Articles | Volume 17, issue 11
Research article
02 Jun 2017
Research article |  | 02 Jun 2017

A new downscaling method for sub-grid turbulence modeling

Lucie Rottner, Christophe Baehr, Fleur Couvreux, Guylaine Canut, and Thomas Rieutord

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Subject: Dynamics | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
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Cited articles

Andrews, N. F.: Simulating the diurnal cycle of the atmospheric boundary layer using large-eddy simulation with vertical adaptive mesh refinement, PhD thesis, The University of Utah, Utah, 2012.
Baehr, C.: Stochastic modeling and filtering of discrete measurements for a turbulent field, Application to measurements of atmospheric wind, Int. J. Mod. Phys. B, 23, 5424–5433, 2009.
Baehr, C.: Nonlinear filtering for observations on a random vector field along a random path. Application to atmospheric turbulent velocities, ESAIM-Math. Model. Num., 44, 921–945, 2010.
Bally, V. and Talay, D.: The law of the Euler scheme for stochastic differential equations, Probab. Theory Rel., 104, 43–60, 1996.
Bernardin, F., Bossy, M., Chauvin, C., Drobinski, P., Rousseau, A., and Salameh, T.: Stochastic downscaling method: application to wind refinement, Stoch. Env. Res. Risk A., 23, 851–859, 2009.
Short summary
In this study we explore a new way to model sub-grid turbulence using particle systems. The ability of particle systems to model small-scale turbulence is evaluated using high-resolution numerical simulations performed with the atmospheric model Meso-NH. The study shows that the particle system is able to reproduce much finer turbulent structures than the high-resolution simulations. It also provides an estimate of the effective spatial and temporal resolution of the numerical models.
Final-revised paper