Download Preferred Modes of Variability and Their Relationship with Climate Change

Preferred Modes of Variability and
Their Relationship with Climate Change
Seok-Woo Son and Sukyoung Lee
The Pennsylvania State University
Department of Meteorology
Annular Mode
- Dominant internal variability of the atmosphere
 Leading EOF of SLP
SH
NH
[u]
 Zonally symmetric
 Quasi-barotropic
 Useful for understanding
internal variability
 Useful for understanding
climate change (?)
SLP
Thompson et al. 2000
Thompson et al. 2000
Kushner et al. 2001
SH [u] response to global warming
NH Annular Mode
SH Annular Mode
pressure (hPa)
pressure (hPa)
NH [u] trend 1968-1997
latitude
“Spatial pattern” of annular mode ≈ recent trend in the
observed and simulated zonal-mean circulation
To what extent annular mode is capable of
predicting zonal-mean climate change?
Purpose and Approaches
Evaluate the predictability of zonal-mean climate change by
annular mode in terms of their spatial structures.
Total 49 simulations by differing radiative heating in a simple GCM
Structure of [u] in the statistically steady state ( [u] )
Internal variability of [u] with a help of EOF1 and EOF2
Annular mode vs. Climate change
Annular mode – EOF1 of [u] (regressed against PC1 time series)
Climate change – difference of [u] between any two adjacent runs
Numerical Model
 A dynamic core of GFDL GCM (symmetric boundary cond.)
 R30L10 but zonal wave number 15
 Driven by relaxing T toward Te with timescale of 30 days
 Dissipated by linear friction and 8th order hyperdiffusion
Te(C,H) = Tbase + ΔTe(C,H)
C : high-latitude cooling (K/day) H : tropical heating (K/day)
Numerical Model (Cont.)
 Total 49 realizations
C (0.00, 0.17, 0.33, 0.50, 0.67, 0.88, 1.00) K/day
H (0.00, 0.33, 0.67, 1.00, 1.33, 1.67, 2.00) K/day
 Statistics are derived from the last 4500 days of each 5000-day
integration. Data of both hemispheres are used.
(C,H)=(0.17,1.67)
(C,H)=(0.17,0.33)
(C,H)=(0.83,0.33)
[u]
Single Jet
Intermediate Jet
Double Jet
[u] : Structure of Westerly Jets
 Strong C & weak H → Double Jet
SJ
 H ≥ 1.00K/day → Single Jet
WJ
DJ
Internal variability of the jets
One-point correlation of 250-hPa [u]'
[u] & EOFs
SJ
Zonal-index
(Jet Meander)
WJ
Transition
DJ
Poleward
Propagation
Time series of PC1 and PC2
Correlation PC1 vs. PC2
SJ
Zonal-index
(Jet Meander)
WJ
Transition
DJ
Poleward
Propagation
Poleward Propagation: i. Correlation between PC1 & PC2 is very high
ii. Var(EOF2) is comparable to Var(EOF1)
Collocates with intermediate- and double-jet
Shading γ ≥ 0.5
Shading χ ≥ 0.5
Annular mode & Climate change in the modeI
 Annular mode : EOF1 of [u]
• [u] is regressed against PC1 time series, unit of m/s.
 Climate change : Difference of [u] between two adjacent runs
• δ[u]H (0.50,1.00) = [u] (0.50,1.33) - [u] (0.50,1.00)
• δ[u]C (0.50,1.00) = [u] (0.67,1.00) - [u] (0.50,1.00)
[u] (0.50,1.00)
δ[u]H (0.50,1.00)
δ[u]C (0.50,1.00)
Predictability of Climate change by Annular mode
I. Global measure
: pattern correlation between EOF1 and δ[u]
from 150-950 hPa and 10-80˚
EOF1 & δ[u]C
EOF1 & δ[u]H
Shading
correlation ≥ 0.8
Predictability is always poor in a poleward propagation regime.
Poor predictability of δ[u]H in a zonal-index regime
 Annular mode in the model is associated with eddy fluxes.
 δ[u]C is associated with eddy fluxes.
• Increase of C → enhances extratropical baroclinicity
 δ[u]H is associated with both eddy fluxes
and mean-meridional circulation.
• Increase of H → enhances subtropical baroclinicity and
intensifies Hadley circulation
 Predictability of δ[u]C would be better than that of δ[u]H.
