A. Alexanderian

A. Bourlioux

A. H. Jazwinski

A. J. Chorin

A. J. Majda

A. Majda

Andrew J. Majda

B. Gershgorin

B. K. Oksendal

C. E. Leith

C. Franzke

C. Gardiner

C. K. Wikle

C. L. Pettit

C. Prévôt

D. Frierson

D. Giannakis

D. M. Titterington

D. Xiu

E. N. Lorenz

E. S. Epstein

G. Branstator

G. E. Karnidakis

H. G. Matthies

H. N. Najm

H. Teng

I. Horenko

J. D. Neelin

J. Harlim

J. Neelin

J. P. Gollub

J. Von Neumann

Jayesh

K. A. Emanuel

K. R. Sreenivasan

L. Arnold

L. M. Smith

M. A. Katsoulakis

M. Avellaneda

M. Branicki

M. D. Chekroun

M. Hairer

M. I. Jordan

Michal Branicki

N. Peters

N. Wiener

O. P. Le Maître

P. E. Kloeden

P. Frauenfelder

R. G. Ghanem

R. H. Cameron

R. H. Kraichnan

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Crossref

Discrete and Continuous Dynamical Systems

Lessons in uncertainty quantification for turbulent dynamical systems

The modus operandi of modern applied mathematics in developing very recent mathematical strategies for uncertainty quantification in partially observed high-dimensional turbulent dynamical systems is emphasized here. The approach involves the synergy of rigorous mathematical guidelines with a suite of physically relevant and progressively more complex test models which are mathematically tractable while possessing such important features as the two-way coupling between the resolved dynamics and the turbulent uxes, intermittency and positive Lyapunov exponents, eddy diffusivity parameterization and turbulent spectra. A large number of new theoretical and computational phenomena which arise in the emerging statistical-stochastic framework for quantifying and mitigating model error in imperfect predictions, such as the existence of information barriers to model improvement, are developed and reviewed here with the intention to introduce mathematicians, applied mathematicians, and scientists to these remarkable emerging topics with increasing practical importance

Majda, A.J.

Branicki, M.

Edinburgh Research Explorer

Lessons in uncertainty quantification for turbulent dynamical systems

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Edinburgh Research Explorer