ECLIPSE
Evaluating the CLimate and Air Quality
ImPacts of Short-livEd Pollutants
NILU,CICERO, METNO, IIASA, Met Office, U. Reading,
UPMC, FORTH, U. Leipzig, U. Peking, U. Tsinghua
Overview
• Motivation for studying short-lived pollutants
• Applications of climate metrics for SLCPs
• ECLIPSE structure
• Conclusions
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Importance of short-lived pollutants
• Control of SLCPs more
important in short-term
<30-40 years
• Control of CO2 more
important in long-term
Gothenburg Protocol + EU CO2 targets
Climate metrics
• Often used to compare and trade climate agents
– CO2 as reference gas
– GWP100=AGWP100/AGWPCO2100
• The absolute metrics parameterise climate impact
– AGWP(t): total energy input from an emission (J kg-1) up to time t
– AGTP(t): surface temperature change (K kg-1) at time t
• Can calculate temperature impacts of any policy knowing
ΔE(t) and AGTP(t)
• SLCPs: heterogeneous impacts, vary with latitude band l.
– ARTPl(t) (Regional rather than Global)
Applications
• Can use regional climate metrics (ARTPs) to identify
regional climate impacts of any emission profile
– Used HTAP results of regional forcing (Collins et al. 2013)
• BC, OC, SO2, NOx, VOC, CO, CH4, (no NH3 in HTAP)
• scaled by Bond et al. efficiencies for BC, OC (incl. indirect effect)
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Calculating metrics
Combination of chemistry and climate models
GCM
(climate)
∆F
CTM
∆B(t)
(radiation)
(chemistry)
∆E
RTM
∆T(t) 𝑑𝑇(𝑡)
𝑑𝐹
𝑑𝑇 𝑡
×
∆F(t)
𝑑𝐸
𝑑𝐹(𝑡)
𝑑𝐸
AGTP(t)
CCM
(chemistry-radiation)
All together in one Earth System model
ESM
∆T(t), ∆P(t) 𝑑𝑇 𝑡
∆E
(chemistry-radiationclimate)
𝑑𝐸
AGTP(t)
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ECLIPSE structure
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Emissions
• Generated by IIASA
• More realistic than CMIP5 RCPs
• Available for use by other projects
– PEGASOS, ECLAIRE
• Will generate “climate optimum” pollution controls
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ECLIPSE model output processing
Overall Model Performance Visualization
Via AeroCom web interface
Where compared ?
Local month to month variation?
ECLIPSE, Paris, 17 June 2013
Correlated ?
Regional Normalized Bias ?
Histogram?
Zonal Absolute Bias ?
met.no
Vertical profile of BC at high latitudes:
Hippo1:
Oslo CTM2
and
RCP emissions
Oslo CTM2
and
ECLIPSE
emissions
Hippo1 Jan 2009 Schwarz et al. (GRL 2009)
DJF mean concentration north of 65 degrees:
← ECLIPSE 2009 simulations
Sensitivity tests CTM2/3→
Totally dominated by FFBF BC!
WP4 – Climate forcing
The overall goal of this work package is to determine climate forcing as
a function of emission sector and emission region for a comprehensive
set of region/sector combinations.
EUROPE
Summer
CO
NOx
nmVOC
SO2
NH3
BC
OC
Winter
EAST ASIA
Summer
Winter
SHIPPING
Summer
Winter
REST OF WORLD
Summer
Winter
Radiative forcings
• In ECLIPSE we use effective RF (ERF) as well as RF.
• ERF includes fast feedbacks
• Fixed SST, but allows temperature profile and clouds to
respond
• Better estimate of temperature response than RF
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RF
• RFs give clear signal (fixed meteorology)
• Can detect differences between regions
and season
Radiative Forcing
per kg emitted
East Asia
Europe
Shipping
ERFs
• ERFs give noisy signal (varying
meteorology)
• Can’t so easily detect differences
between regions and season
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Coupled chemistry-climate simulations
t
e
m
p
e
r
a
t
u
r
e
Global reduction of seven SLCFs
Control simulation: WMGHG
concentrations and SLCF emissions
fixed
simulation time
50 yrs
Analyse climate responses:
- temperature, precipitation, run off,
cloudiness, ecosystem productivity
• Will be even more noisy than ERFs
• Need to run for very long time 50-100 years
Conclusions
• Improve understanding of key processes (esp. in Artic)
• Produce Air Quality and climate metrics relating
emission changes to regional impacts (esp. in Arctic)
– Compare separate steps with full Earth System Model
• These metrics can in principle be used to assess impacts
of any scenario
• They will be used calculate an “optimum” set of emission
control measures balancing air quality and climate
• The research leading to these results has received funding from the
European Union Seventh Framework Programme (FP7/2007-2013)
under grant agreement no 282688 - ECLIPSE
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