Articles | Volume 16, issue 6
https://doi.org/10.5194/tc-16-2183-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-2183-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
GABLS4 intercomparison of snow models at Dome C in Antarctica
Patrick Le Moigne
CORRESPONDING AUTHOR
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Eric Bazile
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Anning Cheng
IMSG, Inc.@EMC/NCEP/NOAA, College Park, Maryland, USA
Emanuel Dutra
Instituto Português do Mar e da Atmosfera, Lisbon, Portugal
John M. Edwards
Met Office, FitzRoy Road, Exeter, UK
William Maurel
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Irina Sandu
Research department, European Centre for Medium-Range Weather Forecasts, Reading, UK
Olivier Traullé
Direction des Systèmes d'Observation, Météo-France,
Toulouse, France
Etienne Vignon
Laboratoire de Météorologie Dynamique/IPSL/Sorbonne
Université/CNRS, UMR 8539, Paris, France
Ayrton Zadra
Atmospheric Numerical Weather Prediction Research Section, Environment
and Climate Change Canada, Dorval, Quebec, Canada
Weizhong Zheng
IMSG, Inc.@EMC/NCEP/NOAA, College Park, Maryland, USA
Data sets
GABLS4, snow model intercomparison Patrick Le Moigne https://doi.org/10.5281/zenodo.5814726
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, under certain conditions, able to reproduce the surface temperature just 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.
This paper describes an intercomparison of snow models, of varying complexity, used for...