Turbulent effects on droplet coalescence: a crucial factor for observed rain development

 

Submitter

Morrison, Hugh Clifton — University Corporation for Atmospheric Research

Area of research

Cloud Processes

Journal Reference

Chandrakar K, H Morrison, W Grabowski, and R Lawson. 2024. "Are turbulence effects on droplet collision–coalescence a key to understanding observed rain formation in clouds?" Proceedings of the National Academy of Sciences, 121(27), e2319664121, 10.1073/pnas.2319664121.

Science

As a critical factor governing the life cycle and radiative forcing of clouds, rain formation is a key element of weather and climate. Cloud microphysics–turbulence interactions occur across a wide range of scales and are challenging to represent in atmospheric models with limited resolution. The goal of this study is to understand the role of turbulence on rain formation through its influence on drop collision coalescence in cumulus clouds.

Impact

NASA’s Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) observations combined with theoretical analysis and large-eddy simulations (LES) using a state-of-the-art Lagrangian particle-based microphysics scheme helped elucidate the problem of the “rain formation bottleneck.” Turbulent effects on drop coalescence were found to be critical for droplet size distribution evolution and rain initiation in cumulus congestus clouds, particularly because of the strong impact at lower cloud levels.

Summary

The flow in most clouds is turbulent, and the effects of cloud–turbulence interactions are challenging to represent in atmospheric models. It has been hypothesized that impacts of turbulence on drop coalescence strongly influence rain formation. Observations of drop size distributions in cumulus congestus clouds from CAMP2Ex, LES with the Lagrangian “superdroplet method”, and a theoretical scaling analysis are combined to provide substantial evidence of the critical impacts of turbulence on rain initiation and growth. Turbulent coalescence considerably enhances rain initiation and must be included in the model to accurately simulate the tail of drop size distributions, especially near cloud base. Large aerosols serving as “giant” cloud condensation nuclei (“giant CCN”) have little impact on rain formation in cumulus clouds when turbulence effects are considered.