Ice velocity

We used feature tracking of Sentinel-1 radar imagery to generate velocity maps at 6-day intervals for five marine-terminating outlet glaciers on the Antarctic Peninsula (Fig. 1), during the period October 2016 to April 2018 (Methods). Four of the glaciers, Drygalski, Hektoria, Jorum and Crane, are on the eastern side of the Antarctic Peninsula, while Cayley Glacier is on the west side (Fig. 1). For each glacier, velocity was analysed across a series of 1 km square regions of interest (ROIs), extending inland from the glacier’s grounding-line. Glacier-averaged ROI velocities reveal three types of velocity fluctuation. First, large-scale seasonal variations, which decrease in magnitude away from the ocean. Second, background velocity fluctuations of ≈50 m a−1 magnitude. Finally, short-lived rapid accelerations in ice velocity to values >20% greater than the annual mean (Fig. 2a). The latter of these we refer to here as speed-up events and are the focus of this paper. Despite being separated by over 100 km, all five glaciers experienced near-synchronous speed-up events in March 2017, November 2017 and March 2018 (Fig. 2a); for example, velocities averaged across all ROIs on Drygalski Glacier (Fig. 1c) increased by 300 m a−1 (≈23% greater than the annual mean) in November 2017 (Fig. 2a). Larger accelerations were recorded in individual ROIs (Supplementary Figs. 1–4), with a 400 m a−1 (100% greater than the annual mean) speed-up occurring 9 km from the grounding line of Hektoria Glacier during the November 2017 event (Supplementary Fig. 4c). These data indicate that speed-up events were short-lived, typically lasting for 6 days or less. Most of the speed-up events were followed immediately by a slow-down before velocities return to below pre-event values. No significant slow-down events were detected in the absence of a speed-up. Slow-down and speed-up events were similar in duration (≤6 days), but the velocity change associated with the slow-downs was typically smaller (Fig. 2a, c; Supplementary Figs. 1–4). Such speed-up events have not previously been reported from Antarctica.

Fig. 1 Mean ice velocity map and location of studied glaciers. a Mean velocity magnitude across the study area, between October 2016 and mid-April 2018. Inset shows the location on the peninsula, and the black line is the grounding line45. b–f Landsat 8 satellite images of glacier surfaces. The black boxes outline the regions of interest. Note the visible water on the glacier surfaces Full size image

Fig. 2 Velocity and modelled surface melt of studied glaciers. a Velocity variations at multiple glaciers display prominent and coincident speed-ups, defined in the text, indicated by dashed lines, which correspond with spikes in modelled melt b. Modelled melt in b is averaged across all glaciers. c velocity in separate ROIs at Drygalski glacier (Fig. 1). Velocity uncertainties are shown by shaded envelopes around the data. These speed-up events correspond with spikes in modelled melt and observations of surface meltwater across Drygalski glacier in Landsat 8 imagery d Full size image

Marine processes

Two sets of processes could be the cause of speed-up events, either marine processes and/or surface meltwater drainage to the base of the glacier. Marine processes, such as tidal fluctuations18, seasonal sea-ice break-up19 or iceberg calving events20, can all lead to changes in ice buttressing forces. If these processes were the trigger for the observed speed-up events (Fig. 2), we would expect an increase in the relative magnitude of speed-up events closer to the glacier terminus and changes in marine conditions to coincide with speed-up events. At each glacier, many speed-up events became larger compared to the annual mean velocity within ROIs further from the marine margin (Figs. 2c and 3; Supplementary Figs. 1–4). The increase in relative magnitude upglacier was particularly apparent for the November 2017 event (Fig. 3). This is opposite of what would be expected if marine processes were the cause of speed-up events. Analysis of the periodicity of the velocity variations indicates that low magnitude tidal (14-day) and seasonal variations were apparent close to the grounding-line but that they diminished in magnitude inland (Fig. 4). These periodic influences on ice motion contrast with the irregular occurrence of relatively larger glacier speed-up events, which occur beyond the region where a tidal influence on ice motion is apparent (Fig. 4). To further investigate the influence of marine processes on ice velocity, we used satellite imagery to record the calving front position and sea ice/shelf conditions of the studied glaciers (Methods). For all five glaciers, frontal position was remarkably stable during the study period, typically varying by <200 m (Supplementary Figs. 5, 6). The clearest temporal patterns during this time period were the minor advances of Crane and Hektoria glaciers, but no clear pattern between the timing of speed-up events and front position change occurred (Supplementary Figs. 5 and 6). At the southern-most three glaciers (Crane, Jorum and Hektoria), sea ice was present in front of the glaciers for the entirety of the study period, with the sea ice edge in this region remaining over 50 km from the glacier fronts (Supplementary Fig. 7). Given the increase in the relative magnitude of speed-up events away from the marine margin and the lack of synchrony between speed-up events and ice shelf, sea ice or tidal processes, we find it unlikely that any of the investigated marine processes caused the observed velocity fluctuations.

