ENSO nonlinearity in a warming climate Julien Boucharel LEGOS /
Univ. Toulouse, France Dewitte B., du Penhoat Y. LEGOS / IRD,
Toulouse, France Garel B. IMT / Univ. Toulouse, France Yeh S.-W.
DEMS, Hanyang Univ., Ansan, South Korea Kug J.-S. KORDI, Hanyang
Univ., Ansan, South Korea Slide 2 ENSO Clivar Workshop, Paris,
November 2010 Why studying ENSO nonlinearity ? LINEAR theories have
provided an understanding of the MAIN mechanisms leading to: the
growth/decay of the initial SST perturbation Bjerknes feedback
(Bjerknes, 1966 ) the oscillatory nature of ENSO Delayed negative
feedback of oceanic dynamic adjustment (e.g. equatorial wave
dynamics) (Cane and Zebiak, 1985; Schopf and Suarez, 1988; Battisti
and Hirst, 1989 ) Slide 3 ENSO Clivar Workshop, Paris, November
2010 LINEAR theories have provided an understanding of the MAIN
mechanisms leading to: the growth/decay of the initial SST
perturbation Bjerknes feedback (Bjerknes, 1966 ) the oscillatory
nature of ENSO Delayed negative feedback of oceanic dynamic
adjustment (e.g. equatorial wave dynamics) (Cane and Zebiak, 1985;
Schopf and Suarez, 1988; Battisti and Hirst, 1989 ) Regular and
periodic oscillatory mode over a wide range of parameters. BUT ..
Why studying ENSO nonlinearity ? Slide 4 Strongly irregular
behaviour of ENSO related timeseries ENSO Clivar Workshop, Paris,
November 2010 SSTA [C] Time [Year] Nio3 SST anomalies from Kaplan
reconstruction (Kaplan et al., 1998). Slide 5 Slowly varying mean
state Inter-decadal variability ENSO Clivar Workshop, Paris,
November 2010 SSTA [C] Time [Year] Nio3 SST anomalies from Kaplan
reconstruction (Kaplan et al., 1998). 12-years running mean Slide 6
Inter-decadal variability reflected by the presence of abrupt
transitions (Climate shifts) Bivariate test for the detection of a
systematic change in mean (shift) Maronna and Yohai (1978), Potter
(1981), Boucharel et al. (2009) ENSO Clivar Workshop, Paris,
November 2010 1903 Cold shift 1976 Warm shift 1998 Cold shift SSTA
[C] Time [Year] Nio3 SST anomalies from Kaplan reconstruction
(Kaplan et al., 1998). Slide 7 ENSO Clivar Workshop, Paris,
November 2010 Homogenous periods in terms of ENSO characteristics:
- Variability - Frequency - Asymmetry- Predictability SSTA [C] Time
[Year] Nio3 SST anomalies from Kaplan reconstruction (Kaplan et
al., 1998). Positive asymmetry Skewness > 0 Pseudo symmetry
Skewness ~ 0 Positive asymmetry Skewness > 0 Pseudo symmetry
Skewness ~ 0 Slide 8 Presence of "anomalous" Extreme Events
Complexity of ENSO system on a wide range of timescales ENSO Clivar
Workshop, Paris, November 2010 SSTA [C] Time [Year] Nio3 SST
anomalies from Kaplan reconstruction (Kaplan et al., 1998). Slide 9
ENSO Clivar Workshop, Paris, November 2010 (Inter-)decadal changes
of ENSO characteristics mirror (inter-)decadal changes of
nonlinearity (as measured by ENSO asymmetry). An and Wang, 2000; Wu
and Hsieh, 2003; An, 2004; Ye and Hsieh, 2006. Dynamical linkage
between these changes (An, 2009) Nonlinear processes are part of
the ENSO system and may be involved in ENSO low-frequency
modulation Why studying ENSO nonlinearity ? Slide 10 ENSO Clivar
Workshop, Paris, November 2010 Outline: 1. Measuring the
nonlinearity of ENSO 2. Interactive feedback between ENSO
irregularity and low-frequency variability 3. ENSO statistics in a
warming climate 4. Conclusions, perspectives Slide 11 ENSO Clivar
Workshop, Paris, November 2010 Outline: 1. Measuring the
nonlinearity of ENSO 2. Interactive feedback between ENSO
irregularity and low-frequency variability 3. ENSO statistics in a
warming climate 4. Conclusions, perspectives Slide 12 ENSO Clivar
Workshop, Paris, November 2010 Statistical measure Smoothed
