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Discussion papers
https://doi.org/10.5194/tc-2019-53
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-2019-53
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 23 Apr 2019

Research article | 23 Apr 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal The Cryosphere (TC).

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

Ward van Pelt1, Veijo Pohjola1, Rickard Pettersson1, Sergey Marchenko1, Jack Kohler2, Bartek Luks3, Jon Ove Hagen4, Thomas V. Schuler4,5, Thorben Dunse4,6, Brice Noël7, and Carleen Reijmer7 Ward van Pelt et al.
  • 1Department of Earth Sciences, Uppsala University, Uppsala, Sweden
  • 2Norwegian Polar Institute, Tromsø, Norway
  • 3Institute of Geophysics, Polish Academy of Sciences, Warszawa, Poland
  • 4Department of Geosciences, University of Oslo, Oslo, Norway
  • 5Department of Arctic Geophysics, University Centre in Svalbard, Longyearbyen, Svalbard
  • 6Department of Environmental Sciences, Western Norway University of Applied Sciences, Norway
  • 7Institute for Marine and Atmospheric Research Utrecht, Utrecht University, Utrecht, The Netherlands

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), snow conditions and runoff with a 1x1-km 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 CMB (+0.09 m w.e. a−1) over the simulation period, which only fractionally compensates for mass loss through calving. Pronounced warming and a weak precipitation increase lead to a spatial-mean negative CMB trend (−0.06 m w.e. a−1 decade-1), and an increase in the equilibrium line altitude (ELA) by 17 m decade−1, with 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 cause 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 (+1.4 days decade−1), while no significant changes occurred in 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.

Ward van Pelt et al.
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A long-term dataset of climatic mass balance, snow conditions and runoff in Svalbard (1957-2018) W. J. J. Van Pelt, V. A. Pohjola, R. Pettersson, S. Marchenko, J. Kohler, B. Luks, J. O. Hagen, T. V. Schuler, T. Dunse, B. Noël, and C. H. Reijmer https://doi.org/10.6084/m9.figshare.7836530.v1

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Short summary
The climate in Svalbard is undergoing amplified change compared to the global mean, which has a strong impact on the climatic mass balance of glaciers and the state of seasonal snow in land areas. In this study we analyze a coupled energy balance – subsurface model dataset, which provides detailed information on distributed climatic mass balance, snow conditions and runoff across Svalbard between 1957 and 2018.
The climate in Svalbard is undergoing amplified change compared to the global mean, which has a...
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