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European Geosciences Union, The Cryosphere, 4(6), p. 743-762, 2012

DOI: 10.5194/tc-6-743-2012

European Geosciences Union, Cryosphere Discussions, 5(5), p. 2723-2764

DOI: 10.5194/tcd-5-2723-2011

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Refreezing on the Greenland ice sheet: a comparison of parameterizations

Journal article published in 2011 by C. H. Reijmer, M. R. van den Broeke, Xavier Fettweis ORCID, J. Ettema, L. B. Stap
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Abstract. Retention and refreezing of meltwater are acknowledged to be important processes for the mass budget of polar glaciers and ice sheets. Several parameterizations of these processes exist for use in energy and mass balance models. Due to a lack of direct observations, validation of these parameterizations is difficult. In this study we compare a set of 6 refreezing parameterizations against output of two Regional Climate Models (RCMs) coupled to an energy balance snow model, the Regional Atmospheric Climate Model (RACMO2) and the Modèle Atmosphérique Régional (MAR), applied to the Greenland ice sheet. In both RCMs, refreezing is explicitly calculated in a snow model that calculates vertical profiles of temperature, density and liquid water content. Between RACMO2 and MAR, the ice sheet-integrated amount of refreezing differs by only 4.9 mm w.e yr−1 (4.5 %), and the temporal and spatial variability are very similar. For consistency, the parameterizations are forced with output (surface temperature, precipitation and melt) of the RCMs. For the ice sheet-integrated amount of refreezing and its inter-annual variations, all parameterizations give similar results, especially after some tuning. However, the spatial distributions differ significantly and the spatial correspondence between the RCMs is better than with any of the parameterizations. Results are especially sensitive to the choice of the depth of the thermally active layer, which determines the cold content of the snow in most parameterizations. These results are independent of which RCM is used to force the parameterizations.