histogram of monthly SST anomalies (1870-2009) averaged in Nio3 [C]
Number of occurences Summary of ENSO statistical properties:
Probability Density Function Gaussian curve corresponding to the
best sampled PDF fit. Quantifying ENSO nonlinearity Slide 13 ENSO
Clivar Workshop, Paris, November 2010 Statistical measure Smoothed
histogram of monthly SST anomalies (1870-2009) averaged in Nio3 [C]
Number of occurences Summary of ENSO statistical properties:
Probability Density Function Presence of Extreme Events Quantifying
ENSO nonlinearity Slide 14 ENSO Clivar Workshop, Paris, November
2010 Statistical measure Smoothed histogram of monthly SST
anomalies (1870-2009) averaged in Nio3 [C] Number of occurences
Summary of ENSO statistical properties: Probability Density
Function Presence of Extreme Events and a strong positive asymmetry
Quantifying ENSO nonlinearity Slide 15 ENSO Clivar Workshop, Paris,
November 2010 Statistical measure Smoothed histogram of monthly SST
anomalies (1870-2009) averaged in Nio3 [C] Number of occurences
Summary of ENSO statistical properties: Probability Density
Function Presence of Extreme Events and a strong positive asymmetry
Contraction of the PDF near 0 Quantifying ENSO nonlinearity Slide
16 But other ENSO statistical peculiarities have to be taken into
account Need to propose a quantification of the presence of EE, the
leptokurtic deformation and the asymmetry of ENSO PDF Higher order
statistics Hypothesis: - The "distorsion" of the PDF of tropical
Pacific climate variables is a signature of the presence of
nonlinearity in the ENSO system. Quantifying this distorsion can
provide insights on an integrated level of ENSO nonlinearity ENSO
Clivar Workshop, Paris, November 2010 Up to now, only ENSO
asymmetry (skewness) has been considered to document the tropical
pacific nonlinearity (Burgers and Stephenson, 1999; An and Jin,
2004) Quantifying ENSO nonlinearity Slide 17 ENSO Clivar Workshop,
Paris, November 2010 ENSO statistical specificities prompt us to
consider heavy-tails laws family: Quantifying ENSO nonlinearity
Slide 18 ENSO Clivar Workshop, Paris, November 2010 The -stable
law, an example of the wide heavy-tails laws family: Lvy (1924);
Mandelbrot (1960, 1963). Benot Mandelbrot (1924-2010) Quantifying
ENSO nonlinearity ENSO statistical specificities prompt us to
consider heavy-tails laws family: Slide 19 ENSO Clivar Workshop,
Paris, November 2010 The -stable law, an example of the wide
heavy-tails laws family: Lvy (1924); Mandelbrot (1960, 1963). Benot
Mandelbrot (1924-2010) Quantifying ENSO nonlinearity ENSO
statistical specificities prompt us to consider heavy-tails laws
family: 4 parameters govern stable distributions and Characteristic
function: Slide 20 ENSO Clivar Workshop, Paris, November 2010 The
-stable law, an example of the wide heavy-tails laws family: Lvy
(1924); Mandelbrot (1960, 1963). Benot Mandelbrot (1924-2010)
Quantifying ENSO nonlinearity ENSO statistical specificities prompt
us to consider heavy-tails laws family: 4 parameters govern stable
distributions and Characteristic function: Slide 21 -stable laws,
examples ENSO Clivar Workshop, Paris, November 2010 Quantifying
ENSO nonlinearity = 0 = 0 = 1 Dependance on Slide 22 controls the
leptokurtic deformation of the PDF associated with the kurtosis ( 4
th -order statistical moment) -stable laws, examples ENSO Clivar
Workshop, Paris, November 2010 Quantifying ENSO nonlinearity = 0 =
0 = 1 Dependance on Slide 23 -stable laws, examples ENSO Clivar
Workshop, Paris, November 2010 controls the leptokurtic deformation
of the PDF associated with the kurtosis ( 4 th -order statistical
moment) associated with the skewness (= 3 rd -order statistical
