Large-scale flows under location uncertainty: a consistent stochastic framework
|Author(s)||Chapron Bertrand1, Derian P.2, Memin E.2, Resseguier Valentin1, 2|
|Affiliation(s)||1 : IFREMER, LOPS, Plouzane, France.
2 : INRIA, IRMAR, Campus Univ Beaulieu, Rennes, France.
|Source||Quarterly Journal Of The Royal Meteorological Society (0035-9009) (Wiley), 2018-01 , Vol. 144 , N. 710 , P. 251-260|
|WOS© Times Cited||25|
|Keyword(s)||large-scale flow modelling, stochastic parametrization, modelling under location uncertainty, stochastic Lorenz model, stochastic transport|
Using a classical example, the Lorenz-63 model, an original stochastic framework is applied to represent large-scale geophysical flow dynamics. Rigorously derived from a reformulated material derivative, the proposed framework encompasses several meaningful mechanisms to model geophysical flows. The slightly compressible set-up, as treated in the Boussinesq approximation, yields a stochastic transport equation for the density and other related thermodynamical variables. Coupled to the momentum equation through a forcing term, the resulting stochastic Lorenz-63 model is derived consistently. Based on such a reformulated model, the pertinence of this large-scale stochastic approach is demonstrated over classical eddy-viscosity based large-scale representations.