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Abyssal ocean overturning slowdown and warming driven by Antarctic meltwater


The abyssal ocean circulation is a key component of the global meridional overturning circulation, cycling heat, carbon, oxygen and nutrients throughout the world ocean1,2. The strongest historical trend observed in the abyssal ocean is warming at high southern latitudes2,3,4, yet it is unclear what processes have driven this warming, and whether this warming is linked to a slowdown in the ocean’s overturning circulation. Furthermore, attributing change to specific drivers is difficult owing to limited measurements, and because coupled climate models exhibit biases in the region5,6,7. In addition, future change remains uncertain, with the latest coordinated climate model projections not accounting for dynamic ice-sheet melt. Here we use a transient forced high-resolution coupled ocean–sea-ice model to show that under a high-emissions scenario, abyssal warming is set to accelerate over the next 30 years. We find that meltwater input around Antarctica drives a contraction of Antarctic Bottom Water (AABW), opening a pathway that allows warm Circumpolar Deep Water greater access to the continental shelf. The reduction in AABW formation results in warming and ageing of the abyssal ocean, consistent with recent measurements. In contrast, projected wind and thermal forcing has little impact on the properties, age and volume of AABW. These results highlight the critical importance of Antarctic meltwater in setting the abyssal ocean overturning, with implications for global ocean biogeochemistry and climate that could last for centuries.

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Fig. 1: Recent and projected bottom water property changes from the main perturbation run.
Fig. 2: Recent and projected abyssal warming trends from the main perturbation run.
Fig. 3: Projected global overturning circulation changes out to 2050.
Fig. 4: Projected Southern Ocean water-mass changes in 2041–2050.
Fig. 5: Schematic showing mechanisms for reduced abyssal ventilation in 2050.

Data availability

The ACCESS-OM2-01 model simulation output is stored on the Consortium for Ocean–Sea Ice Modeling in Australia (COSIMA) data collection website at The JRA55-do v1.3 data used to force the model simulations were obtained for the period 1991–2019 at The CMIP6 data used to force the model simulations were obtained for the period 2020–2050 from the pangeo CMIP6 gallery at The specific additions for generating the model configurations used here can be provided upon request. The ACCESS-ESM1.5 model simulation output from ref. 25 was provided by A. Purich, and the datasets analysed in this study are publicly available in netCDF format at The observed sea-ice-extent data were retrieved from the National Snow and Ice Data Center (NSIDC) for the period 2001–2021 at

Code availability

Model components are all open source. ACCESS-OM2 is available at The Jupyter notebooks used for the analyses described in this study are available in the GitHub repository at


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We thank members of the wider COSIMA community for collaborating with us to develop the ACCESS-OM2 model, and GFDL for providing the original MOM5 configuration on which the ACCESS-OM2 model is based; A. Purich for providing the processed CMIP6 data used to plot Extended Data Figs. 2a,c and 5a and the ACCESS-ESM1.5 model simulation output used to plot Extended Data Figs. 4 and 5b; and R. Holmes for suggesting the application of specific humidity anomalies in the perturbation simulations. This research was undertaken on the National Computational Infrastructure (NCI) in Canberra, Australia, which is supported by the Australian Government. M.H.E. and A.K.M. are supported by the ARC Australian Centre for Excellence in Antarctic Science (ACEAS; ARC Grant No. SR200100008). Q.L. is supported by the NASA MAP programme 19-MAP19-0011 and the MIT-GISS cooperative agreement. M.H.E., A.M.H. and A.K.M. were also supported by Australian Research Council (ARC) Discovery Project DP190100494, and A.K.M. by ARC DECRA Fellowship DE170100184.

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Authors and Affiliations



M.H.E. conceived the study and along with A.M.H. and Q.L. designed the model experiments. Q.L. undertook the model simulations and produced the analyses with input from all authors. M.H.E. and Q.L. led the revisions of the original submitted manuscript. All authors contributed to the development of ideas, analysis, writing and refinement of the paper.

Corresponding author

Correspondence to Matthew H. England.

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Extended data figures and tables

Extended Data Fig. 1 Observed and modelled abyssal ocean temperature and salinity.

Bottom a) temperature (°C) and c) salinity (psu) from the observational climatological mean on the continental shelf over 1975–2012 based on ref. 72 and in the abyss over 1955–2017 based on the World Ocean Atlas 201873) and the equivalent b) temperature (°C) and d) salinity (psu) values in the ACCESS-OM2-01 control run after a 200 year spin-up. All temperatures and salinities shown correspond to the bottom-most value in both observations and the model. Grey contours represent the 4000 m isobath, and the black line denotes the 1000 m isobath around the Antarctic margin.

