Preprints
https://doi.org/10.5194/tc-2022-3
https://doi.org/10.5194/tc-2022-3
 
25 Jan 2022
25 Jan 2022
Status: a revised version of this preprint was accepted for the journal TC and is expected to appear here in due course.

GABLS4 intercomparison of snow models at Dome C in Antarctica

Patrick Le Moigne1, Eric Bazile1, Anning Cheng3, Emanuel Dutra4, John Edwards2, William Maurel1, Irina Sandu5, Olivier Traullé8, Etienne Vignon6, Ayrton Zadra7, and Weizhong Zheng3 Patrick Le Moigne et al.
  • 1CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
  • 2Met Office, FitzRoy Road, Exeter, UK
  • 3IMSG, Inc.@EMC/NCEP/NOAA, College Park, Maryland, United States
  • 4Instituto Português do Mar e da Atmosfera, Lisbon, Portugal
  • 5European Centre for Medium-Range Weather Forecasts, reading, UK
  • 6Laboratoire de Météorologie Dynamique/IPSL/Sorbonne Université/CNRS, UMR 8539, Paris, France
  • 7Atmospheric Numerical Weather Prediction Research Section, Environment and Climate Change Canada, Dorval, Quebec, Canada
  • 8Direction des Systèmes d’Observation, Météo-France, Toulouse, France

Abstract. The Antarctic Plateau, characterized by cold and dry weather conditions with very little precipitation, is mostly covered by snow at the surface. This paper describes an intercomparison of snow models, of varying complexity, used for numerical weather prediction or academic research. The results of offline numerical simulations, carried out during 15 days in 2009, show that the simplest models are able to reproduce the surface temperature as well as the most complex models provided that their surface parameters are well chosen. Furthermore, it is shown that the diversity of the surface parameters of the models strongly impacts the numerical simulations, in particular the temporal variability of the surface temperature and the components of the surface energy balance. The models tend to overestimate the surface temperature by 2–5 K at night and underestimate it by 2 K during the day. The observed and simulated turbulent latent heat fluxes are small, of the order of a few W m−2, with a tendency to underestimate, while the sensible heat fluxes are in general too intense at night as well as during the day. Finally, it is shown that the most complex multi-layer models are able to reproduce well the propagation of the daily diurnal wave, and that the snow temperature profiles in the snowpack are very close to the measurements carried out on site.

Patrick Le Moigne et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2022-3', John King, 16 Feb 2022
    • AC1: 'Reply on RC1', Patrick Le Moigne, 24 Mar 2022
  • RC2: 'Comment on tc-2022-3', Richard L.H. Essery, 20 Feb 2022
    • AC2: 'Reply on RC2', Patrick Le Moigne, 24 Mar 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2022-3', John King, 16 Feb 2022
    • AC1: 'Reply on RC1', Patrick Le Moigne, 24 Mar 2022
  • RC2: 'Comment on tc-2022-3', Richard L.H. Essery, 20 Feb 2022
    • AC2: 'Reply on RC2', Patrick Le Moigne, 24 Mar 2022

Patrick Le Moigne et al.

Patrick Le Moigne et al.

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Short summary
This paper describes an intercomparison of snow models, of varying complexity, used for numerical weather prediction or academic research. The results show that the simplest models are able, under certain conditions, to reproduce the surface temperature as well as the most complex models. Moreover, the diversity of surface parameters of the models has a strong impact on the temporal variability of the components of the simulated surface energy balance.