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ENSO nonlinearity in a warming climate Julien Boucharel LEGOS / Univ. Toulouse, France ewitte B., du Penhoat Y. arel B. eh S.-W. Kug J.-S. LEGOS / IRD, Toulouse, France IMT / Univ. Toulouse, France DEMS, Hanyang Univ., Ansan, South Korea KORDI, Hanyang Univ., Ansan, South Korea 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 …) 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 …) Regular and periodic oscillatory mode over a wide range of parameters. BUT ….. ENSO Clivar Workshop, Paris, November 2010 SSTA [°C] Niño3 SST anomalies from Kaplan reconstruction (Kaplan et al., 1998). Time [Year] Strongly irregular behaviour of ENSO related timeseries ENSO Clivar Workshop, Paris, November 2010 SSTA [°C] Niño3 SST anomalies from Kaplan reconstruction (Kaplan et al., 1998). 12-years running mean Time [Year] Slowly varying mean state Inter-decadal variability ENSO Clivar Workshop, Paris, November 2010 Niño3 SST anomalies from Kaplan reconstruction (Kaplan et al., 1998). SSTA [°C] 1976 Warm shift 1998 Cold shift 1903 Cold shift Time [Year] 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 Niño3 SST anomalies from Kaplan reconstruction (Kaplan et al., 1998). Positive asymmetry Pseudo symmetry Skewness > 0 Skewness ~ 0 Positive asymmetry Pseudo symmetry Skewness > 0 Skewness ~ 0 SSTA [°C] 1 n skewness m3 ( xk x) 3 n k 1 Time [Year] Homogenous periods in terms of ENSO characteristics: - Variability - Asymmetry - Frequency - Predictability … ENSO Clivar Workshop, Paris, November 2010 SSTA [°C] Niño3 SST anomalies from Kaplan reconstruction (Kaplan et al., 1998). Time [Year] Presence of "anomalous" Extreme Events Complexity of ENSO system on a wide range of timescales ENSO Clivar Workshop, Paris, November 2010 Why studying ENSO nonlinearity ? (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 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 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 ENSO Clivar Workshop, Paris, November 2010 Quantifying ENSO nonlinearity Statistical measure Number of occurences Summary of ENSO statistical properties: Probability Density Function Gaussian curve corresponding to the best sampled PDF fit. [°C] Smoothed histogram of monthly SST anomalies (1870-2009) averaged in Niño3 ENSO Clivar Workshop, Paris, November 2010 Quantifying ENSO nonlinearity Statistical measure Summary of ENSO statistical properties: Probability Density Function Number of occurences Presence of Extreme Events… [°C] Smoothed histogram of monthly SST anomalies (1870-2009) averaged in Niño3 ENSO Clivar Workshop, Paris, November 2010 Quantifying ENSO nonlinearity Statistical measure Summary of ENSO statistical properties: Probability Density Function Number of occurences Presence of Extreme Events… and a strong positive asymmetry [°C] Smoothed histogram of monthly SST anomalies (1870-2009) averaged in Niño3 ENSO Clivar Workshop, Paris, November 2010 Quantifying ENSO nonlinearity Statistical measure Summary of ENSO statistical properties: Probability Density Function Contraction of the PDF near 0 Number of occurences Presence of Extreme Events… and a strong positive asymmetry [°C] Smoothed histogram of monthly SST anomalies (1870-2009) averaged in Niño3 ENSO Clivar Workshop, Paris, November 2010 Quantifying ENSO nonlinearity 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 Up to now, only ENSO asymmetry (skewness) has been considered to document the tropical pacific nonlinearity (Burgers and Stephenson, 1999; An and Jin, 2004) 