Direct statistical simulation using generalised cumulant expansions

In recent years, the generalised quasilinear (GQL) approximation has been developed and its efficacy tested against purely quasilinear (QL) approximations. GQL systematically interpolates between QL and fully nonlinear dynamics by employing a generalised Reynolds decomposition. Here, we examine an exact statistical closure for the GQL equations on the doubly periodic $\beta$ -plane. Closure is achieved at second order using a generalised cumulant approach which we term GCE2. GCE2 is shown to yield improved performance over statistical representations of purely QL dynamics (CE2) and thus enables direct statistical simulation of complex mean flows that do not entirely fall within the remit of pure QL theory. Despite the existence of an exact closure, GCE2 like CE2 admits the possibility of a rank instability that leads to differences with statistics obtained from GQL. Recognition of this instability is a necessary step before further progress can be made with the GCE2 statistical closure.

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Publication Details

Journal
Journal of Fluid Mechanics
Published
2024-12-25
DOI
https://doi.org/10.1017/jfm.2024.750
Primary Topic
Model Reduction and Neural Networks
Type
article
Field-Weighted Citation Impact
0.00

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article

Direct statistical simulation using generalised cumulant expansions

J. B. Marston, Steven M. Tobias, Girish V. Nivarti
Journal of Fluid Mechanics
Model Reduction and Neural Networks
article

Direct statistical simulation using generalised cumulant expansions

J. B. Marston, Steven M. Tobias, Girish V. Nivarti
article en

Abstract

In recent years, the generalised quasilinear (GQL) approximation has been developed and its efficacy tested against purely quasilinear (QL) approximations. GQL systematically interpolates between QL and fully nonlinear dynamics by employing a generalised Reynolds decomposition. Here, we examine an exact statistical closure for the GQL equations on the doubly periodic $\beta$ -plane. Closure is achieved at second order using a generalised cumulant approach which we term GCE2. GCE2 is shown to yield improved performance over statistical representations of purely QL dynamics (CE2) and thus enables direct statistical simulation of complex mean flows that do not entirely fall within the remit of pure QL theory. Despite the existence of an exact closure, GCE2 like CE2 admits the possibility of a rank instability that leads to differences with statistics obtained from GQL. Recognition of this instability is a necessary step before further progress can be made with the GCE2 statistical closure.

Journal of Fluid MechanicsVol. 1001
University of Leeds (GB), Brown University (US)
U.S. Department of Energy, Simons Foundation, European Commission, Horizon 2020 Framework Programme
Openalex Percentile: Top 76%
Model Reduction and Neural Networks
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