Stochastic Lagrangian models for turbulent flows. Application to a downscaling method for wind forecast at small scales.
propose a new downscaling method for the simulation of wind at small
scales. Based on an existing numerical weather prediction model, we
introduce a Langevin system as a local Lagrangian model aimed to
estimate the distribution of the wind at small scales. We borrow
and adapt stochastic models proposed by Stephen B. Pope that have been
widely used in the framework of multiphasic fluids.
brief description of the Pope models, we present our adaptation to the
meteorological downscaling problem, the associated numerical
algorithm and some numerical results (joint work with F. Bernardin, C.
Chauvin, P. Drobinski, A. Rousseau, T. Salameh) .
The last part
of this talk will be devoted to the study of the well-posedness of a
simplified Lagrangian model and its confined version in a spatial
sub-domain which is used in the downscaling problem (joint work with