Comment on tc-2021-290 by Daloz et al.

Abstract

In the Northern Hemisphere, the seasonal snow cover plays a major role in the climate system via its effect on surface albedo and fluxes. The parameterization of snow-atmosphere interactions in climate models remains a source of uncertainty and biases in the representation of the local and global climate. Here, we evaluate the ability of an ensemble of regional climate models (RCMs) coupled to different land surface models to simulate the snow albedo effect over Europe, in winter and spring. We use a previously defined index, the Snow Albedo Sensitivity Index (SASI), to quantify the radiative forcing due to the snow albedo effect. By comparing RCM-derived SASI values with SASI calculated from reanalyses and satellite retrievals, we show that an accurate simulation of snow cover is essential for correctly reproducing the observed forcing over mid- and high-latitudes in Europe. The choice of parameterizations with first and foremost the choice of the land surface model but also the convection scheme and the planetary boundary layer, strongly influences the representation of SASI as it affects the ability of climate models to simulate snow cover correctly. The agreement between the datasets differs between the accumulation and ablation periods, with the latter one presenting the greatest challenge for the RCMs. Given the dominant role of land surface processes in the simulation of snow cover during the ablation period, the results suggest that the choice of the land surface model is more critical for the representation of SASI than the atmospheric model during this time period.