Scott Power, Greg Kociuba, Jeff Callaghan Centre for Australian Weather and Climate Research
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Transcript of Scott Power, Greg Kociuba, Jeff Callaghan Centre for Australian Weather and Climate Research
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Decadal and longer-term variability in ENSO, ENSO teleconnections, and the Walker circulation
Scott Power, Greg Kociuba, Jeff Callaghan
Centre for Australian Weather and Climate ResearchBureau of Meteorology
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Contents
1.1. Decadal – interdecadal changes in ENSO Decadal – interdecadal changes in ENSO and ENSO teleconnections and ENSO teleconnections
2.2. A simple model for decadal variability in A simple model for decadal variability in ENSO and “ENSO-related” patterns of ENSO and “ENSO-related” patterns of variabilityvariability
3.3. An inadequacy of this modelAn inadequacy of this model
=>ENSO-driven multi-year variability =>ENSO-driven multi-year variability
=>Multi-year predictability =>Multi-year predictability
4.4. Anthropogenic changes in the Walker Anthropogenic changes in the Walker circulation and the SOI circulation and the SOI
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The SOI – a product of French Australian cooperation!
One of the world’s most important climatic One of the world’s most important climatic indicesindices
Used extensively to estimate and predict Used extensively to estimate and predict changes linked to ENSO and changes in the changes linked to ENSO and changes in the Walker circulation (e.g. in rainfall, agricultural Walker circulation (e.g. in rainfall, agricultural production, disease, streamflow, …)production, disease, streamflow, …)
If SOI < 0 = > weaker Walker circulationIf SOI < 0 = > weaker Walker circulation
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ENSO event frequencies and the SOI
-8
-6
-4
-2
0
2
4
6
8
10
12
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Year
No
. o
f even
ts &
SO
I
No.(LN) No.(EN) No.(EN)-No.(LN) JJASOND SOI
Power and Smith, Geophys. Res. Lett., 2007; updated
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Innisfail 1918
3500 residents, only 12 houses remained intact
Approximately 75-100 deaths
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Mackay 1918
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A new homogeneous tropical cyclone data base for north-eastern Australia
Taken over a decade to developTaken over a decade to develop Extensive primary sources of information:Extensive primary sources of information: Longest (non-palaeo) record in SH Longest (non-palaeo) record in SH
[1[1872/73-2009/10]872/73-2009/10] homogeneoushomogeneous
Callaghan and Power, 2010: Variability and Callaghan and Power, 2010: Variability and decline in tropical cyclones making land-fall decline in tropical cyclones making land-fall over eastern Australia since the late 19over eastern Australia since the late 19 thth century. century. Climate DynamicsClimate Dynamics..
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Delayed-Action Oscillator (DAO)
dT(t) /dt = aT (t) - bT ( t - d)dT(t) /dt = aT (t) - bT ( t - d) T = SOI or east Pacific SST; a, b >0; d=time delayT = SOI or east Pacific SST; a, b >0; d=time delay
Analytic solutions to the DAO Equation (Power 2010) with T(t) = T0 eat, t ≤ 0 :
],)1/(!
)([)(
1
00
kkN
k
at ktk
eTtT
t > 0
Cf. numerical solutions of Battisti and Hirst (1989)
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Simple model for DV(ENSO)
dT/dt(t) - bT ( t - d) + Noise ordT/dt(t) - bT ( t - d) + Noise or
dd22T/dtT/dt22 = - = -σσ0022T + 2T + 2σσRR dT/dt dT/dt + Noise+ Noise
Fitting DAO to SOI:
dT/dt = aT-bT(t-d) + Noise
d=7mo, a=0.13/yr, b=1.4/yr
Noise-driven damped oscillation with period =3.8 yr, decay time (e-folding scale) =
0.9 yr
cf. Thompson and Battisti (2000), Jin (1997), Meinen and McPhaden (2000)
Noise has decadal/interdecadal tail so stochastic forcing drives some of the decadal variability in ENSO
(even if ENSO is partially self-sustained)
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“The relationship between ENSO and Australian climate in both the model and the observations is strong in some
decades, but weak in others. A series of decadal-long perturbation experiments are used to show that if these
interdecadal changes are predictable, then the level of predictability is low”.
