The Southern Ocean (>30° S) has taken up a large amount of anthropogenic heat north of the Subantarctic Front (SAF) of the Antarctic Circumpolar Current (ACC). Poor sampling before the 1990s and decadal variability have heretofore masked the ocean’s dynamic response to this warming. Here we use the lengthening satellite altimetry and Argo float records to show robust acceleration of zonally averaged Southern Ocean zonal flow at 48° S–58° S. This acceleration is reproduced in a hierarchy of climate models, including an ocean-eddy-resolving model. Anthropogenic ocean warming is the dominant driver, as large (small) heat gain in the downwelling (upwelling) regime north (south) of the SAF causes zonal acceleration on the northern flank of the ACC and adjacent subtropics due to increased baroclinicity; strengthened wind stress is of secondary importance. In Drake Passage, little warming occurs and the SAF velocity remains largely unchanged. Continued ocean warming could further accelerate Southern Ocean zonal flow.
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Argo data are available at: http://www.argo.ucsd.edu. IAP data are available at: https://climatedataguide.ucar.edu/climate-data/ocean-temperature-analysis-and-heat-content-estimate-institute-atmospheric-physics. EN4 data are available at: https://www.metoffice.gov.uk/hadobs/en4/. WOA18 data are available at: https://www.nodc.noaa.gov/OC5/woa18/. Satellite altimetry data are available at: https://www.aviso.altimetry.fr/en/data.html. The CMIP6, CanESM5 large ensemble, CESM1-HR and CESM1-SR data are available on the Program for Climate Model Diagnostics and Intercomparison’s Earth System Grid (https://esgf-node.llnl.gov/search/cmip6/). The CESM LENS simulations are available on the Earth System Grid (www.earthsystemgrid.org). The CESM and MITgcm model data used in this study are available from the corresponding author upon request.
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We thank S. T. Gille, S. Sun and Y. Lu for enlightening discussions. J.-R.S. is supported by the US National Science Foundation (AGS-1637450) and the Southern Ocean Carbon and Climate Observations and Modeling project under National Science Foundation Award PLR-1425989. L.D.T. is also supported by the Southern Ocean Carbon and Climate Observations and Modeling project. Q.P. is supported by the National Natural Science Foundation of China (42005035). W.L. is supported by the Regents’ Faculty Fellowship, Alfred P. Sloan Foundation Research Fellowship and US National Science Foundation (OCE-2123422).
The authors declare no competing interests.
Peer review information Nature Climate Change thanks Andrew Hogg and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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(a) Ug from AVISO, same with Fig. 1c. (b) Zonal absolute geostrophic velocity (Ug) trend applying the surface AVISO-based Ug in (a) as a reference velocity. Gray contours are climatological absolute Ug, with solid contours representing eastward flow and dashed contours representing westward flow.
Extended Data Fig. 2 Zonal mean patterns of potential temperature trend/change from observations and models.
Potential temperature trend from 1979 to 2019 from (a) IAP (observations), (b) CMIP6 MMM, (c) CESM1-SR, and (d) CESM1-HR. (e) Zonal mean potential temperature change from the CESM1_∆Buoy experiment relative to the control run. (f) Zonal mean potential temperature change from the MITgcm_∆SST experiment relative to the control run. Green contours are the climatological Ug or U (in cm/s) from the corresponding cases.
(a, b), Time series of upper 100 m zonal velocity averaged between 48˚S-58˚S relative to the average of 1955–2004 from CMIP6 and LENS simulations, respectively. CMIP6 multi-model mean (MMM) is the black curve, with superimposed observation-based products: IAP (brown), EN4 (green), and Argo (red; since 2005). The velocities from observation-based products apply the surface altimetry-based Ug as a reference velocity. (c, d), Same with (a, b), but for the 2,000 m zonal velocity.
(a) Transport changes of zonal mean zonal velocity between 1995–2035 and 1955–1995 from CMIP6 MMM. Total transport change is shown as black curve, upper 2,000 m transport is shown as blue curve, and baroclinic transport with no motion at 2,000 m is shown as red curve. (b) Full-depth zonal velocity change between 1995–2035 and 1955–1995 from CMIP6 MMM. Gray contours are climatological zonal velocity, with solid contours representing eastward flow and dashed contours representing westward flow.
