application of normal mode functions for the improved
TRANSCRIPT
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CSIRO
Application of normal mode functions for theimproved balance in the CAFE data assimilation
system and characterisation of modes of variabilityVassili Kitsios & Terry O’Kane
2nd International Conference on Seasonal to Decadal Prediction (S2D), 17th-21st, Boulder, CO, USA
OCEANS AND ATMOSPHEREwww.csiro.au
Application of normal mode functions for the improved balance in the CAFE data assimilation system and characterisation of modes of variability : Slide 2 of 19
Approach
• Will focus on the characterisation of the Madden Julian Oscillation (MJO)via a Normal Mode Functions (NMF) decomposition of JRA55, and dis-cuss implications for Normal Mode Inialisation (NMI).• MJO is a mode of variability resulting from coupled tropical deep convec-
tion and atmospheric dynamics.• Use key MJO properties to identify representatives NMFs:
– Eastward propagating– Dominant variance over intra-seasonal timescales: 30-90 days.– Tropics centric dynamics.– Horizontal velocity field has a dominant longitudinal wave of k = 1.– Dominant component of the zonal velocity is symmetric about the
equator.• Using one such mode we produce phase and conditional averages of:
– velocity potential to illustrate atmospheric dynamics– outgoing longwave radiation to illustrate convection
• Acknowledge Zagar for sharing the NCAR NMF code, MODES.
Application of normal mode functions for the improved balance in the CAFE data assimilation system and characterisation of modes of variability : Slide 3 of 19
What are Normal Mode Functions ?
• Decompose 3D (λ, φ, σ) velocity (u, v) and geopotential height (h) fieldsinto horizonal and vertical scales, and mode type, using the eigensolu-tion of the linearised primitive equations on a sphere.• Each scale decomposed into: Balanced Component (BAL) ; Eastward
Inertial Gravity Wave (EIG) ; Westward Inertial Gravity Wave (WIG).• Vertical Structure Functions (VSF), Gm in σ coordinates.
• Longitudinal (λ) waves eikλ
• Meridional (φ) Horizonal Structure Functions (HSF) of wind and height(U, V,H) for EIG, WIG and BAL modes.
[u(σ, λ, φ, t)v(σ, λ, φ, t)h(σ, λ, φ, t)
]=
M∑
m=1
Gm(σ)
[ √gDm 0 00
√gDm 0
0 0 gDm
]K∑
k=−Keikλ
N∑
n=0
EIG,WIG,BAL∑
p
[U(φ)−iV (φ)H(φ)
]p
knm
χpknm(t)
• Complex coefficients, χpknm(t), represent contributions of each compo-nent.
Application of normal mode functions for the improved balance in the CAFE data assimilation system and characterisation of modes of variability : Slide 4 of 19
Vertical Structure Functions
• VSF given by solution of the VSF eigenvalue problem (EVP).• VSF EVP requires only a time and horizontally averaged static stability
profile in σ coordinates.• Equivalent heights Dm (eigenvalues) are indicative of vertical scale.• VSFGm(σ) (eigenvectors) havem−1 zero crossings. G1 is the barotropic,G2 the first baroclinic, G3 the second baroclinic, ...• For large m, the VSF represent boundary layer processes.
101 102 103 104 105
Γ0 [K]
100
101
102
103
σ×p 0
[hPa]
(a) static stability ≡ Γ0
0 10 20 30 40vertical mode number
10−1
100
101
102
103
104
Dm[m
etres]
(b) equivalent height ≡ Dm
−0.5 0.0 0.5amplitude [unitless]
100
101
102
103
σ×p 0
[hPa]
(c) vertical structure functions
m=1
m=2
m=8
m=15
m=28
Application of normal mode functions for the improved balance in the CAFE data assimilation system and characterisation of modes of variability : Slide 5 of 19
Horizontal Structure Functions
• HSF given by solution of a HSF EVP for each equivalent height (Dm).• Eigenvectors give meridional dependence, with mode types (EIG, WIG,
BAL) defined by symmetry properties.• Frequency ν (eigenvalue) is indicative of temporal scale.
−30 −20 −10 0 10 20 30longitudinal wavenumber (k)
100
101
102
103
104
1/νq knm[days]
(a) timescales for m = 28
BAL
EIG
WIG
MRG
KW
0 10 20 30 40vertical mode number (m)
100
101
102
103
1/νq knm[days]
90days
60days
30days
(b) timescales
BAL(1,1,m)
WIG(1,0,m)
EIG(1,0,m)
−1 0 1amplitude
−75
−50
−25
0
25
50
75
latitude(φ)
(c) U qknm(φ)
EIG(1,0,28)
EIG(1,0,8)
BAL(1,1,15)
BAL(1,1,8)
• Recall for MJO: k = 1; tropics centric; U is symmetric• Only the EIG n = 0, WIG n = 0, and BAL n = 1 are tropics centric with
the appropriate symmetries.• EIG m = 23− 32 ; BAL m = 11− 22 have intra-seasonal timescales.
