenones and planktonic foraminifera Mg/Ca) proxies for the LGM. The geological age is rigorously defined as the period between 23 and 19 thousand years before present. This multiproxy approach yields the least biased representation for the glacial ocean conditions. The MARGO data are mapped on a global 5°×5° grid. The spatial coverage of proxies is especially dense in the North Atlantic, the Southern Ocean and the tropics. The samples in the subtropical gyres, especially in the Pacific Ocean, however, remain rare.

Kiel Climate Model and experimental setup
The simulations are carried out with a fully coupled atmosphere-ocean-sea ice general circulation model, the Kiel Climate Model82 (KCM). The version of the KCM used here consists of the ECHAM583 atmosphere general circulation model with a horizontal resolution of T42 (2.8°×2.8°), and with 19 vertical levels reaching up to 10 hPa. The atmosphere model is coupled to the NEMO-LIM ocean–sea ice model84 through the OASIS3 coupler85. The horizontal resolution of NEMO is approximately 2° (ORCA2 grid), with a meridional refinement of ~0.5° near the equator and 31 vertical levels.

The KCM suffers from biases in the abyssal ocean which are common to many climate models (Supplementary Fig 9a–c). Yet our aim is to investigate the influences of the abyssal biases on the AMOC, but not their causes. Here we investigate the impact of correcting the AABW salinity biases on the geometry and strength of the glacial AMOC. This is achieved by restoring the AABW salinity towards the palaeoceanographic salinity reconstructed by Adkins et al.36.

The experimental strategy is as follows: we perform two sets of experiments. The first set is performed with the standard KCM, which consists of two experiments: one 5300-year-long pre-industrial control run (PI) that is initialised with the Levitus climatology of temperature and salinity. Pre-industrial greenhouse gases, modern land-sea mask and continental ice-sheet geometry are employed in PI. In the other 5750-year-long simulation (LGM), the boundary conditions including greenhouse gas concentrations and orbital parameters are implemented in accordance with the PMIP4 protocol for the LGM experiments86. The LGM is initialised from the Levitus temperature climatology and salinity climatology to which 1 psu has been added to account for the 116-m drop of global mean sea level during the LGM. The simulated interactions between the tropical Pacific and the North Atlantic, and the multidecadal variability of the AMOC in LGM have been addressed in previous studies87,88.

For the second set of experiments, we apply a three-dimensional relaxation sponge in the Southern Ocean, south of 60°S (Supplementary Fig 2) following the configuration used by Patara and Böning89. As the KCM features strong mixing due to its coarse horizontal and vertical resolution, a relatively strong restoring has to be applied with a relaxation time set to 60 days. To avoid spurious sources of vorticity, the sponge area is restricted away from the Antarctic coast and its northern boundary. The relaxation weakens exponentially in the vicinity of rigid boundaries using the default smoothing function in NEMO. The first experiment (PIres) is a 1100-year-long pre-industrial run starting from the Levitus climatology, yet the salinity below approximately 3250-m in the Southern Ocean (south of 60°S) is restored to monthly values from the Levitus climatology. Notably, the salinity relaxation induces a small deficit in the freshwater budget. We therefore compute the seasonal cycle of the deficit using the initial 300-year monthly data and add the freshwater flux at the surface south of 60°S (Supplementary Fig 10). The zonal mean salinity bias in PIres slightly reduces relative to PI (Supplementary Fig 9). Yet the simulated mean climate and AMOC in PIres remain quite similar to those in PI (not shown). Three additional experiments under the LGM boundary conditions are performed. The salinity in the deep Southern Ocean is restored to monthly salinity climatology from the LGM simulation, to which 1.0 psu (LGMres10), 1.5 psu (LGMres15) or 2.0 psu (LGMres20) is added. Each simulation is integrated for 1600 years, such that the simulated mean climate and circulation reach a quasi-equilibrium state. The last 300-year monthly output from the two sets of simulations are used in the analysis shown here.

Calculation of overturning pathways
As palaeoceanographic reconstructions do not agree on the strength of the glacial AMOC, we seek for alternate ways, such as wind-driven and vertical diffusive processes, to constrain changes in the AMOC strength50,51,60. In the present-day overturning circulation, NADW returns to the ocean surface via either upwelling in the Southern Ocean forced by the westerly winds, or upwelling in the Atlantic and the Indo-Pacific Oceans through vertical diapycnal mixing. In particular, diffusive upwelling in the Indo-Pacific Ocean may significantly impact the global overturning circulation and hence, largely determines the responses of the AMOC strength to anthropogenic global warming in CMIP6 simulations60.

Similarly, we estimate the wind- and diffusion-driven overturning pathways to assess changes in the AMOC during the LGM. Following Baker et al.60, we use streamfunction, which represents the zonally integrated volume transport by Eulerian-mean and parameterised eddy velocity, as a measure for the overturning pathways. The pathways are defined by the processes and regions associated with this upwelling.

In CMIP6 models they can be estimated as follows,
Atdiffu=AMOCmax−AMOCmin (1)
SO_Windtotal=ψjϕ=34.5S (2)
To conserve the total volume of NADW, the diffusive pathway in the Indo-Pacific Ocean can be computed as the residual,
IPdiffu=AMOCmax−Atdiffu−SO_Windtotal, (3)
where AMOCmax represents the total volume of NADW and is defined as the maximum streamfunction in the North Atlantic. AMOCmin represents the NADW entering the Southern Ocean, which is quantified as the minimum streamfunction located between 34.5°S and the latitude of maximum streamfunction in the Atlantic basin. The difference between AMOCmax and AMOCmin thus represents the upwelled NADW via diffusive upwelling in the Atlantic. The total Southern Ocean wind-driven pathway (SO_Windtotal) is defined as the maximum global overturning streamfunciton located at approximately 34.5°S. The Indo-Pacific pathway is the residual arising from volume conservation.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "# Overall Assesment:\nThank you for the opportunity to review this manuscript. The paper demonstrates several strengths, including a systematic\napproach to synthesizing multiple model results and a focused exploration of AMOC variability across different time-scales.\nThese aspects provide valuable insights into climate model behavior under different conditions, particularly regarding the\nLGM and future projections. The topic addressed in this paper is indeed important, and I appreciate the effort the authors\nhave put into their work. However, after a thorough evaluation, I believe that the manuscript, in its current form, does not meet\nthe necessary standards for publication in Nature Communications. Below, I provide detailed comments to explain the\nreasons for my decision and suggestions that the authors may consider for future revisions or resubmissions elsewhere.\n# Major Concerns:\n## Scientific Validity\nThe paper’s systematic synthesis of model outputs is valuable, yet key questions remain regarding the scientific impact of its\nmain findings. Clarifying why the contributions of Southern Ocean wind pathways and Indo-Pacific diffusion pathways differ\nbetween the Last Glacial Maximum (LGM) and future projections would enhance the study's contribution. As demonstrated\nin [e.g., Oka et al., 2021, Commun. Earth Env.], the Southern Ocean plays a crucial role in reproducing MOC during glacial\nperiods, highlighting the need to address such dynamics carefully. Additionally, further discussion on how this study\nadvances the understanding provided by Baker’s findings, and the reasons behind discrepancies in AMOC strength\nestimations across datasets, would strengthen the paper and better situate it within the broader scientific literature.\n## Methodological Issues\nA primary concern is that the AMOC under preindustrial conditions in your model appears weaker than what observational\nconstraints would suggest, raising the question of whether this discrepancy might impact your results. Additionally, how did\nAMOC vary between PI and PIres? Extended Figure 6 indicates that in PIres, a high salinity bias in the Southern Ocean’s\nsurface layer extends into lower latitudes.\nRegarding the LGM, while salinity restoring is employed, the criteria for determining the depth and timescale of this restoring,\nas depicted in Extended Figure 2, remain unclear. This point also links to the prior section—could you elaborate on the data\nassimilation methods and clarify why estimates for LGM AMOC and the contributions of different pathways diverge among\ndatasets?