Extended Data Fig. 2 Model abyssal ocean temperature and salinity evaluation.

Model bottom a, c) temperature (°C) and b, d) salinity (psu) biases relative to observations in the multi-model ensemble mean of CMIP6 models5 during the historical period 1975–2012 and from the baseline ACCESS-OM2-01 control run, respectively. Grey contours represent the 4000 m isobath, and the black line denotes the 1000 m isobath around the Antarctic margin. Note that individual CMIP6 model biases in abyssal temperature and salinity are generally much larger than the biases seen in the multi-model mean5.

Extended Data Fig. 3 Model forcing fields for wind, thermal and meltwater perturbations.

Hovmöller diagram of zonal-mean a) 10-m zonal wind velocity anomaly (m s−1), b) 2-m air temperature anomaly (°C) and c) surface downwelling longwave radiation anomaly (W m−2), from observation-based JRA55-do v1.3 for the historical period 1991–2019 and CMIP6 for the future period 2020–2050 (Methods). These required forcing fields for our simulations were derived using the multi-model mean of all 25 CMIP6 models available at the time of setting up the experiments (listed in the inset box). Sea surface salinity anomaly (psu) during 2041–2050 from the [wind+thermal+meltwater] experiment relative to the control run, around d) Antarctica and e) Greenland, respectively. f) Time series of annual-mean globally integrated Ocean Heat Content (OHC) relative to 2001 (ZJ = 1021 J) from the control run (grey line), the [wind+thermal] run (orange line) and the [wind+thermal+meltwater] run (blue line), respectively.

Extended Data Fig. 4 Meltwater-driven air-sea feedback evaluation.

Hovmöller diagrams of zonal-mean surface forcing, shown as total (left panel) and estimated meltwater feedback (middle panel) for a,b) zonal wind velocity (m s−1), d,e) meridional wind velocity (m s−1), g,h) net air-sea heat flux (W m−2) and j,k) net freshwater flux (kg m−2 s−1) during 2001–2050 from the fully coupled ACCESS-ESM1.5 run with added meltwater. The meltwater feedback is estimated from the difference between fully coupled model runs with and without meltwater, based on simulations run under historical and SSP5-8.5 forcing. To match the meltwater amount we apply, the coupled model output from ref. 25 is weighted by 85% (as detailed in Methods). The total field is the sum of that simulated in the run under historical and SSP5-8.5 forcing, plus the weighted anomaly driven by the meltwater component. The far right hand panels show the 2041–2050-mean anomaly of c) zonal wind velocity (m s−1), f) meridional wind velocity (m s−1), i) net air-sea heat flux (W m−2) and l) net freshwater flux (kg m−2 s−1) driven by the meltwater component (blue lines) vs. anomalies due to climate change forcing without meltwater (orange lines), calculated relative to the 2001–2010-mean. The net heat flux comprises the sum of shortwave radiation, longwave radiation, latent and sensible heat fluxes. The net freshwater flux comprises precipitation, evaporation and run-off (including extra meltwater input where applied; i.e., in panel (l)). Heat and freshwater fluxes are defined positive from the atmosphere into the ocean. Zonal means are calculated over ocean grid boxes only (i.e. not over land).

Extended Data Fig. 5 Model Antarctic sea-ice extent evaluation.

a) Time series of annual-mean sea-ice extent (million km2) from observations70 (black line with hollow circles), the [wind+thermal+meltwater] run (black line) during 2001–2021, the [wind+thermal] run (orange line), and the CMIP6 model simulations24 under historical and SSP5-8.5 forcing (thin blue lines) during 2001–2050. The sea-ice extent is defined as the area covered by ice with a concentration of at least 15%. The thick blue line is the CMIP6 multi-model mean. The decline rate of sea-ice extent from the [wind+thermal] run (−0.53 million km2 per decade; orange line) lies within the range of CMIP6 models (−0.34 ± 0.2 million km2 per decade). b) Time series of the response in annual-mean sea-ice extent (million km2) to an equivalent meltwater anomaly in the [wind+thermal+meltwater] run (violet line), and from the fully coupled ACCESS-ESM1.5 run during 2001–2050, shown as an ensemble mean (thick grey line) and as individual members (thin grey lines).