moment) = 1.2 = 0 = 1 = 0 = 0.5 = 0.8 = 1 Quantifying ENSO
nonlinearity = 0 = 0 = 1 Dependance on Dependance on Slide 24
-stable laws, examples = 2 = 0 Gaussian distribution ENSO Clivar
Workshop, Paris, November 2010 controls the leptokurtic deformation
of the PDF associated with the kurtosis ( 4 th -order statistical
moment) associated with the skewness (= 3 rd -order statistical
moment) = 0 = 0.5 = 0.8 = 1 Quantifying ENSO nonlinearity = 0 = 0 =
1 Dependance on Dependance on = 1.2 = 0 = 1 Slide 25 Koutrouvelis
(1980): Regression method using the sample characteristic function:
Estimation of -stable parameters Rigorous statistical framework to
quantify equivalent of high order statistical moments of ENSO
timeseries Metrics of nonlinearity ENSO Clivar Workshop, Paris,
November 2010 Quantifying ENSO nonlinearity Slide 26 Estimation of
-stable parameters ENSO Clivar Workshop, Paris, November 2010
-stable parameters inferred from Kaplan reconstruction SST
anomalies on the 1870-2009 period. Quantifying ENSO nonlinearity
Slide 27 Estimation of -stable parameters ENSO Clivar Workshop,
Paris, November 2010 During the last 130 years, most of the
tropical Pacific exhibit -stable properties. Coherent with other
reconstructions (HadSST, ERSST) Gaussian features -stable
parameters inferred from Kaplan reconstruction SST anomalies on the
1870-2009 period. Quantifying ENSO nonlinearity Slide 28 Estimation
of -stable parameters ENSO Clivar Workshop, Paris, November 2010
During the last 130 years, most of the tropical Pacific exhibit
-stable properties. Coherent with other reconstructions (HadSST,
ERSST) Particularly the Warm Pool and the Cold Tongue regions
Gaussian features -stable parameters inferred from Kaplan
reconstruction SST anomalies on the 1870-2009 period. Quantifying
ENSO nonlinearity Slide 29 Estimation of -stable parameters ENSO
Clivar Workshop, Paris, November 2010 -stable parameters inferred
from Kaplan reconstruction SST anomalies on the 1870-2009 period.
During the last 130 years, most of the tropical Pacific exhibit
-stable properties. Coherent with other reconstructions (HadSST,
ERSST) Particularly the Warm Pool and the Cold Tongue regions The
asymmetry map exhibits a zonal see-saw pattern Gaussian features
Quantifying ENSO nonlinearity Slide 30 ENSO Clivar Workshop, Paris,
November 2010 Outline: 1. Measuring the nonlinearity of ENSO 2.
Interactive feedback between ENSO irregularity and low- frequency
variability 3. ENSO statistics in a warming climate 4. Conclusions,
perspectives Slide 31 ENSO Clivar Workshop, Paris, November 2010
Inter-decadal changes of ENSO nonlinearity SSTA [C] Time [Year]
Estimation of and on each period Slide 32 ENSO Clivar Workshop,
Paris, November 2010 Estimation of -stable law main parameters
(Boucharel et al., 2009): 1870-1903: 1903-1976: 1976-1998:
1998-2009: Distinct nonlinear behaviours according to the tropical
mean state Inter-decadal changes of ENSO nonlinearity Slide 33 ENSO
Clivar Workshop, Paris, November 2010 Estimation of -stable law
main parameters (Boucharel et al., 2009): 1870-1903: 1903-1976:
1976-1998: 1998-2009: Distinct nonlinear behaviours according to
the tropical mean state Alternation of periods favouring Extreme
Events triggering in the Cold Tongue with other in the Warm Pool
Inter-decadal changes of ENSO nonlinearity Slide 34 ENSO Clivar
Workshop, Paris, November 2010 Estimation of -stable law main
parameters (Boucharel et al., 2009): 1870-1903: 1903-1976:
1976-1998: 1998-2009: Distinct nonlinear behaviours according to
the tropical mean state Alternation of periods favouring Extreme
Events triggering in the Cold Tongue with other in the Warm Pool
Low frequency modulation of the nonlinearity imprint in the
