el nino – southern oscillation (enso) 圣婴现象和南方涛动 mechanism, prediction &...

El Nino – Southern Oscillation (ENSO)

圣婴现象和南方涛动Mechanism, Prediction & Impacts

December 1982SST Anomaly

The white areas off the tropical coasts of South and North America indicate the pool of warm water

• El Niño/La Niña-Southern Oscillation, or ENSO, is a quasiperiodic climate pattern that occurs across the tropical Pacific Ocean roughly every five years.

• It is characterized by variations in the temperature of the surface of the tropical eastern Pacific Ocean—warming or cooling known as El Niño and La Niña respectively—and air surface pressure in the tropical western Pacific—the Southern Oscillation.

• The two variations are coupled: the warm oceanic phase, El Niño, accompanies high air surface pressure in the western Pacific, while the cold phase, La Niña, accompanies low air surface pressure in the western Pacific.

• Mechanisms that cause the oscillation remain under study.

Discovering the Southern Oscillation

ENSO normal state

● Normal equatorial winds warm as they flow westward across the Pacific● Cold water is pulled up along west coast of South America● Warming water is pushed toward west side of Pacific

El Niño state

Sea surface is warm in central and eastern Pacific

Less cold water is pulled up along west coast of South America

Hot air rises in central Pacific, travels east and west before cool

La Niña state

Warm water accumulates in far western Pacific. Equatorial water is cooler than in the normal state

NINO3NINO3.4

NINO3.4 = ENSO index, measuringaverage SST anomaly within box5S-5N; 170W-120W

NINO3 (or NINO3.4) is measureof oceanic part of ENSO.

Southern Oscillation Index* (SOI)is measure of atmospheric part of ENSO.

These two indices are highly correlated.

*Traditional Version:SOI = SLPTahiti - SLPDarwin

(there’s also and equatorial version)

Correlation > 0.9

Although they havesimilarities… ALL El Niño events are unique

Tropical Pacific – Average State

Walker Circulation

Mechanism - How it works: First understand the mean state

SST Winds Upper Ocean

Gradient Structure

Coupled Behavior in tropical Pacific

(Thermocline)

SST pair

x 1

pocean

x

h

x

T

t u

T

x v

dT

dy w

dT

dz T

SS T wdT

dz

w

dT

dz

w

dT

dz

Pacific Ocean Temperatures along Equator

http://www.pmel.noaa.gov/tao/jsdisplay or http://www.tao.noaa.gov

Based on these observationsof equatorial temperatures:

1)Is eastern Pacific thermoclinedeeper or shallower thannormal?2)What direction are thezonal wind anomalies?3)Will eastern Pacific SSTsget warmer or colder?

What is the direct (i.e. oceanic) impact of El Niño events on CO2 variability?

“ There is thus ample reason for a never-ending succession of alternating trends by air-sea interaction in the equatorial belt, but just how the turnabout between trends takes place is not yet quite clear.”

J. Bjerknes 1969

Klaus Wyrti in early 1970sshows through observationsof sea level that changes inupper ocean structure arerelated to ENSO variability,that can influence the initiationof El Nino or transition betweenEl Nino and La Nina thoughocean dynamics

Decrease of sea level = Thermocline riseA dynamical response NOT surface heating

Klaus Wyrtki

--

Wind Anomalyapplied for

30 days

Response ofupper-ocean

structure

Dynes/cm**2

(Courtesy: Dave DeWitt, IRI)

Warm SSTa

+Warm SSTa

Evolution ofupper-ocean structure

(or thermocline)anomalies

Perturbations moveeastward on the equator;westward off the equator

Perturbations move slower as latitude increases

(Courtesy: Dave DeWitt)

Continuing Evolution ofupper-ocean structure

(or thermocline)anomalies

At western boundary,waves are reflected andchanneled onto equator Delayed negative feedback

Warm SSTa

Warm SSTa

(Courtesy: Dave DeWitt)

a

b

c

d

e

Wind Stress

ThermoclineAnomaliesNear peak

El Nino

Near peakLa Nina

Transition(neutral)

Main Points:* The tropical Pacific air-sea system is coupled, with the pattern of SSTs, the low-level winds and the thermocline slope all dynamically connected

* El Nino & La Nina events result from coupled instability of the atmosphere/ocean system in the Tropical PacificBjerknes Hypothesis of coupled growth + equatorial ocean dynamics

* Among the fruits of the Bjerknes hypothesis, with Wyrtki’s contribution…

ENSO events can be predictedENSO events have been predictedThe essence* of ENSO is understood

*The “linear essence” at least

Zebiak-Cane Intermediate Coupled

Ocean-AtmosphereModel

Atmosphere Part –

Low-level winds convergetowards warmest SSTa,so atmospheric heating(SH & LH fluxes) areproportional to SSTa.This effect is amplified in regions where the meanSST is warm (mean convergence).

