Regional distribution and variability of model-simulated Arctic snow on sea ice

kcastro [ at ]


Numerical models face the challenge of representing the present-day spatiotemporal distribution of snow on sea ice realistically. We present modeled Arctic-wide snow depths on sea ice (hs_mod) obtained with the MITgcm configured with a single snow layer that accumulates proportionally to the thickness of sea ice. When compared to snow depths derived from radar measurements (NASA Operation IceBridge, 2009–2013), the model snow depths are overestimated on first-year ice (2.5 ± 8.1 cm) and multiyear ice (0.8 ± 8.3 cm). The large variance between model and observations lies mainly in the limitations of the model snow scheme and the large uncertainties in the radar measurements. In a temporal analysis, during the peak of snowfall accumulation (April), hs_mod show a decline between 2000 and 2013 associated to long-term reduction of summer sea ice extent, surface melting and sublimation. With the aim of gaining knowledge on how to improve hs_mod, we investigate the contribution of the explicitly modeled snow processes to the resulting hs_mod. Our analysis reveals that this simple snow scheme offers a practical solution to general circulation models due to its ability to replicate robustly the distribution of the large-scale Arctic snow depths. However, benefit can be gained from the integration of explicit wind redistribution processes to potentially improve the model performance and to better understand the interaction between sources and sinks of contemporary Arctic snow.

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DOI 10.1016/j.polar.2017.05.003

Cite as
Castro-Morales, K. , Ricker, R. and Gerdes, R. (2017): Regional distribution and variability of model-simulated Arctic snow on sea ice , Polar Science, In Pre , pp. 1-17 . doi: 10.1016/j.polar.2017.05.003

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