J. Climate, 2006
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Suppose Suppose EELFLF is a low pass filtered ENSO index, e.g.: is a low pass filtered ENSO index, e.g.:
11 mm
EELF LF = ------------ Σ E = ------------ Σ E t-kt-k., and ., and r(E, SST)= r(E, SST)= αα.. m+1m+1 k=0k=0
< E< ELFLF, SST, SSTLFLF>>
Then r(EThen r(ELFLF, SST, SSTLFLF) = ________________________ . (1)) = ________________________ . (1)
√ √ [ < E[ < ELFLF, E, ELFLF > <SST > <SSTLFLF, SST, SSTLFLF> ]> ]
Now Now < E< ELFLF, E, ELFLF > = < E > = < Ett, E, Ett + E + Et-1 t-1 + E+ Et-2 t-2 + E+ Et-3 t-3 + … + E+ … + Et-mt-m> / (m+1)> / (m+1)22
+ < E+ < Et-1t-1, E, Ett + E + Et-1 t-1 + E+ Et-2 t-2 + E+ Et-3 t-3 + … E+ … Et-mt-m> / (m+1)> / (m+1)22
+ … + < E+ … + < Et-mt-m, E, Ett + E + Et-1 t-1 + E+ Et-2 t-2 + E+ Et-3 t-3 + … E+ … Et-mt-m>/ (m+1)>/ (m+1)22
= (m+1)/(m+1)= (m+1)/(m+1)22=1 / (m+1), (2)=1 / (m+1), (2) where we have used the fact that E is white noise. Similarly where we have used the fact that E is white noise. Similarly
< SST< SSTLFLF, SST, SSTLFLF > = 1/(m+1), so (3) > = 1/(m+1), so (3)
< SST< SSTLFLF, E, ELFLF > = < SST > = < SSTtt, E, Ett + E + Et-1 t-1 + E+ Et-2 t-2 + …+ E+ …+ Et-mt-m>/ (m+1)>/ (m+1)22
+ < SST+ < SSTt-1t-1, E, Ett + E + Et-1 t-1 + E+ Et-2 t-2 + … E+ … Et-mt-m> / (m+1)> / (m+1)22
+ … + < SST+ … + < SSTt-mt-m, E, Ett + E + Et-1 t-1 + E+ Et-2 t-2 + … E+ … Et-mt-m>/ (m+1)>/ (m+1)22
= (m+1) < SST= (m+1) < SSTtt, E, Ett >/ (m+1) >/ (m+1)22
= α/ (m+1). (4)= α/ (m+1). (4)
Using (2)-(4) in (1) then gives Using (2)-(4) in (1) then gives r(Er(ELFLF, SST, SSTLFLF) = α.) = α.
Power and Colman, 2006: Climate DynamicsPower and Colman, 2006: Climate Dynamics
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Decadal pattern much broader
=> Different physics in off-
equatorial “wings”
c.f. Zhang et al. 1998; Mantua et al. 1997; Power
et al. 1999; Power and
Colman 2006
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CGCM: NINO3(4yra) & 310m Wing Index
-0.4
-0.2
0
0.2
0.4
0 20 40 60 80 100
Year
Ind
ex
Discovery: Sub-surface ENSO-driven off-equatorial decadal variability is highly predictable
Discovery: Sub-surface ENSO-driven off-equatorial decadal variability is highly predictable
Decadal-long Perturbation Experiments
Decadal-long Perturbation Experiments
13 years 13 years
Off-equatorial sub-surface variability is a low pass filtered version of ENSO variability
Off-equatorial sub-surface variability is a low pass filtered version of ENSO variability
Power and Colman, Climate Dynamics, 2006; cf. Newman et al. 2002Power and Colman, Climate Dynamics, 2006; cf. Newman et al. 2002
Low pass filtering due to dominance of low frequency oceanic Rossby waves in response to ENSO wind-stresses
Low pass filtering due to dominance of low frequency oceanic Rossby waves in response to ENSO wind-stresses
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Conclusions so far1.1. Large and important decadal – interdecadal Large and important decadal – interdecadal
changes in ENSO and ENSO indicators have changes in ENSO and ENSO indicators have been observed and modelledbeen observed and modelled
2.2. A simple model for decadal variability in A simple model for decadal variability in ENSO and ENSO-like patterns of variability ENSO and ENSO-like patterns of variability was presentedwas presented
3.3. While useful in capturing some of the While useful in capturing some of the variability, the simple model is inadequate variability, the simple model is inadequate because ocean acts as LPF on ENSO forcing because ocean acts as LPF on ENSO forcing
4.4. This yields e.g. ENSO-driven multi-year This yields e.g. ENSO-driven multi-year predictability in off-equatorial wingspredictability in off-equatorial wings
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Other evidence for more sophisticated physics
Kirtman and Scopf (1998)Kirtman and Scopf (1998) Kleeman et al. (1999)Kleeman et al. (1999) Wang et al. (20xx)Wang et al. (20xx) McGregor et al. (2008)McGregor et al. (2008) ……
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Anthropogenic changes in the Walker circulation and the SOI
4. 4.