\n## Writing Style and Clarity\nWhile the methods section comprehensively describes the experiments and analyses conducted, there is a lack of\ncontextualization regarding the purpose of these approaches and a limited discussion of the outcomes. Clearly articulating\nthe significance of each experiment and how each analysis contributes to the overarching research question would\nstrengthen the narrative and help the reader understand the rationale behind each step. Additionally, a more in-depth\ndiscussion of the results would provide a clearer interpretation and add depth to the study’s findings.\n# Minor Concerns:\n## Novelty and Contribution to the Field\nSystematic Synthesis of Model Results: One notable contribution of this study is the comprehensive synthesis of various\nmodel outputs, which could add clarity to previously complex climate processes and introduce a novel framework for\nassessing these processes across scenarios such as the LGM and future projections.\nComparison with Baker’s Findings: Furthermore, positioning this study in relation to Baker’s findings helps contextualize its\ncontribution within the current research landscape. Highlighting any advancements from Baker’s results, particularly in terms\nof future projections, emphasizes the study’s role in extending existing knowledge.\n## Figures and Visual Presentation\nThere are several figures where visual clarity could be improved. In particular:\nThe spacing between labels and figures is narrow, reducing visibility and readability.\nSome scatter plots contain dense data points, causing numbers to overlap and making it difficult to correlate data accurately.\nSpacing adjustments or alternative layouts might enhance the figures' readability and accessibility.", "reviewer_2": "The article at hand explores the key factors influencing the geometry and strength of the Atlantic Meridional Overturning\nCirculation (AMOC) under different climate conditions—namely, the Last Glacial Maximum (LGM), the present-day climate,\nand under global warming. The authors conclude that the potential density in the deep Southern Ocean plays a pivotal role\nin realistically simulating the depth of the AMOC, highlighting its importance for understanding past and future AMOC\ndynamics. However, several aspects of the study warrant closer scrutiny, particularly in terms of its treatment of stratification\nprocesses in the Atlantic Ocean and the broader mechanisms influencing AMOC strength.\nThe deep-water formation during the Last Glacial Maximum (LGM) has been widely discussed in the paleoclimate literature.\nStudies suggest that North Atlantic Deep Water (NADW) formation was shallower but not significantly weaker (Butzin et al.,\n2005; Curry and Oppo, 2005; Duplessy et al., 1988). In contrast, Antarctic Bottom Water (AABW) export from the Southern\nOcean increased (Ledbetter and Johnson, 1976; Negre et al., 2010). Glacial AABW may have been saltier than today,\nenhancing ocean stratification (Adkins et al., 2002; Bouttes et al., 2009). Modeling studies indicate that the shoaling of the\nglacial AMOC was likely driven by changes in Southern Ocean sea ice (Baker et al., 2020; Ferrari et al., 2014) or freshwater\ninput from ice sheets (Miller et al., 2012).\nStrengths\nThe article successfully builds on recent advancements in climate modeling to emphasize the crucial role of the Southern\nOcean in shaping the AMOC. It synthesizes various modeling studies to show that factors like wind-driven circulation in the\nSouthern Ocean and diffusive pathways in the Indo-Pacific are key to understanding AMOC responses to different climate\nstates. This focus on Southern Ocean dynamics aligns with recent literature, including the findings of Heuzé et al., which\nhighlight the importance of shelf processes and density-driven overflows in shaping Antarctic Bottom Water (AABW)\ncharacteristics. The paper’s quantitative approach, calculating correlations between model responses and major present-\nday overturning pathways, is an important contribution to narrowing down uncertainties in predicting glacial AMOC strength.\nAdditionally, the comparison of CMIP5 and CMIP6 models is a strength, as it identifies key model improvements—such as\nbetter vertical diffusion and mesoscale eddies representation—which contribute to a more accurate depiction of the AMOC.\nThis is a relevant aspect, given the continued evolution of climate modeling capabilities and the need for more robust\nsimulations of oceanic processes at various spatiotemporal scales.\nWeaknesses\nWhile the article makes a contribution to the understanding of AMOC dynamics under LGM conditions, it glosses over\nimportant aspects that could refine its conclusions. A key omission is the lack of detailed discussion on the vertical\nstratification of the Atlantic Ocean, a mechanism that plays a critical role in modulating AMOC strength during the glacial\nperiod. This gap is particularly notable given that studies like those of Adkins et al., 2002; Knorr et al., 2021; Chen et al.,\n2024 have argued that a stronger stratification during the LGM was a critical factor for the shoaling of the AMOC.\nSpecifically, they suggest that the salinity of glacial deep waters, which offset the effect of their warmer temperatures, is\ncrucial for understanding changes in density and, by extension, the depth and strength of the AMOC. Chen et al. further\nargue that strong glacial-ocean stratification, independent of tidal dissipation, was primarily responsible for the shoaled\nAMOC during the glacial period.\nAs one aim is to investigate the influences of the abyssal biases on the AMOC, one might look onto earlier papers analyzing\nthe effect of Southern Ocean warming (Zhang et al., 2013, CP, also discussing PMIP). Similar sensitivity experiments under\nthe LGM boundary with restoring were already performed earlier, but it is not mentioned. Indeed, a salty deep ocean is found\nto be a prerequisite for glacial termination (Knorr et al., 2021, Nat Geo), see also Extended Data Fig. 10: Glacial Atlantic\nsalinity structure in models of the last three PMIP/CMIP generations.\nMoreover, the paper does not engage deeply with the interactions between different ocean basins, particularly the Atlantic\nand Indo-Pacific. While the correlation between the Southern Ocean wind-driven and Indo-Pacific diffusive pathways is\npresented, there is limited discussion of the mechanisms by which these pathways interact to influence the AMOC. Given\nthe complex nature of ocean circulation, particularly in the Southern Ocean, a more detailed treatment of how these\nprocesses interlink would strengthen the authors' argument. My feeling is that this aspect is the truly innovative one.\nAs a more minor Conceptual Gaps and Uncertainties: The authors’ reliance on model correlations to constrain AMOC\nstrength is also problematic because it assumes that the relationships observed in modern climate states are fully\ntransferable to the glacial period. The LGM represents a unique set of conditions—such as the presence of large ice sheets,\naltered atmospheric circulation patterns, and reduced CO₂ concentrations—that may have influenced AMOC dynamics in\nways that are not captured by present-day pathways. This introduces an additional layer of uncertainty that is not fully\naddressed.\nConclusion\nIn conclusion, while the article provides a contribution to our understanding of the AMOC under different climate states, it is\nlimited by its under-exploration of vertical stratification in the Atlantic Ocean, its reliance on uncertain present-day analogs\nfor constraining glacial AMOC strength, and its insufficient treatment of the interactions between different ocean basins. The\nstudy would benefit from a deeper examination of these processes, particularly the role of glacial ocean stratification (some\nreferences are given above) and interbasin linkages, to provide a more comprehensive and accurate picture of AMOC\nvariability across past, present, and future climate states.\nminor point: please update\nBaker, J. A., Renshaw, R., Jackson, L. C., Dubois, C., Iovino, D., Zuo, H., et al. (2022).\nOverturning and heat transport variations in the South Atlantic in an ocean reanalysis ensemble.\nState Planet Discuss. [preprint], accepted.", "reviewer_3": "Authors’ Response to the Referees’ Comments (Round 1)\nJournal: Nature Communications\nTitle of Paper: Southern Ocean influence on Atlantic Meridional Overturning Circulation\nacross climate states\nAuthors: Zhaoyang Song, Mojib Latif, Wonsun Park, Yuming Zhang\nWe appreciate the time and effort by the referees and the editor in reviewing and handling\nour manuscript. We have addressed all suggestions proposed and questions raised by the referees.\nPlease see our detailed response to the referees’ comments below.