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 ENSO Clivar Workshop, Paris, November 2010 Quantifying ENSO nonlinearity ENSO statistical specificities prompt us to consider heavy-tails laws family: ENSO Clivar Workshop, Paris, November 2010 Quantifying ENSO nonlinearity ENSO statistical specificities prompt us to consider heavy-tails laws family: The a-stable law, an example of the wide heavy-tails laws family: Lévy (1924); Mandelbrot (1960, 1963). Benoît Mandelbrot (1924-2010) ENSO Clivar Workshop, Paris, November 2010 Quantifying ENSO nonlinearity ENSO statistical specificities prompt us to consider heavy-tails laws family: The a-stable law, an example of the wide heavy-tails laws family: Lévy (1924); Mandelbrot (1960, 1963). Benoît Mandelbrot (1924-2010) Characteristic function: (t ) E[exp itX ] exp g a t 1 ib sign (t )w(t , a ) id t def a 4 parameters govern stable distributions a, b, g and d ENSO Clivar Workshop, Paris, November 2010 Quantifying ENSO nonlinearity ENSO statistical specificities prompt us to consider heavy-tails laws family: The a-stable law, an example of the wide heavy-tails laws family: Lévy (1924); Mandelbrot (1960, 1963). Benoît Mandelbrot (1924-2010) Characteristic function: (t ) E[exp itX ] exp g a t 1 ib sign (t )w(t , a ) id t def a 4 parameters govern stable distributions a, b, g and d ENSO Clivar Workshop, Paris, November 2010 Quantifying ENSO nonlinearity a-stable laws, examples Dependance on a d=0 b =0 g =1 ENSO Clivar Workshop, Paris, November 2010 Quantifying ENSO nonlinearity a-stable laws, examples Dependance on a d=0 b =0 g =1 a controls the leptokurtic deformation of the PDF a associated with the kurtosis (≥ 4th-order statistical moment) ENSO Clivar Workshop, Paris, November 2010 Quantifying ENSO nonlinearity a-stable laws, examples Dependance on b Dependance on a b=0 b = 0.5 b = 0.8 b=1 d=0 b =0 g =1 a controls the leptokurtic deformation of the PDF a associated with the kurtosis (≥ 4th-order statistical moment) b associated with the skewness (= 3rd-order statistical moment) ENSO Clivar Workshop, Paris, November 2010 a = 1.2 d =0 g =1 Quantifying ENSO nonlinearity a-stable laws, examples Dependance on b Dependance on a b=0 b = 0.5 b = 0.8 b=1 d=0 b =0 g =1 a controls the leptokurtic deformation of the PDF a associated with the kurtosis (≥ 4th-order statistical moment) b associated with the skewness (= 3rd-order statistical moment) ENSO Clivar Workshop, Paris, November 2010 a = 1.2 d =0 g =1 a=2b=0 Gaussian distribution Quantifying ENSO nonlinearity Estimation of a-stable parameters Koutrouvelis (1980): Regression method using the sample characteristic function: (t ) E[exp itX ] exp g a t 1 ib sign (t )w(t , a ) id t def a 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 Estimation of a-stable parameters a b a-stable parameters inferred from Kaplan reconstruction SST anomalies on the 1870-2009 period. ENSO Clivar Workshop, Paris, November 2010 Quantifying ENSO nonlinearity Estimation of a-stable parameters a Gaussian features During the last 130 years, most of the tropical Pacific exhibit a-stable properties. Coherent with other reconstructions (HadSST, ERSST) b a-stable parameters inferred from Kaplan reconstruction SST anomalies on the 1870-2009 period. ENSO Clivar Workshop, Paris, November 2010 Quantifying ENSO nonlinearity Estimation of a-stable parameters a Gaussian features During the last 130 years, most of the tropical Pacific exhibit a-stable properties. Coherent with other reconstructions (HadSST, ERSST) b Particularly the Warm Pool and the Cold Tongue regions