Preprints
https://doi.org/10.5194/egusphere-2022-523
https://doi.org/10.5194/egusphere-2022-523
 
22 Jul 2022
22 Jul 2022
Status: this preprint is open for discussion.

On the interaction of stochastic forcing and regime dynamics

Joshua Dorrington1,2 and Tim Palmer1 Joshua Dorrington and Tim Palmer
  • 1Atmospheric, Oceanic, and Planetary Physics, University of Oxford, Oxford, UK
  • 2Institute for Meteorology and Climate (IMK-TRO), Karlsruher Institute of Technology, Germany

Abstract. In this paper we investigate the curious ability of stochastic forcing to increase the persistence of regimes, in a low-order, stochastically forced system. In recent years, evidence from both simple models and climate simulations have suggested that stochastic forcing can act as a stabilising force to increase regime persistence, but the mechanisms driving this potential reinforcement are unclear. Using a six-mode truncation of a barotropic β-plane model, featuring transitions between analogues of zonal and blocked flow conditions, we show that moderate levels of fast-varying stochastic forcing can increase the low-frequency variability of the system, and act asymmetrically to increase the persistence of certain regimes. We show that the presence of a deterministically-inaccessible unstable fixed point, and the low-dimensionality of the flow during blocking, are vital dynamical components that allow this stochastic persistence to occur. We present a simple geometric argument that explains how stochastic forcing can slow the growth of instabilities, which may have more general applicability in understanding stochastic chaotic systems.

Joshua Dorrington and Tim Palmer

Status: open (until 16 Sep 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on egusphere-2022-523', Paul PUKITE, 22 Jul 2022 reply

Joshua Dorrington and Tim Palmer

Joshua Dorrington and Tim Palmer

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Short summary
Atmospheric models often include random forcings, which aim to replicate the impact of processes too small to be resolved. Recent results in simple atmospheric models suggest that this random forcing can actually stabilise certain slow-varying aspects of the system, which could provide a path for resolving known errors in our models. We use randomly-forced simulations of a 'toy' chaotic system and theoretical arguments to explain why this strange effect occurs: at least in simple models.