On the importance of the albedo parameterization for the mass balance of the Greenland ice sheet in EC-Earth

• Published in: The Cryosphere
• Main Authors: M. M. Helsen, R. S. W. van de Wal, T. J. Reerink, R. Bintanja, M. S. Madsen, S. Yang, Q. Li, Q. Zhang
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2017
• Subjects: geo; envir; Greenland; Ice Sheet; The Cryosphere
• Online Access: https://doi.org/10.5194/tc-11-1949-2017; https://www.the-cryosphere.net/11/1949/2017/tc-11-1949-2017.pdf; https://doaj.org/article/28124894e5c5470ba2db2521c87d64c9

The albedo of the surface of ice sheets changes as a function of time due to the effects of deposition of new snow, ageing of dry snow, bare ice exposure, melting and run-off. Currently, the calculation of the albedo of ice sheets is highly parameterized within the earth system model EC-Earth by taking a constant value for areas with thick perennial snow cover. This is an important reason why the surface mass balance (SMB) of the Greenland ice sheet (GrIS) is poorly resolved in the model. The purpose of this study is to improve the SMB forcing of the GrIS by evaluating different parameter settings within a snow albedo scheme. By allowing ice-sheet albedo to vary as a function of wet and dry conditions, the spatial distribution of albedo and melt rate improves. Nevertheless, the spatial distribution of SMB in EC-Earth is not significantly improved. As a reason for this, we identify omissions in the current snow albedo scheme, such as separate treatment of snow and ice and the effect of refreezing. The resulting SMB is downscaled from the lower-resolution global climate model topography to the higher-resolution ice-sheet topography of the GrIS, such that the influence of these different SMB climatologies on the long-term evolution of the GrIS is tested by ice-sheet model simulations. From these ice-sheet simulations we conclude that an albedo scheme with a short response time of decaying albedo during wet conditions performs best with respect to long-term simulated ice-sheet volume. This results in an optimized albedo parameterization that can be used in future EC-Earth simulations with an interactive ice-sheet component.