Atmospheric dynamics feedback: concept, simulations and climate
implicationsMichael P. Byrne1,2 & Tapio Schneider3
1. Imperial College London 2. ETH Zürich 3. California Institute of Technology
Example of a potential atmospheric dynamics feedback: Tropical iris effect
0 30 latitude
Current climate
weak cooling
[e.g. Pierrehumbert (1995), Lindzen et al. (2001), Mauritsen &
Stevens (2015), Bony et al. (2016)]
strong cooling
0 30 latitude
Future climate
[e.g. Pierrehumbert (1995), Lindzen et al. (2001), Mauritsen &
Stevens (2015), Bony et al. (2016)]
Example of a potential atmospheric dynamics feedback: Tropical iris effect
weak cooling
strong cooling
Outline
1. Calculating the atmospheric dynamics feedback
2. Dynamics feedback in coupled climate models
3. Impact of atmospheric circulation changes on global climate: Inferences from simple theory and idealised simulations
Dynamic/thermodynamic decomposition of top-of-atmosphere radiative anomalies: Bony et al. (2004)
• Premise: Large-scale atmospheric circulation is a strong control on top-of-atmosphere radiation
Bony et al. (2004); Byrne & Schneider (submitted)
Dynamic/thermodynamic decomposition of top-of-atmosphere radiative anomalies: Bony et al. (2004)
• Premise: Large-scale atmospheric circulation is a strong control on top-of-atmosphere radiation
• Bin all-sky TOA fluxes as a function of mid-tropospheric vertical velocity
ω [hPa day−1]
All−
sky
rad.
effe
ct [W
m−2
]
−100 −75 −50 −25 0 25 50 75−80
−60
−40
−20
0
ω [hPa day−1]
Area
PD
F [%
]
−100 −75 −50 −25 0 25 50 750
5
10
15
R(!) A(!)
� = [�30�, 30�]
Bony et al. (2004); Byrne & Schneider (submitted)
Dynamic/thermodynamic decomposition of top-of-atmosphere radiative anomalies: Bony et al. (2004)
• Premise: Large-scale atmospheric circulation is a strong control on top-of-atmosphere radiation
• Bin all-sky TOA fluxes as a function of mid-tropospheric vertical velocity
R(!) A(!)
R =
Z 1
�1R(!)A(!)d!
ω [hPa day−1]
All−
sky
rad.
effe
ct [W
m−2
]
−100 −75 −50 −25 0 25 50 75−80
−60
−40
−20
0
ω [hPa day−1]
Area
PD
F [%
]
−100 −75 −50 −25 0 25 50 750
5
10
15
R(!) A(!)
� = [�30�, 30�]
Bony et al. (2004); Byrne & Schneider (submitted)
Dynamic/thermodynamic decomposition of top-of-atmosphere radiative anomalies: Bony et al. (2004)
�R =
dynamicz }| {Z 1
�1R(!)�A(!)d!+
thermodynamicz }| {Z 1
�1�R(!)A(!)d!+
nonlinearz }| {Z 1
�1�R(!)�A(!)d!
Bony et al. (2004); Byrne & Schneider (submitted)
Dynamic/thermodynamic decomposition of top-of-atmosphere radiative anomalies: Bony et al. (2004)
�R =
dynamicz }| {Z 1
�1R(!)�A(!)d!+
thermodynamicz }| {Z 1
�1�R(!)A(!)d!+
nonlinearz }| {Z 1
�1�R(!)�A(!)d!
ITCZ narrowing, convective aggregation, Hadley cell widening, tropical slowdown, jet shift…
Bony et al. (2004); Byrne & Schneider (submitted)
Dynamic/thermodynamic decomposition of top-of-atmosphere radiative anomalies: Bony et al. (2004)
• Simulations: Use CMIP5 abrupt4xCO2 and piControl runs (27 models) • Method: Perform decomposition at each latitude individually, and for all-
sky fluxes (not only cloud-radiative effect)
�R =
dynamicz }| {Z 1
�1R(!)�A(!)d!+
thermodynamicz }| {Z 1
�1�R(!)A(!)d!+
nonlinearz }| {Z 1
�1�R(!)�A(!)d!