Application of normal mode functions for the improved balance in the CAFE data assimilation system and characterisation of modes of variability : Slide 6 of 19
Energy Contribution χpknm(t)χp∗knm(t) of NMFs in JRA55
• BAL dominates for low k, IG dominate for high k• BAL dominates for all vertical modes m• For (k, n) = (1, 1) BAL HSF eigenvectors have MJO-like properties:
– BAL (k, n,m) = (1, 1, 2) and (1, 1, 2) local peaks in energy, but toofast
– BAL (k, n,m) = (1, 1, 15) has HSF eigenvalue of 46 days.
• For (k, n) = (1, 0) EIG HSF eigenvectors also have MJO-like properties:
– EIG (k, n,m) = (1, 0, 8) has most energy, but timescale too fast
– EIG (k, n,m) = (1, 0, 28) has HSF eigenvalue of 56 days.
100 101 102
zonal wavenumber (k)
10−4
10−3
10−2
10−1
100
101
102
103
104
nonzonal
energy
[J/kg]
(a)
BAL
EIG
WIG
total
0 10 20 30vertical mode (m)
(b)
0 10 20 30vertical mode (m)
(c) (k, n) = (1, 1)
0 10 20 30vertical mode (m)
(d) (k, n) = (1, 0)
Application of normal mode functions for the improved balance in the CAFE data assimilation system and characterisation of modes of variability : Slide 7 of 19
Cross-spectral Analysis of Candidate NMFs
• All candidate modes are tropics centric and have the appropriate symme-tries.• Only EIG (k, n,m) = (1, 0, 28) has an intra-seasonal timescale, and
propagates eastward, but has low energy.• Cross-spectral analysis identifies only slow intra-seasonal timescales are
coherent between EIG (k, n,m) = (1, 0, 28) and the more energeticmodes.• Fast Kelvin wave removed from energetic EIG (k, n,m) = (1, 0, 8).
2 4 6 8 10k
0.0
0.1
0.2
0.3
0.4
0.5
f[1/days]
30days
(a) PSD of EIG(k,0,8) [J/kg]
10−4
10−3
10−2
10−1
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101
2 4 6 8 10k
(b) PSD of EIG(k,0,28) [J/kg]
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10−3
10−2
10−1
2 4 6 8 10k
(c) coherence
0.0
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0.8
1.0
2 4 6 8 10k
(d) coherence output [J/kg]
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10−3
10−2
10−1
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101
5 10 15 20 25 30 35m
0.0
0.1
0.2
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f[1/days]
(e) coherence output of EIG(1,0,m) [J/kg]
10−4
10−3
10−2
10−1
100
101
102
5 10 15 20 25 30 35m
(f) coherence output of BAL(1,1,m) [J/kg]
10−4
10−3
10−2
10−1
100
101
102
Application of normal mode functions for the improved balance in the CAFE data assimilation system and characterisation of modes of variability : Slide 8 of 19
Cross-spectral Analysis of Candidate NMFs
• All candidate modes are tropics centric and have the appropriate symme-tries.• Only EIG (k, n,m) = (1, 0, 28) has an intra-seasonal timescale, and
propagates eastward, but has low energy.• Cross-spectral analysis identifies only slow intra-seasonal timescales are
coherent between EIG (k, n,m) = (1, 0, 28) and the more energeticmodes.• Repeated for all vertical scales (m) with k = 1 for BAL and EIG.
2 4 6 8 10k
0.0
0.1
0.2
0.3
0.4
0.5
f[1/days]
30days
(a) PSD of EIG(k,0,8) [J/kg]
10−4
10−3
10−2
10−1
100
101
2 4 6 8 10k
(b) PSD of EIG(k,0,28) [J/kg]
10−4
10−3
10−2
10−1
2 4 6 8 10k
(c) coherence
0.0
0.2
0.4
0.6
0.8
1.0
2 4 6 8 10k
(d) coherence output [J/kg]
10−4
10−3
10−2
10−1
100
101
5 10 15 20 25 30 35m
0.0
0.1
0.2
0.3
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0.5
f[1/days]
(e) coherence output of EIG(1,0,m) [J/kg]
10−4
10−3
10−2
10−1
100
101
102
5 10 15 20 25 30 35m
(f) coherence output of BAL(1,1,m) [J/kg]
10−4
10−3
10−2
10−1
100
101
102
• Other candidate modes highlighted in coherence output clusters.
