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Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union
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Volume 16, issue 4
Nonlin. Processes Geophys., 16, 453–473, 2009
https://doi.org/10.5194/npg-16-453-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Nonlinear processes in oceanic and atmospheric flows

Nonlin. Processes Geophys., 16, 453–473, 2009
https://doi.org/10.5194/npg-16-453-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.

  06 Jul 2009

06 Jul 2009

ENSO's non-stationary and non-Gaussian character: the role of climate shifts

J. Boucharel1, B. Dewitte1,2,3, B. Garel4, and Y. du Penhoat1,2 J. Boucharel et al.
  • 1Université de Toulouse, UPS, LEGOS, 14 Av, Edouard Belin, 31400 Toulouse, France
  • 2IRD, LEGOS, 31400 Toulouse, France
  • 3IMARPE, Callao, Peru
  • 4Université de Toulouse, INP-ENSEEIHT, UPS, Institut de Mathématiques de Toulouse, France

Abstract. El Niño Southern Oscillation (ENSO) is the dominant mode of climate variability in the Pacific, having socio-economic impacts on surrounding regions. ENSO exhibits significant modulation on decadal to inter-decadal time scales which is related to changes in its characteristics (onset, amplitude, frequency, propagation, and predictability). Some of these characteristics tend to be overlooked in ENSO studies, such as its asymmetry (the number and amplitude of warm and cold events are not equal) and the deviation of its statistics from those of the Gaussian distribution. These properties could be related to the ability of the current generation of coupled models to predict ENSO and its modulation.

Here, ENSO's non-Gaussian nature and asymmetry are diagnosed from in situ data and a variety of models (from intermediate complexity models to full-physics coupled general circulation models (CGCMs)) using robust statistical tools initially designed for financial mathematics studies. In particular α-stable laws are used as theoretical background material to measure (and quantify) the non-Gaussian character of ENSO time series and to estimate the skill of ``naïve'' statistical models in producing deviation from Gaussian laws and asymmetry. The former are based on non-stationary processes dominated by abrupt changes in mean state and empirical variance. It is shown that the α-stable character of ENSO may result from the presence of climate shifts in the time series. Also, cool (warm) periods are associated with ENSO statistics having a stronger (weaker) tendency towards Gaussianity and lower (greater) asymmetry. This supports the hypothesis of ENSO being rectified by changes in mean state through nonlinear processes. The relationship between changes in mean state and nonlinearity (skewness) is further investigated both in the Zebiak and Cane (1987)'s model and the models of the Intergovernmental Panel for Climate Change (IPCC). Whereas there is a clear relationship in all models between ENSO asymmetry (as measured by skewness or nonlinear advection) and changes in mean state, they exhibit a variety of behaviour with regard to α-stability. This suggests that the dynamics associated with climate shifts and the occurrence of extreme events involve higher-order statistical moments that cannot be accounted for solely by nonlinear advection.

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