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Abstract We study the meteorological drivers of melt at two glaciers in Taylor Valley, Antarctica, using 22 years of weather station observations and surface energy fluxes. The glaciers are located only 30 km apart, but have different local climates; Taylor Glacier is generally drier and windier than Commonwealth Glacier, which receives more snowfall due to its proximity to the coast. Commonwealth Glacier shows more inter-annual melt variability, explained by variable albedo due to summer snowfall events. A significant increase in surface melt at Commonwealth Glacier is associated with a decrease in summer minimum albedo. Inter-annual variability in melt at both glaciers is linked to degree-days above freezing during föhn events, occurring more frequently at Taylor Glacier. At Taylor Glacier melt occurs most often with positive air temperatures, but föhn conditions also favour sublimation, which cools the surface and prevents melt for the majority of the positive air temperatures. At Commonwealth Glacier, most of the melt instead occurs with sub-zero air temperatures, driven by strong solar radiative heating. Future melt at Taylor Glacier will likely be more sensitive to changes in föhn events, while Commonwealth Glacier will be impacted more by changes in near coastal weather, where moisture inputs can drive cloud cover, snowfall and change albedo. 

The variability of the Antarctic and Greenland ice sheets occurs on various timescales and is important for projections of sea level rise; however, there are substantial uncertainties concerning future ice-sheet mass changes. In this Review, we explore the degree to which short-term fluctuations and extreme glaciological events reflect the ice sheets’ long-term evolution and response to ongoing climate change. Short-term (decadal or shorter) variations in atmospheric or oceanic conditions can trigger amplifying feedbacks that increase the sensitivity of ice sheets to climate change. For example, variability in ocean-induced and atmosphere-induced melting can trigger ice thinning, retreat and/or collapse of ice shelves, grounding-line retreat, and ice flow acceleration. The Antarctic Ice Sheet is especially prone to increased melting and ice sheet collapse from warm ocean currents, which could be accentuated with increased climate variability. In Greenland both high and low melt anomalies have been observed since 2012, highlighting the influence of increased interannual climate variability on extreme glaciological events and ice sheet evolution. Failing to adequately account for such variability can result in biased projections of multi-decadal ice mass loss. Therefore, future research should aim to improve climate and ocean observations and models, and develop sophisticated ice sheet models that are directly constrained by observational records and can capture ice dynamical changes across various timescales. 

The SUMup database is a compilation of surface mass balance (SMB), subsurface temperature and density measurements from the Greenland and Antarctic ice sheets. This 2023 release contains 4 490 442 data points: 1 778 540 SMB measurements, 2 706 413 density measurements and 5 489 subsurface temperature measurements. This is respectively 1 477 132, 420 825 and 4 715 additional observations of SMB, density and temperature compared to the 2022 release. This new release provides not only snow accumulation on ice sheets, like its predecessors, but all types of SMB measurements, including from ablation areas. On the other hand, snow depth on sea ice is discontinued, but can still be found in the previous releases. The data files are provided in both CSV and NetCDF format and contain, for each measurement, the following metadata: latitude, longitude, elevation, timestamp, method, reference of the data source and, when applicable, the name of the measurement group it belongs to (core name for SMB, profile name for density, station name for temperature). Data users are encouraged to cite all the original data sources that are being used. Issues about this release as well as suggestions of datasets to be added in next releases can be done on a dedicated user forum: https://github.com/SUMup-database/SUMup-data-suggestion/issues. Example scripts to use the SUMup 2023 files are made available on our script repository: https://github.com/SUMup-database/SUMup-example-scripts.