1. Global Simulations of Aerosol Impaction Scavenging with the ECHAM5-HAM GCM
Betty Croft, and Randall V. Martin – Dalhousie University, Canada
Ulrike Lohmann – ETH Zurich, Switzerland
Philip Stier – Oxford University, U.K.
Sabine Wurzler – Landesamt fur Umwelt, Natur, und Verbrauchershutz, Germany
Johann Feichter – Max Planck Institute for Meteorology, Germany
Corinna Hoose – University of Oslo, Norway
CMOS 2009 Congress Radiation, Aerosols, and Cloud Session, June 3,

2. Outline: Introduction to Aerosol Scavenging Processes
Impaction Scavenging by Rain and Snow
Impaction Scavenging by Cloud Droplets and Ice Crystals
Results of Global Simulations
Summary and Outlook

3. Aerosol Scavenging Processes:
Sedimentation and dry deposition
(Figure from Hoose et al. (2008))
Uncertainty in aerosol scavenging contributes to the uncertainties in the estimates of the direct and indirect radiative forcing of aerosols on climate.

4. Impaction Scavenging by Rain and Snow:
Stier et al. (2005) prescribed coefficients for rain of 4mm drops (red steps)
Stier et al. (2005) prescribed coefficient for snow (green)
(Figure from Croft et al. (2009))

5. Contribution of Impaction Scavenging By Rain and Snow to Global and Annual Mean Aerosol Deposition:
Size-dependent impaction
[%]
Prescribed coefficients
Sulfate BC
POM
Dust
Sea Salt
Red: Snow; Blue: Rain; Left: Prescribed coefficients; Right: Size-dependent impaction
All results are for a 1-year T42 nudged simulation with ECHAM5-HAM GCM

6. Global and Annual Mean Sea Salt and Dust Burdens:
Sea salt [mg m-2]
Change relative to prescribed coefficients [%]
Dust [mg m-2]
Change relative to prescribed coefficients [%]

7. Percent Change of Global and Annual Mean Sea Salt and Dust Mass Burdens Relative to Prescribed Coefficient Simulation:
Rain Drop spectra
Fixed 0.4 mm Drops
Fixed 4.0 mm Drops DU DU SS DU SS SS
Dust and sea salt burdens are sensitive to the impaction scavenging parameterization for rain and snow.

8. Impaction Scavenging by Cloud Droplets:
Example for CDNC 40cm-3, assuming a gamma distribution
Prescribed coefficients of Hoose et al. (2008) are shown with red steps
Number scavenging (solid lines); Mass scavenging (dashed lines) Data sources described in Croft et al. (2009)

9. Impaction Scavenging by Column and Plate Ice Crystals:
Prescribed coefficients of Hoose et al. (2008) (red steps)
Assume columns for T<238.15K
Assume plates for <T< K
(Data from Miller and Wang, (1991), and following Croft et al. (2009))

10. Mass mixing ratios:
Black carbon, particulate organic matter, and dust are sensitive to the in-cloud (IC) impaction parameterization in regions of mixed and ice clouds.

11. Percent Change in Aerosol Mass and Number Burdens Relative to A Simulation With No In-Cloud Impaction: NS SU BC
POM SS DU KS AS CS KI AI CI
[%]
The dust mass, and the number of insoluble accumulation and coarse mode aerosols are most sensitive to impaction scavenging.

12. Dust: Fractional Contribution of Stratiform Cloud Processes to the Annual and Global Mean Mass Deposition:
[%]
Warm
Mixed
Ice
Warm
Mixed
Ice
T>273K
238<T<273K
T<238K
T>273K
238<T<273K
T<238K
Nucleation
Impaction

13. Comparison with observed zonal mean aerosol optical depth:
Observations are a MODIS, MISR, AERONET composite from Kinne, (2009)
AOD is more sensitive to impaction scavenging by rain and snow, as opposed to impaction with cloud droplets and ice crystals.

14. Summary and Outlook:
Size-dependent impaction scavenging by rain and snow reduced global sea salt burdens by 15%.
The assumption of a rain drop spectra as opposed to a fixed mean raindrop size changed the global sea salt burdens by near to 10%.
Size-dependent impaction scavenging by cloud droplets and ice crystals reduced concentrations by up to 25% and 100% for carbonaceous aerosols and dust, respectively, in the regions of mixed phase and ice clouds.  prediction of climate change due to absorbing aerosols, particularly in the polar regions, requires consideration of in-cloud impaction scavenging.
Impaction scavenging in convective clouds will be investigated in future work.

15. Acknowledgments:
Thanks!
Questions?

17. Percent Change in Aerosol Mass and Number Burdens Relative to A Simulation With No In-Cloud Impaction:
Aerosol Burden Sensitivity to In-Cloud Scavenging Parameterizations
[%] SU BC
POM SS DU NS KS AS CS AI CI KI
Blue: Size-dependent impaction (diagnostic nucleation)
Red: Hoose et al. (2008) prescribed in-cloud impaction (diagnostic nucleation)
Yellow: Hoose et al. (2008) prescribed in-cloud impaction (prognostic aerosol cloud processing)