a-stable parameters inferred from Kaplan reconstruction SST anomalies on the 1870-2009 period. ENSO Clivar Workshop, Paris, November 2010 Quantifying ENSO nonlinearity Estimation of a-stable parameters a Gaussian features During the last 130 years, most of the tropical Pacific exhibit a-stable properties. Coherent with other reconstructions (HadSST, ERSST) b Particularly the Warm Pool and the Cold Tongue regions The asymmetry map exhibits a zonal see-saw pattern a-stable parameters inferred from Kaplan reconstruction SST anomalies on the 1870-2009 period. ENSO Clivar Workshop, Paris, November 2010 Outline: 1. Measuring the nonlinearity of ENSO 2. Interactive feedback between ENSO irregularity and lowfrequency variability 3. ENSO statistics in a warming climate 4. Conclusions, perspectives ENSO Clivar Workshop, Paris, November 2010 Inter-decadal changes of ENSO nonlinearity SSTA [°C] Estimation of a and b on each period Time [Year] ENSO Clivar Workshop, Paris, November 2010 Inter-decadal changes of ENSO nonlinearity Estimation of a-stable law main parameters (Boucharel et al., 2009): a b Distinct nonlinear 1870-1903: behaviours according to the tropical mean state 1903-1976: 1976-1998: 1998-2009: ENSO Clivar Workshop, Paris, November 2010 Inter-decadal changes of ENSO nonlinearity Estimation of a-stable law main parameters (Boucharel et al., 2009): a b Distinct nonlinear 1870-1903: behaviours according to the tropical mean state 1903-1976: 1976-1998: 1998-2009: ENSO Clivar Workshop, Paris, November 2010 Alternation of periods favouring Extreme Events triggering in the Cold Tongue with other in the Warm Pool Inter-decadal changes of ENSO nonlinearity Estimation of a-stable law main parameters (Boucharel et al., 2009): a b Distinct nonlinear 1870-1903: behaviours according to the tropical mean state 1976-1998: Alternation of periods favouring Extreme Events triggering in the Cold Tongue with other in the Warm Pool 1998-2009: Low frequency modulation of the nonlinearity imprint in the tropical Pacific 1903-1976: ENSO Clivar Workshop, Paris, November 2010 Inter-decadal changes of ENSO nonlinearity High frequency ENSO Irregularity - Asymmetry - Extreme Events Inter-decadal Modulation Mean state Low frequency Inter-decadal 20 – 50 years INTER-SHIFT periods ENSO Clivar Workshop, Paris, November 2010 Inter-decadal changes of ENSO nonlinearity High frequency ENSO Irregularity - Asymmetry - Extreme Events Mean state Low frequency Inter-decadal 20 – 50 years INTER-SHIFT periods ENSO Clivar Workshop, Paris, November 2010 Inter-decadal Modulation ? 2-ways feedback ? Is the ENSO irregularity associated with Extreme Events able to act back on the tropical Pacific mean state? Inter-decadal changes of ENSO nonlinearity 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. Fig. 1. Annual cycle of variance (dashed line; scales in the right yaxis) and skewness (solid line; scales in the left y-axis) of Niño-3 index obtained from ERSST data averaged over 1880 to 2007. ENSO Clivar Workshop, Paris, November 2010 Inter-decadal changes of ENSO nonlinearity An and Choi (2009) Fig. 1. Annual cycle of variance (dashed line; scales in the right yaxis) and skewness (solid line; scales in the left y-axis) of Niño-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 seasondependent nonlinear rectification can modify the annual and semi-annual cycles. ENSO Clivar Workshop, Paris, November 2010 Inter-decadal changes of ENSO nonlinearity SSTA [°C] season-dependant An and Choi (2009) Dewitte et al. (2007) Timmermann et al. (2003) Time [year] ENSO