Abstract

Abstract. The stability properties of intermediate-order climate models are investigated by computing their Lyapunov exponents (LEs). The two models considered are PUMA (Portable University Model of the Atmosphere), a primitive-equation simple general circulation model, and MAOOAM (Modular Arbitrary-Order Ocean-Atmosphere Model), a quasi-geostrophic coupled ocean–atmosphere model on a β-plane. We wish to investigate the effect of the different levels of filtering on the instabilities and dynamics of the atmospheric flows. Moreover, we assess the impact of the oceanic coupling, the dissipation scheme, and the resolution on the spectra of LEs. The PUMA Lyapunov spectrum is computed for two different values of the meridional temperature gradient defining the Newtonian forcing to the temperature field. The increase in the gradient gives rise to a higher baroclinicity and stronger instabilities, corresponding to a larger dimension of the unstable manifold and a larger first LE. The Kaplan–Yorke dimension of the attractor increases as well. The convergence rate of the rate function for the large deviation law of the finite-time Lyapunov exponents (FTLEs) is fast for all exponents, which can be interpreted as resulting from the absence of a clear-cut atmospheric timescale separation in such a model. The MAOOAM spectra show that the dominant atmospheric instability is correctly represented even at low resolutions. However, the dynamics of the central manifold, which is mostly associated with the ocean dynamics, is not fully resolved because of its associated long timescales, even at intermediate orders. As expected, increasing the mechanical atmosphere–ocean coupling coefficient or introducing a turbulent diffusion parametrisation reduces the Kaplan–Yorke dimension and Kolmogorov–Sinai entropy. In all considered configurations, we are not yet in the regime in which one can robustly define large deviation laws describing the statistics of the FTLEs. This paper highlights the need to investigate the natural variability of the atmosphere–ocean coupled dynamics by associating rate of growth and decay of perturbations with the physical modes described using the formalism of the covariant Lyapunov vectors and considering long integrations in order to disentangle the dynamical processes occurring at all timescales.

Highlights

  • The dynamics of the atmosphere and the climate system is characterised by the property of sensitivity to initial states (Kalnay, 2003)

  • As originally envisioned by Ruelle (1979), it is possible to associate with each Lyapunov exponent a corresponding infinitesimal perturbation that co-varies with the orbit that grows or decays asymptotically with the rate given by the corresponding exponent

  • We explore for the first time the Lyapunov spectra of the primitive-equation model, Portable University Model of the Atmosphere (PUMA), and of intermediate-order configurations of the coupled ocean– atmosphere system, MAOOAM

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Summary

Introduction

The dynamics of the atmosphere and the climate system is characterised by the property of sensitivity to initial states (Kalnay, 2003). Lyapunov analysis was the subject of a special issue edited by Cencini and Ginelli (2013) In parallel to these investigations in the context of basic sciences, several attempts to compute Lyapunov exponents in the context of meteorological and climate models have been made (see Vannitsem (2017)), in particular in intermediateorder atmospheric quasi-geostrophic models (with O(1000) variables) (Legras and Ghil, 1985; Vannitsem and Nicolis, 1997; Lucarini et al, 2007; Schubert and Lucarini, 2015, 2016). Vannitsem et al (2015) partly addressed this question in the context of coupled low-order ocean–atmosphere systems They found that the presence of the ocean and its exchanges (heat and momentum) with the atmosphere can drastically reduce the instability properties of the flow, confirming earlier results of Nese and Dutton (1993). The model resolution is expected to play an important role in the instability properties of the flow as discussed in Lucarini et al (2007) in the context of an atmospheric model

The properties of the tangent space
Multiscale properties
Programmatic goals
Model description
MAOOAM
Computation of the Lyapunov exponents
Large deviation laws
Experimental design
Results
Toward a new programme
Full Text
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