A mathematical framework for stochastic climate models

Research output: Contribution to journalArticle

Abstract

There has been a recent burst of activity in the atmosphere-ocean sciences community in utilizing stable linear Langevin stochastic models for the unresolved degrees of freedom in stochastic climate prediction. Here a systematic mathematical strategy for stochastic climate modeling is developed, and some of the new phenomena in the resulting equations for the climate variables alone are explored. The new phenomena include the emergence of both unstable linear Langevin stochastic models for the climate mean variables and the need to incorporate both suitable nonlinear effects and multiplicative noise in stochastic models under appropriate circumstances. All of these phenomena are derived from a systematic self-consistent mathematical framework for eliminating the unresolved stochastic modes that is mathematically rigorous in a suitable asymptotic limit. The theory is illustrated for general quadratically nonlinear equations where the explicit nature of the stochastic climate modeling procedure can be elucidated. The feasibility of the approach is demonstrated for the truncated equations for barotropic flow with topography. Explicit concrete examples with the new phenomena are presented for the stochastically forced three-mode interaction equations. The conjecture of Smith and Waleffe [Phys. Fluids 11 (1999), 1608-1622] for stochastically forced three-wave resonant equations in a suitable regime of damping and forcing is solved as a byproduct of the approach. Examples of idealized climate models arising from the highly inhomogeneous equilibrium statistical mechanics for geophysical flows are also utilized to demonstrate self-consistency of the mathematical approach with the predictions of equilibrium statistical mechanics. In particular, for these examples, the reduced stochastic modeling procedure for the climate variables alone is designed to reproduce both the climate mean and the energy spectrum of the climate variables.

Original languageEnglish (US)
Pages (from-to)891-974
Number of pages84
JournalCommunications on Pure and Applied Mathematics
Volume54
Issue number8
DOIs
StatePublished - Aug 2001

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Climate models
Climate Models
Stochastic models
Climate
Stochastic Model
Statistical mechanics
Stochastic Modeling
Climate Modeling
Statistical Mechanics
Nonlinear equations
Topography
Byproducts
Damping
Geophysical Flows
Mode Interaction
Self-consistency
Fluids
Asymptotic Limit
Prediction
Multiplicative Noise

ASJC Scopus subject areas

  • Mathematics(all)
  • Applied Mathematics

Cite this

A mathematical framework for stochastic climate models. / Majda, Andrew J.; Timofeyev, Ilya; Eijnden, Eric Vanden.

In: Communications on Pure and Applied Mathematics, Vol. 54, No. 8, 08.2001, p. 891-974.

Research output: Contribution to journalArticle

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