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The SOI [and N(EN) – N(LN)]
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Power and Kociuba, Climate Dynamics, 2010 (submitted); see also Vecchi et al. (2006); Meehl et al. (2007)
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The Walker circulation weakens in response to global warming(Vecchi et al. 2006; Meehl et al. 2007 /IPCC AR5;Power and Kociuba 2010)
“This obviously means that the SOI also declines in response to global warming”
“So part of observed decline in SOI due to global warming”
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Or is it?
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The Walker circulation weakens in response to global warming
The SOI does not decline in response to global warming.
The large observed decline in the SOI is therefore natural.
Power & Kociuba, Climate Dynamics (submitted), 2010
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We can therefore infer (taking models at face value) that: Observed weakening of Walker circulation Observed weakening of Walker circulation
over 20over 20thth century due to century due to bothboth natural natural variability and external forcingvariability and external forcing
Supports conclusions of Meehl et al. 2009
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Future work (for dessert*)
Further clarify causes and relative importance of Further clarify causes and relative importance of decadal variability in ENSO activitydecadal variability in ENSO activity
Important that simulation of ENSO in CGCMs Important that simulation of ENSO in CGCMs becomes more realisticbecomes more realistic
* * wine earned by providing numerous references wine earned by providing numerous references during talkduring talk
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The End – thank you for listening!
Scott Power
Centre for Australian Weather and Climate ResearchBureau of Meteorology
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SOI used extensively to estimate and predict changes linked SOI used extensively to estimate and predict changes linked to ENSO and changes in the Walker circulation (rainfall, to ENSO and changes in the Walker circulation (rainfall, streamflow, disease, tropical cyclones, …)streamflow, disease, tropical cyclones, …)
Correlation coefficient between SOI and equatorial MSLP Correlation coefficient between SOI and equatorial MSLP pressure gradient (pressure gradient (ΔΔP) P) = 0.83= 0.83
ΔP = BoxE(5˚S-5˚N, 200˚E-280˚E) - BoxW(5˚S–5˚N, 80˚E–160˚E)
El Niño, weaker Walker circulation, SOI < 0El Niño, weaker Walker circulation, SOI < 0
Impact of global warming on the SOI
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Summary There has been pronounced interdecadal variability There has been pronounced interdecadal variability
in the Walker circulation during the 20in the Walker circulation during the 20 thth century and century and an overall weakening of the Walker circulation in an overall weakening of the Walker circulation in recent decades.recent decades.
Weakening due to both global warming and natural Weakening due to both global warming and natural variability.variability.
Global warming weakens Walker circulation but Global warming weakens Walker circulation but (surprisingly) increases SOI. The SOI is not a good (surprisingly) increases SOI. The SOI is not a good guide to changes in Walker circulation forced by guide to changes in Walker circulation forced by global warming. global warming.
Observed decline in SOI natural and largely due to a Observed decline in SOI natural and largely due to a natural increase in dominance of El Ninatural increase in dominance of El Niñño over La o over La NiNiñña activity.a activity.
