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The Cryosphere An interactive open-access journal of the European Geosciences Union
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Volume 9, issue 4
The Cryosphere, 9, 1373–1383, 2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
The Cryosphere, 9, 1373–1383, 2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 30 Jul 2015

Research article | 30 Jul 2015

Comparison between observed and simulated aeolian snow mass fluxes in Adélie Land, East Antarctica

C. Amory1,2,3,4, A. Trouvilliez1,2,3,4,5, H. Gallée1,2, V. Favier1,2, F. Naaim-Bouvet3,4, C. Genthon1,2, C. Agosta6, L. Piard1,2, and H. Bellot3,4 C. Amory et al.
  • 1University of Grenoble Alpes, LGGE, 38041 Grenoble, France
  • 2CNRS, LGGE, UMR5183, 38401 Grenoble, France
  • 3University of Grenoble Alpes, IRSTEA, 38041 Grenoble, France
  • 4IRSTEA, UR ETNA, 38402 Saint-Martin d'Hères, France
  • 5Cerema-DTecEMF, 29280 Plouzané, France
  • 6University of Liège, Department of Geography, 4020 Liège, Belgium

Abstract. Using the original setup described in Gallée et al. (2013), the MAR regional climate model including a coupled snowpack/aeolian snow transport parameterization, was run at a fine spatial (5 km horizontal and 2 m vertical) resolution over 1 summer month in coastal Adélie Land. Different types of feedback were taken into account in MAR including drag partitioning caused by surface roughness elements. Model outputs are compared with observations made at two coastal locations, D17 and D47, situated respectively 10 and 100 km inland. Wind speed was correctly simulated with positive values of the Nash test (0.60 for D17 and 0.37 for D47) but wind velocities above 10 m s−1 were underestimated at both D17 and D47; at D47, the model consistently underestimated wind velocity by 2 m s−1. Aeolian snow transport events were correctly reproduced with the right timing and a good temporal resolution at both locations except when the maximum particle height was less than 1 m. The threshold friction velocity, evaluated only at D17 for a 7-day period without snowfall, was overestimated. The simulated aeolian snow mass fluxes between 0 and 2 m at D47 displayed the same variations but were underestimated compared to the second-generation FlowCaptTM values, as was the simulated relative humidity at 2 m above the surface. As a result, MAR underestimated the total aeolian horizontal snow transport for the first 2 m above the ground by a factor of 10 compared to estimations by the second-generation FlowCaptTM. The simulation was significantly improved at D47 if a 1-order decrease in the magnitude of z0 was accounted for, but agreement with observations was reduced at D17. Our results suggest that z0 may vary regionally depending on snowpack properties, which are involved in different types of feedback between aeolian transport of snow and z0.

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