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Abstract. Over recent decades, the Greenland Ice Sheet (GrIS) has lost mass through increased melting and solid ice discharge into the ocean. Surface meltwater features such as supraglacial lakes (SGLs), channels and slush are becoming more abundant as a result of the former and are implicated as a control on the latter when they drain. It is not yet clear, however, how these different surface hydrological features will respond to future climate changes, and it is likely that GrIS surface melting will continue to increase as the Arctic warms. Here, we use Sentinel-2 and Landsat 8 optical satellite imagery to compare the distribution and evolution of meltwater features (SGLs, channels, slush) in the Russell–Leverett glacier catchment, southwest Greenland, in relatively high (2019) and low (2018) melt years. We show that (1) supraglacial meltwater covers a greater area and extends further inland to higher elevations in 2019 than in 2018; (2) slush – generally disregarded in previous Greenland surface hydrology studies – is far more widespread in 2019 than in 2018; (3) the supraglacial channel system is more interconnected in 2019 than in 2018; (4) a greater number and larger total area of SGLs drained in 2019, although draining SGLs were, on average, deeper and more voluminous in 2018; (5) small SGLs (≤0.0495 km2) – typically disregarded in previous studies – form and drain in both melt years, although this behaviour is more prevalent in 2019; and (6) a greater proportion of SGLs refroze in 2018 compared to 2019. This analysis provides new insight into how the ice sheet responds to significant melt events, and how a changing climate may impact meltwater feature characteristics, SGL behaviour and ice dynamics in the future. 

Abstract Global Navigation Satellite System (GNSS) observations and ground-based timelapse photography obtained over the record-high 2019/2020 melt season are combined to characterise the flexure and fracture behaviour of a previously formed doline on George VI Ice Shelf, Antarctica. The GNSS timeseries shows a downward vertical displacement of the doline centre with respect to the doline rim of ~60 cm in response to loading from a central meltwater lake. The GNSS data also show a tens-of-days episode of rapid-onset, exponentially decaying horizontal displacement, where the horizontal distance between the doline rim and its centre increases by ~70 cm. We interpret this event as the initiation and/or widening of a fracture, aided by stress perturbations associated with meltwater loading in the doline basin. Viscous flexure modelling indicates that the meltwater loading generates tensile surface stresses exceeding 75 kPa. This, together with our timelapse photos of circular fractures around the doline, suggests the first such documentation of meltwater-loading-induced ‘ring fracture’ formation on an ice shelf, equivalent to the fracture type proposed as part of the chain-reaction lake drainage process involved in the 2002 breakup of the Larsen B Ice Shelf. 

Abstract Antarctic firn is critical for ice-shelf stability because it stores meltwater that would otherwise pond on the surface. Ponded meltwater increases the risk of hydrofracture and subsequent potential ice-shelf collapse. Here, we use output from a firn model to build a computationally simpler emulator that uses a random forest to predict ice-shelf effective firn air content, which considers impermeable ice layers that make deeper parts of the firn inaccessible to meltwater, based on climate conditions. We find that summer air temperature and precipitation are the most important climatic features for predicting firn air content. Based on the climatology from an ensemble of Earth System Models, we find that the Larsen C Ice Shelf is most at risk of firn air depletion during the 21st century, while the larger Ross and Ronne-Filchner ice shelves are unlikely to experience substantial firn air content change. This work demonstrates the utility of emulation for computationally efficient estimations of complicated ice sheet processes. 

Abstract. In late March 2011, landfast sea ice (hereafter, “fast ice”) formed in the northern Larsen B embayment and persisted continuously as multi-year fast ice until January 2022. In the 11 years of fast-ice presence, the northern Larsen B glaciers slowed significantly, thickened in their lower reaches, and developed extensive mélange areas, leading to the formation of ice tongues that extended up to 16 km from the 2011 ice fronts. In situ measurements of ice speed on adjacent ice shelf areas spanning 2011 to 2017 show that the fast ice provided significant resistive stress to ice flow. Fast-ice breakout began in late January 2022 and was closely followed by retreat and breakup of both the fast-ice mélange and the glacier ice tongues. We investigate the probable triggers for the loss of fast ice and document the initial upstream glacier responses. The fast-ice breakup is linked to the arrival of a strong ocean swell event (>1.5 m amplitude; wave period waves >5 s) originating from the northeast. Wave propagation to the ice front was facilitated by a 12-year low in sea ice concentration in the northwestern Weddell Sea, creating a near-ice-free corridor to the open ocean. Remote sensing data in the months following the fast-ice breakout reveals an initial ice flow speed increase (>2-fold), elevation loss (9 to 11 m), and rapid calving of floating and grounded ice for the three main embayment glaciers Crane (11 km), Hektoria (25 km), and Green (18 km). 

Abstract. The Greenland Ice Sheet (GrIS) is losing mass as the climate warms through both increased meltwater runoff and ice discharge at marine-terminating sectors. At the ice sheet surface, meltwater runoff forms a dynamic supraglacial hydrological system which includes stream and river networks and large supraglacial lakes (SGLs). Streams and rivers can route water into crevasses or into supraglacial lakes with crevasses underneath, both of which can then hydrofracture to the ice sheet base, providing a mechanism for the surface meltwater to access the bed. Understanding where, when, and how much meltwater is transferred to the bed is important because variability in meltwater supply to the bed can increase ice flow speeds, potentially impacting the hypsometry of the ice sheet in grounded sectors, and iceberg discharge to the ocean. Here we present a new, physically based, supraglacial hydrology model for the GrIS that is able to simulate (a) surface meltwater routing and SGL filling; (b) rapid meltwater drainage to the ice sheet bed via the hydrofracture of surface crevasses both in and outside of SGLs; (c) slow SGL drainage via overflow in supraglacial meltwater channels; and, by offline coupling with a second model, (d) the freezing and unfreezing of SGLs from autumn to spring. We call the model the Supraglacial Hydrology Evolution and Drainage (or SHED) model. We apply the model to three study regions in southwest Greenland between 2015 and 2019 (inclusive) and evaluate its performance with respect to observed supraglacial lake extents and proglacial discharge measurements. We show that the model reproduces 80 % of observed lake locations and provides good agreement with observations in terms of the temporal evolution of lake extent. Modelled moulin density values are in keeping with those previously published, and seasonal and inter-annual variability in proglacial discharge agrees well with that which is observed, though the observations lag the model by a few days since they include transit time through the subglacial system, while the model does not. Our simulations suggest that lake drainage behaviours may be more complex than traditional models suggest, with lakes in our model draining through a combination of both overflow and hydrofracture and with some lakes draining only partially and then refreezing. This suggests that, in order to simulate the evolution of Greenland's surface hydrological system with fidelity, a model that includes all of these processes needs to be used. In future work, we will couple our model to a subglacial model and an ice flow model and thus use our estimates of where, when, and how much meltwater gets to the bed to understand the consequences for ice flow.