\nReviewer #1\nOverall Assessment:\nThank you for the opportunity to review this manuscript. The paper demonstrates several\nstrengths, including a systematic approach to synthesizing multiple model results and a focused\nexploration of AMOC variability across different time-scales. These aspects provide valuable\ninsights into climate model behavior under different conditions, particularly regarding the LGM\nand future projections. The topic addressed in this paper is indeed important, and I appreciate the\neffort the authors have put into their work. However, after a thorough evaluation, I believe that the\nmanuscript, in its current form, does not meet the necessary standards for publication in Nature\nCommunications. Below, I provide detailed comments to explain the reasons for my decision and\nsuggestions that the authors may consider for future revisions or resubmissions elsewhere.\n# Major Concerns:\n# Scientific Validity\n1. The paper’s systematic synthesis of model outputs is valuable, yet key questions remain\nregarding the scientific impact of its main findings. Clarifying why the contributions of Southern\nOcean wind pathways and Indo-Pacific diffusion pathways differ between the Last Glacial\nMaximum (LGM) and future projections would enhance the study's contribution.\nReviewer #2\nThe article at hand explores the key factors influencing the geometry and strength of the\nAtlantic Meridional Overturning Circulation (AMOC) under different climate conditions—namely,\nthe Last Glacial Maximum (LGM), the present-day climate, and under global warming. The\nauthors conclude that the potential density in the deep Southern Ocean plays a pivotal role in\nrealistically simulating the depth of the AMOC, highlighting its importance for understanding past\nand future AMOC dynamics. However, several aspects of the study warrant closer scrutiny,\nparticularly in terms of its treatment of stratification processes in the Atlantic Ocean and the\nbroader mechanisms influencing AMOC strength.\nThe deep-water formation during the Last Glacial Maximum (LGM) has been widely\ndiscussed in the paleoclimate literature. Studies suggest that North Atlantic Deep Water (NADW)\nformation was shallower but not significantly weaker (Butzin et al., 2005; Curry and Oppo, 2005;\nDuplessy et al., 1988). In contrast, Antarctic Bottom Water (AABW) export from the Southern\nOcean increased (Ledbetter and Johnson, 1976; Negre et al., 2010). Glacial AABW may have been\nsaltier than today, enhancing ocean stratification (Adkins et al., 2002; Bouttes et al., 2009).\nModeling studies indicate that the shoaling of the glacial AMOC was likely driven by changes in\nSouthern Ocean sea ice (Baker et al., 2020; Ferrari et al., 2014) or freshwater input from ice\nsheets (Miller et al., 2012).\nStrengths\nThe article successfully builds on recent advancements in climate modeling to emphasize\nthe crucial role of the Southern Ocean in shaping the AMOC. It synthesizes various modeling\nstudies to show that factors like wind-driven circulation in the Southern Ocean and diffusive\npathways in the Indo-Pacific are key to understanding AMOC responses to different climate states.\nThis focus on Southern Ocean dynamics aligns with recent literature, including the findings of\nHeuzé et al., which highlight the importance of shelf processes and density-driven overflows in\nshaping Antarctic Bottom Water (AABW) characteristics. The paper’s quantitative approach,\ncalculating correlations between model responses and major present-day overturning pathways,\nis an important contribution to narrowing down uncertainties in predicting glacial AMOC strength.\nAdditionally, the comparison of CMIP5 and CMIP6 models is a strength, as it identifies key model\nimprovements—such as better vertical diffusion and mesoscale eddies representation—which\ncontribute to a more accurate depiction of the AMOC. This is a relevant aspect, given the continued\nevolution of climate modeling capabilities and the need for more robust simulations of oceanic\nprocesses at various spatiotemporal scales.\nWeaknesses\n1) While the article makes a contribution to the understanding of AMOC dynamics under\nLGM conditions, it glosses over important aspects that could refine its conclusions. A key omission\nis the lack of detailed discussion on the vertical stratification of the Atlantic Ocean, a mechanism\nthat plays a critical role in modulating AMOC strength during the glacial period. This gap is\nparticularly notable given that studies like those of Adkins et al., 2002; Knorr et al., 2021;\nChen et al., 2024 have argued that a stronger stratification during the LGM was a critical factor for the\nshoaling of the AMOC. Specifically, they suggest that the salinity of glacial deep waters, which\noffset the effect of their warmer temperatures, is crucial for understanding changes in density and,\nby extension, the depth and strength of the AMOC. Chen et al. further argue that strong glacial-\nocean stratification, independent of tidal dissipation, was primarily responsible for the shoaled\nAMOC during the glacial period. As one aim is to investigate the influences of the abyssal biases\non the AMOC, one might look onto earlier papers analyzing the effect of Southern Ocean\nwarming (Zhang et al., 2013, CP, also discussing PMIP). Similar sensitivity experiments under\nthe LGM boundary with restoring were already performed earlier, but it is not mentioned. Indeed,\na salty deep ocean is found to be a prerequisite for glacial termination (Knorr et al., 2021, Nat\nGeo), see also Extended Data Fig. 10: Glacial Atlantic salinity structure in models of the last three\nPMIP/CMIP generations.\nReviewer #3\n1) Lines 140-156: It is difficult to say if there an improvement in North Atlantic biases.\nThis is because the middle row panels and bottom row panels in Figure 4 seem very similar. There are\nsome differences in SST in Figure 4b and 4c, as negative SST extend further south in 4c.\nDo authors claim an improvement because of a more similar SST pattern in 4c with respect to 4a\n(between 40N-60N and 35W-5W)? I assume MARGO SSTs have significant uncertainties\nassociated with reconstructions. Given these limitations, how robust these comparisons and\ninterpretations are, in terms of North Atlantic climate improvement?"}, "author_response": "Authors’ Response to the Referees’ Comments (Round 1)\nJournal: Nature Communications\nTitle of Paper: Southern Ocean influence on Atlantic Meridional Overturning Circulation\nacross climate states\nAuthors: Zhaoyang Song, Mojib Latif, Wonsun Park, Yuming Zhang\nWe appreciate the time and effort by the referees and the editor in reviewing and handling\nour manuscript. We have addressed all suggestions proposed and questions raised by the referees.\nPlease see our detailed response to the referees’ comments below.\nReviewer #1\nOverall Assessment:\nThank you for the opportunity to review this manuscript. The paper demonstrates several\nstrengths, including a systematic approach to synthesizing multiple model results and a focused\nexploration of AMOC variability across different time-scales. These aspects provide valuable\ninsights into climate model behavior under different conditions, particularly regarding the\nLGM and future projections. The topic addressed in this paper is indeed important, and I appreciate the\neffort the authors have put into their work. However, after a thorough evaluation, I believe that the\nmanuscript, in its current form, does not meet the necessary standards for publication in Nature\nCommunications. Below, I provide detailed comments to explain the reasons for my decision and\nsuggestions that the authors may consider for future revisions or resubmissions elsewhere.\n# Major Concerns:\n# Scientific Validity\n1. The paper’s systematic synthesis of model outputs is valuable, yet key questions remain\nregarding the scientific impact of its main findings. Clarifying why the contributions of Southern\nOcean wind pathways and Indo-Pacific diffusion pathways differ between the Last Glacial\nMaximum (LGM) and future projections would enhance the study's contribution.\nResponse:\nThe different contributions of these two pathways to the AMOC are mainly dependent on\nthe westerly winds and ocean stratification in the warm and glacial states.\nDuring both the warm and glacial states, there exist stronger westerly winds over the\nSouthern Ocean (Extended Figure 4). Tilted isopycnals forced by intensified westerly winds tend\nto strengthen the AMOC in the models via the Southern Ocean wind-driven pathway.\nIn response to global warming, the upper ocean stratification becomes stronger due to\nwarming and freshening, as evident from the shallower AMOC (Extended Figure 3 and 6).\nThe enhanced stratification substantially constrains the Indian Ocean inflow to the Atlantic and hence\nthe Indo-Pacific diffusive pathway. The AMOC under global warming is thus dominated by the\nIndo-Pacific diffusive pathway, which overwhelms the compensation from the Southern Ocean\npathway.\nBy contrast, the upper ocean stratification during the LGM is determined by the opposing\nchanges induced by cooling and salinification. Large uncertainties in the simulated glacial ocean\nstratification (Figure 1) and isopycnal depth in the Atlantic leads to a highly variable Indo-Pacific\npathway associated with the inter-basin transport from the Indian to the Atlantic. The overall\nresponse of the AMOC to glacial forcing is thus determined by a strengthening Southern Ocean\npathway and a variable Indo-Pacific pathway, and hence subject to large uncertainties. Further, we\nnote that mesoscale processes may play a crucial role in determining the Indian Ocean inflow to\nthe Atlantic (Biastoch et al., 2009; Schulzki et al., 2024).