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	<journal>
		<journal_title>Nonlinear Processes  in Geophysics</journal_title>
		<journal_url>www.nonlin-processes-geophys.net</journal_url>
		<issn>1023-5809</issn>
		<eissn>1607-7946</eissn>
		<volume_number>16</volume_number>
		<issue_number>4</issue_number>
		<publication_year>2009</publication_year>
	</journal>
	<doi>10.5194/npg-16-453-2009</doi>
	<article_url>http://www.nonlin-processes-geophys.net/16/453/2009/</article_url>
	<abstract_html>http://www.nonlin-processes-geophys.net/16/453/2009/npg-16-453-2009.html</abstract_html>
	<fulltext_pdf>http://www.nonlin-processes-geophys.net/16/453/2009/npg-16-453-2009.pdf</fulltext_pdf>
	<start_page>453</start_page>
	<end_page>473</end_page>
	<publication_date>2009-07-06</publication_date>
	<article_title content_type="html">ENSO&apos;s non-stationary and non-Gaussian character: the role of climate shifts</article_title>
	<authors>
		<author numeration="1" affiliations="1">
			<name>J. Boucharel</name>
			<email>julien.boucharel@legos.obs-mip.fr</email>
		</author>
		<author numeration="2" affiliations="1,2,3">
			<name>B. Dewitte</name>
		</author>
		<author numeration="3" affiliations="4">
			<name>B. Garel</name>
		</author>
		<author numeration="4" affiliations="1,2">
			<name>Y. du Penhoat</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">Université de Toulouse, UPS, LEGOS, 14 Av, Edouard Belin, 31400 Toulouse, France</affiliation>
		<affiliation numeration="2" content_type="html">IRD, LEGOS, 31400 Toulouse, France</affiliation>
		<affiliation numeration="3" content_type="html">IMARPE, Callao, Peru</affiliation>
		<affiliation numeration="4" content_type="html">Université de Toulouse, INP-ENSEEIHT, UPS, Institut de Mathématiques de Toulouse, France</affiliation>
	</affiliations>
	<abstract content_type="html">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.
&lt;br&gt;&lt;br&gt;
Here, ENSO&apos;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&apos;&apos; 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)&apos;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.</abstract>
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