We investigated the influence of atmospheric noise on the generation of interannual El Nino variability. Therefore, we perturbed a conceptual ENSO delay model with surrogate windstress data generated from tropical wind-speed measurements. The effect of the additional stochastic forcing was studied for various parameter sets including periodic and chaotic regimes. The evaluation was based on a spectrum and amplitude-period relation comparison between model and measured sea surface temperature data. The additional forcing turned out to increase the variability of the model output in general. The noise-free model was unable to reproduce the observed spectral bandwidth for any choice of parameters. On the contrary, the stochastically forced model is capable of producing a realistic spectrum. The weakly nonlinear regimes of the model exhibit a proportional relation between amplitude and period matching the relation derived from measurement data. The chaotic regime, however, shows an inversely proportional relation. A stability analysis of the different regimes revealed that the spectra of the weakly nonlinear regimes are robust against slight parameter changes representing disregarded physical mechanisms, whereas the chaotic regime exhibits a very unstable realistic spectrum. We conclude that the model including stochastic forcing in a parameter range of moderate nonlinearity best matches the real conditions. This suggests that atmospheric noise plays an important role in the coupled tropical pacific ocean-atmosphere system.
机构:
Univ Paris 06, LOCEAN, IPSL, UMR 7617,CNRS,IRD,MNHN, FR-75252 Paris 05, FranceUniv Paris 06, LOCEAN, IPSL, UMR 7617,CNRS,IRD,MNHN, FR-75252 Paris 05, France