Large‐eddy simulations of drizzling shallow cumuli using a turbulence‐aware autoconversion parametrization

Abstract

AbstractTurbulence in clouds enhances collision between cloud droplets, which is critical to drizzle formation in shallow cumulus clouds. In this study, we develop an autoconversion parametrization that considers the turbulence‐induced collision enhancement (TICE) obtained from a particle trajectory model. We implement the developed parametrization to a large‐eddy simulation model and simulate the Rain In Cumulus over the Ocean (RICO) case to investigate the effects of TICE on shallow cumulus clouds and their sensitivities to the cloud droplet number concentration and horizontal grid resolution. TICE significantly increases the autoconversion rate, leading to large increases in the accretion rate, rainwater path and surface rain rate. The simulations of shallow cumulus clouds are highly sensitive to the cloud droplet number concentration and horizontal grid resolution, and the inclusion of TICE overall reduces the sensitivities. For example, the large rainwater path and surface rain rate that appear when cloud droplet number concentration is relatively low are reduced by TICE, whereas the very small rainwater path and surface rain rate that appear when cloud droplet number concentration is relatively high are increased by TICE. Comparisons with two other TICE‐aware parametrizations based on direct numerical simulation results of droplet collisions in turbulence show that there are substantial differences in TICE effects for different parametrizations, which implies a large uncertainty in simulating turbulent clouds. Among the three parametrizations, the parametrization developed in this study shows intermediate TICE‐induced increases in rainwater path and surface rain rate.