Simulation of Cloud Droplets in ParameterizedShallow Cumulus During RICO and ICARTT
Knut von Salzen1, Richard Leaitch2, Nicole Shantz3, Jonathan Abbatt3, Frederic Burnet4
1Canadian Centre for Climate Modelling and Analysis (CCCma), EC, Victoria, Canada2Climate Chemistry Measurements and Research, EC, Toronto, Canada3Department of Chemistry, University of Toronto, Toronto, Canada4CNRM/MGEI, Météo France, Toulouse, France
Cloud-Aerosol Feedbacks and Climate (CAFC) research network
ICARTT Experiment
Goal: Study air quality, intercontinental transport, and radiationover North America and Europe.
Location of Canadian experiment: Near Cleveland, OhioTime: 2 flights available, August 3 & 16, 2004Measurements: Canadian Convair 580, R. Leaitch et al. 1Hz Cloud & aerosol microphysics and chemistry
Modelling Approach for Shallow Cumulus- Fundamental Components
• Parameterizations for mixing of thermodynamic properties.
• Parameterizations for mixing of cloud droplets.
• Microphysical model for aerosol and droplet growth (by condensation) for cloud core.
Parameterization for Mixing of ThermodynamicProperties for Shallow Cumulus
von Salzen and McFarlane (2002)von Salzen et al. (2005)- see also talk by Francesco Isotta -
• Entraining plume model, based on continuity equations for mass, total water, energy, and momentum.
• Idealized cumulus lifecycle: Variable cloud top heights and final detrainment.
• Lateral and cloud-top mixing processes.
• Non-homogenous clouds: Statistical distributions of thermodynamic properties consistent with mixing line.
• Cloud-base closure based on simplified mixed layer TKE budget.
• Recent improvements: Mixing probability and vertical velocity.
10f
Linear mixing for total water (rt) and
moist static energy (h):
Evidence for Mixing Line from ObservationsRICO RF06 ICARTT Ft12
ICARTT Ft21
Cloud environment Cloud core
Composites of observations from different levels in the clouds.Dark colours refer to low, light colours to high levels.Crosses: dry samples; bullets: cloudy samples
Total Water Mixing Ratio Probability Distributions
ICARTT Ft12 ICARTT Ft21RICO RF06
Simulated range
Bullets: Mean
SimulatedObserved (cloud)Observed (clear-sky)
• Parameterizations for mixing of thermodynamic properties.
• Parameterizations for mixing of cloud droplets.
• Microphysical model for aerosol and droplet growth (by condensation) for cloud core.
Modelling Approach for Shallow Cumulus- Fundamental Components
Microphysical Aspects of Turbulent Mixing
fraction of environmental air
clou
d d
rople
t co
nce
ntr
ati
on
homogeneous
~ conserved thermodynamic tracer
inhomogeneous
~ liquid water
intermediate
cloudy clear
Microphysical Aspects of Turbulent Mixing
fraction of environmental air
clou
d d
rople
t volu
me
homogeneous
inhomogeneousintermediate
Mixing line Independent columns
Microphysical Aspects of Turbulent Mixing
RICO RF06 ICARTT Ft12
ICARTT Ft21
Bullets: FSSP96Open circles: FSSP124
Composites of observations fromdifferent levels in the clouds.Dark colours refer to low, light colours to high levels in clouds.
Lines refer to parameterizations.
• Parameterizations for mixing of thermodynamic properties.
• Parameterizations for mixing of cloud droplets.
• Microphysical model for aerosol and droplet growth (by condensation) for cloud core.
Modelling Approach for Shallow Cumulus- Fundamental Components
New Model for Nucleation and Growth of Dropletsfor Cloud Core
25 cm/s50 cm/s100 cm/s 200 cm/s
updraft wind speedOpen circles: New modelBullets: Detailed parcel model
• Fully prognostic numerical solution of droplet growth equation (for condensation).
• Efficient: Quasi-steady state approximation for supersaturation ► look-up tables. Few iterations for water and energy budgets.
• Multi-component aerosol size distributions based on PLA method (von Salzen, 2005).
• Vertical velocity, total water, and moist static energy from shallow cumulus scheme (cloud core conditions).
Water-soluble organics in aerosol
Water-insoluble organics in aerosol
supersaturation (%) supersaturation (%)
he
igh
t (m
)
• Parameterizations for mixing of thermodynamic properties.
• Parameterizations for mixing of cloud droplets.
• Microphysical model for aerosol and droplet growth (by condensation) for cloud core.
Modelling Approach for Shallow Cumulus- Fundamental Components
Droplet Effective Radius – Intermediate Mixing
ICARTT Ft12 ICARTT Ft21RICO RF06
Simulated range
Bullets: Mean
Simulated500 cm-3
1000 cm-3
FFSSP
adiabatic
FSSP96FSSP124
obs.
• Realistic representation of thermodynamic cloud properties for 3 flights from RICO and ICARTT.
• Relatively simple convective plume model for cloud droplets, including model for prognostic droplet growth for cloud core and new mixing-line based parameterizations for mixing processes.
• Broadening of droplet size probability distribution towards smaller sizes owing to increasing probability of diluted air away from cloud base for homogeneous and intermediate mixing.
• Free parameter in parameterization for intermediate mixing based on fitting without accounting for turbulent mixing time scales yet.
• No collision/coalescence yet.
• Future research with focus on effects on climate effects in GCM.
Conclusions