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Axel Timmermann F.-F. Jin, J.-S. Kug & S. Lorenz Y. Okumura S.-P. Xie ENSO’s sensitivity to past and future climate change.

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Presentation on theme: "Axel Timmermann F.-F. Jin, J.-S. Kug & S. Lorenz Y. Okumura S.-P. Xie ENSO’s sensitivity to past and future climate change."— Presentation transcript:

1 Axel Timmermann F.-F. Jin, J.-S. Kug & S. Lorenz Y. Okumura S.-P. Xie ENSO’s sensitivity to past and future climate change

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3 ENSO variance maybe skewness Noise level dT/dt=f (T,u..)+Σ(T)ζ Strength of annual cycle dT/dt=f (T,u..)+Asinωt Background state dT/dt=f (T,u,h,v,w) Nonlinearities dT/dt=f (u'T', Σ(T)ζ) External factors Coupling strength Nino 3 SSTA What controls the amplitude of ENSO?

4 ENSO variance maybe skewness Strength of annual cycle dT/dt=f (T,u..)+Asinωt Background state dT/dt=f (T,u,h,v,w) External factors, Orbital forcing Example 1: ENSO’s response to orbital forcing

5 ECHO-G simulation: 140ka B.P.– 20ka A.P. Annual cycle ENSO Zonal SST gradient: obliquity cycle ACY and ENSO amplitude: precessional cycle ka

6 ECHO-G simulation: 140ka B.P.– 20ka A.P. Meridional SST gradient: precessional cycle ACY and ENSO amplitude: precessional cycle

7 ECHO-G simulation: 140ka B.P.– 20ka A.P. ACY strength is driven by meridional SST gradient meridional SST gradient varies with precessional cycle WHY?

8 Annual cycle of cloud albedo Annual cycle of cloudiness < > ~0 < > ≠0 Emergence of an annual mean precessional cycle

9 ENSO response to orbital forcing

10 ENSO variance maybe skewness Strength of annual cycle dT/dt=f (T,u..)+Asinωt Background state dT/dt=f (T,u,h,v,w) External factors, AMOC collapse Example 2: ENSO’s response to AMOC collapse

11 Tropical Pacific response to Heinrich I Pahnke et al. 2007 NADW McManus 2004

12 Tropical Pacific response to AMOC collapse GFDL CM2.1 Waterhosing Experiment Timmermann et al 2007 Stouffer et al 2006

13 Tropical Pacific response to Caribbean SSTA Linear moist baroclinic model coupled to tropical POP

14 Model AtmosphereOceanForcingCO2 GFDL_CM2.1 2x2.5, L241/3-1x1, L50 (MOM4)fresh water286 HadCM3 2.5x3.75, L191.25x1.25, L20 (pre-MOM)virtual salt290 CCSM2 T42, L261x1, L40 (POP)fresh water355 ECHAM5/MPI-OM T31, L193x3virtual salt280 CGCM Hosing Experiments (CMIP) Freshwater flux anomaly in N Atlantic (50-70N) (1Sv X 100 yrs; ~9m increase in sea level) 1Sv Year 100200 Monthly SST, Z20, wind stress (precipitation, geopotential height)

15 Weakening of annual cycle and Intensification of ENSO Tropical Pacific response to AMOC shutdown 5 waterhosing experiments conducted as part of CMIP

16 Weakening of the AMOC Cooling of North Atlantic Caribbean anticyclone Cooling of northeastern tropical Pacific Intensification of Northeasterly trades In tropical Pacific Weakening of Annual cycle in Equatorial Pacific Strengthening Of ENSO Equatorial thermocline shoaling Timmermann et al. (2005) Timmermann et al. (2007)

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18 Gulf Stream 10% weaker Caribbean 2C colder ITCZ south: Cariaco Galapagos wet Reduced Indian monsoon Wetter in Southwest US Palau dry Warm Santa Barbara basin Higher Peru river discharge Central Chile wet Cold MD81 Stronger ENSO Palmyra Pallcacocha Huascaran …. AMOC weakening: a paradigm for LIA-MCA

19 Mechanisms

20 Hurricanes? Wildfires Dust storms Productivity Extremes Indian Monsoon Sahel Impacts

21 ENSO variance maybe skewness Noise level dT/dt=f (T,u..)+Σ(T)ζ Background state dT/dt=f (T,u,h,v,w) External factors Greenhouse warming Example 3: Noise-induced intensification of ENSO under greenhouse warming conditions

22 Noise-induced intensification of ENSO Eisenman et al. 2005 WWB modulation by temperature for present-day climate

23 WWB modulation by temperature (BMRC MJO activity ) Correlation/Regression between Nino3 SSTA and 20-60 day band-pass filtered wind variance Noise-induced intensification of ENSO

24 WWB-ENSO interaction increased during the last 50 years Noise-induced intensification of ENSO AR4 models simulate increased Intraseasonal variability

25 Coupling strength and noise may change slowly over time ENSO recharge model with state-dependent noise

26 State-dependent noise is “coupling” State-dependent noise is also “nonlinearity” Ensemble mean equation for ENSO ENSO recharge model with state-dependent noise

27 Past and future changes of ENSO amplitude Control of ENSO amplitude is a complicated story: not only linear instability We need better theory for annual cycle- ENSO interactions We need better theory for WWB-ENSO interactions We need more realistic representations of WWBs in CGCMs

28 Past and future changes of ENSO amplitude From Collins, pers. comm. HADCM3 multi-model Ensemble: Relationship between Global climate sensitivity and Simulated NINO3 stdv Processes that amplify Global warming weaken ENSO ???

29 We see no statistically significant changes in amplitude of ENSO variability in the future, with changes in the standard deviation of the Southern Oscillation Index that are no larger than observed decadal variations. (Oldenborgh et al. 2005). From Oldenborgh


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