tropical Pacific Inter-decadal changes of ENSO nonlinearity Slide
35 ENSO Clivar Workshop, Paris, November 2010 ENSO - Asymmetry -
Extreme Events Mean state Inter-decadal 20 50 years INTER-SHIFT
periods Inter-decadal Modulation Irregularity Low frequency High
frequency Inter-decadal changes of ENSO nonlinearity Slide 36 ENSO
Clivar Workshop, Paris, November 2010 ENSO - Asymmetry - Extreme
Events Mean state Inter-decadal 20 50 years INTER-SHIFT periods
Inter-decadal Modulation Irregularity 2-ways feedback ? Is the ENSO
irregularity associated with Extreme Events able to act back on the
tropical Pacific mean state? ? Low frequency High frequency
Inter-decadal changes of ENSO nonlinearity Slide 37 ENSO Clivar
Workshop, Paris, November 2010 Fig. 1. Annual cycle of variance
(dashed line; scales in the right y- axis) and skewness (solid
line; scales in the left y-axis) of Nio-3 index obtained from ERSST
data averaged over 1880 to 2007. An and Choi (2009) Decadal changes
in the seasonality of the ENSO asymmetry may influence the decadal
changes in the amplitude of the annual and semi-annual cycles, and
therefore the tropical Pacific decadal mean state. Inter-decadal
changes of ENSO nonlinearity Slide 38 ENSO Clivar Workshop, Paris,
November 2010 Fig. 1. Annual cycle of variance (dashed line; scales
in the right y- axis) and skewness (solid line; scales in the left
y-axis) of Nio-3 index obtained from ERSST data averaged over 1880
to 2007. Decadal changes in the seasonality of the ENSO asymmetry
may influence the decadal changes in the amplitude of the annual
and semi-annual cycles, and therefore the tropical Pacific decadal
mean state. This is because the season- dependent nonlinear
rectification can modify the annual and semi-annual cycles.
Inter-decadal changes of ENSO nonlinearity An and Choi (2009) Slide
39 ENSO Clivar Workshop, Paris, November 2010 An and Choi (2009)
Dewitte et al. (2007) Timmermann et al. (2003) season-dependant
Inter-decadal changes of ENSO nonlinearity Time [year] SSTA [C]
Slide 40 ENSO Clivar Workshop, Paris, November 2010 ENSO -
Asymmetry - Extreme Events Mean state Decadal 10 15 years
Inter-decadal 20 50 years SHIFT Decadal modulation Inter-decadal
modulation Seasonal Cycle NDH Residual Nio/Nia Phase locking -
skewness[SST] - Var[SST] Low frequency High frequency Inter-decadal
changes of ENSO nonlinearity Slide 41 ENSO Clivar Workshop, Paris,
November 2010 ENSO - Asymmetry - Extreme Events Mean state Decadal
10 15 years Inter-decadal 20 50 years SHIFT Decadal modulation
Inter-decadal modulation Seasonal Cycle NDH Residual Nio/Nia Phase
locking - skewness[SST] - [SST] - Var[SST] Low frequency High
frequency Inter-decadal changes of ENSO nonlinearity ? Phase
locking ??? Slide 42 NINO4W 5N 5S 150E190E210E270E NINO3 NINO4W
Inter-decadal variability of nonlinearity as measured by [2- ENSO
Clivar Workshop, Paris, November 2010 [2 ] NINO3 [2 ] NINO4W
Inter-decadal changes of ENSO nonlinearity estimation of parameter
on a 15-years running window Slide 43 NINO4W 5N 5S 150E190E210E270E
NINO3 NINO4W Inter-decadal variability of nonlinearity as measured
by [2- Eastern and Western Tropical Pacific out of phase ENSO
Clivar Workshop, Paris, November 2010 [2 ] NINO3 [2 ] NINO4W
Inter-decadal changes of ENSO nonlinearity estimation of parameter
on a 15-years running window Slide 44 NINO4W 5N 5S 150E190E210E270E
NINO3 NINO4W Inter-decadal variability of nonlinearity as measured
by [2- Eastern and Western Tropical Pacific out of phase Do these
long-term variations have the ability to influence seasonal SST
variations and to rectify into the inter- decadal mean state ? ENSO
Clivar Workshop, Paris, November 2010 [2 ] NINO3 [2 ] NINO4W