Application of normal mode functions for the improved balance in the CAFE data assimilation system and characterisation of modes of variability : Slide 9 of 19
Phase Average on Basis of EIG (k, n,m) = (1, 0, 28)
• Phase angle calculated from complex χpnmk. Dates associated with eachphase angle octant averaged. All modes contribute to phase averages.
• Velocity potential is a propagating longitudinal wave, with a vertical signchange representing upper level divergence and lower level convergence.
Application of normal mode functions for the improved balance in the CAFE data assimilation system and characterisation of modes of variability : Slide 10 of 19
Phase Average on Basis of EIG (k, n,m) = (1, 0, 28)
• Phase angle calculated from complex χpnmk. Dates associated with eachphase angle octant averaged. All modes contribute to phase averages.
• OLR has a dipole pattern over the maritime continent, tracking with veloc-ity potential of like sign.
Application of normal mode functions for the improved balance in the CAFE data assimilation system and characterisation of modes of variability : Slide 11 of 19
Large and Persistent MJO Events
• Start and end of each event defined as discontinuities in phase angle ofEIG (k, n,m) = (1, 0, 28).• Persistent events have a continuous phase for longer than 270◦.• Large events have a magnitude in the upper quartile.• Composite average magnitude is greater than background for 20 days be-
fore and after day 0.• Composite average phase angle indicates eastward propagation.
• Dates associated with each phase shift identified and averaged to producecomposite fields of velocity potential and outgoing longwave radiation.
Application of normal mode functions for the improved balance in the CAFE data assimilation system and characterisation of modes of variability : Slide 12 of 19
Velocity Potential at 200hPa - Wave Like
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Application of normal mode functions for the improved balance in the CAFE data assimilation system and characterisation of modes of variability : Slide 13 of 19
Outgoing Longwave Radiation at 200hPa - Dipole Like
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Application of normal mode functions for the improved balance in the CAFE data assimilation system and characterisation of modes of variability : Slide 14 of 19
Instantaneous Comparison of NMFs and WH
• Wheeler & Hendon index based on first two PCs of meridionally averagedu at 200hPa, 850hPa and OLR within 15◦S and 15◦N .• Compare to tropics centric NMFs, with MJO-like symmetries:
– BAL(k, n,m) = (1, 1, 8) : energetic, but westward, timescale too fast.
– EIG(k, n,m) = (1, 0, 8) : energetic, but timescale too fast.
– BAL(k, n,m) = (1, 1, 15) : intra-seasonal timescale, but westward.
– EIG(k, n,m) = (1, 0, 28) : intra-seasonal timescale, eastward, notenergetic.
• Correlation of BAL (k, n,m) = (1, 1, 8) with WH when filtered to retaintemporal scales coherent with EIG (k, n,m) = (1, 0, 28) is 0.78.
2001 2003 2005 2007 2009 2011 2013 20150.00
0.25
0.50
0.75
1.00
1.25
1.50
1.75
2.00
√〈W
H〉 M
A
0.0
0.5
1.0
1.5
2.0
2.5
3.0
√〈E
q knm〉 M
A
(a) 91 day moving average
BAL(1,1,8) unfiltered BAL(1,1,8) EIG(1,0,8) BAL(1,1,15) EIG(1,0,28) unfiltered WH
2012-0
2-05
2012-0
2-19
2012-0
3-04
2012-0
3-18
2012-0
4-01
2012-0
4-15
−150
−100
−50
0
50
100
150
phaseangle
(b) phase angle
−2 −1 0 1 2RMM1
−2
−1
0
1
2
RMM2
(c) phase space WH
−2 −1 0 1 2 3real(χq
knm)√Dmg/2
−2
−1
0
1
2
imaginary(χq knm)√
Dmg/2
(d) phase space BAL(1,1,8)
Application of normal mode functions for the improved balance in the CAFE data assimilation system and characterisation of modes of variability : Slide 15 of 19
Instantaneous Comparison of NMFs and WH
• Wheeler & Hendon index based on first two PCs of meridionally averagedu at 200hPa, 850hPa and OLR within 15◦S and 15◦N .• In comparision to WH, coherence filtered BAL(k, n,m) = (1, 1, 8) mode
exhibits:– high correlation in magnitude over the entire time series (1958-2016)– consistent phase propagation for a specific event (Jan 2012)– consistent spiralling in for a specific event in phase space
2001 2003 2005 2007 2009 2011 2013 20150.00
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0.50
0.75
1.00
1.25
1.50
1.75
2.00
√〈W
H〉 M
A
0.0
0.5
1.0
1.5
2.0
2.5
3.0
√〈E
q knm〉 M
A
(a) 91 day moving average
BAL(1,1,8) unfiltered BAL(1,1,8) EIG(1,0,8) BAL(1,1,15) EIG(1,0,28) unfiltered WH
2012-0
2-05
2012-0
2-19
2012-0
3-04
2012-0
3-18
2012-0
4-01
2012-0
4-15
−150
−100
−50
0
50
100
150
phaseangle
(b) phase angle
−2 −1 0 1 2RMM1
−2
−1
0
1
2
RMM2
(c) phase space WH
−2 −1 0 1 2 3real(χq
knm)√Dmg/2
−2
−1
0
1
2
imaginary(χq knm)√
Dmg/2
(d) phase space BAL(1,1,8)
Application of normal mode functions for the improved balance in the CAFE data assimilation system and characterisation of modes of variability : Slide 16 of 19
Proposed MJO Skeleton
• Nonlinear interactions of these modes generates an energetic MJO ofeastward propagation and correct phase period.• All modes have MJO-like longitudinal and meridional structure.
