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.

Highlights

  • Snow is an important part of the climate system as it regulates the temperature of the Earth’s surface via its effect on surface albedo and surface fluxes

  • We investigate the ability of an ensemble of regional climate models (RCMs) to represent snow cover and the radiative forcing from the snow albedo effect (SASI) over Europe, including a comparison between midand high-latitude regions

  • 3.1 Snow Albedo Sensitivity Index (SASI) in satellite observations, reanalyses and RCMs over Europe In Figure 2, we first show the geographical distribution of SASI over Europe based on satellite observations, the ERA5-Land reanalysis and the Land Use and Climate Across Scale (LUCAS) models from January to June, averaged over the 1986-2015 period

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Summary

Introduction

Snow is an important part of the climate system as it regulates the temperature of the Earth’s surface via its effect on surface albedo and surface fluxes. The direct impact of snow on the atmosphere is known as the snow albedo effect (SAE; Xu and Dirmeyer, 2011, 2013), where the presence of snow affects the land surface energy budget and influences the local climate, modifying air temperature. The SAF represents changes in surface albedo from cooling (warming) that can cause decreases (increases) in absorbed solar radiation, amplifying the initial cooling (warming) It is an important driver for regional climate change in Northern Hemisphere land areas. We investigate the ability of an ensemble of RCMs to represent snow cover and the radiative forcing from the snow albedo effect (SASI) over Europe, including a comparison between midand high-latitude regions.

The LUCAS experiments
Models and configurations
Snow-buried fraction of vegetation in models
Reanalyses and remote sensing data
Snow Albedo Sensitivity Index (SASI) and geographical scope
SASI in satellite observations, reanalyses and RCMs over Europe
Transition between the accumulation and ablation periods
Inter-model differences in SASI
Conclusion
Figures and Tables
Full Text
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