AEROSOL INDIRECT EFFECT:

1
AEROSOL INDIRECT EFFECT THE ELUSIVE COMPONENT
OF CLIMATE CHANGE
Athanasios Nenes HDGC Seminar, November 20, 2002
photo G.Roberts
2
Global warming vs. climate change.
Global warming is only one aspect. We are really
looking at is climate change. Air pollution is
much more than greenhouse gases. Aerosols
(suspended particles) are a major component why?
2
3
Research focus climate change.
Aerosols and their interaction with clouds play a
major role in the climate system.
3
4
Why are we interested in aerosols?
Aerosols are emitted together with greenhouse
gases.
Pollution plume 1500 km south of India.
Outside of the plume. Pristine state.
4
5
Why are we interested in aerosols?
Pollution plumes off of Asia they are of
continental proportions.
6
Why are we interested in aerosols?
Biomass burning in the Amazon.
7
Research focus aerosol effects on clouds.
Clouds play a major role in the climate system. A
small change in cloud properties can strongly
affect climate.
8
Question How do clouds form? Answer from
aerosols.
Clouds form in regions of the atmosphere where
water vapor is supersaturated. We focus on liquid
water clouds. Water vapor supersaturation is
generated by cooling (primarily through expansion
in updraft regions and radiative cooling) Cloud
droplets form from pre-existing particles found
in the atmosphere (aerosols). This process is
known as activation. Aerosols that can become
droplets are called cloud condensation nuclei
(CCN).
Cloud
CCN that activates into a cloud drop
Aerosol particle that does not activate
9
Example of cloud droplet formation in an updraft.
movie
log10(concentration)
log10(size)
10
What is the aerosol indirect effect?

• It is the change in cloud properties caused by a
  change in the CCN population.
• Cloud properties are a strong function of droplet
  concentration.
• Two kinds of indirect effects lead to climatic
  cooling
• Increase in cloud reflectivity
• Increase in cloud lifetime coverage.

Smaller droplets clouds reflect more and last
longer
11
Observational evidence of indirect effect
Ship tracks linear features of high cloud
reflectivity embedded in marine stratus clouds,
resulting from aerosols emitted by ships.
M.Kulmala Nucleation and Atmospheric Aerosols,
1996
12
Anthropogenic indirect forcing least understood.

• Potentially of large magnitude. (comparable to
  greenhouse gas warming)
• Cooling effect (counteracts greenhouse gas
  warming).
• Large uncertainty.

My focus
13
Why is the indirect effect poorly understood?

• Indirect forcing uncertainties arise because
• Aerosol-cloud interactions take place at smaller
  spatial scales than climate models can resolve,
  and must be parameterized.
• Aerosol-cloud interactions are complex many
  aspects are unknown or poorly understood.
• Climate models provide limited information about
  clouds, and aerosols.
• Central problem of indirect effect
• Determine the relationship between aerosol and
  cloud radiative properties, using the limited
  information available by climate models.
• This problem has historically been reduced to
  finding the relationship between aerosol mass
  concentration and cloud droplet number
  concentration.

14
Current understanding empirical

• Very large variability.
• Unresolved meteorology, cloud microphysics,
  aerosol chemical factors are responsible for the
  variability.
• Need for physically-based parameterizations.

15
Desired approach from first principles.
Cloud droplet number balance in each grid box of
the model
Activation is the direct aerosol-cloud droplet
link. Embedding a numerical activation model is
too slow must use parameterization of
activation. Parameterizations of aerosol
activation have appeared in the literature over
the years (from 1959). They are derived assuming
idealized cloud dynamics, aerosol composition and
size distribution. Are current
parameterizations good enough? (Hint No).
16
Parameterizations prescribed size distribution
bias
Fitting ambient size distributions to prescribed
functional form introduces biases which can be
important for indirect effect.
This aerosol is shifted to larger sizes.
17
Current parameterizations other weaknesses

• Lack of explicit treatment of mass transfer
  limitations in droplet growth this has been
  shown to be important for polluted conditions
  (Nenes et al., 2001).
• Empirical correlations are used in many. They are
  derived from numerical simulations and can
  introduce biases when used outside their region
  of applicability.
• They lack important chemical effects that can
  influence cloud droplet formation. Such effects
  are the presence of
• slightly soluble species in the aerosol (Shulman
  et al., 1996)
• water soluble gas-phase species (Kulmala et al.,
  1993)
• surface tension changes from surface-active
  species in the aerosol (Facchini et al., 1999)
• changes in water vapor accommodation coefficient
  from the presence of film-forming compounds
  (Feingold Chuang, 2002)

