Modeling drifting snow in Antarctica with a regional climate model: 1. Methods and model evaluation

Abstract

[1] To simulate the impact of drifting snow on the lower atmosphere, surface characteristics and surface mass balance (SMB) of the Antarctic ice sheet regional atmospheric climate model (RACMO2.1/ANT) with horizontal resolution of 27 km is coupled to a drifting snow routine and forced by ERA-Interim fields at its lateral boundaries . This paper evaluates the near-surface and drifting snow climate of RACMO2.1/ANT. Modeled near-surface wind speed (squared correlation coefficient R 2 = 0.64) and temperature (R 2 = 0.93) agree well with observations. Wind speed is underestimated in topographically complex areas, where observed wind speeds are locally very high (>20 m s À1 ). Temperature is underestimated in winter in coastal areas due to an underestimation of downward longwave radiation. Near-surface temperature and wind speed are not significantly affected by the inclusion of drifting snow in the model. In contrast, relative humidity with respect to ice increases in regions with strong drifting snow and becomes more consistent with the observations. Drifting snow frequency is the only observable parameter to directly validate drifting snow results; therefore, we derived an empirical relation for fresh snow density, as a function of wind speed and temperature, which determines the threshold wind speed for drifting snow. Modeled drifting snow frequencies agree well with in situ measurements and novel estimates from remote sensing. Finally, we show that including drifting snow is essential to obtaining a realistic extent and spatial distribution of ablation (SMB < 0) areas.

Impact of model resolution on simulated wind, drifting snow and surface mass balance in Terre Adélie, East Antarctica

“…Moreover, both SU ds and ER ds are included as explicit terms in the SMB scheme of RACMO2.1/ANT (Eqn (1)). By removing or depositing mass from the top snow layer, both processes can impact its density, which, in turn, limits the potential for drifting snow (Lenaerts and others, 2012b). Lenaerts and others (2012b) provide additional details of the numerical set-up and a detailed evaluation of the near-surface climate and drifting snow characteristics.…”

“…By removing or depositing mass from the top snow layer, both processes can impact its density, which, in turn, limits the potential for drifting snow (Lenaerts and others, 2012b). Lenaerts and others (2012b) provide additional details of the numerical set-up and a detailed evaluation of the near-surface climate and drifting snow characteristics. Among other things, they show that the model, with a horizontal resolution of 27 km, is able to realistically simulate the near-surface climate (Lenaerts and Van den Broeke, 2012) and SMB (Lenaerts and others, 2012a) of the Antarctic ice sheet, without the need for post-calibration.…”

“…We run the regional atmospheric climate model RACMO2.1/ANT for 1 year (2009) at high horizontal resolution (5.5 km). We compare the wind climate, drifting snow climate and SMB with the output of the previous run with the same model version at 27 km (Lenaerts and others, 2012b), and evaluate the differences using available observations.…”

“…The slope in topography also determines the strength of the katabatic wind and resulting drifting snow. Snowdrift erosion, ER ds , represents the horizontal divergence of the wind transport of snow (Lenaerts and others, 2012b) and strongly depends on spatial variations in wind speed. Lenaerts and Van den Broeke (2012) demonstrated that, at a horizontal resolution of 27 km, ER ds is only significant (>10 mm w.e.…”

Sensitivity of Greenland Ice Sheet surface mass balance to surface albedo parameterization: a study with a regional climate model

“…Table 1 summarizes the various albedo experiments with RACMO2. The ANT settings are the settings used for the Antarctica integration (Kuipers Munneke et al, 2011;Lenaerts et al, 2012). With every new experiment one parameter is changed.…”