Large interannual variability in supraglacial lakes around East Antarctica

Abstract

Antarctic supraglacial lakes (SGLs) have been linked to ice shelf collapse and the subsequent acceleration of inland ice flow, but observations of SGLs remain relatively scarce and their interannual variability is largely unknown. This makes it difficult to assess whether some ice shelves are close to thresholds of stability under climate warming. Here, we present the first observations of SGLs across the entire East Antarctic Ice Sheet over multiple melt seasons (2014-2020). Interannual variability in SGL volume is >200% on some ice shelves, but patterns are highly asynchronous. More extensive, deeper SGLs correlate with higher summer (December-January-February) air temperatures, but comparisons with modelled melt and runoff are complex. However, we find that modelled January melt and the ratio of November firn air content to summer melt are important predictors of SGL volume on some potentially vulnerable ice shelves, suggesting large increases in SGLs should be expected under future atmospheric warming.

Fig. 1. Examples of supraglacial lakes on selected East Antarctic ice shelves and outlet glaciers.

(1) Riiser-Larsen Ice Shelf, (2) Nivlisen Ice Shelf, (3) Roi Baudouin Ice Shelf, (4) Amery Ice Shelf, (5) Polarbroken Glacier/Publications Ice Shelf, (6) Shackleton Ice Shelf, (7) Moscow University Ice Shelf, (8) Nansen Ice Shelf and (9) Koettlitz Glacier. This figure highlights the distribution of SGLs across these major ice shelves but note that lakes occur with less frequency in other regions, for example along the Ingrid Christensen Coast (between Polarbroken Glacier and Shackleton Ice Shelf) and on Voyeykov Ice Shelf (adjacent to Moscow University Ice Shelf). Details of Landsat 8 images are in Supplementary Table 5. Grounding line from ref. and coastline from ref. .

Fig. 2. Interannual changes in supraglacial lake volumes on the East Antarctic Ice Sheet.

a Absolute total SGL volumes (in millions of cubic metres) on the East Antarctic Ice Sheet. b Percentage SGL volume anomalies (i.e. percentages of the mean 2014–2020 maximum total lake volume) on the East Antarctic Ice Sheet. c–j Percentage SGL volume anomalies (i.e. percentages of the mean 2014–2020 maximum total lake volume) on selected major ice shelves and regions. Positive anomalies are shown in red and negative anomalies are shown in blue. See Supplementary Fig. 3 for anomalies as standard deviations. The absolute mean maximum total SGL volume (x̄) is shown in panels a and c–j. Supraglacial lake volume anomalies for two addition regions, the Ingrid Christensen Coast and Voyeykov Ice Shelf, are shown in Supplementary Fig. 4 rather than this figure because lakes occur with less frequency in these two regions. Grounding line from ref. and coastline from ref. .

Fig. 3. Supraglacial lake recurrence around East Antarctica.

(a–j) Normalised count of overlapping lakes at their maximum extent during January from 2014 to 2020 on selected major ice shelves and outlet glaciers, weighted according to the number of useable (partially or totally cloud-free) satellite images in this period. Turquoise/pale blue colours correspond to infrequently-forming lakes (i.e. that formed in a single year) and pink/purple colours correspond to frequently-forming lakes (i.e. that formed on multiple dates in January in several or all years). This figure highlights the distribution of SGLs across these major ice shelves but note that lakes occur with less frequency in other regions, for example along the Ingrid Christensen Coast (between Polarbroken Glacier and Shackleton Ice Shelf) and on Voyeykov Ice Shelf (adjacent to Moscow University Ice Shelf). The grounding line is shown as a solid black line in all panels. Grounding line from ref. and coastline from ref. .

Fig. 4. Maximum elevation of supraglacial lakes in January from 2014 to 2020 around East Antarctica.

Key ice shelves/regions are highlighted. Grey areas are ice shelves and floating glacier tongues. Grounding line from ref. and coastline from ref. . Lake extents in January 2017, the most extensive lake year, are shown in blue.

Fig. 5. Relationships between climatic variables and supraglacial lake volumes on the East Antarctic Ice Sheet.

Scatter plots of mean December-January-February (DJF) 2-m temperature (T_2m) (a–d) mean snowfall in the preceding winter (February to December) (e–h) and mean DJF net surface solar radiation (S_rad) (i–l) from ice shelf grounding zones simulated by ERA5 reanalysis (see Methods) and maximum total SGL volume grouped by major EAIS region. Individual ice shelves are represented by different colours (see Fig. 1 for locations). Significant relationships (p < 0.05) in a linear regression are displayed.

Fig. 6. Relationships between near-surface conditions and supraglacial lake volumes on the East Antarctic Ice Sheet.

Scatter plots of mean November firn air content-to-DJF melt (a–d), mean January surface runoff (i–l) and depth of shallowest ice lens (m–p) (simulated by the Community Firn Model) and mean January total surface melt (e–h) (simulated by MAR) against maximum total SGL volume, grouped by major EAIS region. Individual ice shelves are represented by different colours (see Fig. 1 for locations). Significant relationships (p < 0.05) in a linear regression are displayed.