Ocean Processes and

Pacific Decadal Climate Variability

Michael Alexander

Earth System Research Lab

Physical Science Division

NOAA

Why should we look to the ocean for low-frequency (> 1 season) variability? • Thermal Inertia

– 4 m of ocean holds as much heat as atmosphere above• Water takes a long time to heat up and cool down• Temperature anomalies once created persist

• Dynamical Processes– Some very slow

• Currents slow (1 m/sec) – Advection of temperature anomalies can take many years

• Adjustment of midlatitude currents (~5 years - decades) • Exchanges with the deep ocean can take decades to centuries!

• Important Implications – Marine Ecosystems (fisheries)– Atmospheric Circulation

• ( SSTs => Atmosphere?)

Midlatitude SST Variability

• There are many ways that SST anomalies form– We will explore just a few mechanisms – Ones that are part of larger Pacific climate signals

• Mechanisms for generating midlatitude SST anomalies– Surface heat fluxes - Climate Noise– Upper Ocean mixing processes– “Atmospheric Bridge”: Teleconnections with ENSO

– Changes in ocean currents • Wind driven (through ocean Rossby waves)• Thermal/salt driven: Thermohaline (Atlantic) - next week

Simple model for generating SST variability“stochastic model”

Heat fluxes associated with weather events,“random forcing”

Ocean response to flux back heatwhich slowly damps SST anomalies

SST anomalies formAir-sea interface

Fixed depth oceanNo currents

Bottom

The Simple Ocean’s SST Anomaly Variability

time

SS

TA

Complex behavior withdecadal anomalies!

10 yrs

SSTn+1 = *SSTn + =constant; = Random number

Log plot ofSSTA Spectra

Period1yr10 yr

No damping

SS

TA

Var

ianc

e1 mo

Atm forcing

Simple Ocean Model: correspondence to the real world?Observed and Theoretical Spectra for a location in the

North Atlantic Ocean

Theoretical spectra of Simple ocean model

Observed OWS

Tem

pera

ture

Var

ianc

e

1 year 1 month

(Hz) is the frequency

period:

Atmospheric forcing and ocean feedback estimated from data

Seasonal cycle of Temperature & MLD in N. PacificReemergence Mechanism

• Winter Surface flux anomalies

• Create SST anomalies which spread over ML

• ML reforms close to surface in spring

• Summer SST anomalies strongly damped by air-sea interaction

• Temperature anomalies persist in summer thermocline

• Re-entrained into the ML in the following fall and winter

Qnet’

Alexander and Deser (1995, JPO), Alexander et al. (1999, J. Climate)

MLD

Reemergence in three North Pacific regions

Regression between SST anomalies in April-May with monthly temperature anomalies as a function of depth.

Regions

“The Atmospheric Bridge”

Meridional cross section through the central Pacific

(Alexander 1992; Lau and Nath 1996; Alexander et al. 2002 all J. Climate)

Mechanism for Atmospheric Circulation Changes due to El Nino/Southern Oscillation

Horel and Wallace, Mon. Wea Rev. 1981

Latent heatrelease inthunderstorms

Atmospheric wave forced by tropical heating

El Niño – La Niña Composite: DJF SLP Contour (1 mb); FMA SST (shaded ºC)

Model

Obs

Impact midlatitude SSTs: modest ~2 mb SLPAnd complex - varies with season

Ocean Surface Currents

Surface currents mainly driven by wind

Subtropical Gyre

Subtropical GyreSubtropical Gyre

Leading Pattern (1st EOF) of North Pacific SST

+ Phase - PhaseK

Mantua et al. (BAMS 1997)

PC 1 SST North Pacific

The Pacific Decadal Oscillation (PDO)

•Extratropical Signature•Tropical Linkages

“NP” Index (Nov-Mar) 1900-2002

Trenberth and Hurrell (1994)

Pacific Decadal Atmospheric Variability

EOF1 SLP Pacific/Arctic

PC: Regressed on full field

Independent of the Atlantic

Wet

Precipitation (land only)

Dry

180°

Warm

Cold

Surface Air Temperature

180°

Precipitation and Temperature Patterns Associated with NP Index

Alaska – Japan

Alaska/Canada

SST PC 1

200025 47 77

(- NP Index)

1900

PRECIP

SLP

AIR T

North Pacific Climate Indices (Winter)

Deser et al. (J. Climate, 2004)

What Causes the PDO? and Pacific Decadal Variability in General?

• Random forcing by the Atmosphere– Aleutian low => underlying ocean

• Signal from the Tropics?– Perhaps associated with decadal variability in the

ENSO region

• Midlatitude Dynamics– Shifts in the strength/position of the ocean gyres– Could include feedbacks with the atmosphere

Aleutian Low Impact on Fluxes & SSTs in (DJF)Leading Patterns of Variability AGCM-MLM

EOF 1 SLP (50%)

SLP PC1 - Qnet correlation

SLP PC1 - SST correlation

EOF 1 SST (34%)

PDO or slab ocean forced by noise?