Zebiak-Cane Intermediate Coupled

Ocean-AtmosphereModel

Ocean Part –

Very simplified ocean model(kind of like 2-layer fluid toy).Ekman transport in surfacelayer. Convergence or divergence in surface layerleads to changes in the depthof the thermocline, which sitsat base of upper layer.Temperature anomaly in thesub-surface is determinedby depth of the thermocline.

After Cane, Zebiak and Dolan - Nature 1986 and see

Barnett, Graham, Cane, Zebiak, Dolan, O’Brien and Legler, Science 1988

Contours at 0.5°C

First Successful [Documented] El Niño Prediction

Going back, they were able to get 1982/83:

Going forward, they were able to get 1990/91 (neutral):

Going forward, they were able to get 1991/92 (El Niño):

Going forward, they were NOT able to get 1993:

Factors limiting the current skill of forecasts:

• Model flaws

• Flaws in the way the data is used (data assimilation and initialization)

• Gaps in the observing system

• Inherent limits to predictability

Chen, et al 2004 Nature

Some periods appear to bemore predictable than others

Prediction accuracy decreasesat longer lead-times.

°C

Example of Inherent Limit toPredictability Sensitivity toInitial Conditions

°C

°C

Another Example regarding inherent limits to predictability(and somewhat model flaws also)

Evolution of the 2002-03 El Nino event compared to the 1997-98 El Nino event

“Signal” versus “Noise” issuesENSO is a slowly varying coupled ocean-atmospherephenomenon with a timescale of a year or longer.

Sub-seasonal weather acts rapidly on the coupled ocean-atmospheresystem with a time scale of weeks to months.

Eastward-propagatingconvective anomalyrelated to the MJO(Madden-Julian Oscillation)creates strong low-level winds.

1996-1998 : Low Frequency

1996-1998 : High Frequency

2001-2003 : High Frequency

Even if a model has skillENSO Prediction is Not a Guarantee

El NiñoIMPACTS

Source: Ropelewski & Halpert, 1987 J. Climatehttp://www.cpc.ncep.noaa.gov/products/analysis_monitoring/impacts/warm.gif

“Expectations” of climate anomaliesduring El Niño events

Mo

nso

on

Rai

nfa

ll I

nd

ex

Red = warm NINO3 SSTA - El Niño Blue = cold NINO3 SSTA - La Niña

“ Relative Frequency”

of Climate Impacts(rainfall) due toEl Niño Events

Data & maps available through IRI Data Library:http://iridl.ldeo.columbia.edu/SOURCES/.IRI/.Analyses/.ENSO-RP

Drought & El Nino

Note: 5 month lag between max. NINO3.4 SSTA and extent peaks

Spatial Extent of Tropical Drought Correlated with El Niño

Source: B. Lyon, 2004, GRL

What is the indirect (i.e. through climateteleconnections) impact of El Niño events on CO2 variability?

• The basic ENSO mechanism is understood, and

can be predicted, but gaps remainRole of MJO/WWBs, different “flavors” of ENSO,

decadal differences in predictability

• Prediction skill is limited byModel flaws, data assimilation methods, limited data,

inherent limits to predictability

• ENSO events have global impactsMany occur reliably,

but most are just more likely with an El Niño or La Niña event

• ENSO events impact CO2 variability

Summary

Extra Slides…

1. Climate Mean State (focus on tropics):

Annual Mean Solar Radiation

Annual Mean Heat Flux into the Ocean

Steric Heightrelative to 2000mFrom T, S data

at 1500m

at 0m

Temperature along the equator

Equatorial Undercurrent

SST Anomalies: Dec 1997

1997/98 El Niño

Economic “Cost” of El Nino1982-83

Economic “Cost” of El Nino1997-98

$14b USD : World Meteorological Organization

$36b USD : NOAA OGP (excluding ’98 China floods)

$45b USD : OFDA/CRED Int’l Disaster Database

Caution Must be Exercised when Attributing a “Cost” to an “Event”

In the case of ENSO…

• Would the what is the baseline of ‘cost’?

Or, What is the economic cost of disasters ENSO-neutral years??

• Could the impact (or cost) have occurred in the absence of the event?

DROUGHTS

Southern Africa

FLOODS

Peru Southern California