Proxy-based indicators of past climate change show that current global climate models systematically underestimate Holocene-epoch climate variability on centennial to multi-millennial timescales, with the mismatch increasing for longer periods1,2,3,4,5. Proposed explanations for the discrepancy include ocean–atmosphere coupling that is too weak in models6, insufficient energy cascades from smaller to larger spatial and temporal scales7, or that global climate models do not consider slow climate feedbacks related to the carbon cycle or interactions between ice sheets and climate4. Such interactions, however, are known to have strongly affected centennial- to orbital-scale climate variability during past glaciations8,9,10,11, and are likely to be important in future climate change12,13,14. Here we show that fluctuations in Antarctic Ice Sheet discharge caused by relatively small changes in subsurface ocean temperature can amplify multi-centennial climate variability regionally and globally, suggesting that a dynamic Antarctic Ice Sheet may have driven climate fluctuations during the Holocene. We analysed high-temporal-resolution records of iceberg-rafted debris derived from the Antarctic Ice Sheet, and performed both high-spatial-resolution ice-sheet modelling of the Antarctic Ice Sheet and multi-millennial global climate model simulations. Ice-sheet responses to decadal-scale ocean forcing appear to be less important, possibly indicating that the future response of the Antarctic Ice Sheet will be governed more by long-term anthropogenic warming combined with multi-centennial natural variability than by annual or decadal climate oscillations.
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This work was supported by a grant from the National Oceanographic and Atmospheric Administration (award number NA15OAR4310239 to P.B. and A.S.), the Antarctic Glaciology Program of the National Science Foundation (grant number 1043517 to P.U.C.), the Royal Society of New Zealand’s Marsden Fund (grant number VUW1203 to N.R.G.) and the Deutsche Forschungsgemeinschaft (DFG grant number We2039/8-1 to M.E.W.). We thank L. Menviel for providing us with the LOVECLIM-based Southern Ocean subsurface temperature data. Development of PISM is supported by NASA grants NNX13AM16G and NNX13AK27G.
The authors declare no competing financial interests.
Nature thanks P. Valdes and the other anonymous reviewer(s) for their contribution to the peer review of this work.
Extended data figures and tables
Extended Data Figure 1 Simulated sensitivity of major climate variables to specifics of applied AIS discharge forcing.
Comparison of simulated AABW export strength, AMOC strength and Southern Hemisphere (SH) sea-ice area for the experiment in which all AIS discharge is distributed uniformly over the Southern Ocean south of 60° S (FWF-SO), over the Southern Ocean around the WAIS (south of 60° S and between 150° E and 360° E; FWF-WAIS) or to the Southern Ocean south of 60° S, but including the associated total heat flux (FWF-HEAT) in addition to the AIS discharge forcing. For comparison the results are also presented for the control (CTRL) simulation.
Correlations between key variables as a function of lead-lag (years) and smoothing period length (years; running mean). Black lines indicate lead-lag for which optimal correlation is found at the given smoothing period. a, AIS discharge (FWF) is correlated (approximately 0.5) with LOVECLIM-based subsurface temperature forcing (‘Temp’) at very short lags. b, c, f, Strong correlations are found between AIS discharge and AABW (b), AIS discharge and Southern Ocean surface temperatures (‘SOsurf’; c) and between AABW and AMOC changes (f). d, e, Weakly correlated are Southern Ocean surface and subsurface temperature (‘SOsubsurf’; d), and subsurface temperature forcing (‘Temp’) and the resulting subsurface temperature (e), pointing towards nonlinearities in the involved feedback loops. Note that the correlations between FWF and AABW and between AABW and AMOC are positive because a strengthening of AABW means more negative values.
Temperature anomalies (colour scale) and meridional streamfunction anomalies (contours, in units of Sv) for periods of weak AABW export. a, Southern Ocean; b, Atlantic Ocean; c, Pacific and Indian Oceans. Values for periods of strong AABW are nearly identical albeit with reversed signs. Depicted values are averages over all three experiments. See Methods for definition of the AABW periods.
Extended Data Figure 4 Sensitivity of simulated climate variability to the magnitude of imposed AIS discharge variations.
For different AIS discharge variability forcings (2σ) the resulting variability is presented for: a, AABW export strength; b, AMOC strength; c, Northern Hemisphere surface-air temperatures (‘NH SAT’); and d, Southern Hemisphere surface-air temperatures (‘SH SAT’). Linear regressions are provided (green lines) together with value of the slope and goodness-of-fit (R2). The red crosses give the results for the reference FWF-SO simulation.
Extended Data Figure 5 Simulated Holocene Southern Ocean subsurface temperature variability in the LOVECLIM-based forcing and the Trace21k simulation.
a, b, LOVECLIM and Trace21k (CCSM3) Southern Ocean subsurface temperature anomalies as time series (a) and in frequency space (b). Trace21k results are only given for the part of the simulation referring to 4.5 kyr ago to the present, in order to avoid any impact by remnants of Northern Hemisphere deglaciation.
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Bakker, P., Clark, P., Golledge, N. et al. Centennial-scale Holocene climate variations amplified by Antarctic Ice Sheet discharge. Nature 541, 72–76 (2017). https://doi.org/10.1038/nature20582
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