Inter-decadal changes of ENSO nonlinearity estimation of parameter
on a 15-years running window Slide 45 NINO4W 5N 5S 150E190E210E270E
NINO3 NINO4W Inter-decadal variability of nonlinearity as measured
by [2- Eastern and Western Tropical Pacific out of phase Do these
long-term variations have the ability to influence seasonal SST
variations and to rectify into the inter- decadal mean state ? ENSO
Clivar Workshop, Paris, November 2010 [2 ] NINO3 [2 ] NINO4W
Inter-decadal changes of ENSO nonlinearity estimation of parameter
on a 15-years running window Slide 46 ENSO Clivar Workshop, Paris,
November 2010 NINO3 NINO4 West Inter-decadal changes of ENSO
nonlinearity Mean[SST] Var[SST] [SST] Opposite behaviour between
two consecutive inter-shifts periods 1903-1925 1925-1940 Slide 47
ENSO Clivar Workshop, Paris, November 2010 NINO3 NINO4 West
Inter-decadal changes of ENSO nonlinearity Mean[SST] Var[SST] [SST]
Opposite behaviour between two consecutive inter-shifts periods
Inter-decadal changes in amplitude and phase of mean seasonal cycle
Anti Phase locking Phase locking Anti Phase locking 1903-1925
1925-1940 Slide 48 ENSO Clivar Workshop, Paris, November 2010 NINO3
NINO4 West Inter-decadal changes of ENSO nonlinearity Opposite
behaviour between two consecutive inter-shifts periods
Inter-decadal changes in amplitude and phase of mean seasonal cycle
Extreme Events residual can be rectified into the inter-decadal
tropical Pacific mean state Anti Phase locking Phase locking Anti
Phase locking Mean[SST] Var[SST] [SST] 1903-1925 1925-1940 Slide 49
ENSO Clivar Workshop, Paris, November 2010 Inter-decadal changes of
ENSO nonlinearity Time [year] SSTA [C] Slide 50 ENSO Clivar
Workshop, Paris, November 2010 + = Inter-decadal changes of ENSO
nonlinearity ENSO low-frequency modulation due to its own
irregularity SSTA [C] Time [year] Slide 51 ENSO Clivar Workshop,
Paris, November 2010 ENSO - Asymmetry - Extreme Events Mean state
Decadal 10 15 years Inter-decadal 20 50 years SHIFT Decadal
modulation Inter-decadal modulation Seasonal Cycle NDH Residual
Nio/Nia Phase locking - skewness[SST] - [SST] - Var[SST] Low
frequency High frequency Inter-decadal changes of ENSO nonlinearity
Phase locking Extreme Events Residual Mechanism ? Slide 52 ENSO
Clivar Workshop, Paris, November 2010 ENSO - Asymmetry - Extreme
Events Mean state Decadal 10 15 years Inter-decadal 20 50 years
SHIFT Decadal modulation Inter-decadal modulation Seasonal Cycle
NDH Residual Nio/Nia Phase locking - skewness[SST] - [SST] -
Var[SST] Low frequency High frequency Inter-decadal changes of ENSO
nonlinearity Phase locking Extreme Events Residual Mechanism ?
East-West see-saw Phase-locking alternation Slide 53 ENSO Clivar
Workshop, Paris, November 2010 Outline: 1. Measuring the
nonlinearity of ENSO 2. Interactive feedback between ENSO
irregularity and low-frequency variability 3. ENSO statistics in a
warming climate 4. Conclusions, perspectives Slide 54 ENSO Clivar
Workshop, Paris, November 2010 IPCC database Models selection
according to recent multimodel studies Model NameLength of PICTRL
runLength of 2xCO 2 runLength of 4xCO 2 run 1BCCR-BCM2.0250100-
2CCCMA-CGCM3.1-t47500220290 3CSIRO-MK3.5 run118080- 4CSIRO-MK3.5
run2100-- 5GFDL-CM2.0200280300 6GFDL-CM2.1100200
7GISS-MODEL-E-H280220- 8INM-CM3.0330220290 9MIROC3.2-HIRES100220-
10 MIROC3.2-MEDRES run1 500220290 11 MIROC3.2-MEDRES run2 -70140 12
MIROC3.2-MEDRES run3 -70140 13MRI-CGCM2.3.2A300220290 14UKMO-HadCM3
(run1)341220 ENSO statistics in a warming climate Slide 55 ENSO
Clivar Workshop, Paris, November 2010 IPCC database Models
selection according to recent multimodel studies and 3 scenarios
Model NameLength of PICTRL runLength of 2xCO 2 runLength of 4xCO 2
