Low-dimensional reduced-order models for statistical response and uncertainty quantification: barotropic turbulence with topography

DOI10.1016/j.physd.2016.11.006zbMath1378.86007OpenAlexW2555799101MaRDI QIDQ1691154

Di Qi, Andrew J. Majda

Publication date: 15 January 2018

Published in: Physica D (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.physd.2016.11.006

zbMATH Keywords

uncertainty quantificationreduced-order methodsstatistical responsestopographic barotropic system

Mathematics Subject Classification ID

Stochastic functional-differential equations (34K50) Theoretical approximation in context of PDEs (35A35) Meteorology and atmospheric physics (86A10) PDEs in connection with geophysics (35Q86) Integro-partial differential equations (35R09)

Related Items (8)

Machine learning for prediction with missing dynamics ⋮ Rigorous statistical bounds in uncertainty quantification for one-layer turbulent geophysical flows ⋮ Neural Parametric Fokker--Planck Equation ⋮ Strategies for Reduced-Order Models for Predicting the Statistical Responses and Uncertainty Quantification in Complex Turbulent Dynamical Systems ⋮ Predicting observed and hidden extreme events in complex nonlinear dynamical systems with partial observations and short training time series ⋮ Using statistical functionals for effective control of inhomogeneous complex turbulent dynamical systems ⋮ Linear and nonlinear statistical response theories with prototype applications to sensitivity analysis and statistical control of complex turbulent dynamical systems ⋮ Improving the prediction of complex nonlinear turbulent dynamical systems using nonlinear filter, smoother and backward sampling techniques

Cites Work

• Unnamed Item
• An introduction to turbulent dynamical systems in complex systems
• Predicting fat-tailed intermittent probability distributions in passive scalar turbulence with imperfect models through empirical information theory
• Ergodicity of truncated stochastic Navier Stokes with deterministic forcing and dispersion
• An ensemble Kalman filter for statistical estimation of physics constrained nonlinear regression models
• A statistically accurate modified quasilinear Gaussian closure for uncertainty quantification in turbulent dynamical systems
• Linear response theory for statistical ensembles in complex systems with time-periodic forcing
• Dynamic mean flow and small-scale interaction through topographic stress
• Subgrid modelling for geophysical flows
• Intermittency in turbulent diffusion models with a mean gradient
• Systematic forcing of large-scale geophysical flows by eddy-topography interaction
• Nonlinear stability and statistical mechanics of flow over topography
• Statistical dynamics of two-dimensional flow
• The QDIA and regularized QDIA closures for inhomogeneous turbulence over topography
• Link between statistical equilibrium fidelity and forecasting skill for complex systems with model error
• Statistically accurate low-order models for uncertainty quantification in turbulent dynamical systems
• Distinct metastable atmospheric regimes despite nearly Gaussian statistics: A paradigm model
• Inhomogeneous closure and statistical mechanics for Rossby wave turbulence over topography
• Information Theory and Stochastics for Multiscale Nonlinear Systems
• On Information and Sufficiency
• Improving prediction skill of imperfect turbulent models through statistical response and information theory

This page was built for publication: Low-dimensional reduced-order models for statistical response and uncertainty quantification: barotropic turbulence with topography