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MMEM of the SOI (A2 and C20), the observed SOI, and associated confidence levels, 30yr averages, JJASOND
-4
-2
0
2
4
6
8
1900 1920 1940 1960 1980 2000 2020 2040 2060 2080 2100
SO
I (O
bser
ved
and
mod
elle
d)
95% confidence interval for 30yra MMEM SOI 95% confidence interval for 30yra SOI
MMEM, 30yra Obs SOI, 30yra
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Power (2010), Theoret. Appl. Climatol.; cf. numerical sols of Battisti and Hirst (1987)
-3
-2
-1
0
1
2
3
-1 1 3 5 7 9T(t
*)
t*=time/(delay time)
Analytic Solutions of the Linear DAO Equation, a=0.13/yr, delay=7mo, ICs:
T(t<0)=T(0)exp(at)
b=0.01
b=0.5
b=1.4
b=3
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Contents
1.1. Australian tropical cyclones: interannual-Australian tropical cyclones: interannual-decadal variability, and long-term trends decadal variability, and long-term trends and links to ENSO and the SPCZand links to ENSO and the SPCZ
2.2. Interdecadal variability and trends in the Interdecadal variability and trends in the Walker circulation, ENSO activity, and the Walker circulation, ENSO activity, and the Southern Oscillation IndexSouthern Oscillation Index
3.3. Predictability of ENSO teleconnections, Predictability of ENSO teleconnections, origin of decadal ENSO-like patternsorigin of decadal ENSO-like patterns
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CGCM: SST IndicesNINO3 & SST (205-270E, 8-12S)
-1.3
-0.65
0
0.65
1.3
0 20 40 60 80 100
Year
Te
mp
An
om
aly
(K
)
Power and Colman, Climate Dynamics, 2006Power and Colman, Climate Dynamics, 2006
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Wind-stress forced shallow water model and simplified coupled models
Equatorial region forcing Off-equatorial region forcing
McGregor et al., 2007McGregor et al., 2007
Off-equatorial region forcing
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First EOFs from Wind-forced Shallow Water Model
McGregor, Holbrook and Power, 2007; see also Wang et al. 2003, Part 1 – “wind-stress in eastern tropical &
subtropical basin most effective in driving this kind of zonal equatorial response (from theory and wind-forced
SWM)
McGregor, Holbrook and Power, 2007; see also Wang et al. 2003, Part 1 – “wind-stress in eastern tropical &
subtropical basin most effective in driving this kind of zonal equatorial response (from theory and wind-forced
SWM)
Forcing applied everywhere
Forcing applied everywhere
Off-equatorial forcing only
Off-equatorial forcing only
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Summary DCV in El Niño-Southern Oscillation is an DCV in El Niño-Southern Oscillation is an
important part of DCV in the Pacificimportant part of DCV in the Pacific Randomness seems to explain a lotRandomness seems to explain a lot Nevertheless predictability is evidentNevertheless predictability is evident
as ENSO-modified red noiseas ENSO-modified red noise equatorial variability driven by off-equatorial variability driven by off-
equatorial wind-stressesequatorial wind-stresses ENSO-driven decadal climate variability in ENSO-driven decadal climate variability in
sub-surface ocean sub-surface ocean ……
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CGCM: SST IndicesNINO3 & SST (205-270E, 8-12S)
-1.3
-0.65
0
0.65
1.3
0 20 40 60 80 100
Year
Te
mp
An
om
aly
(K
)
Power and Colman, Climate Dynamics, 2006; see also Newman et al. 2007 for similar behaviour in PDO Index
Power and Colman, Climate Dynamics, 2006; see also Newman et al. 2007 for similar behaviour in PDO Index
dT/dt = -aT + bE + dT/dt = -aT + bE + cNcN
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No. severe land-falling TCs & the SPIstandardized, normalized, 11yr raves, Correl Coeff=0.64
-2
-1
0
1
2
3
1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Nov Apr neg SPIa_11yra/SD nTCsa_11yra/SD
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Newspaper archives Brisbane Courier MailBrisbane Courier Mail held at the held at the
Queensland State LibraryQueensland State Library Maryborough ChronicleMaryborough Chronicle researched by researched by
the Hervey Bay City Councilthe Hervey Bay City Council Townsville Historical SocietyTownsville Historical Society Mackay MercuryMackay Mercury Cairns PostCairns Post Rockhampton Morning BulletinRockhampton Morning Bulletin Cairns Historical Society Cairns Historical Society Archives of various newspapers held by Archives of various newspapers held by
the Bureau of Meteorology, Brisbanethe Bureau of Meteorology, Brisbane
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Interannual variability in the SOI is an Interannual variability in the SOI is an excellent proxy for interannual variability in excellent proxy for interannual variability in ΔΔPPequatorequator and and the Walker circulation:the Walker circulation: SOI > 0 => La Niña SOI > 0 => La Niña SOI < 0 => El Niño SOI < 0 => El Niño
But under global warming But under global warming ΔΔPPequatorequator
decreases whereas the SOI increasesdecreases whereas the SOI increases
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Paths of cyclones in El Nino (top) vs La Nina (bottom) years
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Power et al., 1999: Clim. Dyn.