Bony et al. (2004); Byrne & Schneider (submitted)
ITCZ narrowing, convective aggregation, Hadley cell widening, tropical slowdown, jet shift…
Atmospheric dynamics feedback vs lat: Smaller than thermodynamic feedbacks but shapes tropical cloud response
All-sky radiative effect Cloud radiative effect
Latitude [deg]
−δR
(clo
ud) [
W m
−2] ×
cosφ
−60 −30 0 30 60−1
0
1
2
3
4 TotalThermodynamicDynamic + Nonlinear
Latitude [deg]
δR (a
ll sk
y) [W
m−2
] × c
osφ
−60 −30 0 30 60
−6
−5
−4
−3
−2
−1
0
1
(multimodel mean, averaged over 100 years following 4xCO2)
warming
cooling
Byrne & Schneider (submitted)
Influence of circulation changes on global radiative balance is negligible
Surface temperature response [K]
Glo
bal r
ad. a
nom
aly
[W m
−2]
1 2 3 4 5
−7−6−5−4−3−2−1
01
TotalThermodynamicDynamic + NonlinearFit
CCSM4 model
estimated equilibrium temperature change
Byrne & Schneider (submitted)
Global dynamics feedback is small & positive: Increases temperature response by 0.2K (3% of total warming)
CCSM4 model
Surface temperature response [K]
Glo
bal r
ad. a
nom
aly
[W m
−2]
1 2 3 4 5
−7−6−5−4−3−2−1
01
FitFit (thermo. only)
estimated equilibrium temperature change
(thermodynamic only)
Byrne & Schneider (submitted)
Why is the global atmospheric dynamics feedback small?
Byrne & Schneider (submitted); see also Wyant et al. (2006)
• A simple explanation with two ingredients: Mass budget + linearity of R(ω)
1. Mass budget: “what goes up must come down”
2. Assume TOA radiation depends linearly on ω
R(!) = a+ b!
Why is the global atmospheric dynamics feedback small?
• A simple explanation with two ingredients: Mass budget + linearity of R(ω)
upward fluxz }| {Z 0
�1!A(!)d! = �
Z 1
0!A(!)d!
| {z }downward flux
Byrne & Schneider (submitted); see also Wyant et al. (2006)
1. Mass budget: “what goes up must come down”
2. Assume TOA radiation depends linearly on ω
upward fluxz }| {Z 0
�1!A(!)d! = �
Z 1
0!A(!)d!
| {z }downward flux
R(!) = a+ b!
Why is the global atmospheric dynamics feedback small?
• A simple explanation with two ingredients: Mass budget + linearity of R(ω)
Byrne & Schneider (submitted); see also Wyant et al. (2006)
1. Mass budget: “what goes up must come down”
2. Assume TOA radiation depends linearly on ω
Why is the global atmospheric dynamics feedback small?
ω [hPa day−1]
All−
sky
rad.
effe
ct [W
m−2
]
−100 −75 −50 −25 0 25 50 75−80
−60
−40
−20
0
area PDF of ω
• A simple explanation with two ingredients: Mass budget + linearity of R(ω)
upward fluxz }| {Z 0
�1!A(!)d! = �
Z 1
0!A(!)d!
| {z }downward flux
R(!) = a+ b!
Byrne & Schneider (submitted); see also Wyant et al. (2006)
1. Mass budget: “what goes up must come down”
2. Assume TOA radiation depends linearly on ω
upward fluxz }| {Z 0
�1!A(!)d! = �
Z 1
0!A(!)d!
| {z }downward flux
R(!) = a+ b!
dynamic comp.z }| {Z 1
�1R(!)�A(!)d! =
a
Z 1
�1�A(!)d! + b
Z 1
�1!�A(!)d! = 0
Why is the global atmospheric dynamics feedback small?