\nThe above discussion is added to the main text of the revised manuscript.\nExtended Figure 4. Modelled zonal mean zonal wind stress as a function of latitude. Solid lines represent the\nMulti-Model Mean (MMM) zonal wind stress (unit: N/m2) in the LGM (blue), SSP585 (red) and pre-industrial\ncontrol (black) simulations. Colour shading indicates ± one standard deviation from the MMM. The LGM MMM\nis computed using 15 simulations (KCM, PMIP3 and PMIP4 models). The SSP585 MMM is computed using 90\nsimulations from 25 CMIP6 model ensembles. The PI MMM is computed using 25 CMIP6 models.\n2). As demonstrated in [e.g., Oka et al., 2021, Commun. Earth Env.], the Southern Ocean plays a\ncrucial role in reproducing MOC during glacial periods, highlighting the need to address such\ndynamics carefully. Additionally, further discussion on how this study advances the\nunderstanding provided by Baker’s findings, and the reasons behind discrepancies in AMOC\nstrength estimations across datasets, would strengthen the paper and better situate it within the\nbroader scientific literature.\nResponse:\nAs shown in Figure 1d and 1e, the PMIP models generally exhibit warm abyssal biases and\nfresh salinity biases in the Southern Ocean in the LGM simulations. While Oka et al. (2021)\nhighlights the influence of the thermal conditions over Southern Hemisphere on the glacial AMOC,\nwe focus on the impact of abyssal haline conditions on the glacial AMOC. Following the second\nreferee’s comments, the study by Oka et al. (2021) is referenced in the text.\nBaker and colleagues find that the weakening of the AMOC in response to GHG forcing is\nlargely dependent on the present-day Indo-Pacific pathway. We find that the constraint of the Indo-\nPacific pathway on the AMOC response varies across climate states, which is affected by the\nIndian Ocean inflow to the Atlantic associated with the ocean stratification (Ferrari et al., 2017).\nShelf processes and density-driven overflow are crucial to simulate realistically changes in deep\nwaters and hence ocean stratification. Our results thus reinforce the essential role of the Southern\nOcean for the AMOC across varying climate states. As suggested, this advancement is added to\nthe discussion.\nThere is a large model spread of the simulated AMOC strength in the LGM and SSP585\nsimulations.\nAs shown by Reintges et al. (2016, Climate Dynamics), the AMOC index (defined as the\nmaximum overturning streamfunction at 30ºN) is significantly related to the depth-averaged\nmeridional potential density difference in the Atlantic between 74ºN and 30ºS down to 1400 m in\nthe CMIP5 ensemble. Similarly, we find that the AMOC strength at 30ºN is significantly related\nto the meridional density σ (in reference to 2000 m) difference between 65ºN and 30ºS in the\n2\nglacial AMOC (Figure R1b), which is likely associated with overly strong wind forcing in the\nNorth Atlantic (Muglia and Schmittner, 2015). Influence of the Southern Ocean appears to be\ninsignificant (Figure R2). For the SSP585 simulations in the CMIP6 ensemble, the meridional\ndensity difference in the Atlantic between 65ºN and 30ºS is significantly related to the projected\nAMOC strength at 30ºN, with relatively larger contributions from the North Atlantic (Figure R2).\nAs indicated by previous studies, the simulated AMOC is associated with all processes\nmaintaining the density distribution in the water column, such as surface wind forcing, buoyancy\nforcing, vertical diffusivity and eddies (e.g., Bellomo et al., 2021; Reintges et al., 2016; Sun et al.,\n2020). The mechanisms in the individual models may also differ. Hence, it would be rather difficult\nto quantify the relative contributions of the different processes and far beyond the scope of this\nstudy.\nFigure R1. Scatter plots of the maximum overturning streamfunction at 30ºN with a) the meridional potential\ndensity 𝜎 (in reference to 2000 m) difference between 65ºN and 30ºS, b) the potential density 𝜎 at 65 ºN, and\n! !\nwith c) potential density 𝜎 at 30ºS down to 1,400 m depth in the LGM simulations performed with 11 PMIP\n!\nmodels. The linear correlation coefficient (Corr.) is given in each panel, with no, one, two, or three stars\nindicating an insignificant correlation or a significant correlation at the 90%, 95% or 99% confidence level using\nthe Pearson correlation coefficient, respectively.\nFigure R2. Scatter plots of the maximum overturning streamfunction at 30ºN with a) the meridional potential\ndensity 𝜎 (in reference to 2000 m) difference between 50ºN and 30ºS, b) the potential density 𝜎 at 50 ºN, and\n! !\nwith c) potential density 𝜎 at 30ºS down to 1,400 m depth averaged over 2071-2100 in the SSP585 simulations\n!\nperformed with 25 CMIP6 models. The linear correlation coefficient (Corr.) is given in each panel, with no, one,\ntwo, or three stars indicating an insignificant correlation or a significant correlation at the 90%, 95% or 99%\nconfidence level using the Pearson correlation coefficient, respectively.\n## Methodological Issues\n3) A primary concern is that the AMOC under preindustrial conditions in your model appears\nweaker than what observational constraints would suggest, raising the question of whether this\ndiscrepancy might impact your results.\nResponse:\nIndeed, the KCM exhibits a relatively shallow and weak AMOC in the pre-industrial\nsimulation relative to observations. Thus, the shoaling of the AMOC in the salinity restoring\nexperiments could be underestimated. Yet our conclusion that the potential density in the deep\nSouthern Ocean is crucial to simulate the AMOC depth still stands, since it is supported by many\nother climate models as shown in Figure 2.\nSimilarly, the relationship between changes in the AMOC strength across climate states\nand the pre-industrial overturning pathways is obtained also from the PMIP and CMIP ensembles.\nBiases in the AMOC strength in each individual model barely affect the conclusion.\n4) Additionally, how did AMOC vary between PI and PI ? Extended Figure 6 indicates that in\nres\nPI , a high salinity bias in the Southern Ocean’s surface layer extends into lower latitudes.\nres\nResponse:\nWe find from the restoring experiments that a strong forcing is required to change the\nAMOC. Relative to PI, PI slightly reduces the high salinity bias in the Southern Ocean by\nres\napproximately 0.1 psu. Such small differences in the salinity and resulting density distribution\nbetween PI and PI hardly affect the AMOC (Figure R3).\nres\nFigure R3. Simulated overturning streamfunction (unit: Sv) in (a) PI, (b) PI and (c) the differences. Green\nres\ncontours in (c) show the mean overturning streamfunction in PI. Hatching indicates the differences are significant\nat the 95% confidence level using Student’s t-test.\n5) Regarding the LGM, while salinity restoring is employed, the criteria for determining the depth\nand timescale of this restoring, as depicted in Extended Figure 2, remain unclear. This point also\nlinks to the prior section—could you elaborate on the data assimilation methods and clarify why\nestimates for LGM AMOC and the contributions of different pathways diverge among datasets?\nResponse:\nThe description of the restoring experiments is added to the text as follows:\nWe apply a three-dimensional relaxation sponge in the Southern Ocean, south of 60ºS\n(Extended Figure 2). As the KCM features strong mixing due to its coarse horizontal and vertical\nresolution, a relatively strong restoring has to be applied with a relaxation time set to 60 days. To\navoid spurious sources of vorticity, the sponge area is restricted away from the Antarctic coast and\nits northern boundary. The relaxation weakens exponentially in the vicinity of rigid boundaries\nusing the default smoothing function in NEMO. The first experiment (PI ) is a 1,100-year-long\nres\npre-industrial run starting from the Levitus climatology, yet the salinity below approximately\n3250-m in the Southern Ocean (south of 60°S) is restored to monthly values from the Levitus\nclimatology. Notably, the salinity relaxation induces a small deficit in the freshwater budget. We\ntherefore compute the seasonal cycle of the deficit using the initial 300-year monthly data and add\nthe freshwater flux at the surface south of 60°S (Extended Figure 8). The zonal mean salinity bias\nin PI slightly reduces relative to PI (Extended Figure 7). Yet the simulated mean climate and\nres\nAMOC in PI remain quite similar to those in PI (not shown). Three additional experiments\nres\nunder the LGM boundary conditions are performed. The salinity in the deep Southern Ocean is\nrestored to monthly salinity climatology from the LGM simulation, to which 1.0 psu (LGM ),\nres10\n1.5 psu (LGM ) or 2.0 psu (LGM ) is added. Each simulation is integrated for 1,600 years,\nres15 res10\nsuch that the simulated mean climate and circulation reach a quasi-equilibrium state.