Abstract

Abstract. Hysteresis diagrams of the Atlantic meridional overturning circulation (AMOC) under freshwater forcing from climate models of intermediate complexity are fitted to a simple model based on the Langevin equation. A total of six parameters are sufficient to quantitatively describe the collapses seen in these simulations. Reversing the freshwater forcing results in asymmetric behaviour that is less well captured and appears to require a more complicated model. The Langevin model allows for comparison between models that display an AMOC collapse. Differences between the climate models studied here are mainly due to the strength of the stable AMOC and the strength of the response to a freshwater forcing.

Highlights

  • The Atlantic meridional overturning circulation (AMOC) is an important circulation in the Atlantic Ocean

  • The AMOC is partly buoyancy-driven by the deep water formations in the North Atlantic subpolar gyre, which produces the North Atlantic Deep Water (NADW) (e.g. Rahmstorf, 2000)

  • We attempt to construct a simple model based on the Langevin equation and fit its dynamics to salt-advection-driven collapse trajectories of the AMOC seen in climate models (Rahmstorf et al, 2005)

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Summary

Introduction

The Atlantic meridional overturning circulation (AMOC) is an important circulation in the Atlantic Ocean. The Langevin equation has been posited before as being suitable to capture the essential dynamics of an AMOC collapse (Ditlevsen and Johnsen, 2010; Berglund and Gentz, 2002). It has been used elsewhere as the basis for describing the dynamics of climate subsystems (Kwasniok and Lohmann, 2009; Livina et al, 2010) and the AMOC in particular (Kleinen et al, 2003; Held and Kleinen, 2004). We attempt to construct a simple model based on the Langevin equation and fit its dynamics to salt-advection-driven collapse trajectories of the AMOC seen in climate models (Rahmstorf et al, 2005).

The Langevin model
Multiple stable AMOC states
Potential description
Stochastic interpretation
AMOC collapse parameter estimation
Parameter estimation
Prior distributions
Fitting EMIC collapse trajectories
Discussion and conclusion
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