Title: Influences of In-cloud Scavenging and Cloud Processing on Aerosol Concentrations in ECHAM5-HAM
1Influences of In-cloud Scavenging and Cloud
Processing on Aerosol Concentrations in
ECHAM5-HAM
Betty Croft - Dalhousie University, Halifax,
Canada Ulrike Lohmann - ETH Zurich, Zurich,
Switzerland Randall Martin - Dalhousie
University, Halifax, Canada Philip Stier -
University of Oxford, Oxford, U.K. Johann
Feichter - MPI for Meteorology, Hamburg,
Germany Sabine Wurzler - LANUV, Recklinghausen,
Germany Corinna Hoose - University of Oslo, Oslo,
Norway Aaron van Donkelaar - Dalhousie
University, Halifax, Canada
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----------------------- HAMMOZ
Meeting, ETH Zurich, March 26, 2010
2Motivation Significant inter-model aerosol
profile differences
Koch et al. (2009), ACP Black carbon profiles
differ by 2 orders of magnitude among global
models.
? Do in-cloud scavenging parameterizations
contribute to these differences?
3The aerosol-cloud-precipitation interaction
puzzle
AEROSOLS
CLOUDS
PRECIPITATION
This problem involves many processes. Isolating
the effects of one on the other is difficult.
4Aerosol Scavenging Processes
Sedimentation and dry deposition
(Figure adapted from Hoose et al. (2008))
Wet scavenging accounts for 50-95 of aerosol
deposition, and strongly controls aerosol
3-dimensional distributions, which influence
climate both directly and indirectly.
5Aerosol wet scavenging processes
Aerosols ? Cloud Droplets / Ice Crystals ?
Precipitation
- Processes
- Nucleation of droplets/crystals
- Impaction with droplets/crystals
- Processes
- In-cloud (tuning parameters)
- Autoconversion
- Accretion
- Aggregation
- Below-cloud
- 1) Impaction with rain/snow
We will examine the relative contributions of
nucleation and impaction to in-cloud scavenging.
6Modeling of Aerosol In-Cloud Scavenging
- Methodologies -
- Prescribed scavenging ratios (e.g., Stier et al.
(2005)) - Diagnostic - cloud droplet and ice crystal number
concentrations are used to diagnose nucleation
scavenging size-dependent impaction scavenging
(e.g. Croft et al. (2010)) - 3) Prognostic - in-droplet and in-crystal
aerosol concentrations are prognostic species
that are passed between model time-steps (e.g.,
Hoose et al. (2008))
Using the ECHAM5-HAM GCM, we can compare the
strength/weaknesses of these 3 fundamental
approaches, and examine the sensitivity of
predicted aerosol profiles to differences in the
parameterization of in-cloud scavenging.
71) Prescribed in-cloud scavenging ratios
standard ECHAM5-HAM (nucleationimpaction)
Tgt273K 238ltTlt273K Tlt238K
NS
KS
AS
CS
KI
AI
CI
82) Diagnostic scheme Size-Dependent Nucleation
Scavenging
Assume each cloud droplet and ice crystal
scavenge 1 aerosol by nucleation, and apportion
this number between the j1-4 soluble modes,
based on the fractional contribution of each
mode to the total number of soluble aerosols
having radius gt35 nm, which are the aerosols that
participate in the Ghan et al. (1993) activation
scheme.
Find rcrit that contains Nscav,j in the
lognormal tail.
From the cumulative lognormal size-distribution,
Scavenge all mass above this radius for
nucleation scavenging. Thus, we typically
scavenge a higher fraction of the mass versus
number distribution.
9Size-Dependent Impaction Scavenging by Cloud
Droplets
Example for CDNC 40 cm-3, assuming a gamma
distribution
Prescribed coefficients of Hoose et al. (2008)
prognostic scheme are shown with red steps
Solid lines Number scavenging coefficients
Dashed lines Mass scavenging coefficients
Data sources described in Croft
et al. (2009)
10Impaction Scavenging by Column and Plate Ice
Crystals
Prescribed coefficients of Hoose et al. (2008)
(red steps)
Assume columns for Tlt238.15K
Assume plates for 238.15ltTlt273.15 K
(Data from Miller and Wang, (1991), and following
Croft et al. (2009))
113) Prognostic scheme Aerosol-cloud processing
approach (Hoose et al. (2008))
Stratiform in-droplet and in-crystal aerosol
concentrations are additional prognostic
variables.