\nThe description on the reanalysis datasets is added to the text as follows:\nForced by the ERA-Interim data over the period 1992-2015, ECCO v4 uses a general\ncirculation model (MITgcm) and assimilates most of available satellite and in-situ data. The data\ninclude satellite sea surface height, ocean bottom pressure, sea surface temperature, sea surface\nsalinity, in-situ temperature and salinity, and sea-ice measurements from satellite and in-situ\nobservations. The state estimation uses the adjoint method to iteratively minimize the squared sum\nof weighted model data misfits and control adjustments. The horizontal resolution varies from 22\nkm to 110 km, with the highest resolution in high latitudes and lowest resolution in midlatitudes.\nGloRanV14 uses the eddy-permitting (1/4° horizontal resolution) Nucleus for European\nModelling of the Ocean (NEMO) model, driven with atmospheric forcing from ERA-Interim over\nthe period 1993-2021. Satellite sea surface height, sea surface temperature, sea-ice concentrations,\nand in situ temperature and salinity are assimilated.\nECCO v4 and GloRan V14 are based on different general circulation models and are\nconstrained by different observational variables. We are not able to explain the differences in the\nAMOC and in the pathways between the data sets. Comparing these reanalyses would be an\ninteresting topic, such comparison is, however, beyond the scope of this study.\n## Writing Style and Clarity\nWhile the methods section comprehensively describes the experiments and analyses conducted,\nthere is a lack of contextualization regarding the purpose of these approaches and a limited\ndiscussion of the outcomes. Clearly articulating the significance of each experiment and how\neach analysis contributes to the overarching research question would strengthen the narrative\nand help the reader understand the rationale behind each step. Additionally, a more in-depth\ndiscussion of the results would provide a clearer interpretation and add depth to the study’s\nfindings.\nResponse:\nWe revised manuscript for better readability. Please refer to the text for details.\n# Minor Concerns:\nSystematic Synthesis of Model Results: One notable contribution of this study is the comprehensive\nsynthesis of various model outputs, which could add clarity to previously complex climate\nprocesses and introduce a novel framework for assessing these processes across scenarios such as\nthe LGM and future projections. Comparison with Baker’s Findings: Furthermore, positioning this\nstudy in relation to Baker’s findings helps contextualize its contribution within the current research\nlandscape. Highlighting any advancements from Baker’s results, particularly in terms of future\nprojections, emphasizes the study’s role in extending existing knowledge.\nResponse:\nPlease see our response to the second comment.\nThere are several figures where visual clarity could be improved. In particular:\nThe spacing between labels and figures is narrow, reducing visibility and readability.\nSome scatter plots contain dense data points, causing numbers to overlap and making it difficult\nto correlate data accurately. Spacing adjustments or alternative layouts might enhance the figures'\nreadability and accessibility.\nResponse:\nWe have revised the figures for better visibility.\nReviewer #2\nThe article at hand explores the key factors influencing the geometry and strength of the\nAtlantic Meridional Overturning Circulation (AMOC) under different climate conditions—namely,\nthe Last Glacial Maximum (LGM), the present-day climate, and under global warming. The\nauthors conclude that the potential density in the deep Southern Ocean plays a pivotal role in\nrealistically simulating the depth of the AMOC, highlighting its importance for understanding past\nand future AMOC dynamics. However, several aspects of the study warrant closer scrutiny,\nparticularly in terms of its treatment of stratification processes in the Atlantic Ocean and the\nbroader mechanisms influencing AMOC strength.\nThe deep-water formation during the Last Glacial Maximum (LGM) has been widely\ndiscussed in the paleoclimate literature. Studies suggest that North Atlantic Deep Water (NADW)\nformation was shallower but not significantly weaker (Butzin et al., 2005; Curry and Oppo, 2005;\nDuplessy et al., 1988). In contrast, Antarctic Bottom Water (AABW) export from the Southern\nOcean increased (Ledbetter and Johnson, 1976; Negre et al., 2010). Glacial AABW may have been\nsaltier than today, enhancing ocean stratification (Adkins et al., 2002; Bouttes et al., 2009). Modeling\nstudies indicate that the shoaling of the glacial AMOC was likely driven by changes in Southern\nOcean sea ice (Baker et al., 2020; Ferrari et al., 2014) or freshwater input from ice\nsheets (Miller et al., 2012).\nStrengths\nThe article successfully builds on recent advancements in climate modeling to emphasize\nthe crucial role of the Southern Ocean in shaping the AMOC. It synthesizes various modeling\nstudies to show that factors like wind-driven circulation in the Southern Ocean and diffusive\npathways in the Indo-Pacific are key to understanding AMOC responses to different climate states.\nThis focus on Southern Ocean dynamics aligns with recent literature, including the findings of\nHeuzé et al., which highlight the importance of shelf processes and density-driven overflows in\nshaping Antarctic Bottom Water (AABW) characteristics. The paper’s quantitative approach,\ncalculating correlations between model responses and major present-day overturning pathways,\nis an important contribution to narrowing down uncertainties in predicting glacial AMOC strength.\nAdditionally, the comparison of CMIP5 and CMIP6 models is a strength, as it identifies key model\nimprovements—such as better vertical diffusion and mesoscale eddies representation—which\ncontribute to a more accurate depiction of the AMOC. This is a relevant aspect, given the continued\nevolution of climate modeling capabilities and the need for more robust simulations of oceanic\nprocesses at various spatiotemporal scales.\nWeaknesses\n1) While the article makes a contribution to the understanding of AMOC dynamics under\nLGM conditions, it glosses over important aspects that could refine its conclusions. A key omission\nis the lack of detailed discussion on the vertical stratification of the Atlantic Ocean, a mechanism\nthat plays a critical role in modulating AMOC strength during the glacial period. This gap is\nparticularly notable given that studies like those of Adkins et al., 2002; Knorr et al., 2021; Chen\net al., 2024 have argued that a stronger stratification during the LGM was a critical factor for the\nshoaling of the AMOC. Specifically, they suggest that the salinity of glacial deep waters, which\noffset the effect of their warmer temperatures, is crucial for understanding changes in density and,\nby extension, the depth and strength of the AMOC. Chen et al. further argue that strong glacial-\nocean stratification, independent of tidal dissipation, was primarily responsible for the shoaled\nAMOC during the glacial period. As one aim is to investigate the influences of the abyssal biases\non the AMOC, one might look onto earlier papers analyzing the effect of Southern Ocean\nwarming (Zhang et al., 2013, CP, also discussing PMIP). Similar sensitivity experiments under\nthe LGM boundary with restoring were already performed earlier, but it is not mentioned. Indeed,\na salty deep ocean is found to be a prerequisite for glacial termination (Knorr et al., 2021, Nat\nGeo), see also Extended Data Fig. 10: Glacial Atlantic salinity structure in models of the last three\nPMIP/CMIP generations.\nResponse:\nThe suggested references and discussion are added to the text.\n2) Moreover, the paper does not engage deeply with the interactions between different\nocean basins, particularly the Atlantic and Indo-Pacific. While the correlation between the\nSouthern Ocean wind-driven and Indo-Pacific diffusive pathways is presented, there is limited\ndiscussion of the mechanisms by which these pathways interact to influence the AMOC. Given\nthe complex nature of ocean circulation, particularly in the Southern Ocean, a more detailed treatment\nof how these processes interlink would strengthen the authors' argument. My feeling is that this\naspect is the truly innovative one.\nResponse:\nThe influences of the different pathways on the AMOC can be summarised as follows:\na) The Southern Ocean wind-driven pathway is primarily dependent on the westerly surface\nwinds. Intensified westerly winds exist in the glacial and warm climates (Extended Figure 4),\nwhich strengthens the AMOC.\nb) At the present-day climate, the Indo-Pacific and the Atlantic basin are linked via the Indian\nOcean inflow, resulting from shallower mid-depth isopycnal depth in the Atlantic. During the\nwarm state, such link is weakened due to reduced inter-basin transport caused by strong upper-\nocean stratification induced by surface warming and freshening.