Benefits from representing snow properties and related processes in coupled ocean–sea ice models. (March 2015)

• Record Type: Journal Article
• Authors: Lecomte, Olivier; Fichefet, Thierry; Massonnet, François; Vancoppenolle, Martin
• Is Part Of: Ocean modelling. Volume 87(2015:Mar.)
• Page Start: 81
• Page End: 85
• Publication Date: 2015-03
• Subjects: Snow -- Sea ice -- Model -- Arctic -- Antarctic; Oceanography -- Periodicals; Océanographie -- Périodiques; Oceanography; Periodicals; 551.46
• DOI: 10.1016/j.ocemod.2014.11.005
• Languages: English
• ISSNs: 1463-5003

Abstract

Highlights: The influence snow physics in asea ice model is analyzed. Perennial ice seems more sensitive to changes in snow physics than seasonal ice. Representing snow in sea ice models is important for simulations of Arctic sea ice. Antarctic sea ice in model simulations is mostly driven by the ocean and atmosphere. Abstract: Several large-scale sea ice simulations are performed over the last three decades using a coupled ocean–sea ice model under the same experimental setup but partly modifying the representation of snow physics in the model. The inter-simulation spread analysis yields that the simulated multi-year ice is sensitive to such changes while the seasonal sea ice, is rather dominantly driven by the external oceanic and atmospheric forcings. In the context of a thinning Arctic sea ice cover, those findings suggest that including snow processes in large-scale sea ice models is beneficial, if not necessary, to predict the timing of the Arctic multi-year ice disappearance, whereas the operational forecasting of first-year ice extent using fully coupled models will likely require improvement to the oceanic and atmospheric components themselves.