Stochastic superparameterization in quasigeostrophic turbulence

DOI10.1016/j.jcp.2013.09.020zbMath1349.76107DBLPjournals/jcphy/GroomsM14arXiv1310.1474OpenAlexW2097396498WikidataQ61785911 ScholiaQ61785911MaRDI QIDQ349249

Andrew J. Majda, Ian Grooms

Publication date: 5 December 2016

Published in: Journal of Computational Physics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1310.1474

zbMATH Keywords

multi-scale algorithmsstochastic backscatterefficient subgrid scale closure

Mathematics Subject Classification ID

Hydrology, hydrography, oceanography (86A05) Statistical turbulence modeling (76F55) Meteorology and atmospheric physics (86A10) Computational methods for problems pertaining to geophysics (86-08)

Related Items (14)

Geophysical flows under location uncertainty, Part I Random transport and general models ⋮ Numerical Schemes for Stochastic Backscatter in the Inverse Cascade of Quasigeostrophic Turbulence ⋮ New perspectives on superparameterization for geophysical turbulence ⋮ Testing of kinetic energy backscatter parameterizations in the NEMO ocean model ⋮ A causality-based learning approach for discovering the underlying dynamics of complex systems from partial observations with stochastic parameterization ⋮ Energy-conserving Galerkin approximations for quasigeostrophic dynamics ⋮ Initial investigations of precipitating quasi-geostrophic turbulence with phase changes ⋮ Stochastic Superparameterization and Multiscale Filtering of Turbulent Tracers ⋮ Ensemble Kalman filters for dynamical systems with unresolved turbulence ⋮ On energy exchanges between eddies and the mean flow in quasigeostrophic turbulence ⋮ Parameter estimation in the stochastic superparameterization of two-layer quasigeostrophic flows. Estimation of subgrid-scale modeling parameters in the stochastic superparameterization of two-layer quasigeostrophic turbulence ⋮ On dynamically unresolved oceanic mesoscale motions ⋮ An information-theoretic framework for improving imperfect dynamical predictions via multi-model ensemble forecasts ⋮ Multiscale Methods for Data Assimilation in Turbulent Systems

Uses Software

• CRCP

Cites Work

• New perspectives on superparameterization for geophysical turbulence
• A statistically accurate modified quasilinear Gaussian closure for uncertainty quantification in turbulent dynamical systems
• Stochastic superparameterization in a one-dimensional model for wave turbulence
• A stochastic multicloud model for tropical convection
• CRCP: a cloud resolving convection parameterization for modeling the tropical convecting atmosphere
• A new algorithm with plane waves and wavelets for random velocity fields with many spatial scales
• Additive Runge-Kutta schemes for convection-diffusion-reaction equations
• Automatic control and adaptive time-stepping
• Stochastic subgrid parameterizations for atmospheric and oceanic flows
• Mathematical test models for superparametrization in anisotropic turbulence
• Convection of Microstructure and Related Problems
• Pair dispersion over an inertial range spanning many decades
• Efficient stochastic superparameterization for geophysical turbulence
• Test Models for Filtering with Superparameterization
• Turbulence in fluids.

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