Extended Data Fig. 6 Control and projected Dense Shelf Water formation changes in 2050.

a) Surface water-mass transformation (on the continental shelf; 10−5 m s−1) and bathymetry (in the abyss; km) from the control run. Surface water-mass transformation integrated over the Antarctic continental shelf area (poleward of the 1000 m isobath; Sv) for the net, salt and heat components b) in climatology from the control run and c,d,e) in 2050 from the control run, the [wind+thermal] run and the [wind+thermal+meltwater] run. Dashed line in b,c,d,e) denotes the 32.57 kg m−3 isopycnal (referenced to 1000 m), across which the most significant reduction in water-mass transformation in 2050 for the [wind+thermal+meltwater] run is evident. The surface water-mass transformation rate in a) is also computed across this potential density layer.

Extended Data Fig. 7 Recent and projected bottom water property changes due to the meltwater anomalies.

ac) Surface water-mass transformation (on the continental shelf; 10−5 m s−1) and bottom seawater age anomaly (in the abyss; years), df) bottom salinity anomaly (psu) and gi) bottom temperature anomaly (°C) from the meltwater component during the decades 2001–2010, 2021–2030 and 2041–2050, respectively, relative to the control run. Grey contours represent the 4000 m isobath, and the black line denotes the 1000 m isobath around the Antarctic margin. The surface water-mass transformation rate is computed across the 32.57 kg m−3 isopycnal (referenced to 1000 m), across which the SWMT shows the most significant reduction.

Extended Data Fig. 8 Recent and projected abyssal warming trends from the [wind+thermal] run and the estimated meltwater component.

Warming is shown as the heat flux anomaly (W m−2) across 4000 m implied by the warming below 4000 m during the period a,b) 1991–2010, c,d) 1991–2030 and e,f) 1991–2050 from the [wind+thermal] run and the meltwater component, respectively. Grey contours represent the 4000 m isobath. The four arrow tail symbols along the coast of Antarctica denote the key locations of DSW and AABW formation.

Extended Data Fig. 9 Recent and projected abyssal freshening.

Freshwater flux anomaly (cm yr−1) across 4000 m during the period a,d,g) 1991–2010, b,e,h) 1991–2030 and c,f,i) 1991–2050 from the [wind+thermal+meltwater] run, the [wind+thermal] run and the estimated meltwater component, respectively. Grey contours represent the 4000 m isobath. The Australian–Antarctic basin (AAB), Weddell–Enderby basin (WEB) and Amundsen–Bellingshausen basin (ABB) are indicated in a).

Extended Data Fig. 10 Recent and projected sea-ice changes.

Sea-ice concentration anomaly (%) during the decade a,d,g) 2001–2010, b,e,h) 2021–2030 and c,f,i) 2041–2050 from the [wind+thermal+meltwater] run, the [wind+thermal] run and the estimated meltwater component, respectively. Positive and negative values indicate sea-ice growth and decline, respectively.

Extended Data Fig. 11 Projected global seawater age changes during 2041–2050.

Vertical cross-sections of zonal-mean a) climatological mean seawater age (years) from the control run, and b,c,d) seawater age anomaly (years) during 2041–2050 from the [wind+thermal+meltwater] run, the [wind+thermal] run and the estimated meltwater component, respectively. Contours represent the climatological mean seawater age with an interval of 15 years.

Extended Data Fig. 12 Projected Southern Ocean water-mass properties in 2041–2050.

Vertical cross-sections of zonal-mean ad) potential density (kg m−3), eh) salinity (psu), i-l) temperature (°C) and m-p) seawater age (years) during 2041–2050 from the control run, the [wind+thermal+meltwater] run, the [wind+thermal] run and the estimated meltwater component, respectively. The far right hand panels show the sum of the mean properties from the control run and the estimated meltwater contribution. Contours show the corresponding potential density (referenced to 2000 m) during 2041–2050, ranging from 36.91 kg m−3 to 37.18 kg m−3 with an interval of 0.03 kg m−3. Latitude is shown relative to the 1000 m isobath.

Extended Data Fig. 13 Decomposition of projected meltwater-driven water-mass changes during 2041–2050.

Vertical cross-sections of zonal-mean ac) salinity anomaly (psu), df) temperature anomaly (°C) and gi) seawater age anomaly (years) during 2041–2050 estimated for the meltwater component of the total change, heave component and residual component due to water-mass transformation (i.e. once heave is removed), respectively (Methods). Contours show the corresponding potential density (referenced to 2000 m) during 2041–2050, ranging from 36.91 kg m−3 to 37.18 kg m−3 with an interval of 0.03 kg m−3. Latitude is shown relative to the 1000 m isobath. Stippling indicates missing values due to transforming the vertical coordinates between depth and density values.

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Li, Q., England, M.H., Hogg, A.M. et al. Abyssal ocean overturning slowdown and warming driven by Antarctic meltwater. Nature 615, 841–847 (2023).

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