\nc) The opposing changes induced by cooling and salinification leads to large uncertainties in\nthe upper ocean stratification and a highly variable Indo-Pacific pathway during the LGM. The\nglacial AMOC is the result of a strengthening Southern Ocean pathway and a variable Indo-Pacific\npathway, and hence subject to large uncertainty.\nd) Moreover, mesoscale processes may have significant contributions to the inter-basin\ntransport and hence the AMOC via the salt-advection feedback as revealed by eddy-permitting\nmodels (e.g., Biastoch et al., 2009).\nThe discussion is added to the text as suggested. Please refer to the revised manuscript for\ndetails.\n3) As a more minor Conceptual Gaps and Uncertainties: 3) The authors’ reliance on\nmodel correlations to constrain AMOC strength is also problematic because it assumes that the\nrelationships observed in modern climate states are fully transferable to the glacial period. The\nLGM represents a unique set of conditions—such as the presence of large ice sheets, altered\natmospheric circulation patterns, and reduced CO₂ concentrations—that may have influenced\nAMOC dynamics in ways that are not captured by present-day pathways. This introduces an\nadditional layer of uncertainty that is not fully addressed.\nResponse:\nThis is correct. We have taken up the limitations of our approach in the discussion. Please\nrefer to the text in the revised manuscript.\nIn conclusion, while the article provides a contribution to our understanding of the AMOC\nunder different climate states, it is limited by its under-exploration of vertical stratification in the\nAtlantic Ocean, its reliance on uncertain present-day analogs for constraining glacial AMOC\nstrength, and its insufficient treatment of the interactions between different ocean basins. The study\nwould benefit from a deeper examination of these processes, particularly the role of glacial\nocean stratification (some references are given above) and interbasin linkages, to provide a more\ncomprehensive and accurate picture of AMOC variability across past, present, and future climate\nstates.\nResponse:\nWe have revised our discussion following the referee’s comment. Please refer to the text in\nthe revised manuscript.\nReviewer #3\n1) Lines 140-156: It is difficult to say if there an improvement in North Atlantic biases. This\nis because the middle row panels and bottom row panels in Figure 4 seem very similar. There are\nsome differences in SST in Figure 4b and 4c, as negative SST extend further south in 4c.\nDo authors claim an improvement because of a more similar SST pattern in 4c with respect to 4a\n(between 40N-60N and 35W-5W)? I assume MARGO SSTs have significant uncertainties\nassociated with reconstructions. Given these limitations, how robust these comparisons and\ninterpretations are, in terms of North Atlantic climate improvement?\nResponse:\nFigure 4 is revised to highlight the glacial changes in the surface climate over the eastern\nNorth Atlantic (40N-60N and 35W-5W). The improvement in the simulated SST in the salinity\nrestoring experiments manifests itself as larger southward extension of the cooling over the eastern\nNorth Atlantic. The root-mean-square-error (RMSE) averaged over the eastern North Atlantic\nreduces from 5.32 ºC to 3.87 ºC in the salinity restoring experiments. The relative decrease in\nRMSE amounts to 27%. Going along with the enhanced surface cooling, sea ice extends eastwards,\nwhich weakens the surface heat flux and hence reduces the MLD in the restoring experiments.\nTherefore, we conclude that there is significant improvement in the simulated North Atlantic\nclimate.\nFigure 4. (a) Reconstructed January-February-March (JFM) mean differences in the sea surface temperature\n(SST"}, {"round": 2, "reviewer_comments": {"reviewer_1": "Review of NCOMMS-24-64658\nSouthern Ocean influence on Atlantic Meridional Overturning Circulation across Climate States\nby Zhaoyang Song et al.\nOverall Assesment:\nThe PMIP models are well-organized, and the contributions of each AMOC pathway are presented. The analysis\ndemonstrates a strong relationship between AMOC strength and the contributions from the Atlantic and Indo-Pacific diffusive\npathways. The decomposition method follows Baker et al. (2023), which is understandable, and its explanation is properly\nprovided.\nHowever, it remains unclear why the magnitudes of these pathways differ across models and whether there is a connection\nbetween the differences in NADW and AABW potential density shown in Figures 1 and 2 and the strength of each pathway.\nThis point should be addressed in future revisions.\nThe conclusion states that combining observationally based reanalysis datasets and constraints from climate models\nreveals a stronger AMOC during the glacial period compared to the pre-industrial state. However, the methodology used to\nderive this estimate is barely explained, making it difficult to understand the logic behind this conclusion. Given this lack of\nclarity, the study does not yet meet the standards for publication in Nature Communications and requires substantial\nrevisions in the future.\nSpecific comments:\nIn the Response letter: \"The enhanced stratification substantially constrains the Indian Ocean inflow to the Atlantic and\nhence the Indo-Pacific diffusive pathway. The AMOC under global warming is thus dominated by the Indo-Pacific diffusive\npathway, which overwhelms the compensation from the Southern Ocean pathway. \"\nI find the logical connection between these two sentences somewhat unclear. The first sentence suggests that enhanced\nstratification constrains the Indo-Pacific diffusive pathway, implying a weakening of this pathway. However, the second\nsentence states that the AMOC under global warming is dominated by the Indo-Pacific diffusive pathway, which seems to\ncontradict the earlier statement. Could you clarify whether the Indo-Pacific diffusive pathway is being weakened or if it\nremains dominant despite the constraint?\nL133: \"We correct the σ2 bias in the deep Southern Ocean by relaxing the KCM’s salinity below 3250 m south of 60oS\ntowards the palaeoceanographic salinity reconstructions (Methods).\"\nIn salinity-restoring experiments, it has been shown that increasing salinity relaxation in the deep Southern Ocean results in\na weaker and shallower LGM AMOC. This approach has already been tested in Kobayashi et al. (2015) to explain the\nglacial salinity distribution proposed by Adkins et al. (2002), and should therefore be appropriately cited. Additionally, while\nthe Methods section describes the procedure, it remains unclear on what basis the spatial distribution of the sponge\nregion and relaxation timescale has been determined.\nAdditionally, in addition to deep-water temperature and salinity, comparisons between proxies and models can also be\nmade for SST and sea ice distribution. This would help support how well each experiment represents the actual LGM\nconditions.\nL224: \"Since the glacial AMOC strength in the models exhibits a dependence on the pre-industrial Southern Ocean wind-\ndriven as well as Indo-Pacific diffusive pathway, we use this dependence, as represented by linear regression, to estimate\nthe glacial AMOC strength (green lines in Figure 5a, b).\"\nIt is unclear why this relationship, derived from pre-industrial conditions, can be directly extended to the glacial period. Are\nthere assumptions or justifications that support the applicability of this dependence under glacial conditions?\nClarifying this point would strengthen the argument.\nFigure 4: The authors describe the LGM changes in SST, SIC, and MLD, but how about also showing the actual values?\nAdditionally, as mentioned earlier, comparisons between these LGM reconstructions and the model should be possible.\nReferences:\nAdkins, Jess F. et al. (2002). The Salinity, Temperature, and δ18O of the Glacial Deep Ocean. Science 298,1769-1773.\nBaker, J. A., Bell, M. J., Jackson, L. C., Renshaw, R., Vallis, G. K., Watson, A. J., & Wood, R. A. (2023). Overturning\npathways control AMOC weakening in CMIP6 models. Geophysical Research Letters, 50, e2023GL103381.\nKobayashi, H., Abe-Ouchi, A., & Oka, A. (2015). Role of Southern Ocean stratification in glacial atmospheric CO2 reduction\nevaluated by a three-dimensional ocean general circulation model, Paleoceanography, 30(9), 1202-1216.", "reviewer_3": "Authors have addressed comments in my review and revised the manuscript accordingly. I recommend this manuscript for\npublication after minor revisions.\nThere are some minor points that I would like to stress upon (line numbers from revised manuscript with track-changes).\n1. I appreciate that authors have added detailed descriptions of datasets in methods section. In line 159, It would be\nworthwhile to clearly mention that MARGO is proxy-based estimates. It would help readers who are not familiar with this\ndataset. Something like \"SST during the LGM from MARGO, which is proxy-based construction of glacial ocean conditions,\ndepicts a cooling ...