Charmaine Franklin 11 June 2009

The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

The Effect of Turbulence on Cloud Microstructure, Precipitation Formation and the Organisation of Stratocumulus and Shallow Cumulus Convection

Charmaine Franklin

11 June 2009

www.cawcr.gov.au

The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

Motivation

• Marine boundary layer clouds cover vast areas of the globe and their feedbacks on climate are a leading order uncertainty in GCMs

• Autoconversion of cloud droplets to rain is one key process that determines precipitation and cloud cover

• Changing autoconversion schemes in GCMs can reduce the globally averaged second indirect aerosol affect by 60%

dro

ple

t ra

diu

s

collision-coalescence

growth

condensation growth

time

• Theoretical growth times of cloud droplets are too slow to describe observed onset of precipitation

• Turbulence has long been recognised to affect autoconversion & reduces the growth time of rain drops in simple models

• What are the effects in full physics models?


Effect of turbulence on cloud droplet collisions

droplet

radius m

droplet radius m

Turbulence increases the collision rate by up to 3 times

dissipation rate of turbulent kinetic energy 100 cm2 s-3

1000 cm2 s-3 1500 cm2 s-3

500 cm2 s-3

DNS results of the turbulent collision kernel/non-turbulent collision kernel

For details see Franklin 2008 JAS


Stochastic collection equation results

gravity 1%

100 cm2 s-3 21%

500 cm2 s-3 41%

1000 cm2 s-3 52%

1500 cm2 s-3 58%

Percentage of mass contained in drop sizes > 40 m radius after 20 minutes

lwc 1 g m-3 no. conc 240 cm-3 dispersion 0.5 mean vol radius ~ 10m

gravity 100

500 1000

1500

Temporal evolution of the mass weighted mean radius

0 20 min


UCLA LES

• Developed by Bjorn Stevens• Cloud water mass is defined implicitly through l and total condensate• Cloud droplet number concentration is fixed• Cloud droplet sedimentation included• Double moment warm rain microphysics parameterisations of

Franklin (JAS 2008) implemented in the model: • one suite that considers the effects of turbulence on droplet collisions• one suite that does not include turbulence effects

non-turbulent autoconversion rate

turbulent autoconversion rate

equations for accretion and self collection as well

12410201.09.05.28.0978.1505.0tan2003|

RR

c

R

cautor NqRt

q

32.189.24102|

ccautor Nqt

q


Shallow cumulus convection – RICO case

• Domain 19.2 x 19.2 x 5 km

• Resolution 100m horizontal, 40m vertical

• Variable timestep, typically 1.6 s

• Initial & boundary conditions are from GCSS intercomparison case study

• Observed cloud droplet number 70 cm-3

• Simulation length 24 hours

• Statistics collected over last 4 hours

• Clouds have tops around 2.5 km, bases at 600 m, horizontal extent of 1-2 km

• Large cloud area with TKE dissipation rates > 100 cm2 s-3, significant areas > 1500 cm2 s-3


Shallow cumulus convection – liquid water

• Including turbulence effects on microphysical processes significantly increases rain water

• Reduced Nc gives close to turb rain amount

• Cloud fraction fairly insensitive to microphysics changes for 70 cm-3, compared to reduced Nc more rain = more cloud

• Largest liquid water increases in clouds at heights above 2500 m, mostly from rain water


• Larger rain water amounts leads to increased evaporation within cloud

• TKE in cloud reduced but enhanced in subcloud layer

• evaporation below cloud increases horizontal variability and TKE

• increased rain = net latent heating, reduced entrainment and buoyancy production of TKE

Shallow cumulus convection – TKE


• More precip in turb reduces buoyancy and entrainment within the cloud layer

• Turb case has lower variance in cloud, but updrafts stronger in upper region of cloud

• Increased precip enhances cumulus-type motions, more positively skewed vertical velocity

Shallow cumulus convection – buoyancy


Aerosol effects – shallow cumulus cloud properties at different cloud droplet concentrations

• At lowest CDNC turb case has more variability with significantly larger LWP

• Similar relationships at Nc = 70 and 100, with turb tending to have larger LWP and lower cfrac

• At Nc=200 the opposite occurs with turb having lower LWP and higher cfrac


Aerosol effects – shallow cumulus cloud properties at different cloud droplet concentrations

• As CDNC increases, LWP of turb case decreases but not so for non-turb

• For same TKE, turb produces greater LWP for all Nc values

• For a fixed LWP as CDNC increases the TKE increases

• Higher correlations for turb cases ~0.9 compared to 0.85


• Domain 6.6 x 6.6 x 2 km

• Resolution: horizontal 50 m, vertical 5 m at surface & inversion – 80 m at top

• Initial & boundary conditions are from GCSS intercomparison case study

• Observed cloud droplet number 55 cm-3

• Simulation length 6 hours

• Statistics collected over last 4 hours

• Nocturnal stratocumulus case under dry inversion with embedded pockets of heavy drizzling open cellular convection

• Small regions of dissipation rate of TKE >100 cm2 s-3 at cloud top

Stratocumulus – DYCOMS II case


Stratocumulus – DYCOMS II case

• Turbulence effects on microphysics increases the precipitation flux

• Greater amounts of rainwater increases evaporation below cloud base in turb case

• Enhanced evaporation leads to stronger circulations and greater variability & TKE

• More precipitation results in more well mixed BL in agreement with observations


Aerosol effects – stratocumulus cloud properties at different cloud droplet concentrations

• As CDNC increases, cloud fraction increases and rain water path decreases

• Agrees with conceptual model that greater aerosol loading suppresses precip formation and leads to larger cloud fractions

• Cloud bases increase with aerosol loading – effect of precip on thermodynamics of subcloud air


Conclusions

• Including effect of turbulence on droplet collision rates makes a significant change to rain water produced by the cloud and subsequently to the organisation of the cloud

• Shallow cumulus case showed that enhanced precipitation generation results in less entrainment and reduced buoyancy driven TKE in cloud but greater TKE in subcloud layer due to increased evaporation

• When turbulence effects included less of a need to reduce CDNC to obtain observed precipitation rates

• Stratocumulus case compared more favourably with observations in that turbulent enhanced precipitation amounts produced stronger circulations and TKE – positive feedback on precipitation

• Preferred location for enhanced precip efficiency may make difference• Effect of turbulence is to partly offset the aerosol indirect effects by

increasing the precipitation efficiency

Thank you

The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

Charmaine Franklin

Phone: +61 3 9239 4559Email: [email protected]: www.cawcr.gov.au

Thank youwww.cawcr.gov.au

Documents

Charmaine Franklin 11 June 2009