Atmospheric warming is increasing surface melting across the Antarctic Peninsula, with unknown impacts upon glacier dynamics at the ice-bed interface. Using high-resolution satellite-derived ice velocity data, optical satellite imagery and regional climate modelling, we show that drainage of surface meltwater to the bed of outlet glaciers on the Antarctic Peninsula occurs and triggers rapid ice flow accelerations (up to 100% greater than the annual mean). This provides a mechanism for this sector of the Antarctic Ice Sheet to respond rapidly to atmospheric warming. We infer that delivery of water to the bed transiently increases basal water pressure, enhancing basal motion, but efficient evacuation subsequently reduces water pressure causing ice deceleration. Currently, melt events are sporadic, so efficient subglacial drainage cannot be maintained, resulting in multiple short-lived (<6 day) ice flow perturbations. Future increases in meltwater could induce a shift to a glacier dynamic regime characterised by seasonal-scale hydrologically-driven ice flow variations.
Abstract. Surface meltwater is widespread around the Antarctic Ice Sheet margin and has the potential to influence ice shelf stability, ice flow and ice–albedo feedbacks. Our understanding of the seasonal and multi-year evolution of Antarctic surface meltwater is limited. Attempts to generate robust meltwater cover time series have largely been constrained by computational expense or limited ice surface visibility associated with mapping from optical satellite imagery. Here, we add a novel method for calculating visibility metrics to an existing meltwater detection method within Google Earth Engine. This enables us to quantify uncertainty induced by cloud cover and variable image data coverage, allowing time series of surface meltwater area to be automatically generated over large spatial and temporal scales. We demonstrate our method on the Amery Ice Shelf region of East Antarctica, analysing 4164 Landsat 7 and 8 optical images between 2005 and 2020. Results show high interannual variability in surface meltwater cover, with mapped cumulative lake area totals ranging from 384 to 3898 km2 per melt season. By incorporating image visibility assessments, however, we estimate that cumulative total lake areas are on average 42 % higher than minimum mapped values. We show that modelled melt predictions from a regional climate model provide a good indication of lake cover in the Amery region and that annual lake coverage is typically highest in years with a negative austral summer SAM index. Our results demonstrate that our method could be scaled up to generate a multi-year time series record of surface water extent from optical imagery at a continent-wide scale.
Abstract. Surface meltwater is widespread around the margin of the Antarctic Ice Sheet and has the potential to influence ice-shelf stability, ice-dynamic processes and ice-albedo feedbacks. Whilst the general spatial distribution of surface meltwater across the Antarctic continent is now relatively well known, our understanding of the seasonal and multi-year evolution of surface meltwater is limited. Attempts to generate robust time series of melt cover have largely been constrained by computational expense or limited ice surface visibility associated with mapping from optical satellite imagery. Here, we implement an existing meltwater detection method alongside a novel method for calculating visibility metrics within Google Earth Engine. This enables us to quantify uncertainty induced by cloud cover and variable image data coverage, allowing us to automatically generate time series of surface melt area over large spatial and temporal scales. We demonstrate our method on the Amery Ice Shelf region of East Antarctica, analysing 4,164 Landsat 7 and 8 optical images between 2005 and 2020. Results show high interannual variability in surface meltwater cover, with mapped cumulative lake area totals ranging from 384 km2 to 3898 km2 per melt season. However, by incorporating image visibility assessments into our results, we estimate that cumulative total lake areas are on average 42 % higher than minimum mapped values, highlighting the importance of accounting for variations in image visibility when mapping lake areas. In a typical melt season, total lake area remains low throughout November and early December, before increasing, on average, by an order of magnitude during the second half of December. Peak lake area most commonly occurs during January, before decreasing during February as lakes freeze over. We show that modelled melt predictions from a regional climate model provides a good indication of lake cover in the Amery region, and that annual lake coverage is strongly associated with phases of the Southern Annular Mode (SAM); surface melt is typically highest in years with a negative austral summer SAM index. Furthermore, we suggest that melt-albedo feedbacks modulate the spatial distribution of meltwater in the region, with the exposure of blue ice from persistent katabatic wind scouring influencing the susceptibility of melt ponding. Results demonstrate how our method could be scaled up to generate a multi-year time series record of surface water extent from optical imagery at a continent-wide scale.
The future sea-level contribution from the Antarctic ice sheets is highly uncertain. Ice dynamic, hydrofracture, and radiative processes related to surface meltwater are predicted to become increasingly important for Antarctic mass-loss as atmospheric temperatures rise. Our understanding of Antarctic surface meltwater, however, remains limited, with previous studies restricted in spatial or temporal scope. Here, we leverage cloud computing to overcome these limitations and produce the first Antarctic-wide, monthly dataset of surface meltwater spanning 2006 to 2021. Surface meltwater covered 3732 km2 across Antarctica on average during each melt season, with 30% on grounded ice. High interannual variability in meltwater coverage across the Antarctic Peninsula and in East Antarctica correlates with large-scale modes of climate variability, but this control is absent where meltwater coverage is comparatively low in West Antarctica. In East Antarctica, we find a significant increasing trend in meltwater area of 66 km2 per year (197% total change) which, in the absence of a clear climatic trend, we attribute to ice sheet surfaces becoming more favourable to ponding. Future increases in melt rate could therefore cause proportionally larger increases in meltwater coverage with implications for the resilience of ice shelves, and increased surface-to-bed hydraulic connections on grounded ice.
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