Cloud and Precipitation

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Incorporating aerosol-cloud interactions in GCMS
photo S.Lance
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Anthropogenic indirect forcing important and
elusive
IPCC (2001)
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Research focus understanding climate change.
Clouds play a major role in the climate system.

• Facts
• Clouds account for 50 of planetary albedo.
• Small changes in clouds yield large changes in
  global energy balance.
• 1 increase in global cloud cover can counteract
  warming from doubling atmospheric CO2
  concentrations.
• Consequence
• Understanding cloud formation is necessary for
  reliable climate change predictions.

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How do clouds form?
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
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How can humans affect clouds?

• By changing CCN cloud properties are a strong
  function of their concentration.
• This phenomenon is known as aerosol indirect
  effect.
• The aerosol indirect effect can lead to climatic
  cooling by
• Increasing cloud reflectivity (albedo)
• Increasing cloud lifetime coverage.

Higher A
l
bedo

Lower A
l
bedo





CCN
CCN
Clean Environment


Polluted Environment





(few CCN)
(more CCN)
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Indirect Effect Haywood and Boucher Revs.
Geophys. 2000
1) Increased CCN - reduces reff 2) Drizzle
suppression - increases LWC 3) Increased cloud
height 4) Increased cloud lifetime
First indirect effect
Second indirect effect
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Quantification of the Indirect Effect
Aerosol Size Distribution and Chemical Composition
Cloud Radiative Properties
Cloud Droplet Number and Size
Well Defined
This problem has historically been reduced to
finding the relationship between aerosol number
concentration and cloud droplet number
concentration. Empirical relationships are often
used.
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Aerosol-Cloud Interaction Modules

• Goal
• Couple all aerosol-cloud-radiation interactions
  within a framework of parameterizations
  appropriate for global models.
• Input variables (from GCM)
• Cloud liquid water content.
• Aerosol size distribution and chemistry.
• Wind fields.
• Static stability/turbulence.
• Output variables (to GCM)
• Droplet number, distribution characteristics
• Cloud optical properties
• Cloud coverage, subgrid statistics

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Simplest aerosol-cloud interaction module
correlations
Pro Very simple relationship to implement. Fast
computation. Con Large predictive uncertainty,
without chance of improving.
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An Outstanding Issue in Estimation of Global
Aerosol Indirect Forcing
Anderson et al. (2003, Science)
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Conventional Approach for Studying Aerosol
Indirect Effects

• IE -D ln re / D ln ta (1)
• IE -Dln re /D ln Na (2)
• Values of IE reported in the past
• AVHRR (Nakajima et al. 2001)
• IE 0.17 (Oceans)
• POLDER (Breon et al. 2002)
• IE0.085 (oceans) 0.04 (land)
• Surface Observation (Feingold et al. 2003)
• IE0.020.82

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Relationship between cloud droplet size and
aerosol extinction
Courtesy of Feingold
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Unaccounted chemical effects on droplet
activation
Slightly soluble compounds (Shulman et al.,
1996) They add solute to the drop as it grows
this facilitates their ability to
activate. Examples organics (succinic acid),
CaSO4.
Soluble gases (Kulmala et al., 1993) 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)
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Unaccounted chemical effects on droplet
activation
Surface-active soluble compounds (Facchini et
al., 1999) They decrease surface tension of
droplets this facilitates their ability to
activate. Examples organics (succinic acid,
humic substances).
Surface tension data from cloud and fog water
samples.
Pure water
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The departure from pure water values can be very
large! Surface tension change is different for
each CCN.
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Droplet concentration range at activation
Surface tension (dyne/cm)
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Charlson et al., Science, 2001
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1e-4
1e-3
1e-2
1e-1
-1
C(mol l
)
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Unaccounted chemical effects on droplet
activation
Film-forming compounds (e.g., Feingold Chuang,
2002) They can slow down droplet growth. Once
the film breaks, rapid growth is resumed
Examples hydrophobic organics. Such substances
do not necessarily alter droplet thermodynamics
they affect the kinetics of droplet growth. If
present, such substances can strongly affect
droplet number.
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Physically-based aerosol-cloud interaction modules
Uncertainties can be decreased by using first
principles. Cloud droplet balance
Activated droplets for updraft w
Probability of updraft w

• Activation is the direct aerosol-cloud
  microphysical link. Two types of information are
  necessary for its calculation
• Aerosol chemistry and size distribution (CCN)
• Representation of subgrid dynamics in
  cloud-forming regions.
• Embedding a numerical activation model is too
  slow must parameterize.