From David Pierce 2001, Progress in Oceanography

- NP Index

1900 2000

25 47 77 (Boreal Winter)Climate Indices

Indian Ocean SST

(poleward side)

(C Eq Pac) Cloud

SLP (“SOI”)(Indian – Pac)

- SPCZ Rain

(eq’ward side)SPCZ Rain

Tropical

“Decadal” variability in the North Pacific: tropical (ENSO) Connection?

Observed SST Nov-Mar (1977-88) – (1970-76)

MLM SST Nov-Mar (1977-88) – (1970-76)

Wind Generated Rossby Waves

West East

Atmosphere

Ocean

Thermocline

ML

L

Rossby Waves

1) After waves pass ocean currents adjust2) Waves change thermocline depth, if mixed layer reaches that

depth, cold water can be mixed to the surface

Observed Rossby Waves & SST

t o xP c F τ∂ − ∂ = ∇×∫:

Schneider and Miller 2001 (J. Climate)

March

KE Region: 40°N, 140°-170°E

SSTOBS

T400SSTfcst

Correlation Obs SST hindcast With thermocline depth anomaly

Forecast equation for SST based on integrating wind stress (curl) forcing and constant propagation speed of the (1st Baroclinic) Rossby wave

Ocean Response to Change in Wind Stress

Contours: geostrophic flow from change in wind stress

Shading: vertically integrated temperature (0-450 m): 1982-90 – 1970-80

Deser, Alexander & Timlin 1999 J. Climate

SLP 1977-88 - 1968-76

Response to Midlatitude SST Anomalies

SST Anomaly (°C) specified as the Boundary Condition in an AGCM

CI = 0.5°C

2.5

Peng et al. 1997 J Climate; Peng and Whittaker 1999, J. Climate

Response to Midlatitude SST anomalies

30

30

30

120W120E

Cross Section of heights along 40ºNCI = 5m

Heights250 mbCI = 5m

200

500

1000

40

30

120W120E

-20

PDO: Multiple Causes?• Newman, Compo, Alexander 2003, Schneider and Miller 2005,

Newman 2006 (All in Journal of Climate)

• Interannual timescales:– Integration of noise (Fluctuations of the Aleutian Low)– Response to ENSO (Atmospheric bridge)

• Decadal timescales (% of Variance)– Integration of noise (1/3)– Response to ENSO (1/3)– Ocean dynamics (1/3) – Predictable out to (but not beyond) 1-2 years

• We developed a statistical method gives skillful PDO prediction out ~1 year

• Trend– Most Prominent in Indian Ocean and far western Pacific– Likely associated with Global warming

Prediction of the PDO

Monthly values PDO Index1998 Transition?

Curve Extrapolation

Summary• Climate noise

– Expect decadal variability when looking at SST time series

• Atmospheric Bridge– Cause and effect well understood– Tropical Pacific => Global SSTs– Influence of air-sea feedback on extratropical atmosphere complex

• PDO (1st EOF of North Pacific SST)– Thermal response to random fluctuations in Aleutian Low– A significant fraction of the signal comes from the tropics

• Extratropical ocean integrates (reddens) ENSO signal• Decadal variability in tropics – impact atmosphere & ocean

– Ocean currents & Rossby waves in western N. Pacific– extratropical air-sea feedback: modest amplitude

• Other Processes/modes of variability– Other variability besdies PDO, focused on west Pacific– Extratropical => tropical interactions

Extratropical => Tropical Connections

Meridional cross section through the central Pacific

Subduction

Upwelling +entrainment

(SFM: Vimont et al. 2003; Subduction: Schneider et al. 1999 JPO)

Seasonal Footprinting Mechanism (SFM)

Winter:Intrinsic atmosphericvariability

Spring-Summer: atmosphere Responds to subtropical SSTs

Winds drive oceanLeads to ENSO

Seasonal Footprinting Mechanism

Subduction and the Subtropical Cell

Subtropical Cell

Ekman

McPhaden and Zhang 2002 Nature

Change in Subduction Rate

Transport at 9ºN & 9ºS Convergence & SST

Subduction

Colored contours -0.3C anomaly isotherms for 3 different pentads

Black lines – mean isopycnal surfaces (lines of constant density)

Central North Pacific

Averaged over 170ºW-145ºW

Do subducting anomalies reach the equator and influence ENSO?

