Section: New Results

Stochastic Downscaling Method

Participants : Antoine Rousseau, Claire Chauvin.

In collaboration with TOSCA (Inria Sophia-Antipolis), LMD (Ecole Polytechnique) and CETE (Clermont-Ferrand), we investigate a new method for the numerical simulation of the wind at small scales. Thanks to boundary data provided at large scales by the weather forecasting code MM5 , we propose a Langevin model that rules the behavior of stochastic particles. The development of this model, called SDM (Stochastic Downscaling Method), is funded by ADEME (Agence de Développement de l'Écologie et de la Maîtrise de l'Énergie).

After spending 6 months (January-June) in Sophia-Antipolis (EPI TOSCA), Claire Chauvin joined MOISE in July 2008. Together with Antoine Rousseau and co-authors, they obtained some encouraging numerical results on SDM that have been published in [2] . Since then, a review paper has been submitted with co-authors of TOSCA and new investigations started in order to compare numerical results provided by SDM and outputs obtained thanks to large eddy simulations (LES).