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            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.more » « less
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            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.more » « less
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            Abstract A World Meteorological Organization (WMO) Extremes Evaluation Committee investigated an observation of −69.6 °C by Klinck Automatic Weather Station (AWS) in Greenland on 22 December 1991 as the lowest temperature observed in Greenland, thereby making it the lowest recorded near‐surface air temperature for the Northern and Western Hemispheres and for WMO Region VI. The committee examined the metadata and observations of the station as well as the regional synoptic circulation. The committee concluded that the observation is credible in terms of instrument calibration, monitoring of the station and the synoptic situation. Consequently, the WMO Rapporteur accepted the observation as the officially lowest observed near‐surface air temperature for Greenland, the Northern and Western Hemisphere and for WMO Region VI. As a supplement to this investigation, the committee also recommends that opportunities be investigated such that AWS data from Greenland can be efficiently incorporated into real‐time weather forecasts and hence into reanalysis datasets.more » « less
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