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CGCM: All-Australia Rainfall v. NINO4
-0.8
-0.4
0
0.4
0.8
0 100
Year
CG
CM
vari
ab
le
CGCM: All-Australia Rainfall v. NINO4
-0.8
-0.4
0
0.4
0.8
0 100
Year
CG
CM
vari
ab
le
Correlation Coefficients in 13 yr running blocks NINO4/-ozT, NINO4/ozR in CGCM
-1
-0.5
0
0.5
1
0 20 40 60 80 100
time
co
rre
l. c
oe
ff
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Non-linear impact of ENSO on southwest USA/Mexico?
Power et al. 2006
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Summary so far ENSO teleconnections to Australia vary substantially from ENSO teleconnections to Australia vary substantially from
generation-to-generationgeneration-to-generation This variability seems to have very little predictability This variability seems to have very little predictability The changes are in phase with IPO/PDO because of non-The changes are in phase with IPO/PDO because of non-
linearity in the ENSO teleconnection to Australialinearity in the ENSO teleconnection to Australia This gives interesting effects that seem to point to decadal This gives interesting effects that seem to point to decadal
predictability but this is not necessarily the casepredictability but this is not necessarily the case Non-linear teleconnections may exist elsewhereNon-linear teleconnections may exist elsewhere The IPO and PDO have strong linksThe IPO and PDO have strong links Discussion of PDO emphasizes North Pacific Discussion of PDO emphasizes North Pacific
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Correlation Coefficients
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The SOI and beer consumption in Australia
Hot, dry Thirsty
Go to pub to get drink
Cool, wet => Go to pub to get out of rain
Number of visits to pub/month
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CGCM: All-Australia Rainfall v. NINO4
-0.8
-0.4
0
0.4
0.8
0 100
Year
CG
CM
vari
ab
le
CGCM: All-Australia Rainfall v. NINO4
-0.8
-0.4
0
0.4
0.8
0 100
Year
CG
CM
vari
ab
le
Power et al., J. Climate, 2006
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Decadal pattern much broader
=> Different physics in off-
equatorial “wings”
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Brisbane - 1893 flood – 23 deaths
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Next: Decadal changes in ENSO teelconnections
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All-Australia Rainfall v. SOI, 1900-2004, Annual Data
200
400
600
800
-25 -20 -15 -10 -5 0 5 10 15 20 25
SOI
Rain
fall
ObservationsObservations
Power et al. 2006: J. Climate.Power et al. 2006: J. Climate.
CGCM: All-Australia Rainfall v. NINO4 (JJASOND)
-2
-1
0
1
2
3
4
5
-10 -5 0 5 10
NINO4
Rain
fall
Coupled GCM
Coupled GCM
Discovery: Australian response to ENSO is asymmetric in observations and CGCM
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Power 2010
Fitting DAO to SOI:
dT/dt = aT-bT(t-d) + Noise
d=7mo, a=0.13/yr, b=1.4/yr
damped oscillation with period =3.8 yr, decay time (e-folding scale) = 0.9 yr
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Decadal changes in ENSO teleconnections
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SPI (Nov-Apr) & SOI (June-Dec), Correl Coeff = -0.79, 11yra
-2.5
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Nov Apr neg SPIa_11yra/SD June-Dec SOIa_11yra/SD