Two new aerosol modes ? In-droplet
(CD) In-crystal (IC)
12Histograms of diagnosed vs. prescribed scavenging
ratios
Aitken mode ?
Accumulation mode ?
Coarse mode ?
Tgt273 K
238ltTlt273 K
Tlt238 K
13Uncertainty in global and annual mean mass
burdens
SO4
BC
POM
DUST
SS
14Uncertainties in Aerosol Mass Mixing Ratios
Zonal and annual mean black carbon mass is
increased by near to one order of magnitude in
regions of mixed and ice phase clouds relative to
the simulation with prescribed scavenging ratios.
15Uncertainties in Accumulation Mode Number
Assuming 100 of the in-cloud aerosol is cloud
borne reduces the accumulation mode number
burden by up to 0.7, but the diagnostic and
prognostic scheme give increases up to 2 and 5
times, respectively relative to the prescribed
fractions.
16Uncertainties for Nucleation Mode Number
Increased new particle nucleation is found for
the simulation that assumes 100 of the in-cloud
aerosol is cloud-borne.
17(nm)
Uncertainties in Aerosol Size The size of the
accumulation mode particles changes by up to 100.
18Contributions of nucleation vs. impaction to
annual and global mean stratiform in-cloud
scavenging Diag. scheme
SO4
BC
POM
Dust
SS
Number
gt90 of mass scavenging by nucleation (dust50)
gt90 of number scavenging by impaction.
19Influence of impaction on black carbon scavenged
mass
20Observed black carbon profiles from aircraft
(Koch et al. 2009)
21Observations of MBL size distributions
(Heintzenberg et al. (2000))
22Observations of AOD from MODIS MISR composite
(van Donkelaar et al., subm.)
23Observations of sulfate wet deposition (Dentener
et al. (2006))
24Observed 210Pb and 7Be concentrations and
deposition (Heikkilä et al. (2008))
25Current work Coupled Stratiform-Convective
Aerosol Processing
Stratiform Clouds
Convective Clouds
Detrainment
CD CV
Detrainment
IC CV
CDVC and ICCV will not be prognostic variables
since the convective clouds entirely evaporate or
sublimate after the above processes for each
timestep.
26Preliminary results Zonal mean process transfer
rates for the coupled stratiform-convective
aerosol cloud processing
LATITUDE
27LATITUDE
28LATITUDE
29(No Transcript)
30Aerosol Processing by Convective Clouds
CCN0.6/CN
CN Solid CCN0.6 Dotted
Evidence for dust coating by sulfate above the
boundary layer as a result of cloud processing.
Red 12 hours before convective system Blue 12
hours after convective system Figure from
Crumeyrolle et al. (2008), ACP - case study
from Niger.
31- Summary and Outlook
- Mixed /ice phase cloud scavenging was most
uncertain between the parameterizations.
Middle/upper troposphere black carbon
concentrations differed by more than 1 order of
magnitude between the scavenging schemes.
Recommend ? understanding nucleation and
impaction processes for cloud temperatures
Tlt273K. - In stratiform clouds, number scavenging is
primarily (gt90) by impaction, and largely in
mixed and ice phase clouds (gt99). Mass
scavenging is primarily (gt90) by nucleation,
except for dust (50). Recommend ?
understanding of impaction processes for cloud
temperatures lt273K, and for dust at all cloud
temperatures. - Better agreement with black carbon profiles for
diagnostic and prognostic schemes. ? ? prescribed
ratios for mixed phase clouds. - Recommend diagnostic and prognostic schemes over
the prescribed ratio scheme, which can not
represent variability of scavenging ratios. - Recommend further development of the prognostic
aerosol cloud processing approach for convective
clouds.
Thanks! Questions?
Acknowledgements