Reduction methods in climate dynamics—A brief review

Hummel, Felix; Ashwin, Peter; Kuehn, Christian

doi:10.1016/j.physd.2023.133678

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2023

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“…Another direction of research points toward the investigations of systems with a large numbers of degrees of freedom, e.g. models relevant to climate dynamics [HAK23], or small systems of interest in modern nanotechnologies, such as biomolecular motors [WKST16].…”

Section: Discussionmentioning

confidence: 99%

Model reduction of Brownian oscillators: quantification of errors and long-time behavior

Colangeli

Duong

Muntean

2023

J. Phys. A: Math. Theor.

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A procedure for model reduction of stochastic ordinary diﬀerential equations with additive noise was recently introduced in [CDM22], based on the Invariant Manifold method and on the Fluctuation-Dissipation relation. A general question thus arises as to whether one can rigorously quantify the error entailed by the use of the reduced dynamics in place of the original one. In this work we provide explicit formulae and estimates of the error in terms of the Wasserstein distance, both in the presence or in the absence of a sharp time-scale separation between the variables to be retained or eliminated from the description, as well as in the long-time behaviour.

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Section: Discussionmentioning

confidence: 99%