Global Simulations of BelowCloud and InCloud Aerosol Scavenging

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Global Simulations of Below-Cloud and In-Cloud
Aerosol Scavenging

• 1Betty Croft, 2Ulrike Lohmann, 1Randall Martin,
  3Johann Feichter, 4Philip Stier, 5Sabine Wurzler,
  and 2Sylvaine Ferrachat
• 1Dalhousie University, Canada, 2ETH Zurich,
  Switzerland, 3MPI
  Hamburg, Germany, 4California Tech, USA, 5LANUV,
  Germany
• CAFC Winter Meeting University of Toronto
• January 18, 2007

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Outline

• Motivation and scientific basis
• Below-cloud scavenging importance of aerosol
  size (ECHAM5-HAM GCM)
• Sensitivity study thermophoretic effects
• In-cloud scavenging collision nucleation
  scavenging
• Future work

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Below-cloud and in-cloud scavenging strongly
control global aerosol burdens and all aerosol
climate effects.
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Scavenging by collision processes
Precipitation-aerosol, and cloud particle-aerosol
collision efficiencies, and scavenging
coefficients vary considerably with aerosol size.
Grover et al. (1977) Wang et al. (1978) and
Hall (1980) and others, for rain.
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Below-cloud scavenging by rain
Present-day GCMs use mean scavenging coefficients
(solid red steps). This study selects mass (solid
lines) and number (dashed lines) below-cloud
scavenging coefficients from a look-up table
based on aerosol size and rainfall rate. Requires
model prediction of aerosol modal radius,
assuming lognormal distribution.
Solid red steps show mean rain coefficients
(Seinfeld Pandis), normalized by rainfall rate,
in units of mm-1.
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The coefficients are found assuming both a
raindrop (or cloud droplet) distribution and a
log-normal aerosol distribution
Below-cloud N(Dp) Marshall-Palmer
distribution In-cloud N(Dp) Gamma distribution
Then,
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The seven log-normal aerosol modes of the
ECHAM5-HAM GCM (Stier et al. 2005) aerosol
modal radius is predicted.
All results shown are from 1-year simulation
after 3-month spin-up using T42 resolution.
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Below-cloud scavenging Annual and global mean
mass deposition results
B) Aerosol size-dependent below-cloud scavenging
coefficients
A) Mean modal coefficients
Sulphate

• Burdens
• 0.86 Tg S
• 0.81 Tg S

Black Carbon

• Burdens
• 0.113 Tg C
• 0.109 Tg C

Below-cloud In-cloud Dry
Deposition Sedimentation
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B) Aerosol size-dependent below-cloud scavenging
coefficients
A) Mean modal coefficients
Dust

• Burdens
• 18.7 Tg
• 16.5 Tg

Sea Salt

• Burdens
• 11.6 Tg
• 11.0 Tg

Below-cloud In-cloud Dry
Deposition Sedimentation
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(No Transcript)
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Validation using NADP deposition observations
(year 2000)
A) Mean modal coefficients
B) Size-dependent below-cloud scavenging
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Thermophoretic effects
Thermophoresis evaporative cooling causes a
higher collision efficiency

Similarly, turbulence and electric charge may
increase scavenging efficiencies.
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Below-cloud scavenging with thermophoresis Annual
and global mean mass deposition results
B) Size-dependent scavenging with thermophoresis
A) Size-dependent scavenging
Sulphate

• Burdens
• 0.82 Tg S
• 0.83 Tg S

Black Carbon

• Burdens
• 0.109 Tg C
• 0.110 Tg C

Below-cloud In-cloud Dry
Deposition Sedimentation
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In-cloud scavenging - collisions
Plot is for CDNC1/cm3, multiply by CDNC to
obtain required coefficient. Solid Mass
coeffs Dashed Numb. coeffs Red steps mean
coeffs
In-cloud collision scav. f(CDNC, aerosol modal
radius, mean CD radius), assuming a Gamma
distribution. Included with look-up table
In-cloud nucleation scav. assume a critical
aerosol radius (based on supersat) and scavenge
all mass and number above that radius assuming a
log-normal aerosol distribution.
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Future work

• Size-dependent in-cloud scavenging global
  simulations
• Scavenging by snow and ice crystals
• Further validation, including aerosol vertical
  profiles and precipitation analysis
• Sensitivity studies related to turbulence
• Understanding the effects of aerosol
  hygroscopicity (chemical properties) and shape
  (physical properties) on collision-collection
  scavenging