18
Currently unaccounted chemical effects.
Slightly soluble compounds They add solute to
the drop as it grows this facilitates their
ability to activate. Examples organics (succinic
acid), CaSO4.
Soluble gases They add solute to the drop as it
grows this facilitates their ability to
activate. Examples HNO3, HCl, NH3.
A(g)
A(g)
A(g)
A(aq)
A(aq)
A(aq)
19
Currently unaccounted chemical effects
Surface-active soluble compounds They decrease
surface tension of droplets this facilitates
their ability to activate. Examples organics
(succinic acid, humic substances). Their
solubility can be large.
Data of surface tension of concentrated samples
from Tenerife clouds and Po Valley
fogs (Charlson et al., 2001)
20
Currently unaccounted chemical effects
Film-forming compounds They can slow down
droplet growth. Once the film breaks, rapid
growth is resumed
Examples hydrophobic organics. Such substances
do not alter droplet thermodynamics kinetics of
droplet growth are affected. If present, such
substances can strongly affect droplet number.
21
Cloud droplet formation with film-forming
compounds.
movie
log10(concentration)
log10(size)
22
Chemical effects assessment of their importance.
Calculate the potential change in cloud
properties when a chemical effect is present.
23
Chemical effects summary, implications for
parameterizations
Chemical effects are seen to be important for
many conditions. They can even be more effective
than doubling aerosol concentrations (i.e. more
effective than the Twomey effect). Chemical
effects can be synergistic. One effect can be
important for low updrafts (e.g. soluble gas
effects) and another at higher updrafts (e.g.
surface tension effects). This would lead to a
systematic increase in droplet number for almost
any cloud type. Lack of including them in
activation parameterizations can lead to
important uncertainties in indirect
forcing. What does all this mean for current
aerosol activation parameterizations? They are
not adequate. We need to develop a new approach.
24
New parameterization Underlying ideas
Use sectional representation of aerosol chemistry
and size distribution.

• Each section can
• have its own chemical composition
• i-th section characterized by (i-1, i)
  boundaries
• piecewise linear profiles between boundaries
• Multiple populations with their own distributions
  can co-exist and compete for water vapor.
  Modified Köhler theory for computing CCN
• properties.

25
New parameterization conceptual framework

• Properties calculated from energy, mass balances.
  Adiabatic parcel model used to calculate droplet
  number.
• Lagrangian framework of reference
• Parcel properties are uniform
• Constant updraft velocity
• Parcel pressure is equal to ambient
• Explicit treatment of mass transfer limitations
  of water vapor to droplet phase.

t
Smax
S
26
New parameterization Formulation
Input P,T, updraft velocity (cooling rate), RH,
aerosol characteristics. Output Droplet
number How Solve the algebraic equation
(numerically)
27
Performance of new parameterization (200 test
cases)
28
Performance of existing parameterization (Ghan et
al, 2000)
29
New parameterization Marine aerosol with
surfactants
30
New parameterization assessment.

• A powerful activation parameterization for
  climate models has been developed for aerosol of
  
• arbitrary (non-ideal) size distribution,
• complex chemical and size-dependant composition
  (surfactants,
• slightly soluble substances present).
• Furthermore, it
• is fast (gt 1000 times quicker than full
  numerical parcel model).
• uses minimal amount of empirical information.
• is more robust and accurate than other
  parameterizations in use.
• Some future directions
• incorporate other activation effects.
• use it in a global model (GISS GCM with TOMAS).

31
New effect Black Carbon heating
Black carbon exists in polluted aerosol it
absorbs visible sunlight and heats the
surrounding air. This can leads to decreased
cloud coverage, and climatic warming. If black
carbon is included in cloud droplets, the heat
released can increase the droplet temperature
enough to affect the droplet equilibrium. This is
a new effect.
BC core
drop
Absence of heating
Presence of heating droplet and gas phase get
heated
32
New effect Black Carbon heating
BC heating can have an important effect on CCN of
large dry diameter only. This results in three
effects 1. Inhibition of the activation of
large CCN. This would make water vapor available
for the activation of smaller (and more numerous)
CCN. This tends to increase droplet
concentrations and cool climate. 2. Release of
heat into the gas phase drops parcel
supersaturation. This tends to decrease droplet
concentrations, and warm climate. 3. Decreased
size of low Sc CCN can decrease the chance of
drizzle formation (Giant CCN can initiate drizzle
formation). This would tend to increase cloud
lifetime and cool climate. Which of the
mechanisms can prevail?
33
Black Carbon heating effect on cloud albedo
Consider a case where Mechanism 1,2 are
strongest.
Simulation is for urban aerosol, 20 BC, 0.1 m
s-1 updraft. Conditions were chosen so that the
heating released from the BC in each curve is the
same. Albedo calculated by a two-stream
approximation. Differences are compared to
absence of BC heating.
Droplet changes are alone not significant but
they can affect the magnitude of albedo change
from BC heating.
34
Black Carbon heating effect on drizzle formation.
Assess the size of Giant CCN with and without BC
heating, for a marine stratocumulus cloud. We use
a Large Eddy Simulation of non-precipitating
marine stratocumulus (Stevens et al.,
J.Atmos.Sci, 1996).
500 Lagrangian trajectories derived from the LES
are used to drive a cloud parcel model and grow
the giant CCN in the cloud. Ensemble 1-hr
averages of the parcel properties yield average
cloud properties.
35
Black Carbon heating 50 selected LES
trajectories.
Cloud
Height
movie
Horizontal extent
36
Activation along one of the 500 trajectories.
movie
log10(concentration)
log10(size)
37
Black Carbon heating potential effect on drizzle
BC can effectively decrease the probability for
drizzle formation. A heating mechanism can lead
to climatic cooling! This effect can be
parameterized (not shown). Is it important? We
dont know yet.
500 parcel average
Cloud top
Cloud base
38
CCN INSTRUMENTS What do they do?
Purpose Measure the number of cloud droplets
that can form for a variety of water vapor
supersaturations (CCN spectrum), at a given
point in space and time. Operation principle
Expose particle sample to a known water vapor
supersaturation, and measure those that become
droplets.
Desired range 0.01 - 1.0 supersaturation
39
CCN INSTRUMENTS The need for theoretical
analysis

