Evaluation of a multilayer snow scheme in NEMO-LIM3

Abstract

<p>Arctic sea ice is a major component of the Earth’s climate system and has been experiencing a drastic decline over the past decades, with important consequences regionally and globally. With the sustained warming of the Arctic, sea ice loss is expected to continue in the future. However, the estimation of its magnitude is model-dependent. As a result, the representation of sea ice in climate models requires further consideration. A major issue relates to the long-standing misrepresentation of snow properties on sea ice. However, the presence of snow strongly impacts sea ice growth and surface energy balance. Through its high albedo, snow reflects more solar radiation than bare sea ice does. When a snow cover is present, sea ice growth is reduced because snow is an effective insulator, with a thermal conductivity an order of magnitude lower than that of sea ice. Ocean circulation models usually use multiple layers to resolve sea ice thermodynamics but only one single layer for snow. Lecomte et al. (2013) developed a multilayer snow scheme for ocean circulation models and improved the snow depth distribution by considering the macroscopic effects of wind packing and redeposition. Since then, this snow scheme has been revisited and implemented in a more recent and much more robust NEMO-LIM version, using a simpler technical approach. In addition, new instrumental observations of snow thickness, distribution and density are available since these exploratory works. They are used in the current study to: 1) evaluate the performance of the multilayer snow scheme for sea ice in the NEMO-LIM3 model, and 2) investigate the climatic importance of this snow scheme. Here, we present results of simulations with a varying number of snow layers. By comparing these to the latest observational datasets, we recommend an optimum number of snow  layers to be used in ocean circulation models in both hemispheres. Finally, we explore the impact of a few specific parameterizations of snow thermophysical properties on the representation of sea ice in climate models.</p>