Articles | Volume 9, issue 9
https://doi.org/10.5194/gmd-9-2925-2016
https://doi.org/10.5194/gmd-9-2925-2016
Model evaluation paper
 | 
31 Aug 2016
Model evaluation paper |  | 31 Aug 2016

Large-eddy simulation and stochastic modeling of Lagrangian particles for footprint determination in the stable boundary layer

Andrey Glazunov, Üllar Rannik, Victor Stepanenko, Vasily Lykosov, Mikko Auvinen, Timo Vesala, and Ivan Mammarella

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Cited articles

Anderson, P. S.: Measurement of Prandtl number as a function of Richardson number avoiding self-correlation, Bound.-Lay. Meteorol., 131, 345–362, https://doi.org/10.1007/s10546-009-9376-4, 2009.
Banta, R. M., Pichugina, Y. L., and Brewer, W. A.: Turbulent Velocity-Variance Profiles in the Stable Boundary Layer Generated by a Nocturnal Low-Level Jet, J. Atmos. Sci., 63, 700–2719, https://doi.org/10.1175/JAS3776.1, 2006.
Barad, M.: Project Prairie Grass, a field program in diffusion, vol 2. Technical Report Geophysical Research Papers No. 59, TR-58-235(II)m Air Force Cambridge Research Center, Bedford, 209 pp., http://www.jsirwin.com/PGrassVolumeII.pdf, 1958.
Bardina, J., Ferziger, J. H., and Reynolds, W. C.: Improved subgrid scale models for large-eddy simulation, Am. Inst. Aeronaut. Astronaut., paper 80-1357, https://doi.org/10.2514/6.1980-1357, 1980.
Basu, S. and Porté-Agel, F.: Large-Eddy Simulation of Stably Stratified Atmospheric Boundary Layer Turbulence: A Scale-Dependent Dynamic Modeling Approach, J. Atmos. Sci., 63, 2074–2091, https://doi.org/10.1175/JAS3734.1, 2006.
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Short summary
Large-eddy simulation (LES) and Lagrangian stochastic modeling of passive particle dispersion were applied to the scalar flux footprint determination in the stable atmospheric boundary layer. The footprint functions obtained in LES were compared with the functions calculated with the use of first-order single-particle Lagrangian stochastic models (LSMs) and zeroth-order Lagrangian stochastic models - the random displacement models (RDMs).