Extended Data Fig. 5 Scatter plot of zonal velocity trend against temperature trend and against wind trend.
(a) Scatter plot of trend (1979–2014) of upper 100 m zonal velocity relative to 2,000 m depth versus trend of temperature difference between 45˚S and 60˚S, along with the linear relationship for the CMIP6 models: BBC-CSM2-MR, BCC-ESM1, CAMS-CSM1-0, CanESM5, CAS-ESM2-0, CESM2, CESM2-FV2, CESM2-WACCM, CESM2-WACCM-FV2, CMCC-CM2-HR4, CMCC-CM2-SR5, EC-Earth3, EC-Earth3-Veg, FGOALS-g3, FIO-ESM-2-0, GFDL-CM4, GISS-E2-1-G, IPSL-CM6A-LR, MCM-UA-1-0, MIROC6, MPI-ESM1-1-2-HAM. MPI-ESM1-2-LR, MRI-ESM2-0, NESM3, SAM0-UNICON, and TaiESM1. Each red triangle indicates the result of each CMIP6 model. The correlation coefficient is 0.71 across models. The black triangle represents the trend from the IAP product. (b) Scatter plot of velocity trend versus SAM. Each blue square indicates the result from each CMIP6 model. The correlation coefficient is 0.16 across models. The black square represents the SAM trend from ERA5 (observations).
(a, c) Zonal mean potential temperature change and (b, d) U change induced by wind stress change (∆Wind) from CESM1_∆Wind (a, b) relative to CESM1_∆Buoy and MITgcm_∆Wind (c, d) relative to MITgcm_CTL (Methods). Gray contours are the climatological zonal velocity U (in m/s) from the corresponding cases. Upper 100 m U change driven by wind stress change from (e) CESM1 and (f) MITgcm. Mean zonal velocities of 6 cm/s and 12 cm/s are shown as thin and thick green contours.
Extended Data Fig. 7 Baroclinic transport change from CMIP6 ensemble mean and the position of mean ‘SAF’.
Upper 2,000 m baroclinic transport change (shadings) between 1998–2018 and 1940–1960 from CMIP6 ensemble mean. Black curve is the mean ‘SAF’ during 1940–1960 and cyan is the mean ‘SAF’ during 1998–2018. Red curve is the 1993–2019 mean ‘SAF’ based on the sea surface height from satellite observations.
Extended Data Fig. 8 Streamwise mean of upper 2,000 m baroclinic transport change and zonal velocity change.
(a) upper 2,000 m baroclinic transport change and (b) zonal geostrophic velocity change between 1998–2018 and 1940–1960 from IAP data. The ‘SAF’ is defined as the observed 1993–2019 mean sea surface height passing through the Drake Passage at the point 67.5˚W, 57.5˚S. (c)-(d), same with (a)-(b), but the simulated velocity/transport change and the ‘SAF’ are based on CMIP6 ensemble mean. Gray curves in (b) and (d) are the streamwise mean climatological zonal velocity.
Extended Data Fig. 9 Zonal velocity, potential density and potential temperature changes from observed datasets.
Upper 100 m zonal geostrophic velocity, Ug, trend (1993–2019) from the IAP, EN4 and change from WOA18 (1985–2017 mean minus 1955–1984 mean) (top row). Corresponding trend/change of upper 2,000 m averaged potential density and potential temperature are shown in middle row and bottom row, respectively. Black contours indicate Subantarctic Front and Southern ACC Front. Stippling indicates regions exceeding 90% statistical significance computed from the two-tailed t-test.
(a) Upper 2,000 m potential temperature trend from Argo observations (2005–2019). Black contours indicate the Subantarctic Front (SAF) and Southern ACC Front (SACCF). (b, c) Upper 2,000 m potential temperature trend from CESM1-SR (b) and CESM1-HR (c). (d, e) Upper 2,000 m potential temperature change from the CESM1_∆Buoy experiment (d) and the MITgcm_∆SST experiment (e) relative to the corresponding control runs. Stippling indicates regions exceeding 90% statistical significance computed from the two-tailed t test.
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Shi, JR., Talley, L.D., Xie, SP. et al. Ocean warming and accelerating Southern Ocean zonal flow. Nat. Clim. Chang. 11, 1090–1097 (2021). https://doi.org/10.1038/s41558-021-01212-5
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