Temporal structure of ENSO in 20 th Century Climate simulations Antonietta Capotondi NOAA/Earth System Research Laboratory Collaborators: Andrew Wittenberg, Simona Masina, Clara Deser, Mike Alexander, Yuko Okumura

ENSO in coupled climate models 2 Evolution of the Niño3.4 index Observations CCSM3 (NCAR) GFDL NASA GISS

Spectral characteristics Nino3.4 index (5°S-5°N, 170°W-120°W) Capotondi, Wittenberg and Masina 2006

What determines the ENSO timescale? Guilyardi et al. (2004) have shown that atmospheric model resolution can be important. Higher atmospheric resolution leads to more realistic (longer) periods. Fedorov and Philander (2001) have emphasized the importance of the mean state (intensity of the winds, depth and strength of the equatorial thermocline) as a controlling factor for ENSO properties. Dewitte et al. (2007) have stressed the importance of thermocline depth. A shallow thermocline in the central- west Pacific may favor fast equatorial modes, and lead to a shorter timescale. Simple oscillator models: Delayed oscillator, Recharge oscillator, Western Pacific oscillator, Advective-Reflective oscillator. Unified theory provided by Wang (2001).

What determines the ENSO timescale? Studies based on intermediate coupled models emphasize the importance of the spatial structure of the anomalous wind stress Kirtman (1997) used an intermediate complexity model and surface wind stresses of different meridional scales.

What determines the ENSO timescale? Studies based on intermediate coupled models An and Wang (2000) examined the causes for the longer ENSO period after the climate regime shift, and examined the changes in the pattern of the wind stress. Important aspects of anomalous wind stress pattern: Meridional width: increases adjustment time through extra-equatorial Rossby waves Longitudinal position: Controls whether anomalous advection of zonal mean temperature gradients promotes ENSO growth or phase transition.

Regression of τ x upon the Niño3.4 index NCEP/NCAR Reanalyses ‘Center of mass’ of τ x 168°W

Regression of τ x upon the Niño3.4 index CCSM3 GFDL-CM2.0 IPSL-CM4 NCEP

Regression of τ x upon the Niño3.4 index GISS-EH PCM MRI

Regression of τ x upon the Niño3.4 index UKMO-HadCM3 CSIRO CNRM

Dependency of period upon structure of anomalous wind stress T vs. L y T vs. CT vs. T p (L y,C)

CCSM3 vs. HadCM3

Influence of meridional width of τ x Regression of the curl(τ) upon the Nino3.4 index

Curl(τ) vs. Standard Deviation of pycnocline transport Meridional transport between the base of the mixed layer and the 26σ θ isopycnal, zonally averaged from the eastern edge of the WBC and the eastern ocean boundary POP simulation forced with COARE climatology

Thermocline Variability Depth of 15°C isotherm (Z15) Meinen and McPhaden 2000 EOF2EOF1 INGV ocean analysis

Influence of meridional width of τ x EOF2 of thermocline depth INGV CCSM3 HadCM3 10°N 10°S

Phase relationship between the Z15 modes INGV CCSM3 UKMO-HadCM3 PC2-PC1 lag-correlation

CCSM4 Niño3.4 time series Observations HadISST

CCSM4- Spectra

CCSM4: Wind Stress and Curl(τ) CCSM4

CCSM4: Thermocline variability INGV CCSM4

Seasonal Footprinting mechanism: CCSM4 vs. obs

Seasonal Footprinting mechanism: CCSM3 vs. obs

Asymmetry in the duration of El Niño and La Niña ( Okumura and Deser 2010) HadISST HadISST/NCEP CCSM4 El Niño La Niña Dec0 Dec+1 Dec0 Dec+1

Open Questions Relative importance of wind forcing vs. mean upper-ocean stratification in determining the ENSO timescale SST variations appear strongly correlated with thermocline variability in the CMIP3 models. What about S-modes? Can models reproduce the SFM? SFM is a precursor of a large fraction of ENSO events. What is its connection with the Western Wind Events (WWE)? Is the difference in duration of El Niño and La Niña events an important metrics to include in evaluating models? Can the models reproduce the observed ENSO diversity, including amplitude and frequency modulation, and longitudinal position of the warming? What are the mechanisms?