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Effects of Airborne Particles on Climate:
an Expert Elicitation
M. Granger Morgan, Peter J. Adams, and David W. Keith
7 March 2006
2
Overview
Background• Radiative forcing• Aerosol (airborne particles) climate effects• Previous assessments (IPCC TAR)• Aerosols and climate uncertainty
Expert Elicitation• Design• Results
Lessons Learned
3
Overview
Background• Radiative forcing• Aerosol (airborne particles) climate effects• Previous assessments (IPCC TAR)• Aerosols and climate uncertainty
Expert Elicitation• Design• Results
Lessons Learned
4
Earth’s Energy Balance
Sunlight (Shortwave, visible radiation)
235 Watts per square meter (W/m2)
Heat (Longwave, infrared radiation)
235 Watts per square meter (W/m2)
Perturbations to energy balance are known as “radiative forcings”
5
Radiative Forcings
Shortwave (incoming) or longwave (outgoing)
Both positive (warming) and negative (cooling)
Computed at various altitudes• Top-of-atmosphere (TOA): most useful
metric for global average temperature• Surface: useful metric for evaporation /
changes to hydrological cycle
6
Source: IPCC Third Assessment Report
7
Overview
Background• Radiative forcing• Aerosol (airborne particles) climate effects• Previous assessments (IPCC TAR)• Aerosols and climate uncertainty
Expert Elicitation• Design• Results
Lessons Learned
8
Aerosols Scattering Sunlight
Dust and smoke over Australia (Terra)
9
Aerosols Absorbing Sunlight
Kuwaiti oil fires
photo courtesy of Jay Apt (via Steve Schwartz)
10
Aerosols and Clouds
AVHRR satellite “false color” image
Red: darker clouds (large droplets)
Green: brighter clouds (small droplets)
Blue: clear sky
Power plant
Lead smelter
Port
Oil refineries
Rosenfeld, Science (2000)
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Aerosols and Clouds
Clean Air
Polluted Air
Aerosol Particles
Cloud Droplets
Brighter, more
persistent clouds
12
How direct is direct?
Direct effect: scattering/absorbing sunlight
Semi-direct effect:• aerosol absorption heats atmospheric layer• warmer air → lower relative humidity → less/no cloud
Indirect effect: modifying cloud properties• “brightness (first) effect”• “lifetime (second) effect”
13
Overview
Background• Radiative forcing• Aerosol (airborne particles) climate effects• Previous assessments (IPCC TAR)• Aerosols and climate uncertainty
Expert Elicitation• Design• Results
Lessons Learned
14
Source: IPCC Third Assessment Report
Indirect effect(s):
•TAR figure shows “brightness” effect only
•“lifetime” effect potentially comparable
•discussion buried in text
Direct effect(s):
•best understood
•divided by aerosol type
Semi-direct effect(s):
•not shown on TAR figure
•postulated in 2000
•discussed in text but no global estimate given
15
Overview
Background• Radiative forcing• Aerosol (airborne particles) climate effects• Previous assessments (IPCC TAR)• Aerosols and climate uncertainty
Expert Elicitation• Design• Results
Lessons Learned
16
Climate Change Uncertainty
“Climate sensitivity” is a key parameter
is “climate sensitivity”• 0.3 to 1 °C per W/m2
• 1.5 - 4.5 °C for doubling of CO2
In climate models, representation of cloud feedback is largest source of uncertainty
In retrospective studies, knowledge of aerosol forcing is lacking
FT global average temperature
change
global average radiative forcing
17
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
Forcing (W m-2)
Tem
per
atu
re C
han
ge
(K)
Aerosols and Climate Uncertainty
High sensitivity
Low sensitivity
GHG forcing
20th century T increase
Aerosol + GHG forcing
??
18
Aerosols and Climate Uncertainty
Uncertainty in aerosol forcing makes testing climate models against 20th century temperature record almost meaningless
Nevertheless all climate models do this test and claim good agreement as “validation” of their model
Aerosol forcing is a “tunable” parameter High sensitivity models ↔ Strong aerosol
cooling Low sensitivity models ↔ Weak aerosol
cooling
19
NH/SH mixing
intra-hemispheric
mixing
Challenges
Need to characterize particle• mass/number concentration• size distribution: ~10 nm to 10 m• chemical composition: >hundreds compounds• mixing state• interactions with clouds
Highly variable in space and time:
centurydecadalannualdaily monthlyhourly
Mean CO2
residenceMean
aerosol
residence
20
Overview
Background• Radiative forcing• Aerosol (airborne particles) climate effects• Previous assessments (IPCC TAR)• Aerosols and climate uncertainty
Expert Elicitation• Design• Results
Lessons Learned
21
Expert Elicitation
Granger Morgan “unofficially” invited by IPCC to survey expert opinion
Not intended to replace peer-reviewed scientific studies in literature
Usefulness• reveal agreement/disagreement between
experts• little systematic work on uncertainty in
aerosol forcing
22
Elicitation Methodology
Administered by mail 52 experts invited from broad base of
expertise types• Aerosols, clouds, and climate• Modeling, experimental• Global to micro scale
29 agreed• 2 said they lacked expertise• 3 did not complete
24 useable responses Participants acknowledged but responses are
anonymous
23
Elicitation Methodology
Six parts1. Direct: scattering/absorption of sunlight
2. Semi-direct: change in clouds as absorbing aerosols heat atmosphere
3. Cloud brightness (first indirect): smaller droplets → brighter clouds
4. Cloud lifetime (second indirect): smaller droplets → less precipitation
5. Total: net effect of above at top-of-atmosphere
6. Surface: net effect of above at surface
24
Elicitation Methodology
For each part/effect:a) list top factors contributing to uncertaintiesb) estimate radiative forcing probability distributions
upper/lower bounds “counterfactual” question 5/95% confidence intervals 25/75% confidence intervals best estimate
c) probability uncertainty will (in 20 years) increase shrink by 0-50% shrink by 50-80% shrink more than 80%
25
Overview
Background• Radiative forcing• Aerosol (airborne particles) climate effects• Previous assessments (IPCC TAR)• Aerosols and climate uncertainty
Expert Elicitation• Design• Results
Lessons Learned
•Best understood
•Responses broadly consistent with IPCC TAR
•One respondent: “semi-direct effect is positive by definition”
•Absorbing aerosols above marine stratocumulus increase reflectivity via dynamical effects – “still semi-direct”?
•Forcing or feedback?
•Most experts mostly in 0 to -2 W m-2 range of IPCC TAR
•A minority suggest possible effects of -3 to -4 W m-2
•Omitted from IPCC TAR•Many reflect “conventional wisdom” of 0 to -2 W m-2
•Significant minority give wider uncertainties•Believers in positive – an enlightened minority?
•“Forward” modeling: estimate forcing based on aerosol physics•“Reverse” modeling: estimate aerosol forcing as that needed to match historical temperature trends
0
+1
-1
-2
-3
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Surface Forcing
-4
-5
-6
-7
-9
-8
-10
NA
NA
to -12
NA
?
?
16 17 18 19 20 21
NA
NA
NA
NA
22 23 24
N+A
4 4 4 4 5 6 6 5 6 6 74 2 1 0 2 2 5 3
ExpertLevel of expertise 0 - 7
32
Conclusions
IPCC TAR assessment ok for what was reported
Significant uncertainties (cloud lifetime and semi-direct) unreported
Field is not “mature”: new physical mechanisms being uncovered/studied, significant chances of uncertainty increasing
Terminology is ambiguous (as well as confusing)
Lines between “forcings” and “feedbacks” blurred
Aerosols are part of the (irreducible?) climate uncertainty