1. 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, MPI Hamburg, Germany, 4California Tech, USA, 5LANUV, Germany
CAFC Winter Meeting – University of Toronto
January 18, 2007

2. 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

3. Below-cloud and in-cloud scavenging strongly control global aerosol burdens and all aerosol climate effects.

4. 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.

5. 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.

6. 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,

7. The seven log-normal aerosol modes of the ECHAM5-HAM GCM (Stier et al
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.

8. 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

9. Below-cloud In-cloud Dry Deposition Sedimentation
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

11. Validation using NADP deposition observations (year 2000):
A) Mean modal coefficients
B) Size-dependent below-cloud scavenging

12. Thermophoretic effects
Thermophoresis: evaporative cooling causes a higher collision efficiency
Similarly, turbulence and electric charge may increase scavenging efficiencies.

13. 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

14. In-cloud scavenging - collisions
Plot is for CDNC=1/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.

15. 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