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Ice front blocking of ocean heat transport to an Antarctic ice shelf


Mass loss from the Antarctic Ice Sheet to the ocean has increased in recent decades, largely because the thinning of its floating ice shelves has allowed the outflow of grounded ice to accelerate1,2. Enhanced basal melting of the ice shelves is thought to be the ultimate driver of change2,3, motivating a recent focus on the processes that control ocean heat transport onto and across the seabed of the Antarctic continental shelf towards the ice4,5,6. However, the shoreward heat flux typically far exceeds that required to match observed melt rates2,7,8, suggesting that other critical controls exist. Here we show that the depth-independent (barotropic) component of the heat flow towards an ice shelf is blocked by the marked step shape of the ice front, and that only the depth-varying (baroclinic) component, which is typically much smaller, can enter the sub-ice cavity. Our results arise from direct observations of the Getz Ice Shelf system and laboratory experiments on a rotating platform. A similar blocking of the barotropic component may occur in other areas with comparable ice–bathymetry configurations, which may explain why changes in the density structure of the water column have been found to be a better indicator of basal melt rate variability than the heat transported onto the continental shelf9. Representing the step topography of the ice front accurately in models is thus important for simulating ocean heat fluxes and induced melt rates.

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Fig. 1: Blocking of topographically steered current at the Getz Ice Shelf front.
Fig. 2: The baroclinic velocity component at GW2 is similar to the total velocity at GW3.
Fig. 3: Experimental set-up and difference between barotropic and baroclinic flow.
Fig. 4: Blocking of depth-independent currents in laboratory.

Data availability

The mooring data analysed during the current study (raw data for Figs. 1, 2 and Extended Data Figs. 16) are available at the Norwegian Marine Data Centre (, GW1, 2)40 and at the SOOS database at NODC ( and, GW3). Raw data obtained from the PIV calculations (raw data for Fig. 4 and Extended Data Fig. 9) are available at Zenodo (

Code availability

The PIV calculations were conducted with the matlab software UVMAT developed at LEGI available at Independent results were also obtained with the MatPIV package available at


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Our experiments were supported by the European Union’s H2020 programme through the grant to Hydralab-plus, contract number 654110. We gratefully acknowledge grant support for the authors as follows: E.D. and N.S. from the Norwegian Research Council through grants 267660 (TOBACO) and 231549 (WARM); A.J. from the UK Natural Environment Research Council through grant number NE/L013770/1 (FISS); A.K.W. from the Swedish Research Council and the Swedish Foundation for Strategic Research through the Swedish Maritime Robotics Center (SMaRC); T.W.K. from the Korea Polar Research Institute, grant KOPRI PE19060; and L.H.B. from the H2020 grant number 661015 and the Centre for Southern Hemisphere Oceans Research. We thank I. Fer for lending instrumentation for GW1 and GW2.

Author information




A.K.W. proposed the research. A.K.W., N.S., E.D. and K.M.A. wrote the first draft. J.S. assisted with analyses and a repository of laboratory data. All authors contributed to the laboratory experiments, to data processing, and/or to the field work. A.K.W., N.S., S.V. and A.K.M. prepared the figures. All authors read and commented on the text.

Corresponding author

Correspondence to A. K. Wåhlin.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature thanks Ala Khazendar, Veronica Tamsitt and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Two year time series of velocity and temperature from the GW1 mooring.

ac, Time series of eastward velocity (a; in m s−1), northward velocity (b; in m s−1) and temperature (c; in °C) for the GW1 mooring. Black lines in c indicate positions of Microcats (instruments that measure temperature and salinity; thick lines) and SBE56 (instruments that measure temperature; thin lines).

Extended Data Fig. 2 Two year time series of velocity and temperature from the GW2 mooring.

ac, Time series of eastward velocity (a; in m s−1), northward velocity (b; in m s−1) and temperature (c; in °C) for the GW2 mooring. Black lines in c indicate positions of Microcats (thick lines) and SBE56 (thin lines).

Extended Data Fig. 3 Two year time series of velocity and temperature from the GW3 mooring.

ac, Time series of eastward velocity (a; in m s−1), northward velocity (b; in m s−1) and temperature (c; in °C) for the GW3 mooring. Black lines in c indicate positions of Microcats (thick lines) and SBE56 (thin lines).

Extended Data Fig. 4 Comparison of methods for calculating the barotropic current component.

ac, Each panel shows the along-slope barotropic current component calculated in three ways (see Methods): blue curve, option (i), using the vertical average; red curve, option (ii), using the vertical average of the water more than 150 m above the seabed; and orange curve, option (iii), using the vertical average of water above the −0.5 °C isotherm. Three-day-averaged results are shown for mooring GW1 (a), mooring GW2 (b) and mooring GW3 (c).

Extended Data Fig. 5 The barotropic velocity is larger for GW1 and GW2 than GW3, the baroclinic velocity and the temperature increase towards the bottom.

a, Thick lines show average along-slope velocities as a function of distance above bottom, with colours indicating mooring (see key). Thin vertical lines show the barotropic components estimated according to method (i) (dotted lines), method (ii) (dashed lines), and method (iii) (solid lines). b, Baroclinic velocity components as a function of distance above bottom. c, Average temperature as a function of distance above bottom.

Extended Data Fig. 6 The barotropic heat flux component is larger than the baroclinic component for GW1 and GW2.

ac, Each panel shows the time series of total heat flux (blue curve) and the barotropic and baroclinic components (respectively, red and orange curves) using equation (2) and definition (ii) of barotropic velocity, as described in Methods. a, Mooring GW1; b, mooring GW2; and c, mooring GW3.

Extended Data Fig. 7 Experiment set-up and dimensions.

a, Top view drawing of V-shaped channel (blue), ice shelf (white), camera views (PCO1, green; PCO2, orange) and the source (to scale). b, Side view drawing looking into the ice shelf facing south (right side in a). c, Side view drawing looking east (top of a). df, Top views of topography (grey scale bar indicates depth (in metres)) and water column thickness (coloured lines, labels, in metres) for ice shelf draughts of 0 cm (d), 30 cm, tilted (e), and 30 cm, horizontal (f).

Extended Data Fig. 8 Photographs of the experiments.

a, Top view showing the experimental set-up with the horizontal and vertical laser sheets. b, Technicians and students preparing for an experiment. c, Time series showing the ice shelf cavity filling up with dense water for the baroclinic experiments. d, Top view photograph showing a barotropic current moving towards the ice shelf. See Methods for details.

Extended Data Fig. 9 No blocking of depth-varying currents in laboratory.

ai, Horizontal velocities from the laboratory experiments for baroclinic flow with the three different ice shelf configurations (Fig. 3b–d). Colours indicate velocity in the y direction, arrows indicate velocity vectors. ac, Velocities at the horizontal plane in the centre of the current (black lines in di). df, Velocities at vertical sections underneath the ice shelf (green lines in ac) and gi in front of it (magenta lines in ac). Dashed and shadowed rectangles indicate the ice shelf, grey shading indicates topography and grey lines are bathymetric lines that the current is expected to follow. White areas are not-measured or missing data. The cyan bar beneath the scale arrow in ac indicate the temporal standard deviation of the velocity, and the magenta bar indicates the error (Methods).

Extended Data Table 1 Barotropic heat transport component is large compared to baroclinic
Extended Data Table 2 Non-dimensional scales are similar in laboratory experiments and observations

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Wåhlin, A.K., Steiger, N., Darelius, E. et al. Ice front blocking of ocean heat transport to an Antarctic ice shelf. Nature 578, 568–571 (2020).

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