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Abstract Observations show increases in river discharge to the Arctic Ocean especially in winter over the last decades but the physical mechanisms driving these changes are not yet fully understood. We hypothesize that even in the absence of a precipitation increase, permafrost degradation alone can lead to increased annual river runoff. To test this hypothesis we perform 12 millennium-long simulations over an idealized hypothetical watershed (1 km 2 ) using a distributed, physically based water balance model (Water flow and Balance Simulation Model, WaSiM). The model is forced by both a hypothetical warming defined by an air temperature increase of 7.5 ∘ C over 100 years, and a corresponding cooling scenario. To assess model sensitivity we vary soil saturated hydraulic conductivity and lateral subsurface flow configuration. Under the warming scenario, changes in subsurface water transport due to ground temperature changes result in a 7%–14% increase in annual runoff accompanied by a 6%–20% decrease in evapotranspiration. The increase in runoff is most pronounced in winter. Hence, the simulations demonstrate that changes in permafrost characteristics due to climate warming and associated changes in evapotranspiration provide a plausible mechanism for the observed runoff increases in Arctic watersheds. In addition, our experiments show that when lateral subsurface moisture transport is not included, as commonly done in global-scale Earth System Models, the equilibrium water balance in response to the warming or cooling is similar to the water balance in simulations where lateral subsurface transport is included. However, the transient changes in water balance components prior to reaching equilibrium differ greatly between the two. For example, for high saturated hydraulic conductivity only when lateral subsurface transport is considered, a period of decreased runoff occurs immediately after the warming. This period is characterized by a positive change in soil moisture storage caused by the soil moisture deficit developed during prior cooling. 

ABSTRACT Glaciers spanning large altitudinal ranges often experience different climatic regimes with elevation, creating challenges in acquiring mass-balance and climate observations that represent the entire glacier. We use mixed methods to reconstruct the 1991–2014 mass balance of the Kahiltna Glacier in Alaska, a large (503 km 2 ) glacier with one of the greatest elevation ranges globally (264–6108 m a.s.l.). We calibrate an enhanced temperature index model to glacier-wide mass balances from repeat laser altimetry and point observations, finding a mean net mass-balance rate of −0.74 mw.e. a −1 ( ± σ = 0.04, std dev. of the best-performing model simulations). Results are validated against mass changes from NASA's Gravity Recovery and Climate Experiment (GRACE) satellites, a novel approach at the individual glacier scale. Correlation is strong between the detrended model- and GRACE-derived mass change time series ( R 2 = 0.58 and p ≪ 0.001), and between summer ( R 2 = 0.69 and p = 0.003) and annual ( R 2 = 0.63 and p = 0.006) balances, lending greater confidence to our modeling results. We find poor correlation, however, between modeled glacier-wide balances and recent single-stake monitoring. Finally, we make recommendations for monitoring glaciers with extreme altitudinal ranges, including characterizing precipitation via snow radar profiling. 

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.