\" would suffice.\n2. Line 186-190: I did not understand what kind of functional form is considered in y = f(x) + c and how is it related to\ncorrelation analyses discussed later in this section. Could you add more information on this functional relationship and its\nimportance for the analysis in the manuscript?\n2. Line 17: Typo in the sentence."}, "author_response": "Authors’ Response to the Referees’ Comments (Round 2)\nJournal: Nature Communications\nTitle of Paper: Southern Ocean influence on Atlantic Meridional Overturning Circulation\nacross climate states\nAuthors: Zhaoyang Song, Mojib Latif, Wonsun Park, Yuming Zhang\nWe appreciate the time and effort by the referees and the editor in reviewing and handling\nour manuscript for a second round. We have addressed all suggestions proposed and questions\nraised by the referees. Please see our detailed response to the referees’ comments below.\nReviewer #1\nOverall Assessment:\nThe PMIP models are well-organized, and the contributions of each AMOC pathway are\npresented. The analysis demonstrates a strong relationship between AMOC strength and the\ncontributions from the Atlantic and Indo-Pacific diffusive pathways. The decomposition method\nfollows Baker et al. (2023), which is understandable, and its explanation is properly provided.\nHowever, it remains unclear why the magnitudes of these pathways differ across models\nand whether there is a connection between the differences in NADW and AABW potential density\nshown in Figures 1 and 2 and the strength of each pathway. This point should be addressed in\nfuture revisions.\nResponse:\nThis point is well taken. The comment helps to establish the connection among the\noverturning pathways, the AMOC and the potential density of deep waters.\nAs suggested, relationships of the overturning pathways with the potential density of the\nNADW, the AABW, and with the density contrast between the NADW and AABW are examined\n(Figure R1-R4).\nThe Southern Ocean wind-driven pathway (SO_Wind ) is positively correlated with the\ntotal\npotential density contrast between the NADW and AABW in the LGM simulations with the KCM\nand PMIP models (Figure R1). The correlation coefficient amounts to 0.62, which is significant at\nthe 95% confidence level against the Pearson correlation coefficient (Figure R1c). Consistent with\nthe LGM simulations, the potential density contrast between the NADW and AABW also\ndetermines the magnitude of the Southern Ocean wind-driven pathway under global warming in\nthe CMIP6 simulations, with a correlation of 0.42 that is significant at the 95% confidence level\n(Figure R2).\nThe Indo-Pacific diffusive pathway, however, exhibits no significant dependence on the\npotential density of the NADW and AABW in the LGM simulations with the PMIP models (blue\nlines Figure R3). Salinity-restoring experiments with the KCM suggest that enhanced potential\ndensity in the Atlantic basin tends to weaken the Indo-Pacific pathway (green lines in Figure R3b\nand R3c). In contrast, global warming simulations with the CMIP6 models exhibit a positive\ncorrelation of the Indo-Pacific diffusive pathway with the potential density of the AABW, with a\ncorrelation coefficient of 0.53 that is significant at the 99% confidence level (Figure R4).\nDifferences in the influence of the AABW on the Indo-Pacific diffusive pathway across the glacial\nand warming climate states are likely associated with the boundary conditions, particularly in the\nNorthern Hemisphere.\nIt should be noted that all processes maintaining the stratification in the water column, such\nas surface wind and buoyancy forcing, vertical diffusivity and eddies (e.g., Bellomo et al., 2021;\nReintges et al., 2016; Sun et al., 2020), may influence the overturning pathways. Thus, it would be\nrather difficult to quantify the relative contributions of the different processes across models.\nWe have incorporated the above analyses and discussion in the revised manuscript.\nFigure R1. Modelled relationships of the Southern Ocean wind-driven (SO_Wind ) pathway with (a) the\ntotal\npotential density contrast between the NADW and AABW, with (b) the potential density of the NADW,\nand (c) with the potential density of the AABW in the LGM simulations with the KCM and PMIP models.\nThe blue and green solid (dashed) lines indicate the significant (insignificant) linear regression for the PMIP\nand all models, respectively. The linear correlation coefficient (Corr.) is given at the bottom, with no, one,\ntwo, or three stars indicating an insignificant correlation or a significant correlation at the 90%, 95% or 99%\nconfidence level, respectively.\nFigure R2. As in Figure R1, but for global warming simulations under Shared Socio-economic Pathway\n(SSP) 5-85 with 25 CMIP6 models.\nFigure R3. As in Figure R1, but for the Indo-Pacific diffusive pathway.\nFigure R4. As in Figure R1, but for the Indo-Pacific diffusive pathway in global warming simulations\nunder Shared Socio-economic Pathway (SSP) 5-85 with 25 CMIP6 models.\nThe conclusion states that combining observationally based reanalysis datasets and constraints\nfrom climate models reveals a stronger AMOC during the glacial period compared to the pre-\nindustrial state. However, the methodology used to derive this estimate is barely explained, making\nit difficult to understand the logic behind this conclusion. Given this lack of clarity, the study does\nnot yet meet the standards for publication in Nature Communications and requires substantial\nrevisions in the future.\nResponse:\nThe method used to constrain the changes of the glacial AMOC based on observational\nestimates is similar to the ‘emergent constraints’ approach (Hall et al., 2019). This method assumes\nthat relationships between variables of the present-day and their responses to glacial climate\nconditions are implicit within the model solutions of the partial differential equations governing\nphysical processes and associated parameterization schemes, in spite of differences across climate\nmodels. The relationship between the responses of glacial AMOC (𝑦 ) and the present-day\nconstraint variables (𝑥 ) can be simplified as 𝑦 = 𝑓(𝑥)+ 𝜀 , where 𝜀 represents negligible\ndeviations from the function 𝑓. The dependence relationship f becomes apparent through analysis\nof a diverse model ensemble with various parameterization schemes, such as the PMIP/CMIP\nensemble.\nHere we define the glacial AMOC response (𝑦 ) as the changes of the maximum\nstreamfunction in the North Atlantic (AMOC ) in the LGM relative to the pre-industrial\nmax\nsimulation. Then we derive constraint functions based on two present-day variables (𝑥), which are\nthe Southern Ocean wind-driven (SO_Wind ) and the Indo-Pacific diffusive pathway (IP ).\ntotal diffu\nLinear regression in Figure 6a shows a constraint function between changes in glacial AMOC\nmax\nand the present-day SO_Wind , which can be expressed as 𝑦 = 0.85∗𝑥 −3.31. Substituting\ntotal\nthe estimates for the Southern Ocean wind-driven pathway by GloRan V14 (7.6 Sv) and ECCOv4\n(14 Sv) in the constraint relationship, we obtain positive changes of AMOC amounting to 3.2\nmax\nSv (GloRan V14) and 8.6 Sv (ECCOv4). Both datasets suggest a stronger glacial AMOC.\nSimilarly, regression analysis in Figure 5b shows a constraint relationship between changes\nin glacial AMOC and the present-day IP simplified as 𝑦 = −0.82∗𝑥 +9.13. Estimates for\nmax diffu,\nthe present-day IP by GloRan V14 and ECCOv4 are 8.1 Sv and 0.0 Sv, respectively. Hence,\ndiffu\npositive changes of 2.5 Sv (GloRan V14) and 9.1 Sv (ECCOv4) in glacial AMOC can be\nmax\nobtained by substituting the estimates for IP in the constraint function.\ndiffu\nOverall, the combination of the estimates for the two overturning pathways with the\nconstraint relationships suggests a stronger glacial AMOC relative to the present-day.\nSpecific comments:\n1. In the Response letter: \"The enhanced stratification substantially constrains the Indian Ocean\ninflow to the Atlantic and hence the Indo-Pacific diffusive pathway. The AMOC under global\nwarming is thus dominated by the Indo-Pacific diffusive pathway, which overwhelms the\ncompensation from the Southern Ocean pathway. \"\nI find the logical connection between these two sentences somewhat unclear. The first sentence\nsuggests that enhanced stratification constrains the Indo-Pacific diffusive pathway, implying a\nweakening of this pathway. However, the second sentence states that the AMOC under global\nwarming is dominated by the Indo-Pacific diffusive pathway, which seems to contradict the earlier\nstatement. Could you clarify whether the Indo-Pacific diffusive pathway is being weakened or if it\nremains dominant despite the constraint?\nResponse:\nWe agree that the second sentence is confusing. The second sentence is changed as follows,\n“The weakening AMOC under global warming is thus mainly attributed to the reduced Indo-\nPacific diffusive pathway and compensated by the Southern Ocean pathway.”