FN Archimer Export Format PT J TI Geophysical flows under location uncertainty, Part II Quasi-geostrophy and efficient ensemble spreading BT AF RESSEGUIER, Valentin MEMIN, E. CHAPRON, Bertrand AS 1:1,2;2:1;3:2; FF 1:PDG-ODE-LOPS-SIAM;2:;3:PDG-ODE-LOPS-SIAM; C1 Irstea, Fluminance Grp, IRMAR, Inria, Rennes, France. IFREMER, LOPS, Plouzane, France. C2 INRIA, FRANCE IFREMER, FRANCE SI BREST SE PDG-ODE-LOPS-SIAM UM LOPS IN WOS Ifremer jusqu'en 2018 copubli-france IF 1.417 TC 52 UR https://archimer.ifremer.fr/doc/00385/49599/51087.pdf LA English DT Article DE ;Stochastic sub-grid parameterization;Uncertainty quantification;ensemble forecasts AB 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. MATLABĀ® code examples are available online. PY 2017 SO Geophysical And Astrophysical Fluid Dynamics SN 0309-1929 PU Taylor & Francis Ltd VL 111 IS 3 UT 000401010100002 BP 177 EP 208 DI 10.1080/03091929.2017.1312101 ID 49599 ER EF