Clivar Workshop, Paris, November 2010 Inter-decadal changes of ENSO nonlinearity High frequency ENSO - Asymmetry Phase locking - skewness[SST] - Var[SST] NDH Residual Niño/Niña Mean state Decadal 10 – 15 years Inter-decadal 20 – 50 years SHIFT Low frequency ENSO Clivar Workshop, Paris, November 2010 Inter-decadal Seasonal Cycle modulation Decadal modulation - Extreme Events Inter-decadal changes of ENSO nonlinearity High frequency ENSO - Asymmetry - skewness[SST] - a[SST] - Var[SST] NDH Residual Niño/Niña Phase locking ??? Phase locking modulation Seasonal Cycle Mean state Decadal 10 – 15 years Inter-decadal 20 – 50 years SHIFT Low frequency ENSO Clivar Workshop, Paris, November 2010 ? Inter-decadal Decadal modulation - Extreme Events Inter-decadal changes of ENSO nonlinearity 150°E 190°E NINO4W 210°E 270°E 5°N NINO3 5°S [2 – a]NINO3 [2 – a]NINO4W NINO4W estimation of a parameter on a 15-years running window ENSO Clivar Workshop, Paris, November 2010 Inter-decadal variability of nonlinearity as measured by [2-a Inter-decadal changes of ENSO nonlinearity 150°E 190°E NINO4W 210°E 270°E 5°N NINO3 5°S [2 – a]NINO3 [2 – a]NINO4W NINO4W estimation of a parameter on a 15-years running window ENSO Clivar Workshop, Paris, November 2010 Inter-decadal variability of nonlinearity as measured by [2-a Eastern and Western Tropical Pacific out of phase Inter-decadal changes of ENSO nonlinearity 150°E 190°E NINO4W 210°E 270°E 5°N NINO3 5°S [2 – a]NINO3 [2 – a]NINO4W NINO4W estimation of a parameter on a 15-years running window ENSO Clivar Workshop, Paris, November 2010 Inter-decadal variability of nonlinearity as measured by [2-a 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 interdecadal mean state ? Inter-decadal changes of ENSO nonlinearity 150°E 190°E NINO4W 210°E 270°E 5°N NINO3 5°S [2 – a]NINO3 [2 – a]NINO4W NINO4W estimation of a parameter on a 15-years running window ENSO Clivar Workshop, Paris, November 2010 Inter-decadal variability of nonlinearity as measured by [2-a 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 interdecadal mean state ? Inter-decadal changes of ENSO nonlinearity Opposite behaviour between two consecutive inter-shifts periods Mean[SST] 1903-1925 1925-1940 Var[SST] NINO3 a[SST] NINO4 West ENSO Clivar Workshop, Paris, November 2010 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 Mean[SST] 1903-1925 1925-1940 Phase locking Var[SST] NINO3 Anti Phase locking a[SST] Phase locking Anti Phase locking ENSO Clivar Workshop, Paris, November 2010 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 Mean[SST] 1903-1925 1925-1940 Phase locking Var[SST] NINO3 Anti Phase locking a[SST] Phase locking Anti Phase locking ENSO Clivar Workshop, Paris, November 2010 NINO4 West Inter-decadal changes of ENSO nonlinearity SSTA [°C] Time [year] ENSO Clivar Workshop, Paris, November 2010 Inter-decadal changes of ENSO nonlinearity SSTA [°C] = + Time [year] ENSO low-frequency modulation due to its own irregularity ENSO Clivar Workshop, Paris, November 2010 Inter-decadal changes of ENSO nonlinearity High frequency ENSO - Asymmetry - skewness[SST] - a[SST] - Var[SST] Phase locking Phase locking modulation Seasonal Cycle NDH Residual Niño/Niña Extreme Events Residual Mechanism ? Mean state Decadal 10 – 15 years Inter-decadal 20 – 50 years SHIFT Low frequency ENSO Clivar Workshop, Paris, November 2010 Inter-decadal Decadal modulation - Extreme Events Inter-decadal changes of ENSO nonlinearity High frequency ENSO - Asymmetry Phase locking - skewness[SST] - a[SST] - Var[SST] East-West see-saw Phase-locking