run 1BCCR-BCM2.0250100- 2CCCMA-CGCM3.1-t47500220290 3CSIRO-MK3.5
run118080- 4CSIRO-MK3.5 run2100-- 5GFDL-CM2.0200280300
6GFDL-CM2.1100200 7GISS-MODEL-E-H280220- 8INM-CM3.0330220290
9MIROC3.2-HIRES100220- 10 MIROC3.2-MEDRES run1 500220290 11
MIROC3.2-MEDRES run2 -70140 12 MIROC3.2-MEDRES run3 -70140
13MRI-CGCM2.3.2A300220290 14UKMO-HadCM3 (run1)341220 ENSO
statistics in a warming climate Slide 56 -stable parameters: 2xCO 2
PICTRL :Boucharel et al. (2010), in rev. - Patterns of indicate
more drastic changes over Nio4 region. More nonlinear More
linearMore negative asym More positive asym ENSO Clivar Workshop,
Paris, November 2010 2xCO 2 PICTRL 2xCO 2 PICTRL Multi- Models Mean
ENSO statistics in a warming climate Slide 57 -stable parameters:
2xCO 2 PICTRL :Boucharel et al. (2010), in rev. - Patterns of
indicate more drastic changes over Nio4 region. - Zonal tripole
pattern of More nonlinear More linearMore negative asym More
positive asym ENSO Clivar Workshop, Paris, November 2010 2xCO 2
PICTRL 2xCO 2 PICTRL Multi- Models Mean ENSO statistics in a
warming climate Slide 58 -stable parameters: 2xCO 2 PICTRL :
Boucharel et al. (2010), in rev. - Patterns of indicate more
drastic changes over Nio4 region. - Zonal tripole pattern of
Intensification of Extreme El Nio events and nonlinearity over the
western Pacific ( Modoki ) Decrease of the traditional Cold Tongue
El Nio. More nonlinear More linearMore negative asym More positive
asym ENSO Clivar Workshop, Paris, November 2010 2xCO 2 PICTRL 2xCO
2 PICTRL Multi- Models Mean ENSO statistics in a warming climate
Slide 59 4xCO 2 PICTRL: 4xCO 2 PICTRL 4xCO 2 PICTRL -stable
parameters: More nonlinear More linearMore negative asym More
positive asym Multi- Models Mean ENSO Clivar Workshop, Paris,
November 2010 ENSO statistics in a warming climate Slide 60 4xCO 2
PICTRL: - Same tendency than for 2xCO 2 PICTRL. Patterns of change
not altered - Treshold effect of climate change impact on the mean
state 4xCO 2 PICTRL 4xCO 2 PICTRL -stable parameters: More
nonlinear More linearMore negative asym More positive asym Multi-
Models Mean ENSO Clivar Workshop, Paris, November 2010 ENSO
statistics in a warming climate Slide 61 Is it an artefact of one
particular model ? ENSO Clivar Workshop, Paris, November 2010 ENSO
statistics in a warming climate Slide 62 Is it an artefact of one
particular model ? ENSO Clivar Workshop, Paris, November 2010 A
Nio4WNio3 Nio4W ENSO statistics in a warming climate Slide 63 BCCR
CCCMA CSIRO1 CSIRO2 GFDL0 GFDL1 GISSEh INM MIROC Hires MIROC Medres
MRI UKMO Ensemble Mean ENSO Clivar Workshop, Paris, November 2010
Ensemble mean ENSO statistics in a warming climate Wide range of
behaviours in terms of nonlinearity Slide 64 BCCR CCCMA CSIRO1
CSIRO2 GFDL0 GFDL1 GISSEh INM MIROC Hires MIROC Medres MRI UKMO
Ensemble Mean ENSO Clivar Workshop, Paris, November 2010 Ensemble
mean ENSO statistics in a warming climate Wide range of behaviours
in terms of nonlinearity But 10/14 models exhibit a decrease in '
trip with 70 % of them being confident at 95% Slide 65 BCCR CCCMA
CSIRO1 CSIRO2 GFDL0 GFDL1 GISSEh INM MIROC Hires MIROC Medres MRI
UKMO Ensemble Mean ENSO Clivar Workshop, Paris, November 2010 ENSO
statistics in a warming climate Wide range of behaviours in terms
of nonlinearity But 10/14 models exhibit a decrease in ' trip with
70 % of them being confident at 95% Dominated by changes over the
western tropical Pacific Ensemble Mean for NINO4W Slide 66 ENSO
Clivar Workshop, Paris, November 2010 ENSO statistics in a warming
climate BCCR CCCMA CSIRO1 CSIRO2 GFDL0 GFDL1 GISSEh INM MIROC Hires
MIROC Medres MRI UKMO Ensemble Mean Confirmed by asymmetry changes
Decrease towards a strong negative asymmetry. Reduction of