Fig. 3 Relative velocity of studied glaciers during the November 2017 speed-up event. Note how the relative magnitude of the speed-up increases further away from the marine margin. Ice velocity was detrended using a 144-day running mean. Melt rates are mean values for every ROI studied at the respective glacier Full size image

Fig. 4 Periodicity of tides and velocity data. Scalograms (upper) and time series (lower) of tidal a and detrended velocity data b–f of Hektoria Glacier. Scalograms show the strength of signal variability (a strong variability is represented by yellow colours) at each period over time. White line delimits the cone of influence, beyond which edge-effects occur. Note the prominent 14-day periodicity of the tidal model a. This signal is apparent in the velocity data close to the grounding-line b, c, but dissipates further inland e, f, where a more sporadic signal dominates, corresponding to the speed-up events we observe e, f. Note how the relative magnitude of the meltwater-induced speed-up event increases away from the sea up to 8 km before starting to decrease again Full size image

Regional climate modelling

To investigate whether there was a temporal correspondence between surface meltwater generation and the observed speed-up events, we compared our velocity data to surface melt rates from a regional climate model21. The modelled melt season lasted from October to April, and a small Föhn wind-induced melt event was modelled in July 2017, during the austral winter. Multiple large (>3 mm w.e. day−1) but short-lived (<1 week) spikes in melt are modelled, separated by periods of little-to-no melting. The large spikes in melt are coincident with austral summer Föhn events. There is a striking qualitative correspondence between periods of modelled surface melting and speed-up events (Fig. 2), with speed-up events generally occurring during large modelled melt events (e.g., March 2017), or during a less intense melt event preceded by a period of limited or no melt (e.g., November 2017; March 2018). The lowest melt rates were modelled for the western Antarctic Peninsula, where melting is supressed due to high snowfall rates21. Despite this, Cayley Glacier still exhibits several speed-up events coincident with the spikes in modelled surface melting (Supplementary Fig. 3). Speed-up events also occurred during periods when water was visible in satellite imagery of the ice surface (Fig. 2c). The correspondence between large and/or initial melt events and glacier speed-up is consistent with theoretical predictions22 and observations1,9 of ice flow variations induced by surface melt drainage to the bed on the Greenland Ice Sheet and Arctic Glaciers6,23. Subglacial hydraulic efficiency adapts to accommodate meltwater inputs at timescales longer than the melt events22. This means that during periods of rapidly varying meltwater flux, such as large or initial melt events, more water is delivered to the ice-bed interface than can be evacuated by the subglacial system. This leads to a spike in basal water pressure, and an increase in basal sliding, which we suggest causes the observed speed-up events. We also observe that prolonged periods of high volume, but low variability melt did not elicit a large or extended velocity response (Supplementary Figs 1–4). During these periods, the subglacial system is likely to have had time to adapt to steady surface meltwater inputs.

Optical satellite imagery

To help determine whether surface melt reaches the bed of the studied glaciers, we examined the optical satellite image record (Methods). Surface melt features were observed upglacier of the grounding line of each glacier, including small lakes fed by streams and water-filled crevasses (Fig. 5; Supplementary Figs. 8–12). Although lake refreezing was observed to occur in some localities indicating long-term surface storage of water (Fig. 5f), we also recorded multiple occasions where lakes disappeared between satellite images, which we interpret as drainage events. While there is a chance that the lakes could have drained over the ice surface, or into local firn layers, they possessed no apparent outlet stream, coincident waxing and waning of nearby lakes was not observed, and the lake beds following drainage were heavily crevassed (Fig. 5b, c; Supplementary Figs. 5g, 10c, 11e). In these instances, we suggest that lakes drained into the ice, potentially reaching the bed. Abrupt stream terminations (which may either indicate moulins or points where water drains into firn) and meltwater-filled crevasses are additional potential routes for surface meltwater to access the bed. The pressure exerted by water within crevasses can cause hydrofracture24, which creates surface-to-bed hydraulic connections.