Simulation of Below-cloud and In-cloud Aerosol Scavenging in

ECHAM5-HAM

Betty Croft, Ulrike Lohmann, Philip Stier, Sabine Wurzler, Sylvaine Ferrachat, Hans Feichter, Randall Martin,

and Ulla Heikkilä

ETH Group Retreat Presentation

Einsiedeln, Switzerland

February 6, 2008

Motivation :Below-cloud scavenging should depend on aerosol size and precipitation rates, as opposed to fixed scavenging ratios for each aerosol mode.

In-cloud scavenging should be linked to the cloud microphysicsand depend on cloud droplet (or ice crystal) number concentrations,cloud droplet size and aerosol size, as opposed to fixed scavengingratios for each aerosol mode.

Project Goals:1) Size-dependent below-cloud scavenging2) Microphysically-dependent in-cloud scavenging

In-cloud scavenging processes

(aerosol droplets or crystals)

1) Nucleation

2) Impaction

Below-cloud scavenging processes (precipitation-aerosol collisions)

1) Inertial impaction and interception

2) Brownian motion

3) Thermophoresis and diffusionphoresis

4) Turbulence

5) Electrostatic attraction

Wet scavenging of aerosols:

ECHAM5-HAM has 7 lognormal aerosol modes and includes black carbon, particulate organic matter, sulfate, sea salt and dust.

All results shown are from 5-year simulations after 3-month spin-up.

Below-cloud scavenging coefficients for rain:Present-day GCMs use typically 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.

Below-cloud: N(Dp) = Marshall-Palmer distribution

In-cloud: N(Dp)= Gamma distribution

Then,

The scavenging coefficients are found assuming both a raindrop (or cloud droplet) distribution and a log-normal aerosol distribution

Below-cloud scavenging coefficients for snow (Slinn, 1984) : (normalized by precipitation rate)

Previously, ECHAM5-HAM used 5x10-3 mm-1 for all aerosol sizes (dashed line).

Global and annual mean deposition budgets (black carbon):Below-cloud scavenging (BCS) is increased with the new parameterization.

Simulated Geographic distribution of wet deposition (SO4):

Changes in the annual mean wet deposition near source regions can be above 10% as compared to the simulation with mean coefficients. Scavenging is increased for rain rates near 1mm/hr and higher, but decreased for rain rates below 1mm/hr . All scavenging by snow is increased.

Validation with MODIS-MISR: (global zonal mean optical depth comparison)

Compare the control simulation (MEANC) and revised below cloud scavenging (ASDS-RS) with solid red (observations from MODIS-MISR).

Validation with NADP data: (observed sulfate wet deposition from US)

Sea salt deposition has improved correlation coefficients and slope-offset parameters in simulation ASDS-RS as opposed to the MEANC simulations. Sulfate deposition is more within factor of 2.

Part II - In-cloud scavenging:

1) Impaction scavenging (aerosol-cloud droplet collisions)

Project goal: Introduce aerosol size dependent in-cloud impaction scavenging.

Look-up table is a function of mean cloud droplet size, aerosol size and CDNC.

Mass (dashed) and number (solid) coefficients

In-cloud scavenging:

2) Nucleation scavenging parameterization:

Standard ECHAM5-HAM uses fixed in-cloud stratiform scavenging ratios for each of the 7 modes. These are 0.1, 0.25, 0.85, 0.99 for the NS, KS, AS, and CS modes, respectively.

Revised scavenging parameterization is consistent with the Lin and Leaitch cloud droplet activation scheme.

Assume CDNC = total number of aerosols to be scavenged .

Scavenging ratio for ith mode is,

Where Na is the sum over all soluble modes of the number of aerosols > 35nm, and xfracni is the fraction of aerosol number >35 nm in the ith mode.

We use the cumulative lognormal function to find a critical radius where Ci is the number in the lognormal tail if r > rcrit. Scavenge all aerosol mass above rcrit.

For mixed clouds, same approach but CDNC+ICNC = total number of aerosols scavenged.

Ice clouds, do not use same activation, so assumeICNC = total number scavenged and scavenge from largest to smallest mode progressively and find rcrit for the partially scavenged mode.

Alternatively, Tost et al., 2006 gave the scavenging ratio as a function of aerosol radius. We also tested this parameterization.

Predicted scavenging ratios: (normalized frequency of occurrence)

Warm stratiform clouds Warm convective clouds

Generally, unity for AS and CS modes and greatest variability in KS mode, zero for NS mode.

Greater variability in predicted convective cloud scavenging ratios.

Example: Dust deposition budgets -Higher stratiform in-cloud scavenging and lower convective in-cloud scavenging,comparing IC-ALL with CTL.

Validation: (global SO4 wet deposition – Dentener et al, 2006)

Correlation coefficients are improved by revisions to in-cloud scavenging.

Summary and future work:

1) Aerosol size-dependent below-cloud scavenging was introduced to ECHAM5-HAM and is a more physical representation of below-cloud scavenging2) Microphysically dependent in-cloud scavenging was implemented in all stratiform, and warm convective clouds and results are comparable with simulations using fixed coefficients and the method of Tost et al. (2005). This approach is desirable since the scavenging physics are now more consistent with the cloud parameterizations.3) Convective ice cloud scavenging will be implemented.4) The sensitivity of the below-cloud scavenging to the assumptions about the raindrop distribution will be investigated.5) Global validation of vertical profiles of extinction will be conducted with CALIPSO data to better examine influence of the scavenging parameterizations on the vertical aerosol profiles.

Simulations:

MEANC – uses the existing mean below-cloud scavenging coefficients

ASDS-RS – revised below-cloud scavenging by both rain and snow (aerosol size dependent scavenging).

ASDS-R – revisions only for rain

ASDS-RS-PF – as ASDS-RS but uses the old precipitation fraction parameterization labelled as method 1 in the subsequent slides.

ASDS-RT – as ASDS-R but add the thermophoretic effects – so that scavenging also depends on the below-cloud relative humidity

IC-ALL – revised in-cloud impaction and nucleation scavenging

IC-WARM – revised in-cloud scavenging only in warm clouds

IC-WARM-T – applies the parameterization of Tost et al (2006) for warm clouds

IC-STRAT – revised in-cloud scavenging only for stratiform clouds

Collection efficiency for snow (Slinn 1984):

where,

Scavenging coefficient, normalized by precipitation rate is,

Parameters are varied for different types of snow (powder, rimed and dendrites).

Precipitation fraction parameterization:

Methods for finding the fraction of grid box that is raining (PF), using cloud fraction (CF) – all simulations use method 2 except ASDS-RS-PF:

Method 1 (Stratiform):

Method 2 (Stratiform):

If

then

else Weighting similar to method 1 only if CF(k) > PF (k-1).

Where CF(k) follows Tompkins, 2001

Sensitivity to precipitation fraction parameterization:

Method 1 (Convective):

Based on updraft mass flux and velocity.

Method 2 (Convective):

Kiehl et al. 1996; Xu and Krueger (1991)

PF (k) is limited to be within the range of 0.05 to 0.8