asymmetry in the Cold Tongue (not shown). Slide 67 ENSO Clivar
Workshop, Paris, November 2010 Beyond inter- decadal variability,
dominant phase- locking in the Eastern Pacific in 20th century and
pre-industrial climate Mean[SST] Var[SST] [SST] ENSO statistics in
a warming climate Slide 68 Beyond inter- decadal variability,
dominant phase- locking in the Eastern Pacific in 20th century and
pre-industrial climate In a warming climate, dominant phase-locking
in the Western Pacific ENSO Clivar Workshop, Paris, November 2010
Var[SST] [SST] ENSO statistics in a warming climate Mean[SST]
Var[SST] [SST] Slide 69 Beyond inter- decadal variability, dominant
phase- locking in the Eastern Pacific in 20th century and
pre-industrial climate In a warming climate, dominant phase-locking
in the Western Pacific Change in dynamic attractor, Bifurcation ?
ENSO Clivar Workshop, Paris, November 2010 Var[SST] [SST] ENSO
statistics in a warming climate Mean[SST] Var[SST] [SST] Slide 70
ENSO Clivar Workshop, Paris, November 2010 Outline: 1. Measuring
the nonlinearity of ENSO 2. Interactive feedback between ENSO
irregularity and low-frequency variability 3. ENSO statistics in a
warming climate 4. Conclusions, perspectives Slide 71 -stable laws
allow defining relevant and mathematically defined metrics of high-
statistical moments and therefore nonlinearity High Statistical
moments = important indicators of human-induced climate change
(Timmermann, 1999). ENSO Clivar Workshop, Paris, November 2010
Conclusions Slide 72 -stable laws allow defining relevant and
mathematically defined metrics of high- statistical moments and
therefore nonlinearity High Statistical moments = important
indicators of human-induced climate change (Timmermann, 1999). ENSO
Clivar Workshop, Paris, November 2010 Conclusions Tropical Pacific
system nonlinear by nature (Jin et al., 1994; Tziperman et al.,
1994) Nonlinearity associated with EE are involved in low-frequency
modulation and may be responsible for abrupt transitions of
tropical Pacific mean state (climate shifts). Evidence of a
significant change in nonlinearity patterns under greenhouse
warming Changes not so sensitive between 2xCO2 and 4xCO2 Threshold
/ bifurcation crossed ? Slide 73 -stable laws allow defining
relevant and mathematically defined metrics of high- statistical
moments and therefore nonlinearity High Statistical moments =
important indicators of human-induced climate change (Timmermann,
1999). ENSO Clivar Workshop, Paris, November 2010 Conclusions
Tropical Pacific system nonlinear by nature (Jin et al., 1994;
Tziperman et al., 1994) Nonlinearity associated with EE are
involved in low-frequency modulation and may be responsible for
abrupt transitions of tropical Pacific mean state (climate shifts).
Evidence of a significant change in nonlinearity patterns under
greenhouse warming Changes not so sensitive between 2xCO2 and 4xCO2
Threshold / bifurcation crossed ? Apply this method on the new
generations of CGCMs (CMIP5) even in PMIP (longer timeseries)
Identify the nonlinear processes associated with these changes
(NDH, intra seasonal variability, TIW ?) Slide 74 ENSO Clivar
Workshop, Paris, November 2010 ENSO - Asymmetry - Extreme Events
Mean state Decadal 10 15 years Inter-decadal 20 50 years SHIFT
Decadal modulation Inter-decadal modulation Seasonal Cycle NDH
Residual Nio/Nia Phase locking Low frequency High frequency ENSO
modulation & Climate change Phase locking Extreme Events
Residual Mechanism ? - skewness[SST] - [SST] - Var[SST] El Nio
Modoki Cold Tongue East-West see-saw Phase-locking alternation
Climate change Treshold Shift + tendency = Bifurcation ?? Slide 75
ENSO Clivar Workshop, Paris, November 2010 THANK YOU
