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H. H. H. Role of the Indo-Pacific Interbasin Coupling in Predicting Asymmetric ENSO Transition and Duration Masamichi Ohba (Central Research Institute of Electric Power Industry, Abiko, Japan)

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Role of the Indo-Pacific Interbasin Coupling

in Predicting Asymmetric ENSO Transition and Duration

Masamichi Ohba(Central Research Institute of Electric Power Industry, Abiko, Japan)

Masahiro Watanabe(Atmosphere and Ocean Research Institute, The University of Tokyo, Kashiwa, Japan)

J. Climate in press.

Circles: observed strong event

3. Asymmetric impact of IO on ENSO transition

a. Perfect model experiment

1. Introduction

Prediction skill of El Nino and La Nina for growth and decay (dash) phase of ENSO

Relationship of forecast skills between the TPO and IO

Coupled-IO simulation from Oct0 to Aug1 :each ensemble

El Nino-Southern Oscillation (ENSO)

Evolution of the Nino 3.4 index

El Nino phase: the IO prediction skill is relatively

collaborated with the following TPO predictability

La Nina phase: the Indo-Pacific interbasin coupling is much weaker than El Nino

  • “Spring barrier”: the prediction of the decay phase is very difficult.
  • There are asymmetry of “spring barrier”: El Nino rapidly loose skill in spring, while La Nina loose gradually.
  • Such a difference is possibly related with the asymmetry of ENSO transition system(e.g., Ohba and Ueda 2009; Ohba et al. 2010; Okumura and Deser 2010).
  • ⇒El Niño tends to shift rapidly to La Niña after the mature phase, while La Niña tends to persist for up to two years (asymmetry in duration between El Niño and La Niña).
  • The asymmetry in the ENSO transition system mainly arise from the asymmetry of WP wind response to SST anomalies over the Indo-Pacific.
  • Recent studies show the “Impact of IO warming on the El Nino transition (e.g., Kug et al. 2006; Ohba and Ueda 2007) through the enhancement of WP easterly (Watanabe and Jin 2002; Annamalai et al. 2005). However, the importanceof IO feedback on the ENSO prediction during the opposite phase has not been fully clarified.
  • During La Niña, negative precipitation anomalies over the CEP shift westward compared to positive anomalies during El Niño. The zonal displacement of the Pacific precipitation anomalies may alter the balance of local and remote wind forcing over the WP between El Niño and La Niña.

Spread of individual

forecast for NIO

(yellow shade)

ACC of Nino3


The decline of the ACCs swerves to the left


Both the ACCs drop along the one-to-one line


Jin and Kinter (2009,JC)

The La Nina events endure in both simulation& the spread is much small


The difference begins to spread after the spring

Similar asymmetry of the IO-ENSO relationship is found in the 450-yr coupled-IO ctrl run

Coupled-IO hasting the El Niño transitionconsistent with the previous studies.

(e.g., Kug et al. 2006; Ohba and Ueda 2007)

b. Long-term IO-decoupled simulation

Easterly wind anom. in both phase

after their mature phase


From Ohba and Ueda 2009

One-sided lag regression (cont) and correlation (shd) of equatorial SST onto the positive and negative DJF Nino-3.4 index

Total asym.

EPAC only vs IO+PAC

The other half is likely due to direct nonlinear atmospheric response to local CEP forcing

(e.g. Hoerling et al. 2001; Ohba and Ueda 2009)

About half of the ENSO asymmetry

arise from the asymmetry of IO feedback

Surface wind response to SST anom.


IO-decoupled simulationshows

El Niño:increase the duration period

La Niña:relatively small difference




Anomaly correlation for ensemble mean SST over the tropical Pacific Ocean (TPO)

Reduced WP easterly with

theweakened transition

ENSO-related symmetric SST forcing

Asymmetry of WP zonal wind

is significantly reduced !!

TPO: 120°E-90°W, 15°S-15°N

Solid: Ctrl vs coupled-IO

Dash: Ctrl vs decouple-IO

4. Summary and discussion

a. Discussion

Skewness of simulated SST and

Tropospheric temp (850-250 hPa)

Coupled-IO extends skillful

prediction about 1.5 year

Nonlinear atmospheric response to SST around the boreal winter-spring is responsible for the ENSO asym.

(Ohba and Ueda 2009)

(Okumura et al. 2011)

Purpose of this study is to evaluate the extent to which the interactive IO

is responsible for the ENSO asymmetry in duration

Decoupled-IO: about 8mon

The skill drops rapidlyas seen in the “spring prediction barrier”

  • What causes the asymmetry of the IO feedback?
  • 1. Skewness of IO SST (Hong et al.)
  • The IO basin-wide warming is greater than that in the cooling
  • 2. Asymmetry of the zonal distance of convection between El Nino and La Nina (Okumura et al. 2011; the Pacific precip. anom. during La Nina are displaced westward by 10-40 °in longitude)
  • possibly change the sensitivity of WP zonal wind to IO
  • Linear atmospheric model (LBM:T42L20) (Watanabe and Kimoto 2000)
  • We check the wind response to change in the peak longitude of CEP heating

2. Coupled GCM: MIROC5(T42 ver.)

Shade: SST , contour: Toropos. temp

  • Reproduction of the ENSO asymmetry is difficult in most CGCMs (Ohba et al. 2010).
  • However, MIROC5 well capture the both spatial and temporal asymmetry (i.e., El Niñorapidly turn into La Niña, whileLa Niña tend to remainLa Niña state)

The difference between the CIO vs NIO is very minorin La Niña

The amplitude of the Indian Ocean SST warming is much stronger than that of the cooling.

Asymmetry of ENSO in CMIP3 & 5

Cor. DJF Nino34 vs DJF(+1yr) nino34

How the El Nino transition is accelerated?

When El Nino-direct heating exists in the WP, the IO feedback(easterly anom.) is significantly interfered.

→ The zonal distance is important factor for the ENSO asymmetry

Most remarkable case:

El Nino oct0037 simulation

b. Summary

IO warming

Remarkable cooling with the anomalous easterlies

Red: El Niño

Blue: La Niña

Effect of the IO feedback is different between El Nino and La Nina

About half of ENSO asymmetry arises from asymmetry of the Indo-Pacific interbasin coupling (the other half is possibly due to nonlinear atmospheric response to local SST in the Pacific as Ohba and Ueda 2009)

Experimental design

Interactive Air-Sea Coupled-IO(CIO) V.S. Decoupled-IO(NIO) by prescribing the clim. SST

a. Idealized twin forecast experiment & b. Long-term NIO experiment (100-yr)

The LBM responses to the heating located on various longitudes well capture the observed relationship.

Enhanced generationof Kelvin wave-like

-> Acceleration of the ENSO transition

Selected case

Four El Nino &

Two La Nina



110-yr Ctrl simulation


WP easterly

  • IO SST variation is possibly one of regulation factor of “spring prediction barrier”.
  • By improving the SST response of the IO, we can expect to overcome the spring prediction barrier of ENSO.

Shade: SST Counter: zonal wind





7 member ensemble (LAF), 18 mon forecasts: 1st October0 ~the end of April+2