alternation Phase locking NDH Residual Niño/Niña modulation Seasonal Cycle Extreme Events Residual Mechanism ? Mean state Decadal 10 – 15 years Inter-decadal 20 – 50 years SHIFT Low frequency ENSO Clivar Workshop, Paris, November 2010 Inter-decadal Decadal modulation - Extreme Events 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 ENSO Clivar Workshop, Paris, November 2010 ENSO statistics in a warming climate IPCC database Models selection according to recent multimodel studies Model Name Length of PICTRL run Length of 2xCO2 run Length of 4xCO2 run 1 BCCR-BCM2.0 250 100 - 2 CCCMA-CGCM3.1-t47 500 220 290 3 CSIRO-MK3.5 run1 180 80 - 4 CSIRO-MK3.5 run2 100 - - 5 GFDL-CM2.0 200 280 300 6 GFDL-CM2.1 100 200 200 7 GISS-MODEL-E-H 280 220 - 8 INM-CM3.0 330 220 290 9 MIROC3.2-HIRES 100 220 - 10 MIROC3.2-MEDRES run1 500 220 290 11 MIROC3.2-MEDRES run2 - 70 140 12 MIROC3.2-MEDRES run3 - 70 140 13 MRI-CGCM2.3.2A 300 220 290 14 UKMO-HadCM3 (run1) 341 220 220 ENSO Clivar Workshop, Paris, November 2010 ENSO statistics in a warming climate IPCC database Models selection according to recent multimodel studies and 3 scenarios Model Name Length of PICTRL run Length of 2xCO2 run Length of 4xCO2 run 1 BCCR-BCM2.0 250 100 - 2 CCCMA-CGCM3.1-t47 500 220 290 3 CSIRO-MK3.5 run1 180 80 - 4 CSIRO-MK3.5 run2 100 - - 5 GFDL-CM2.0 200 280 300 6 GFDL-CM2.1 100 200 200 7 GISS-MODEL-E-H 280 220 - 8 INM-CM3.0 330 220 290 9 MIROC3.2-HIRES 100 220 - 10 MIROC3.2-MEDRES run1 500 220 290 11 MIROC3.2-MEDRES run2 - 70 140 12 MIROC3.2-MEDRES run3 - 70 140 13 MRI-CGCM2.3.2A 300 220 290 14 UKMO-HadCM3 (run1) 341 220 220 ENSO Clivar Workshop, Paris, November 2010 ENSO statistics in a warming climate a-stable parameters: Da a2xCO2 – aPICTRL Db b2xCO2 – bPICTRL MultiModels Mean More nonlinear 2xCO2 – PICTRL: More linear More negative asym More positive asym Boucharel et al. (2010), in rev. - Patterns of b indicate more drastic changes over Niño4 region. ENSO Clivar Workshop, Paris, November 2010 ENSO statistics in a warming climate a-stable parameters: Da a2xCO2 – aPICTRL Db b2xCO2 – bPICTRL MultiModels Mean More nonlinear More linear 2xCO2 – PICTRL: More negative asym More positive asym Boucharel et al. (2010), in rev. - Patterns of b indicate more drastic changes over Niño4 region. - Zonal tripole pattern of a ENSO Clivar Workshop, Paris, November 2010 ENSO statistics in a warming climate a-stable parameters: Da a2xCO2 – aPICTRL Db b2xCO2 – bPICTRL MultiModels Mean More nonlinear More linear 2xCO2 – PICTRL: More negative asym More positive asym Boucharel et al. (2010), in rev. - Patterns of b indicate more drastic changes over Niño4 region. - Zonal tripole pattern of a Intensification of Extreme El Niño events and nonlinearity over the western Pacific (« Modoki ») Decrease of the traditional Cold Tongue El Niño. ENSO Clivar Workshop, Paris, November 2010 ENSO statistics in a warming climate a-stable parameters: More nonlinear More linear More negative asym Da a4xCO2 – aPICTRL More positive asym Db b4xCO2 – bPICTRL MultiModels Mean 4xCO2 – PICTRL: ENSO Clivar Workshop, Paris, November 2010 ENSO statistics in a warming climate a-stable parameters: More nonlinear More linear More negative asym Da a4xCO2 – aPICTRL More positive asym Db b4xCO2 – bPICTRL MultiModels Mean 4xCO2 – PICTRL: - - Same tendency than for 2xCO2 – PICTRL. Patterns of change not altered Treshold effect of climate change impact on the mean state ENSO Clivar Workshop, Paris, November 2010 ENSO statistics in a warming climate Is it an artefact of one particular model ? ENSO Clivar