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Intercomparison of Large-Eddy Simulations of the Antarctic Boundary Layer for Very Stable Stratification

Boundary-Layer Meteorology volume 176, pages 369–400 (2020)Cite this article

Abstract

In polar regions, where the boundary layer is often stably stratified, atmospheric models produce large biases depending on the boundary-layer parametrizations and the parametrization of the exchange of energy at the surface. This model intercomparison focuses on the very stable stratification encountered over the Antarctic Plateau in 2009. Here, we analyze results from 10 large-eddy-simulation (LES) codes for different spatial resolutions over 24 consecutive hours, and compare them with observations acquired at the Concordia Research Station during summer. This is a challenging exercise for such simulations since they need to reproduce both the 300-m-deep convective boundary layer and the very thin stable boundary layer characterized by a strong vertical temperature gradient (10 K difference over the lowest 20 m) when the sun is low over the horizon. A large variability in surface fluxes among the different models is highlighted. The LES models correctly reproduce the convective boundary layer in terms of mean profiles and turbulent characteristics but display more spread during stable conditions, which is largely reduced by increasing the horizontal and vertical resolutions in additional simulations focusing only on the stable period. This highlights the fact that very fine resolution is needed to represent such conditions. Complementary sensitivity studies are conducted regarding the roughness length, the subgrid-scale turbulence closure as well as the resolution and domain size. While we find little dependence on the surface-flux parametrization, the results indicate a pronounced sensitivity to both the roughness length and the turbulence closure.

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Notes

  1. Commonwealth Scientific and Industrial Research Organization LES model (Huang and Bou-Zeid 2013).

  2. Matlab LES model based on the locally-averaged scale-dependent dynamic SGS modelling approach(Basu and Porte-Agel 2006).

  3. The Mesoscale Non-Hydrostatic model (Lac et al. 2018).

  4. The Parallelized Large-Eddy Simulation Model (Maronga et al. 2015, 2020a).

  5. The Met Office NERC Cloud model, a re-write of the UK Met-Office Large-Eddy Model (Edwards et al. 2014, Brown et al. 2015).

  6. Extended Large-Eddy Microscale Model (Fuka and Brechler 2011, Fuka 2015).

  7. Computational fluid dynamics code made for direct numerical simulation and large-eddy simulation (Van Heerwaarden et al. 2018).

  8. This is the classical cut-off frequency used for flux computation, and, using ogive computation, it was checked that this is appropriate for turbulence measurements in this situation.

  9. Dutch Atmosphere Large-Eddy Simulation (Heus et al. 2010).

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Acknowledgements

The first author would like to acknowledge E Coppa and B Alaoui who worked on a small internship on the first analysis of the intercomparison of the experiment 3 runs. The authors are also grateful to P LeMoigne, O Traullé, F Favot and W Maurel for their help in preparation of the GABLS4 intercomparaison and thanks B Holtslag for its promotion, and B. Holtslag and B Van de Wiel for the numerous and constructive discussions.

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Authors and Affiliations

  1. CNRM, Université de Toulouse Météo-France CNRS, 31057, Toulouse, France

    Fleur Couvreux, Eric Bazile, Quentin Rodier & Guylaine Canut

  2. Institute of Meteorology and Climatology, Leibniz University Hannover, Hannover, Germany

    Björn Maronga

  3. Geophysical Institute, University of Bergen, Bergen, Norway

    Björn Maronga

  4. Department of Mechanical Engineering, University of Connecticut, Storrs, USA

    Georgios Matheou

  5. Joint Institute for Regional Earth System Science and Engineering, University of California and Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA

    Maria J. Chinita

  6. Faculdade de Ciencias, Instituto Dom Luiz, Universidade de Lisboa, Lisbon, Portugal

    Maria J. Chinita

  7. Met Office, Exeter, UK

    John Edwards

  8. Wageningen University and Research, Wageningen, The Netherlands

    Bart J. H. van Stratum, Chiel C. van Heerwaarden & Arnold F. Moene

  9. Oceans and Atmosphere, CSIRO, Canberra, Australia

    Jing Huang

  10. IMSG Inc./Environmental Modeling Center, National Centers for Environmental Protection, Center for Weather and Climate Prediction, College Park, USA

    Anning Cheng

  11. Delft University of Technology, Delft, The Netherlands

    Sukanta Basu

  12. Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic

    Vladimir Fuka

  13. Department of Civil and Environmental Engineering, Princeton University, Princeton, USA

    Elie Bou-Zeid

  14. LTE, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Etienne Vignon

  15. Institut des Géosciences de l’Environnement CNRS, Université Grenoble Alpes, Grenoble, France

    Etienne Vignon

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  1. Fleur Couvreux
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  2. Eric Bazile
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  13. Vladimir Fuka
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  16. Guylaine Canut
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Correspondence to Fleur Couvreux.

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Appendix 1: Initial Conditions

Appendix 1: Initial Conditions

Initial conditions and forcing for experiments 1, 2 and 3 of the GABLS4 intercomparison are provided in Table 5.

Table 5 Description of the initial profiles and forcing for the runs initialized at 0000 UTC or at 1000 UTC as well as the time series of the prescribed surface temperature
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Couvreux, F., Bazile, E., Rodier, Q. et al. Intercomparison of Large-Eddy Simulations of the Antarctic Boundary Layer for Very Stable Stratification. Boundary-Layer Meteorol 176, 369–400 (2020). https://doi.org/10.1007/s10546-020-00539-4

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