ocean processes and pacific decadal climate variability michael alexander earth system research lab...
TRANSCRIPT
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Ocean Processes and
Pacific Decadal Climate Variability
Michael Alexander
Earth System Research Lab
Physical Science Division
NOAA
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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?)
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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
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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
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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
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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
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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
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Reemergence in three North Pacific regions
Regression between SST anomalies in April-May with monthly temperature anomalies as a function of depth.
Regions
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“The Atmospheric Bridge”
Meridional cross section through the central Pacific
(Alexander 1992; Lau and Nath 1996; Alexander et al. 2002 all J. Climate)
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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
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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
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Ocean Surface Currents
Surface currents mainly driven by wind
Subtropical Gyre
Subtropical GyreSubtropical Gyre
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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)
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•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
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Wet
Precipitation (land only)
Dry
180°
Warm
Cold
Surface Air Temperature
180°
Precipitation and Temperature Patterns Associated with NP Index
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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)
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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
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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%)
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PDO or slab ocean forced by noise?
From David Pierce 2001, Progress in Oceanography
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- 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
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“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)
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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
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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
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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
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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
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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
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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
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Prediction of the PDO
Monthly values PDO Index1998 Transition?
Curve Extrapolation
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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
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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
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Seasonal Footprinting Mechanism
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Subduction and the Subtropical Cell
Subtropical Cell
Ekman
McPhaden and Zhang 2002 Nature
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Change in Subduction Rate
Transport at 9ºN & 9ºS Convergence & SST
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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
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Do subducting anomalies reach the equator and influence ENSO?
Year
Latitude
a) b) c) d)
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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
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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
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Process that Influence SST
Vek important on all time scalesVg associated with eddies (~50km) & large-scale Rossby waves
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Model Experiments to Test Bridge
Hypothesis
SpecifiedSSTs
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Influence of Air-sea Feedback on the atmospheric response to ENSO
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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
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Basin-wide Reemergence
Alexander et al. 2001, Progress in Oceanography
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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
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Upper Ocean: Temperature and mixed layer depth
El Niño – La Niña model composite: Central North Pacific
Alexander et al. 2002, J. Climate
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Forecast Skill: Correlation with Obs SST Wave Model & Reemergence
Wave Model Reemergence
years
Schneider and Miller 2001 (J. Climate)
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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.
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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
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SLP & SST Patterns of Pacific VariabilityWhat process are involved?
ENSO PDO
Regressions: SLP – Contour; SST Shaded
Mantua et al. 1997, BAMS
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Schematic of the Latif and Barnett Hypothesis
Warm SSTs
Positive air - sea feedback
Hwind
~5yrs to crossWeakens warmKuroshio Current
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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
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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
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“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
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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.
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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)
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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
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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)