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• Interaction strength inferred from cross-spectral analysis.• In the future will calculate the nonlinear transfer terms explicitly.
Application of normal mode functions for the improved balance in the CAFE data assimilation system and characterisation of modes of variability : Slide 17 of 19
Concluding Remarks
• NMFs decompose a 3-D atmospheric geopotential height and horizon-tal velocity field into scale (zonal, meridional, vertical) and mode class(BAL, EIG, WIG).• MJO-like NMF modes and their interactions were isolated in the JRA-55.• A skeleton physical model of the MJO was proposed.
• Implications for Normal Modes Initialisation:– Since the IG waves have shorter timescales, they are potentially less
predictable over a multi-year period.– Naively one would think that filtering the IG waves would improve pre-
dictability.– However, the EIG waves (even of small vertical scale and low energy)
are shown here to be dynamically important for the MJO.
Application of normal mode functions for the improved balance in the CAFE data assimilation system and characterisation of modes of variability : Slide 18 of 19
QuestionsVertical Structure Functions Horizontal Structure Functions
101 102 103 104 105
Γ0 [K]
100
101
102
103
σ×p 0
[hPa]
(a) static stability ≡ Γ0
0 10 20 30 40vertical mode number
10−1
100
101
102
103
104
Dm[m
etres]
(b) equivalent height ≡ Dm
−0.5 0.0 0.5amplitude [unitless]
100
101
102
103
σ×p 0
[hPa]
(c) vertical structure functions
m=1
m=2
m=8
m=15
m=28
−30 −20 −10 0 10 20 30longitudinal wavenumber (k)
100
101
102
103
104
1/νq knm[days]
(a) timescales for m = 28
BAL
EIG
WIG
MRG
KW
0 10 20 30 40vertical mode number (m)
100
101
102
103
1/νq knm[days]
90days
60days
30days
(b) timescales
BAL(1,1,m)
WIG(1,0,m)
EIG(1,0,m)
−1 0 1amplitude
−75
−50
−25
0
25
50
75
latitude(φ)
(c) U qknm(φ)
EIG(1,0,28)
EIG(1,0,8)
BAL(1,1,15)
BAL(1,1,8)
Cross-Spectral Analysis Phase Averages2 4 6 8 10k
0.0
0.1
0.2
0.3
0.4
0.5
f[1/days]
30days
(a) PSD of EIG(k,0,8) [J/kg]
10−4
10−3
10−2
10−1
100
101
2 4 6 8 10k
(b) PSD of EIG(k,0,28) [J/kg]
10−4
10−3
10−2
10−1
2 4 6 8 10k
(c) coherence
0.0
0.2
0.4
0.6
0.8
1.0
2 4 6 8 10k
(d) coherence output [J/kg]
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10−3
10−2
10−1
100
101
5 10 15 20 25 30 35m
0.0
0.1
0.2
0.3
0.4
0.5
f[1/days]
(e) coherence output of EIG(1,0,m) [J/kg]
10−4
10−3
10−2
10−1
100
101
102
5 10 15 20 25 30 35m
(f) coherence output of BAL(1,1,m) [J/kg]
10−4
10−3
10−2
10−1
100
101
102
Composite Averages Skeleton Physical Model
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(g) 10 days
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0◦7.5◦N15◦N
(h) 15 days
15◦S7.5◦S
0◦7.5◦N15◦N
0◦ 90◦E 180◦ 90◦W0◦
(i) 20 days
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CSIRO
OCEANS AND ATMOSPHEREwww.csiro.au
CSIRO Oceans and Atmosphere
Vassili Kitsiost 0362325312e [email protected] research.csiro.au/dfp/
CSIRO Oceans and Atmosphere
Terry O’Kanete Terrence.O’[email protected] research.csiro.au/dfp/