Geophysical flows under location uncertainty, Part II Quasi-geostrophy and efficient ensemble spreading
|Copyright||2017 Informa UK Limited|
|Author(s)||Resseguier Valentin1, 2, Memin E.1, Chapron Bertrand2|
|Affiliation(s)||1 : Irstea, Fluminance Grp, IRMAR, Inria, Rennes, France.
2 : IFREMER, LOPS, Plouzane, France.
|Source||Geophysical And Astrophysical Fluid Dynamics (0309-1929) (Taylor & Francis Ltd), 2017 , Vol. 111 , N. 3 , P. 177-208|
|WOS© Times Cited||8|
|Keyword(s)||Stochastic sub-grid parameterization, Uncertainty quantification, ensemble forecasts|
Models under location uncertainty are derived assuming that a component of the velocity is uncorrelated in time. The material derivative is accordingly modified to include an advection correction, inhomogeneous and anisotropic diffusion terms and a multiplicative noise contribution. In this paper, simplified geophysical dynamics are derived from a Boussinesq model under location uncertainty. Invoking usual scaling approximations and a moderate influence of the subgrid terms, stochastic formulations are obtained for the stratified Quasi-Geostrophy and the Surface Quasi-Geostrophy models. Based on numerical simulations, benefits of the proposed stochastic formalism are demonstrated. A single realization of models under location uncertainty can restore small-scale structures. An ensemble of realizations further helps to assess model error prediction and outperforms perturbed deterministic models by one order of magnitude. Such a high uncertainty quantification skill is of primary interests for assimilation ensemble methods. MATLAB® code examples are available online.