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Stochastic Downscaling Method: Application to Wind Refinement

Frédéric Bernardin 1 Mireille Bossy 2 Claire Chauvin 3 Philippe Drobinski 4 Antoine Rousseau 3, * Tamara Salameh 4
* Corresponding author
2 TOSCA
CNRS - Centre National de la Recherche Scientifique : UMR7502, INPL - Institut National Polytechnique de Lorraine, Université Nancy 2, UHP - Université Henri Poincaré - Nancy 1, CRISAM - Inria Sophia Antipolis - Méditerranée , INRIA Lorraine
3 MOISE - Modelling, Observations, Identification for Environmental Sciences
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology
Abstract : In this article, we propose a new stochastic downscaling method: provided a numerical prediction of wind at large scale, we aim to improve the approximation at small scales thanks to a local stochastic model. We first recall the framework of a Lagrangian stochastic model borrowed from S.B. Pope. Then, we adapt it to our meteorological framework, both from the theoretical and numerical viewpoints. Finally, we present some promising numerical results corresponding to the simulation of wind over the Mediterranean Sea.
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Submitted on : Friday, November 7, 2008 - 11:46:30 AM
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Frédéric Bernardin, Mireille Bossy, Claire Chauvin, Philippe Drobinski, Antoine Rousseau, et al.. Stochastic Downscaling Method: Application to Wind Refinement. Stochastic Environmental Research and Risk Assessment, Springer Verlag (Germany), 2009, 23 (6), pp.851-859. ⟨10.1007/s00477-008-0276-9⟩. ⟨inria-00337526⟩

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