Abstract
Abstract. Observations and numerical simulations have shown that the meridional overturning circulation (MOC) exhibits substantial variability on sub- to interannual timescales. This variability is not fully understood. In particular it is not known what fraction of the MOC variability is caused by processes such as mesoscale ocean eddies and waves which are ubiquitous in the ocean. Here we analyse twin experiments performed with a global ocean model at eddying (1/4°) and non-eddying (1°) resolutions. The twin experiments are forced with the same surface fluxes for the 1958 to 2001 period but start from different initial conditions. Our results show that on subannual to interannual timescales a large fraction of MOC variability directly reflects variability in the surface forcing. Nevertheless, in the eddy-permitting case there is an initial-condition-dependent MOC variability (hereinafter referred to as "chaotic" variability) of several Sv (1Sv = 106 m3 s−1) in the Atlantic and the Indo-Pacific. In the Atlantic the chaotic MOC variability represents up to 30% of the total variability at the depths where the maximum MOC occurs. In comparison the chaotic MOC variability is only 5–10% in the non-eddying case. The surface forcing being almost identical in the twin experiments suggests that mesoscale ocean eddies are the most likely cause for the increased chaotic MOC variability in the eddying case. The exact formation time of eddies is determined by the initial conditions which are different in the two model passes, and as a consequence the mesoscale eddy field is decorrelated in the twin experiments. In regions where eddy activity is high in the eddy-permitting model, the correlation of sea surface height variability in the twin runs is close to zero. In the non-eddying case in contrast, we find high correlations (0.9 or higher) over most regions. Looking at the sub- and interannual MOC components separately reveals that most of the chaotic MOC variability is found on subannual timescales for the eddy-permitting model. On interannual timescales the amplitude of the chaotic MOC variability is much smaller and the amplitudes are comparable for both the eddy-permitting and non-eddy-permitting model resolutions. Whereas the chaotic MOC variability on interannual timescales only accounts for a small fraction of the total chaotic MOC variability in the eddy-permitting case, it is the main contributor to the chaotic variability in the non-eddying case away from the Equator.
Highlights
Climate variability consists of both predictable and unpredictable components where there is no predictability beyond a decorrelation time
As for the correlations we chaotic meridional overturning circulation (MOC) variability between experiments A100/B100 just discussed we look at the total, subannual and interan- and A025/B025 at the Equator is expected since ORCA1 nual chaotic MOC variability (Figs. 12 and 13)
We have studied the chaotic and forced MOC variability by comparing eddy-permitting and non-eddy-permitting twin experiments which start from different initial conditions but which are forced with the same atmospheric forcing
Summary
Climate variability consists of both predictable and unpredictable (chaotic) components where there is no predictability beyond a decorrelation time. An example of predictable variability on much longer timescales is the timing of the multimillennial ice age cycles which have characterised the Earth’s climate for the last 2 Ma. The timing of the ice age cycles are given by changes in radiative forcing due to periodically changing parameters in the Earth’s orbit around the Sun (Imbrie et al, 1992; Bradley, 1985). The timing of the ice age cycles are given by changes in radiative forcing due to periodically changing parameters in the Earth’s orbit around the Sun (Imbrie et al, 1992; Bradley, 1985)
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