The Influence of Tropical-Extratropical Interactions

on ENSO Variability

Michael Alexander

NOAA/Earth System Research Lab

Pacific Ocean-Atmosphere Variability Nov-Mar

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Deser and Blackmon, 1995, J. Climate

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CI = 5 m

Z500EOF 1 SST

Response to tropical SSTAs

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SSTA °C

Z 200 (m)

Blackmon, Geisler and Pitcher 1983

Response to North Pacific SSTAs

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Z 200 (m)

SSTA °C

Pitcher, Blackmon, Bates, and Muñoz, 1988

Response to Tropical and North Pacific SSTs

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Pacific SST Structure and Atmospheric Forcing/Feedback

Pitcher et al.:

• Noted that past work indicated significant correlation between tropical and midlatitude SSTs and that the two might be related

• “For example, a tropical Pacific SST could produce an atmospheric anomaly which could produce a midlatitude SST anomaly”

• “Another possibility is that an enhanced atmospheric anomaly might occur if both a tropical SST anomaly and a favored midlatitude SST anomaly were to occur simultaneously”

• “Other permutations of possible cause and effects can be imagined.”

Oceanic Response to ENSO:the “Atmospheric Bridge”

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Alexander 1990 Climate Dyn.; Alexander 1992 J Climate

Prescribed Climatological SSTs

Mixed Layer Ocean ModelL

ENSO’s impact on the North Pacific

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SSTx 10 °C

Qnet

W m-2

Response to Pacific SST Anomalies

z200 (m) DJF

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Tropical

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North

Shading: > 95% significance by t-test

Response to ENSO: Role of Ekman transport

El Niño – La Niña SST (˚C) JFM

Alexander et al. 2002 J. Climate; Alexander and Scott 2007

Z500 (m) Niño - Niña Composite

Obs

MLM

EKM

∆

Niño - Niña SST, SLP, JFM

Extratropical => Tropical Air Sea Interactions

Seasonal Foot Printing Mechanism (SFM)

• NPO in NDJ (-1)

• Winds & Heat Flux • SST in MAM (0)

• Tropical Winds

• Bjerknes Feedback

• El Nino in NDJ(0)

(Vimont et al. 2001, 2003a&b J. Climate)

• Model (Chang et al. 2007, GRL):

•AGCM: CCM3

•Reduced Gravity Ocean (Cane-Zebiak) Model 30S-30N in Pacific.

•Slab model over remainder of the ocean

•Models are anomaly coupled

•100-year Control run

•SFM Experiment

•Add additional heat flux forcing associated with the NPO

•20°S-60°N; similar results when forcing > 10°N

•Initiate 60 heat flux anomaly runs from Nov in control run.

•Apply Heat flux anomaly during first Nov-Mar

•Then let model evolve with unperturbed fluxes for 12 more months.

• Compare ENSO evolution in perturbation and control runs.

• Note: model already includes SFM

Experiment Design

Additional SFM Forcing

• NPO from AGCM

– With Climatological SST• Isolates intrinsic variability

– 2nd EOF of SLP EOF in North Pacific in Winter

– Regress Sfc Heat flux on PC

– double flux values • Max values of ~30 Wm-2

• Add identical/constant forcing in

each of the experiments

Nov MarNov Mar Nov MarControl

Exp n Exp n+1 Exp n+2

2nd EOF SLP & Qnet Nov-Mar

SLP

Qnet

Experiment - Control

SST (°C)

Winds &SST

MJJ(0)

Experiment - Control

SST (°C) NDJ(1)

Thermocline depth (m)

Experiment - Control Nino 3.4 SST (°C) NDJ(1)

In 43 of the 60 cases (~72%) SSTs warmed in the Nino 3.4 region in the subsequent winter after the forcing was applied. The Mean difference between Exp and Control is 0.47°C (significant at the 99% level). Forcing added 11 more warm events - Nino 3.4 NDJ > 1 control.

Run number

Summary• Connection Between tropical Pacific and extratropics:

• Atmospheric Bridge

• Global, including N. Pacific & N Atlantic

• Ekman transport important in generating SSTs

• Feedback of bridge-related SST anomalies on the atmosphere:

• ~1/3 of response to ENSO SSTs (signal/noise issues)

• May involve multiple bridges

• Nature of feedback depends on region/seasonal cycle

• Model dependence?

• Extratropics => Tropics

• Atmosphere

• Seasonal Footprinting Mechanisms

• Ocean Pathways

• Rossby waves

• Subtropical Cells

Additional Slides

Model Configration

Net Surface Heat FLux

Ekman

U200 (m/sec)

Composite Niño - Niña JFM Precipitation, 200 mb streamlines

Air-Sea Feedback N. Atlantic

Peng, Robinson, Li, Hoerling, Alexander

N. Atl: 50 m slab ocean

N. Atl: 75 m slab + Ekman Trans

Atmospheric Response500 mb January

SSTA

N. Atl: Climatological SST

Africa

SouthAmerica

Optimal Structure

SST pattern that undergoes maximum growth - defined here as the domain integrated SSTA variance

When is Optimal Structure most likely to occur?

Evolution of Air-Sea System based on OS:

Difference maps between composite averages when the correlation between the OS and the observed SSTA field > 0.4 and < -0.4 during MAM.Starting in the winter before through the following winter

Composite Based on Optimal Structure in MAM

Composite Based on Optimal Structure II