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

The effect of aerosols on clouds remains one of the largest sources of uncertainty in climate studies and many of the complex aerosol-cloud interactions are associated with cloud microphysical processes. To enable greater confidence in climate projections one of the processes that requires a quantitative analysis is the second indirect aerosol effect, which is the effect from enhanced aerosol concentrations in clouds suppressing drizzle and prolonging cloud lifetimes. To be able to quantify this effect with any real certainty, the cloud microphysical processes must be accurately represented in global climate models, in particular the autoconversion process, which describes the collision and coalescence of small cloud droplets to form larger raindrops. Studies have demonstrated how changing autoconversion schemes in models can decrease the globally averaged second indirect aerosol effect by 60%, highlighting the need for increased understanding and a more accurate parameterisation of autoconversion. Recently a double moment warm rain parameterisation has been developed that includes the effects of turbulence (Franklin 2008, JAS). This parameterisation has been implemented in a large-eddy model to investigate the impact of turbulence effects on shallow cloud microstructure and morphology. Understanding cloud microphysics in shallow clouds is important for quantifying the aerosol effect on climate because the albedo effect of low clouds is greater than their greenhouse effect, which could reduce global temperatures with increased aerosol loading.

Large-eddy simulations of shallow cumulus convection and stratocumulus show that different precipitation-dynamical feedbacks occur in these regimes when the effect of turbulence is included in cloud droplet collisions through the processes of autoconversion, accretion and self-collection. Turbulence has a greater effect on the simulated precipitation rates in the shallow convection case, where the higher turbulent kinetic energy dissipation rates produce a more rapid conversion of cloud water to rain water. The much weaker dissipation rates in the stratocumulus case, however, also show a marked change in the simulated precipitation when the effects of turbulence on microphysical processes are included in the model. Both cases produce greater evaporation rates of rain water, which cause a change in the thermodynamics of the subcloud layer and increase the horizontal variability and turbulent kinetic energy in this region. In both cases the lower and more variable cloud fractions associated with the turbulence simulations suggests that the evaporation of the enhanced precipitation plays an important role in reorganising the circulations. In the stratocumulus case the enhanced evaporation leads to stronger circulations, greater variability and turbulent kinetic energy throughout the boundary layer. Hence for this case, the turbulence effects on cloud microphysical processes has a positive feedback on the generation of precipitation. The opposite is true for the shallow convection case. While the subcloud layer of the shallow convection simulation features enhanced turbulent kinetic energy in the turbulent case, within the cloud layer the increased rain water produces a net latent heating that reduces the entrainment and subsequently the buoyancy production of turbulent kinetic energy. This results in a reduction of turbulent kinetic energy throughout the cloud layer, particularly in the upper levels where the enhancement of rain water production by turbulence effects predominately takes place. Sensitivity tests show that by including the turbulence effects on the cloud microphysical processes overcomes the need to artificially reduce aerosol loading to obtain realistic precipitation rates.

Sensitivity studies for the stratocumulus case where the cloud droplet number concentration is varied show agreement with the conceptual model that greater aerosol loading, as manifested in greater cloud droplet number concentrations, suppresses precipitation formation and leads to larger cloud fractions. Other studies have shown that increased precipitation in stratocumulus clouds can lead to a reduction of liquid water path and cloud fraction. While the same result was found in this study for the cloud fraction, the liquid water paths for both the non-turbulent and turbulent simulations do not show a montonic decrease in liquid water path as cloud droplet number is decreased and therefore, precipitation is increased. The inclusion of turbulence effects on the cloud microphysical processes reduces the cloud fraction but increases the liquid water path in the drizzling stratocumulus clouds considered in this case study. This means that previous studies of aerosol effects on clouds and precipitation that have not considered these turbulence effects may have overestimated the cloud fractions and underestimated the liquid water paths and precipitation rates.