Workshop, Paris, November 2010 ENSO statistics in a warming climate Is it an artefact of one particular model ? b Niño4W A Niño4W ' a trip a' A a' Niño3 Niño4W Niño3 a' Niño4W 2 [ a A a Niño3 a Niño4W ] ENSO Clivar Workshop, Paris, November 2010 ENSO statistics in a warming climate Ensemble mean Wide range of behaviours in terms of nonlinearity ENSO Clivar Workshop, Paris, November 2010 ENSO statistics in a warming climate Ensemble mean Wide range of behaviours in terms of nonlinearity But 10/14 models exhibit a decrease in a'trip with 70 % of them being confident at 95% ENSO Clivar Workshop, Paris, November 2010 ENSO statistics in a warming climate Ensemble Mean for NINO4W Wide range of behaviours in terms of nonlinearity But 10/14 models exhibit a decrease in a'trip with 70 % of them being confident at 95% Dominated by changes over the western tropical Pacific ENSO Clivar Workshop, Paris, November 2010 ENSO statistics in a warming climate Confirmed by asymmetry changes Decrease towards a strong negative asymmetry. Reduction of asymmetry in the Cold Tongue (not shown). ENSO Clivar Workshop, Paris, November 2010 ENSO statistics in a warming climate Mean[SST] Var[SST] Beyond interdecadal variability, dominant phaselocking in the Eastern Pacific in 20th century and pre-industrial climate a[SST] ENSO Clivar Workshop, Paris, November 2010 ENSO statistics in a warming climate Mean[SST] Var[SST] Var[SST] Beyond interdecadal variability, dominant phaselocking in the Eastern Pacific in 20th century and pre-industrial climate a[SST] a[SST] In a warming climate, dominant phase-locking in the Western Pacific ENSO Clivar Workshop, Paris, November 2010 ENSO statistics in a warming climate Mean[SST] Var[SST] Var[SST] Beyond interdecadal variability, dominant phaselocking in the Eastern Pacific in 20th century and pre-industrial climate a[SST] a[SST] In a warming climate, dominant phase-locking in the Western Pacific Change in dynamic attractor, Bifurcation ? 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 ENSO Clivar Workshop, Paris, November 2010 Conclusions a-stable laws allow defining relevant and mathematically defined metrics of highstatistical moments and therefore nonlinearity High Statistical moments = important indicators of human-induced climate change (Timmermann, 1999). ENSO Clivar Workshop, Paris, November 2010 Conclusions a-stable laws allow defining relevant and mathematically defined metrics of highstatistical moments and therefore nonlinearity High Statistical moments = important indicators of human-induced climate change (Timmermann, 1999). 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 ? ENSO Clivar Workshop, Paris, November 2010 Conclusions a-stable laws allow defining relevant and mathematically defined metrics of highstatistical moments and therefore nonlinearity High Statistical moments = important indicators of human-induced climate change (Timmermann, 1999). 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 …?) ENSO Clivar Workshop, Paris, November 2010 ENSO modulation & Climate change High frequency ENSO Climate change - Asymmetry - Extreme Events Treshold Phase locking - skewness[SST] - a[SST] - Var[SST] East-West see-saw Phase-locking alternation Phase locking NDH Residual Niño/Niña modulation Seasonal Cycle Extreme Events Residual Mechanism ? Mean state Decadal 10 – 15 years Inter-decadal 20 – 50 years SHIFT Low frequency ENSO Clivar Workshop, Paris, November 2010 Inter-decadal Decadal modulation El Niño Modoki – Cold Tongue THANK YOU ENSO Clivar Workshop, Paris, November 2010