Year

Latitude

a) b) c) d)

Additional Information

• Processes that influence SSTs

• PDO verses ENSO

• Reemergence as a function of time

• Ocean Dynamics:– Rossby waves, – Ocean Rossby waves– Latif & Barnett Hypothesis for decadal variability– Subduction

SST Tendency Equatione.g. Frankignoul (1985, Reviews of Geophysics)

VariablesTm – mixed layer temp (SST)

Tb – temp just beneath ML

Qnet – net surface heat flux

Qswh – penetrating shortwave radiation

h – mixed layer depthw – mean vertical velocitywe – entrainment velocity

v - velocity (current in ML) vek – Ekman + vg - geostrophic

A – horizontal eddy viscosity coefficient

( ) 2vm net swh eb m m m

Q QT w wT T T A T

t ch hρ

−∂ +⎛ ⎞= + − − ⋅∇ + ∇⎜ ⎟∂ ⎝ ⎠

r

Process that Influence SST

Vek important on all time scalesVg associated with eddies (~50km) & large-scale Rossby waves

Model Experiments to Test Bridge

Hypothesis

SpecifiedSSTs

Influence of Air-sea Feedback on the atmospheric response to ENSO

Atmospheric Response to ENSO over the North Pacific

El Niño – La Niña 30-day Running Mean Composite 500 mb height anomaly (176ºE-142ºW; 32ºN-48ºN)

Aleutian L

ow

Basin-wide Reemergence

Alexander et al. 2001, Progress in Oceanography

Evolution of the leading pattern of SST variability

as indicated by extended EOF analyses

Alexander et al. 2001, Prog. Ocean.

No ENSO;Reemergence

ENSO;No Reemergence

Upper Ocean: Temperature and mixed layer depth

El Niño – La Niña model composite: Central North Pacific

Alexander et al. 2002, J. Climate

Forecast Skill: Correlation with Obs SST Wave Model & Reemergence

Wave Model Reemergence

years

Schneider and Miller 2001 (J. Climate)

PDO: The Latif and Barnett Hypothesis

• Coupled atmosphere-ocean interaction in the extratropics causes variability with a period of ~20 years

• Key processes: Atmosphere strongly responds to SST anomalies near Japan. Atmospheric circulation maintains SST through surface heat fluxes but drive changes in the ocean surface currents which reverse the SSTs ~5-10 years later. Time scale determined by oceanic Rossby waves.

Mechanisms for North Pacific Decadal Variability

• Air-sea interaction within the North Pacific basin – stochastic forcing (null hypothesis, simple slab)

– Ocean dynamics (Latif and Barnett 1994, 1996) Time scale set by changes in ocean currents (oceanic Rossby waves). Relies on strong atmospheric response to midlatitude SST anomalies.

• Tropical-extratropical interactions– Subduction: ocean transport from N. Pacific to tropics; atmospheric

teleconnections from Tropics to midlatitudes close the loop (Gu and Philander . Observations indicate this pathway is unlikely (Schneider et al., 1999).

– Air-sea interaction within the Tropical Indo-Pacific basin, with atmospheric teleconnections to the North Pacific as a by-product

• Tropical Ocean has ENSO + Reemergence => PDO (Null hypothesis II)• Tropical ocean has a mechanism for decadal variability

SLP & SST Patterns of Pacific VariabilityWhat process are involved?

ENSO PDO

Regressions: SLP – Contour; SST Shaded

Mantua et al. 1997, BAMS

Schematic of the Latif and Barnett Hypothesis

Warm SSTs

Positive air - sea feedback

Hwind

~5yrs to crossWeakens warmKuroshio Current

Impact of Ocean Currents on the Atmosphere

15 Wm-2

Prescribed ocean heat flux convergence in a slab ocean model coupled to a AGCMMimics ocean heat transport anomaliesin Kuroshio region

eq

30N

60N

SLP (mb x 100)

500 mb (m)

From Yulaeva et al., 2001, J Climate

PDO Null hypothesis II:ENSO + Reemergence + Noise?

Newman et al, 2003, J. Climate

Obs PDO

ENSOModel PDO, Ensemble Ave

Model PDO, 95% confidence interval

Model PDO, Ave of 20% closest to PDO

“Model”: PDOn+1 = PDOn + *ENSOn+1 + and are constants estimated from data, then ran model 1000 times

“Forecast” of Annual Mean Anomalies PDO vs. observed PDO

Correlation = 0.74

1ˆ

n n nPDO PDO ENSO −= +

=0.58; =0.58

Newman et al. 2003, J. Climate

Skill of Seasonal Statistical PDO predictions by verification season during 1971-2000

PDO (1st EOF of N. Pacific SST) Nino 3.4

Correlation between prediction and observed time series.

PDO & ENSO combined influence on SLP signal?a) El Niño b) La Niña

e) El Niño Low PDO

c) El Niño High PDO d) La Niña High PDO

f) La Niña Low PDO

-8.5

-4.5

-1.51.5

3.5

Gershunov and Barnett (1998, J. Climate)

Testing the PDO’s influence on the ENSO SLP signal

High-Low PDO, El Niño High-Low PDO, La Niña

Pierce (2002, J. Climate)

Obs

300 yrCoupledGCM

Fixed SSTs

1900:24

1925:46minus

1947:76

1977:97

1947:76

1925:46minus

minus

Wet

Dry

Winter Epoch Differences: High – Low SLP North Pacific

Land Precipitation Deser et al. (In preparation)