How do Westerly Wind Bursts Affect

ENSO Characteristics?

OR

Westerly Wind Bursts:

ENSO's Tail Rather than Dog?

Geoffrey Gebbie, Ian Eisenman, and Eli Tziperman

Harvard University, Cambridge, MA, USA

Andrew Wittenberg

Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA

Westerly Wind Bursts Are ...

5 or more days with wind speed > 4 m/s and peak > 7 m/s

Defined to be the strong WWEs, i.e., 'mega-WWEs' of HV97

Defined relative to seasonal variations

Approx. 3 WWBs/yr

Verbickas 1998, Yu et al. 2003

Harrison and Vecchi, 1997

Eisenman, pers. comm.

In space:

In time:

A Link Between WWBs and the Ocean State

WWBs are 3x more common when warm pool

extends past date line

Vecchi and Harrison 2000, Yu et al. 2003, Eisenman et al. 2005

The TAO Array

Pink: >29 C

Wind speed is

overlaid.

Objective:

Are the characteristics of ENSO

(i.e., amplitude, frequency, irregularity)

sensitive to the link between WWBs and SST?

Test: Use a hybrid coupled GCM with

an explicit coupled representation of WWBs

to determine the sensitivity of ENSO characteristics.

Ocean model: GFDL MOM4

Global domain

½ resolution in tropics

Statistical atmosphere:

Linear regression of ERA40

monthly-mean wind stress onto

SST (1979-2001)

Griffies et al. 2004, Wittenberg and Vecchi 2005

The Model:

Modeling WWBs

WWBs applied 5W of warm pool edge.

No WWBs in boreal summer.

29C

1. Increase coupling coefficient.

2. Deterministic: When warm pool extends past 180, WWB occurs.

3. Stochastic. No dependence on warm pool.

4. Semi-stochastic. Probability of WWB increases with warm pool extent.

P

Pmax

Warm pool extent

stochastic

semi-stochastic

The model without WWBs

coupling determined by ECMWF ERA40 reanalysis

Decays to seasonal cycle

NINO 3.4

SST

C

Zonal

Windstress

Anomaly

N/m

:”Stable

C

Blue: dateline

Black: 29

The model stability con't.

:”1.5x coupling coeff.

std(NINO3) = 0.8 C

2.5 year ENSO

recurrence time

Periodic

Characteristics:

Wind anomalies are

1.5x larger than

ECMWF regression

values.

Dots represent

warm events.

Deterministic WWBs

If warm pool extends past date line, WWB occurs.

std(NINO3) = 0.6 C

2 yr period

3.5 WWBs/yr

Inclusion of WWBs

gives interannual

variability.

No external forcing.

Black dots indicate WWBs.

Deterministic WWBs con't.

40 day WWB lifecycle

std(NINO3) = 0.6 C

2 year period

25 day WWB lifecycle

std(NINO3) = 0.7 C

4 year period

The magnitude and period are sensitive to WWB formulation.

2 WWB representations:

Purely Stochastic WWBs

WWBs occur

independently

of ocean state.

std(NINO3.4)=0.3C

2-3 year recurrence

interval

Irregular

3.5 WWBs/yr

Weak interannual

variability.

Semi-stochastic WWBs

WWBs more likely

with extended

warm pool.

std(NINO3.4)=0.45C

2-5 year

recurrence intervals

Irregular

2.9 WWBs/yr

'Bunching' of WWBs.

Stronger interannual

variability than

purely stochastic case.

Conclusions

ENSO Amplitude:

Warm event recurrence times:

ENSO irregularity:

Deterministic WWBs give interannual

variability near observed levels without

any other forcing.

WWBs based upon a purely-stochastic

atmosphere give weak variability.

'Semi-stochastic' WWBs are conceptually

appealing and also give more variability

than purely-stochastic WWBs.

Sensitive to particular WWB

formulation.

In this model, irregularity comes from

the fast timescale atmospheric variability.

2005-04-21T17:09:58