Summary
Structure of Westerly Jet
• Strong C & weak H → Double Jet
• H ≥ 1.00 K/day → Single Jet
Internal Variability
• Strong C & weak H → Poleward propagation
(Comparable effect of EOF2)
• Weak C & strong H → Zonal index
(Dictated by EOF1)
• Broad transition zone
Predictability of Climate change by Annular mode
• Dependent on the dominant internal variability
• Relative good in a transition regime
Application to the Southern Hemisphere
 Applied to the SH climate change at equinoctial condition
Global warming at SH → ENSO-like tropical heating & enhanced
extratropical baroclinicity (Son and Lee 2005a) → increase of H and C.
 Structure of the jet
Wide range of interannual variability from single- to double-jet states
 Internal variability
Both poleward propagation and zonal index (e.g., Feldstein 1998;
Hartmann and Lo 1998) with γ ≈ 0.5 and χ ≈ 0.3 (Son and Lee 2005b).
[u]: structure of the jet
EOF1 & δ[u]C
EOF1 & δ[u]H
Application to the Southern Hemisphere (Cont.)
 Predictability is marginally good in the SH-like parameter regime.
 Annular mode may not be useful for understanding paleoclimate
change.
Slight climate drift to the poleward propagation regime
→ poor predictability.
EOF1 & δ[u]C
EOF1 & δ[u]H
Any comment and suggestion
are welcome. Thank you!
Contact information
Seok-Woo Son: [email protected]
Dependency of internal variability to the mean flow
 The meridional radiation of the waves is prohibited if the PV gradient of
the ambient flow is sufficiently sharp (e.g., Hoskins and Ambrizzi 1993)
 Poleward propagation of westerly anomalies may occur only when the PV
gradient is relatively weak and broad.
The latitudinal distance over which the
value of 250-hPa quasi-geostrophic PV
gradient ([q]y) is greater than 60% of its
maximum value. Shading for ≥ 35˚.
Prediction of Climate-change ‘Direction’ by Annular mode?
 Climate change direction (positive or negative phase of annular mode) is
determined not by the annular mode but by the nature of external forcing.
 Climate change associated with H increase (warming at tropics) →
negative phase of annular mode (out of phase).
 Climate change associated with C increase (broadening of extratropical
baroclinic zone) → positive phase of annular mode (in phase).
[u] (0.50,100)
- +
δ[u]H (0.50,100)
δ[u]C (0.50,100)
Prediction of Climate-change ‘Direction’ ? (Cont.)
Climate change in SH: tropical
warming & enhanced extratropical
baroclinicity (Son and Lee 2005a)
→ increase of H and C.
Climate change in SH is in phase
with SH annular mode.
SH [u] response to global warming
SH Annular Mode
By the overwhelming effect of
enhanced baroclinicity (C) over
tropical warming (H) ?
Kushner et al. 2001
Predictability of Climate change by Annular mode
II. Local measure
: latitudinal distance between extrema of EOF1 and δ[u] at 250 hPa
• δφC : between EOF1 and δ[u]C
• δφH : between EOF1 and δ[u]H
EOF1 & δ[u]C (line A)
• measured at both
subtropics and extratropics
δφC
A
 Weak latitudinal dependency of
δ[u]C prediction by annular mode.
δφC (low-latitude)
Shading δφ ≤ 2˚
δφC (mid-latitude)
δφH (low-latitude)
δφH (mid-latitude)
 Poor predictability of δ[u]H in a
zonal-index regime is due to
the mid-latitudes.
 Predictability is generally good
when γ ≤ 0.5 or
Var(EOF1) ≥ 2•Var(EOF2)
Shading γ ≥ 0.5
Prediction of Climate-change ‘Amplitude’ by Annular mode?
II. Local measure
: Compare amplitude of 250-hPa |EOF1| and |δ[u]| at 250 hPa
EOF1 & δ[u]C (line A)
A
δφC
Prediction of Climate-change ‘Amplitude’ by Annular mode?
shading: δφC ≤ 2˚
shading: δφH ≤ 2˚
ratio |δ[u]|/|EOF1|
difference (|δ[u]| - |EOF1|)
• Ratios of |δ[u]C| to |EOF1| are 0.3 to 0.8.
• Ratios of |δ[u]H| to |EOF1| are 1.0 to 2.5
Ratios vary only by a factor of two!
Predictable? No theories yet!