Articles | Volume 19, issue 1
Nonlin. Processes Geophys., 19, 9–22, 2012
https://doi.org/10.5194/npg-19-9-2012
Nonlin. Processes Geophys., 19, 9–22, 2012
https://doi.org/10.5194/npg-19-9-2012

Research article 03 Jan 2012

Research article | 03 Jan 2012

Bistable systems with stochastic noise: virtues and limits of effective one-dimensional Langevin equations

V. Lucarini1,2, D. Faranda1, and M. Willeit3 V. Lucarini et al.
  • 1Klimacampus, Institute of Meteorology, Hamburg Universität, Hamburg, Germany
  • 2Department of Mathematics and Statistics, University of Reading, Reading, UK
  • 3Potsdam Institute for Climate Impact Research, Potsdam, Germany

Abstract. The understanding of the statistical properties and of the dynamics of multistable systems is gaining more and more importance in a vast variety of scientific fields. This is especially relevant for the investigation of the tipping points of complex systems. Sometimes, in order to understand the time series of given observables exhibiting bimodal distributions, simple one-dimensional Langevin models are fitted to reproduce the observed statistical properties, and used to investing-ate the projected dynamics of the observable. This is of great relevance for studying potential catastrophic changes in the properties of the underlying system or resonant behaviours like those related to stochastic resonance-like mechanisms. In this paper, we propose a framework for encasing this kind of studies, using simple box models of the oceanic circulation and choosing as observable the strength of the thermohaline circulation. We study the statistical properties of the transitions between the two modes of operation of the thermohaline circulation under symmetric boundary forcings and test their agreement with simplified one-dimensional phenomenological theories. We extend our analysis to include stochastic resonance-like amplification processes. We conclude that fitted one-dimensional Langevin models, when closely scrutinised, may result to be more ad-hoc than they seem, lacking robustness and/or well-posedness. They should be treated with care, more as an empiric descriptive tool than as methodology with predictive power.

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