\n2. L133: \"We correct the σ2 bias in the deep Southern Ocean by relaxing the KCM’s salinity below\n3250 m south of 60oS towards the palaeoceanographic salinity reconstructions (Methods).\"\nIn salinity-restoring experiments, it has been shown that increasing salinity relaxation in the deep\nSouthern Ocean results in a weaker and shallower LGM AMOC. This approach has already been\ntested in Kobayashi et al. (2015) to explain the glacial salinity distribution proposed by Adkins et\nal. (2002), and should therefore be appropriately cited. Additionally, while the Methods section\ndescribes the procedure, it remains unclear on what basis the spatial distribution of the sponge\nregion and relaxation timescale has been determined.\nAdditionally, in addition to deep-water temperature and salinity, comparisons between proxies and\nmodels can also be made for SST and sea ice distribution. This would help support how well each\nexperiment represents the actual LGM conditions.\nResponse:\nThe study by Kobayashi et al. (2015) is referenced.\nWe choose to restore salinity below 3250 m south of 60°S for two reasons. First, the AABW\nis located in this region. Second, this region is selected to ensure numerical stability following the\nsuggestions of our colleagues. Patara and Böning (2014) investigated the influence of abyssal\nocean warming around Antarctica on the AMOC by temperature-relaxation using also the NEMO\nocean model. We adopt their configurations for the sponge area and switch on the default\nsmoothing function provided by the ocean model. The study is referenced in the Methods section.\nA relaxation time 360 days is commonly used. We performed several sensitivity\nexperiments with various relaxation times ranging from 360 days to 30 days. It took a strong\nrestoring to alleviate the large salinity bias in the deep Southern Ocean. We state in the Methods\nsection: “As the KCM features strong mixing due to its coarse horizontal and vertical\nresolution,\na relatively strong restoring has to be applied with a relaxation time set to 60 days.” It is also\nfound from the sensitivity experiments that an even shorter relaxation time may lead to\nmisrepresentations of the AABW cell.\nIt should be noted that the specific configuration for the sponge region and relaxation time\nmay be sensitive to the choice of the ocean model.\nFollowing the referee’s comment, we add one figure that compares the simulated mean\nSST and SIC in the KCM with the reconstructions from the MARGO project in the supplement.\nPlease find details in our response to specific comment #4.\nPatara, L., and C. W. Böning (2014), Abyssal ocean warming around Antarctica strengthens the\nAtlantic overturning circulation, Geophys. Res. Lett., 41, 3972–3978"}, {"round": 3, "reviewer_comments": {"reviewer_1": "Review of NCOMMS-24-64658\nSouthern Ocean influence on Atlantic Meridional Overturning Circulation across Climate States\nby Zhaoyang Song et al.\nOverall Assesment:\nI appreciate the detailed response provided, and I now have a much clearer understanding\nof how the emergent constraint approach was applied in your study, including how present-day\npathway metrics were linked to simulated changes in glacial AMOC strength across the\nPMIP/CMIP ensemble. The explanation of the regression relationships and the use of\nobservational estimates to constrain AMOC changes was particularly helpful in following the\nlogic behind your conclusion.\nHowever, there are still some concerns, and I believe additional revisions are necessary.\nWhile the correlation between the Southern Ocean wind-driven pathway, the Indo-Pacific diffusive\npathway, and AMOC changes is shown, the authors themselves acknowledge that most of these\nmodels contain systematic biases. It seems that the experiments that enhanced salinity\nstratification helped mitigate these biases, but the impact of this on the conclusions presented is\nnot adequately discussed. Applying the emergent constraint results derived from models with\nmultiple biases to reach the conclusion that AMOC strengthens during the glacial period seems\nsomewhat oversimplified.\nI would suggest a deeper discussion of the processes by which LGM stratification alters\nthe wind-driven and Indo-Pacific diffusive pathways. Notably, some model studies comparing with\nactual proxies have supported the idea of a shallower and weaker AMOC, and the potential\ninequality in the results (e.g., Menviel et al., 2017, Muglia et al., 2018, Kobayashi et al., 2021)\nshould be addressed more clearly.\nReferences:\n1. Muglia, J., Skinner, L. C. & Schmittner, A. Weak overturning circulation and high Southern Ocean nutrient utilization\nmaximized glacial ocean carbon. Earth and Planetary Science Letters 496, 47–56 (2018). doi: 10.1016/j.epsl.2018.05.038\n2. Menviel, L. et al. Poorly ventilated deep ocean at the Last Glacial Maximum inferred from carbon isotopes: A data‐model\ncomparison study. Paleoceanography 32, 2–17 (2017). doi: 10.1002/2016PA003024\n3. Kobayashi, H., Oka, A., Yamamoto, A. & Abe-Ouchi, A. Glacial carbon cycle changes by Southern Ocean processes with\nsedimentary amplification. Sci. Adv. 7, (2021). doi: 10.1126/sciadv.abg7723"}, "author_response": "Authors’ Response to the Referee’s Comments (Round 3)\nJournal: Nature Communications\nTitle of Paper: Southern Ocean influence on Atlantic Meridional Overturning Circulation\nacross climate states\nAuthors: Zhaoyang Song, Mojib Latif, Wonsun Park, Yuming Zhang\nWe appreciate the time and effort of the referee and the editor in reviewing and handling\nour manuscript for an additional round. Please see our detailed response to the referee’s comments\nbelow.\nReviewer #1:\nOverall Assessment:\nI appreciate the detailed response provided, and I now have a much clearer understanding\nof how the emergent constraint approach was applied in your study, including how present-day\npathway metrics were linked to simulated changes in glacial AMOC strength across the\nPMIP/CMIP ensemble. The explanation of the regression relationships and the use of\nobservational estimates to constrain AMOC changes was particularly helpful in following the\nlogic behind your conclusion.\nHowever, there are still some concerns, and I believe additional revisions are necessary.\nWhile the correlation between the Southern Ocean wind-driven pathway, the Indo-Pacific diffusive\npathway, and AMOC changes is shown, the authors themselves acknowledge that most of these\nmodels contain systematic biases. It seems that the experiments that enhanced salinity\nstratification helped mitigate these biases, but the impact of this on the conclusions presented is\nnot adequately discussed. Applying the emergent constraint results derived from models with\nmultiple biases to reach the conclusion that AMOC strengthens during the glacial period seems\nsomewhat oversimplified.\nResponse:\nModels with relatively small biases in the AABW properties tend to exhibit a slightly\nstronger or comparable glacial AMOC relative to its present-day magnitude. This statement is\nadded to the discussion as suggested by the Referee.\nWe agree with the referee that the assumption of a linear constraint relationship may cause\nadditional uncertainties for the estimated AMOC strength. Nonlinear dynamics, such as ice-sheet\nretreat and glacial isostatic adjustment, may play a pivotal role in the climate evolution during the\ndeglaciation (Friedrich et al., 2016; Mikolajewicz et al, 2025). Limitations of our approach are\nnow stated in the discussion.\nI would suggest a deeper discussion of the processes by which LGM stratification alters\nthe wind-driven and Indo-Pacific diffusive pathways. Notably, some model studies comparing with\nactual proxies have supported the idea of a shallower and weaker AMOC, and the potential\ninequality in the results (e.g., Menviel et al., 2017, Muglia et al., 2018, Kobayashi et al., 2021)\nshould be addressed more clearly.\nResponse:\nMultiple processes, such as the Southern Ocean surface buoyancy flux, the maximum and\nlatitudinal position of Southern Ocean westerly wind stress, and related Ekman transport, can\ninfluence the Southern Ocean wind-driven pathway in the models (Baker et al., 2025). However,\nthe impact of individual process on the wind-driven pathway may vary across models. The\npotential density of the AABW influences the Indo-Pacific diffusive pathway by modulating the\ninter-basin transport (Ferrari et al., 2017), where parameterized mixing processes and mesoscale\neddies play a role. The discussion is added as suggested by the Referee.\nStudies that showed a shallower and weaker glacial AMOC are now referenced in the text.\nUsing a comprehensive coupled atmosphere-ocean-ice-sheet-solid Earth model, Mikolajewicz et\nal. (2025) managed to simulate stronger, comparable and slightly weaker glacial AMOC relative\nto its present-day intensity in an ensemble of eight simulations. The glacial AMOC is influenced\nby the prescribed model parameters, particularly the vertical background mixing in the ocean. This\nmay account for the large spread of simulated glacial AMOC across studies. The discussion is\nadded to the text."}]

Decision letter