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Mechanistic parameterizations underlying ideas

• Approach
• Assume an aerosol size distribution and chemical
  composition below cloud.
• Aerosols rise into cloud.
• Expansion generates cooling and supersaturation.
• Aerosols activate into droplets.
• Köhler theory links aerosols to CCN properties.

t
Smax
S

• Major challenge
• Derive expression for the condensational growth
  of CCN include within the supersaturation
  balance for the parcel, and solve for the
  maximum.
• Solution
• Depends on the approach used in each
  parameterization.
• Uuse Population splitting (Nenes and Seinfeld,
  JGR, 2003)

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Module Evaluation

• How to evaluate?
• Process-based approach evaluate each component
  (process) of parameterizations using closure
  studies.
• Aerosol-CCN
• CCN-cloud droplet number
• Cloud droplet number precipitation
• Chemistry-CCN evolution
• Field data detailed modeling must be used for
  all of evaluations.
• Comparison with models can suggest improvements
  field data give the reality check.
• Coupling of multiple processes within simple
  modeling frameworks and Single Column Models to
  evaluate performance within GCM.
• Point of concern for field data the limited
  spatial/temporal scales covered.

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Giant CCN (GCCN) effect on cloud lifetime

• How can cloud lifetime be modified?
• Changing CCN concentration (drop size effect)
• Not the only way!

• Studies show that Low concentrations of Giant CCN
  are able to transform clouds from a
  non-precipitating state to a precipitating one.

CCN vs GCCN 109 m-3
102 m-3

• GCCN in past studies were assumed to be seasalt,
  dust or ice.
• GCCN are not composed solely of soluble salts
• Other chemical effects may modify the growth of
  GCCN
• Film Forming Compounds
• Black Carbon (Nenes et al., JGR, 2003)

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A-Train Tracks
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Persistent Elevated dust layers over Taklamakan
desert
CALIPSO, July 30, 2006
CALIPSO, Aug 6, 2006
CLOUDSAT, Aug, 2006
CALIPSO, Aug 30, 2006
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2003
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Black Carbon and Giant CCN effect on cloud
lifetime
If black carbon is included in GCCN, the heat
released can increase the droplet temperature
enough to partially evaporate the droplet. If
important, this mechanism would tend to increase
cloud extent and lifetime and cool climate
through a previously unexplored
pathway. Question What is the BC content needed
to significantly reduce GCCN size?
BC core
drop
Absence of heating
Presence of heating droplet and gas phase get
heated
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Two Types of Clouds and Two Distinct Atmospheric
Dynamics

• Processes that have no bearing on aerosol effect
• Cloud drifts in and out
• Cloud drops grow due to water convergence
• Cloud drops grow due to adiabatic cooling
• Cloud drops shrinks due to evaporation
• Aerosol effect may be isolated if
• Clouds are classified
• Growing and maturing clouds are separated
• Atmospheric circulation remains the same
• Thermodynamic condition remains the same

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DER-AOD relationship
AIE efficiency is defined as the slope of the
correlation.
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AIE efficiency determining factor
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Mexico
US
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Rainfall enhancement downstream of Huston
Shepherd et al. (2002)
Urban Heat Island Effect, orAerosol Effect,
or Both Effects
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Summary
The indirect effect of atmospheric aerosols is
one of the most elusive aspects of climate
prediction science. A variety of aerosol
activation effects need to be included (chemical
composition) in parameterizations of
aerosol-cloud interactions. There are possibly
many (counterintuitive) aerosol-cloud interaction
mechanisms yet to be discovered. New
parameterizations are being developed, and
included within a comprehensive climate model
system to address the problem Laboratory and
in-situ experiments are necessary for
constraining parameterizations. CCN
instrumentation is a key source of such
data. Current instrumentation is not adequate in
fulfilling its task. New CCN instrument promises
to fill (revolutionize?) the field.