Articles | Volume 20, issue 11
https://doi.org/10.5194/tc-20-6521-2026
https://doi.org/10.5194/tc-20-6521-2026
Research article
 | 
12 Nov 2026
Research article |  | 12 Nov 2026

Effects of snow redistribution parameterization on simulated snow thickness validated by MOSAiC observations

Fengguan Gu, Changwei Liu, Bo Han, Qinghua Yang, and Jiping Liu

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Cited articles

Bitz, C. M.: Description of initial conditions and forcing data for the SHEBA single column model runs, University of Washington, https://atmos.washington.edu/~bitz/column_model/notes_forcing_data, last access: 16 January 2026. 
Bliss, A. C., Hutchings, J. K., and Watkins, D. M.: Sea ice drift tracks from autonomous buoys in the MOSAiC Distributed Network, Sci. Data, 10, 403, https://doi.org/10.1038/s41597-023-02311-y, 2023. 
Briegleb, B. P. and Light, B.: A Delta-Eddington multiple scattering parameterization for solar radiation in the sea ice component of the Community Climate System Model, NCAR Technical Note NCAR/TN-472+STR, National Center for Atmospheric Research, Boulder, CO, USA, https://doi.org/10.5065/D6B27S71, 2007. 
Cheng, B., Launiainen, J., and Vihma, T.: Modelling of Superimposed Ice Formation and SubSurface Melting in the Baltic Sea, Geophysica, 39, 31–50, 2003. 
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Short summary
Snow on Arctic sea ice acts like a blanket that traps heat and reflects sunlight, so it matters for the climate. Drawing on measurements from a year-long Arctic expedition, we improved models that simulate snow on the ice. Without wind-driven snow movement, the models overestimated snow depth. Adding a wind-driven scheme cut the average error by more than half. After tuning, simulated snow matched observations. The findings help project how Arctic sea ice may evolve in a warming climate.
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