Axel TimmermannF.-F. Jin, J.-S.

Kug &S. Lorenz

Y. OkumuraS.-P. Xie

ENSO’s sensitivity to past and

future climate change

ENSO variancemaybe skewness

Noise leveldT/dt=f (T,u..)+Σ(T)ζ

Strength of annual cycle

dT/dt=f (T,u..)+Asinωt

Background statedT/dt=f (T,u,h,v,w)

NonlinearitiesdT/dt=f (u'T', Σ(T)ζ)

External factors

Coupling strength

Nino 3 SSTA

What controls the amplitude of ENSO?

ENSO variancemaybe skewness

Strength of annual cycle

dT/dt=f (T,u..)+Asinωt

Background statedT/dt=f (T,u,h,v,w)

External factors,Orbital forcingOrbital forcing

Example 1:ENSO’s response to orbital forcing

ECHO-G simulation: 140ka B.P.– ECHO-G simulation: 140ka B.P.– 20ka A.P.20ka A.P.

Annual cycle

ENSO

Zonal SST gradient: obliquity

cycle

ACY and ENSOamplitude:

precessional cycle

ka

ECHO-G simulation: 140ka B.P.– ECHO-G simulation: 140ka B.P.– 20ka A.P.20ka A.P.

Meridional SST

gradient: precessional

cycle

ACY and ENSOamplitude:

precessional cycle

ECHO-G simulation: 140ka B.P.– ECHO-G simulation: 140ka B.P.– 20ka A.P.20ka A.P.

ACY strength is driven by meridional

SST gradient

meridional SST gradient varies with precessional

cycle

WHY?

Annual cycle of cloud albedo

Annual cycle of cloudiness

< > ~0

< > ≠0

Emergence of an annual mean Emergence of an annual mean precessional cycleprecessional cycle

ENSO response to orbital forcingENSO response to orbital forcing

ENSO variancemaybe skewness

Strength of annual cycle

dT/dt=f (T,u..)+Asinωt

Background statedT/dt=f (T,u,h,v,w)

External factors,AMOC collapseAMOC collapse

Example 2:ENSO’s response to AMOC collapse

Tropical Pacific response to Heinrich Tropical Pacific response to Heinrich II

Pahnke et al. 2007

NADWMcManus2004

Tropical Pacific response to AMOC collapseTropical Pacific response to AMOC collapse

GFDL CM2.1WaterhosingExperiment

Timmermann et al 2007

Stouffer et al 2006

Tropical Pacific response to Caribbean SSTATropical Pacific response to Caribbean SSTA

Linear moist baroclinic model coupled to tropical POP

Model Atmosphere Ocean Forcing CO2

GFDL_CM2.1 2x2.5, L24 1/3-1x1, L50 (MOM4) fresh water 286

HadCM3 2.5x3.75, L19 1.25x1.25, L20 (pre-MOM) virtual salt 290

CCSM2 T42, L26 1x1, L40 (POP) fresh water 355

ECHAM5/MPI-OM T31, L19 3x3 virtual salt 280

CGCM Hosing Experiments (CMIP)

Freshwater flux anomalyin N Atlantic (50-70N)(1Sv X 100 yrs; ~9m increase in sea level)

1Sv

Year100 200

Monthly SST, Z20, wind stress (precipitation, geopotential height)

Weakening of annualcycle and

Intensificationof ENSO

Tropical Pacific response to AMOC shutdownTropical Pacific response to AMOC shutdown

5 waterhosing experiments conducted as part of CMIP

Weakening of theAMOC

Cooling of North Atlantic

Caribbean anticyclone

Cooling of northeastern tropical

Pacific

Intensification ofNortheasterly trades

In tropical Pacific

Weakening of Annual cycle in

Equatorial Pacific

StrengtheningOf ENSO

Equatorial thermoclineshoaling

Timmermann et al. (2005)

Timmermann et al. (2007)

Gulf Stream 10% weakerCaribbean 2C colderITCZ south: CariacoGalapagos wetReduced Indian monsoonWetter in Southwest USPalau dryWarm Santa Barbara basinHigher Peru river dischargeCentral Chile wetCold MD81Stronger ENSO PalmyraPallcacochaHuascaran

….

AMOC weakening: a paradigm for LIA-MCA

Mechanisms

Hurricanes?Wildfires

Dust stormsProductivityExtremes

IndianMonsoon

Sahel

Impacts

ENSO variancemaybe skewness

Noise leveldT/dt=f (T,u..)+Σ(T)ζ

Background statedT/dt=f (T,u,h,v,w)

External factorsGreenhouse warmingGreenhouse warming

Example 3: Noise-induced intensification of ENSO under greenhouse warming conditions

Noise-induced intensification of ENSO

Eisenman et al. 2005

WWB modulation by temperature for present-day climate

WWB modulation by temperature(BMRC MJO activity)

Correlation/Regression betweenNino3 SSTA and 20-60 day

band-pass filtered windvariance

Noise-induced intensification of ENSO

WWB-ENSO interaction increased during the

last 50 years

Noise-induced intensification of ENSO

AR4 models simulate increased

Intraseasonal variability

dT

dt T h (t)G,   

dh

dt T a(t)G,   

d

dt r w(t) .

G 1 BT

PDFT

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

-2 -1 0 1 2 3

B=0

B=1

PDFT

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

-2 -1 0 1 2 3

B=0

B=1

Coupling strength and noise may change slowlyover time

ENSO recharge model with state-dependent noise

d T dt

E T h 2B / (r 2 / r)  ,d h

dt T

E 2B2 / (r 2 / r)

State-dependent noise is “coupling”State-dependent noise is also “nonlinearity”

Ensemble mean equation for ENSO

ENSO recharge model with state-dependent noise

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

Past and future changes of ENSO amplitude

From Collins, pers. comm.

HADCM3 multi-modelEnsemble:

Relationship betweenGlobal climate sensitivity and

Simulated NINO3 stdv

Processes that amplifyGlobal warming weaken ENSO

???

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