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Brief communication: How deep is the snow on Mount Everest?

There is very strong scientific and public interest regarding the snow thickness on Mountain Everest. Previously reported snow depths derived by different methods and instruments ranged from 0.92 to 3.5 m. Our measurements in 2022 provide the first clear radar image of the snowpack at the top of Mount Everest. The snow thickness at Earth’s summit was averaged to be 9.5 ± 1.2 m. This updated snow thickness is considerably deeper than values reported during the past 5 decades.

Brief communication: Rapid ∼ 335 × 106 m3 bed erosion after detachment of the Sedongpu Glacier (Tibet)

Following the detachment of the 130 × 10^6 m^3 Sedongpu Glacier (south-eastern Tibet) in 2018, the Sedongpu Valley underwent massive large-volume landscape changes. An enormous volume of in total around 330 × 10^6 m^3 was rapidly eroded, forming a new canyon of up to 300 m depth, 1 km width, and almost 4 km length. Such consequences of glacier change in mountains have so far not been considered at this magnitude and speed.

Reversible ice sheet thinning in the Amundsen Sea Embayment during the Late Holocene

Samples of bedrock recovered from below the West Antarctic Ice Sheet show that part of the ice sheet was thinner several thousand years ago than it is now and subsequently thickened. This is important because of concern that present ice thinning in this region may lead to rapid, irreversible sea level rise. The past episode of thinning at this site that took place in a similar, although not identical, climate was not irreversible; however, reversal required at least 3000 years to complete.

Slowdown of Shirase Glacier, East Antarctica, caused by strengthening alongshore winds

Satellite observations have shown that the Shirase Glacier catchment in East Antarctica has been gaining mass over the past 2 decades, a trend largely attributed to increased snowfall. Our multi-decadal observations of Shirase Glacier show that ocean forcing has also contributed to some of this recent mass gain. This has been caused by strengthening easterly winds reducing the inflow of warm water underneath the Shirase ice tongue, causing the glacier to slow down and thicken.

Improving interpretation of sea-level projections through a machine-learning-based local explanation approach

To improve the interpretability of process-based projections of the sea-level contribution from land ice components, we apply the machine-learning-based “SHapley Additive exPlanations” approach to a subset of a multi-model ensemble study for the Greenland ice sheet. This allows us to quantify the influence of particular modelling decisions (related to numerical implementation, initial conditions, or parametrisation of ice-sheet processes) directly in terms of sea-level change contribution.

The Antarctic contribution to 21st-century sea-level rise predicted by the UK Earth System Model with an interactive ice sheet

The UK Earth System Model is the first to fully include interactions of the atmosphere and ocean with the Antarctic Ice Sheet. Under the low-greenhouse-gas SSP1–1.9 (Shared Socioeconomic Pathway) scenario, the ice sheet remains stable over the 21st century. Under the strong-greenhouse-gas SSP5–8.5 scenario, the model predicts strong increases in melting of large ice shelves and snow accumulation on the surface. The dominance of accumulation leads to a sea level fall at the end of the century.

The impact of climate oscillations on the surface energy budget over the Greenland Ice Sheet in a changing climate

To overcome internal climate variability, this study uses k-means clustering to combine NAO, GBI and IWV over the Greenland Ice Sheet (GrIS) and names the approach as the North Atlantic influence on Greenland (NAG). With the support of a polar-adapted RCM, spatio-temporal changes on SEB components within NAG phases are investigated. We report atmospheric warming and moistening across all NAG phases as well as large-scale and regional-scale contributions to GrIS mass loss and their interactions.

TermPicks: a century of Greenland glacier terminus data for use in scientific and machine learning applications

Terminus traces have been used to understand how Greenland’s glaciers have changed over time; however, manual digitization is time-intensive, and a lack of coordination leads to duplication of efforts. We have compiled a dataset of over 39 000 terminus traces for 278 glaciers for scientific and machine learning applications. We also provide an overview of an updated version of the Google Earth Engine Digitization Tool (GEEDiT), which has been developed specifically for the Greenland Ice Sheet.

A probabilistic framework for quantifying the role of anthropogenic climate change in marine-terminating glacier retreats

Marine-terminating glaciers have recently retreated dramatically, but the role of anthropogenic forcing remains uncertain. We use idealized model simulations to develop a framework for assessing the probability of rapid retreat in the context of natural climate variability. Our analyses show that century-scale anthropogenic trends can substantially increase the probability of retreats. This provides a roadmap for future work to formally assess the role of human activity in recent glacier change.

Clouds drive differences in future surface melt over the Antarctic ice shelves

Model projections suggest large differences in future Antarctic surface melting even for similar greenhouse gas scenarios and warming rates. We show that clouds containing a larger amount of liquid water lead to stronger melt. As surface melt can trigger the collapse of the ice shelves (the safety band of the Antarctic Ice Sheet), clouds could be a major source of uncertainties in projections of sea level rise.

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