Sensitivity of simulated Arctic sea ice to realistic ice thickness distributions and snow parameterizations

Sea ice and snow on sea ice to a large extent determine the surface heat budget in the Arctic Ocean. In spite of the advances in modeling sea-ice thermodynamics, a good number of models still rely on simple parameterizations of the thermodynamics of ice and snow. Based on simulations with an Arctic sea-ice model coupled to an ocean general circulation model, we analyzed the impact of changing two sea-ice parameterizations: (1) the prescribed ice thickness distribution (ITD) for surface heat budget calculations, and (2) the description of the snow layer. For the former, we prescribed a realistic ITD derived from airborne electromagnetic induction sounding measurements. For the latter, two different types of parameterizations were tested: (1) snow thickness independent of the sea-ice thickness below, and (2) a distribution proportional to the prescribed ITD. Our results show that changing the ITD from seven uniform categories to fifteen nonuniform categories derived from field measurements, and distributing the snow layer according to the ITD, leads to an increase in average Arctic-wide ice thickness by 0.56 m and an increase by 1 m in the Canadian Arctic Archipelago and Canadian Basin. This increase is found to be a direct consequence of 524 km(3) extra thermodynamic growth during the months of ice formation (January, February, and March). Our results emphasize that these parameterizations are a key factor in sea-ice modeling to improve the representation of the sea-ice energy balance. Key Points Use of realistic ice thickness distributions in a regional Arctic Ocean model Snow layer distributed as the ITD increases considerably the sea-ice thickness Model sea-ice thickness agrees well with winter satellite retrieved data