• A simple explanation with two ingredients: Mass budget + linearity of R(ω)
Byrne & Schneider (submitted); see also Wyant et al. (2006)
1. Mass budget: “what goes up must come down”
2. Assume TOA radiation depends linearly on ω
A strong constraint on ability of atmospheric dynamics feedbacks to influence global climate
=0 by definition =0 by mass balance
upward fluxz }| {Z 0
�1!A(!)d! = �
Z 1
0!A(!)d!
| {z }downward flux
R(!) = a+ b!
dynamic comp.z }| {Z 1
�1R(!)�A(!)d! =
a
Z 1
�1�A(!)d! + b
Z 1
�1!�A(!)d! = 0
• A simple explanation with two ingredients: Mass budget + linearity of R(ω)
Byrne & Schneider (submitted); see also Wyant et al. (2006)
1. Mass budget: “what goes up must come down”
2. Assume TOA radiation depends linearly on ω
A strong constraint on ability of atmospheric dynamics feedbacks to influence global climate
=0 by definition =0 by mass balance
upward fluxz }| {Z 0
�1!A(!)d! = �
Z 1
0!A(!)d!
| {z }downward flux
R(!) = a+ b!
dynamic comp.z }| {Z 1
�1R(!)�A(!)d! =
a
Z 1
�1�A(!)d! + b
Z 1
�1!�A(!)d! = 0
• A simple explanation with two ingredients: Mass budget + linearity of R(ω)
Difficult for atmospheric circulation changes to create
large TOA anomalies
Byrne & Schneider (submitted); see also Wyant et al. (2006)
Influence of hypothetically large dynamics feedbacks on global climate? Test using idealised simulations
• BUT… Processes not captured by global models could produce a large dynamics feedback [e.g. strongly nonlinear R(ω), convective aggregation]
• Investigate using an idealised GCM
Byrne & Schneider (submitted)
Latitude [deg]
TOA
forc
ing
[W m
−2]
−60 −30 0 30 60
0
5
10
Tropical forcingExtratropical forcing
• Slab-ocean aquaplanet with simplified radiative transfer [see Frierson et al. (2006), Frierson (2007), O’Gorman & Schneider (2008)]
• Impose two stylised longwave top-of-atmosphere forcings: tropical and extratropical
• Motivated by work on ocean heat uptake at different latitudes [e.g. Armour et al. (2013), Rose et al. (2014)]
Forcings
• BUT… Processes not captured by global models could produce a large dynamics feedback [e.g. strongly nonlinear R(ω), convective aggregation]
• Investigate using an idealised GCM:
Influence of hypothetically large dynamics feedbacks on global climate? Test using idealised simulations
Byrne & Schneider (submitted)
Tropical forcing ineffective at changing global temperature -> difficult for iris-type dynamic feedbacks to influence climate
Byrne & Schneider (submitted); see Rose et al. (2014) for ocean uptake analogy
• Tropical TOA anomalies less than half as effective at changing global surface temperature
Latitude [deg]
TOA
forc
ing
[W m
−2]
−60 −30 0 30 60
0
5
10
Tropical forcingExtratropical forcing
Forcings
Latitude [deg]
Surfa
ce te
mpe
ratu
re re
spon
se [K
]
−60 −30 0 30 60
−0.5
0
0.5
1
1.5
Tropical forcingExtratropical forcing
Responses
Tropical forcing ineffective at changing global temperature -> difficult for iris-type dynamic feedbacks to influence climate
Byrne & Schneider (submitted); see Rose et al. (2014) for ocean uptake analogy
• Tropical TOA anomalies less than half as effective at changing global surface temperature
Latitude [deg]
TOA
forc
ing
[W m
−2]
−60 −30 0 30 60
0
5
10
Tropical forcingExtratropical forcing
Forcings
Latitude [deg]
Surfa
ce te
mpe
ratu
re re
spon
se [K
]
−60 −30 0 30 60
−0.5
0
0.5
1
1.5
Tropical forcingExtratropical forcing
ResponsesTropical TOA anomalies inefficient at changing global
temperature
Summary• Atmospheric dynamics feedback calculated for coupled climate
models
• Dynamics feedback smaller than thermodynamic feedbacks at all latitudes, but relatively important in the tropics
• Two reasons why iris-type mechanisms unlikely to strongly influence global climate:
1. Mass balance + quasi-linear R(ω) constrain dynamics feedback to be small on large scales
2. Tropical TOA anomalies (e.g. iris) are relatively inefficient at changing global temperature