A long-term dataset of climatic mass balance, snow conditions, and runoff in Svalbard (1957-2018)

Abstract

The climate in Svalbard is undergoing amplified change compared to the global mean. This has major implications for runoff from glaciers and seasonal snow on land.We use a coupled energy balance-subsurface model, forced with downscaled regional climate model fields, and apply it to both glacier-covered and land areas in Svalbard. This generates a long-term (1957-2018) distributed dataset of climatic mass balance (CMB) for the glaciers, snow conditions, and runoff with a 1km-1km spatial and 3-hourly temporal resolution. Observational data including stake measurements, automatic weather station data, and subsurface data across Svalbard are used for model calibration and validation. We find a weakly positive mean net CMB (C0.09mw.e. a-1) over the simulation period, which only fractionally compensates for mass loss through calving. Pronounced warming and a small precipitation increase lead to a spatial-mean negative net CMB trend (-0.06mw.e. a-1 decade-1), and an increase in the equilibrium line altitude (ELA) by 17m decade-1, with the largest changes in southern and central Svalbard. The retreating ELA in turn causes firn air volume to decrease by 4% decade-1, which in combination with winter warming induces a substantial reduction of refreezing in both glacier-covered and land areas (average -4% decade-1). A combination of increased melt and reduced refreezing causes glacier runoff (average 34.3 Gt a-1) to double over the simulation period, while discharge from land (average 10.6 Gt a-1) remains nearly unchanged. As a result, the relative contribution of land runoff to total runoff drops from 30% to 20% during 1957-2018. Seasonal snow on land and in glacier ablation zones is found to arrive later in autumn (C1.4 d decade-1), while no significant changes occurred on the date of snow disappearance in spring-summer. Altogether, the output of the simulation provides an extensive dataset that may be of use in a wide range of applications ranging from runoff modelling to ecosystem studies.