• Objective Assess the performance and
  limitations of current CCN measurement
  methodologies.
• Few designs available we focus on spectrometers
• Most attractive for aircraft missions.
• Minimal theoretical assessment of their
  capabilities.

• Approach
• Develop comprehensive models that express
  optimum instrument behavior.
• Simulate instrument response, assuming that
  inlet aerosol is monodisperse.

40
Fukuta Saxena (1979) CCN Spectrometer (FCNS)
Outlet, droplet detection
Metal envelope
Insulation
Inlet
Metal envelope
Hot tip
Thot
Wetted walls
Flow
Insulation
Smax
Tcold
Cold tip
(cross section)
Thot-Tcold
Property
Smax
Distance from tips

41
FCNS How is it used?
Characteristics Each streamline has different
S S constant along a streamline Detection must
distinguish droplets from unactivated
aerosol. Usage Measure droplet concentration at
a (centerline) streamline. CCN droplet
concentration. Scan for all streamlines.
42
FCNS Mathematical model
Droplet phase
(Lagrangian)
Gas phase
(Eulerian)
43
FCNS Activation along different streamlines
movie
log10(concentration)
Each color represents a different
streamline CCN activate as they flow through the
instrument
log10(size)
44
FCNS Activation at outlet of instrument
Note Droplets separate well from aerosol at high
S. Separation degrades as S decreases.
45
FCNS Why does performance degrade as S decreases?
1.5
High s 1.05 (good)
1.0
0.5
0.0
Centerline supersaturation ()
-0.5
-1.0
-1.5
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Distance from entrance of instrument (m)
y-position (m)
46
FCNS Why does performance degrade as S decreases?
1.5
1.0
Medium s 0.60 (good)
0.5
0.0
Centerline supersaturation ()
-0.5
-1.0
-1.5
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Distance from entrance of instrument (m)
y-position (m)
47
FCNS Why does performance degrade as S decreases?
1.5
Outlet
1.0
Inlet
0.5
Low s 0.14 (fair)
0.0
Centerline supersaturation ()
-0.5
-1.0
-1.5
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Distance from entrance of instrument (m)
y-position (m)
48
FCNS Why does performance degrade as S decreases?
Low S takes longer to develop than high S, and
CCN are exposed to S gt Sc for less time. Growth
at low S is much slower than at high
S activation takes longer than at high S.
Separation between droplets and
non-activated aerosol is lost at low S.
49
CCN INSTRUMENTS Assessment

• Fukuta CCN spectrometer
• sensitivity problems under low supersaturations.
• optimum Sc range 0.2 to 1.1
• not sensitive to aerosol chemical
  characteristics.
• All instruments displayed sensitivity problems
  for Sc lt 0.08-0.1. Some display large
  sensitivity to chemical composition.
• Model captures instrument behavior very well. Can
  be reliably used.
• Conclusion
• Instrumentation needs to be further improved.
  This is currently being done (Caltech, UCSD).
• A deep theoretical understanding of any
  instrument is necessary for reliable CCN
  measurements.

50
GENERAL SUMMARY
The indirect effect of atmospheric aerosols is
one of the most important and challenging aspects
of climate prediction science. A variety of
aerosol activation effects need to be included in
parameterizations of aerosol-cloud
interactions. There are possibly many
(counterintuitive) mechanisms to be
discovered. Parameterizations are being
developed, and included within a comprehensive
climate model system. CCN instrumentation is a
key tool for untangling the aerosol-cloud
puzzle. Current instrumentation is not adequate
in fulfilling its task. Source of problems
identified. New CCN instruments under
construction will.
51
ACKNOWLEDGMENTS
Funding EPA NASA ONR
People John Seinfeld, Caltech Rick Flagan,
Caltech Bill Conant, Caltech Tracey Rissman,
Caltech Graham Feingold, NOAA Bob Charlson,
University of Washington Christina Facchini,
Instituto ISAO, C.N.R. Steven Ghan, PNNL Peter
Adams, Carnegie Mellon Greg Roberts, UCSD