Are Turbulence Effects on Droplet Collision–Coalescence a Key to Understanding Observed Rain Formation in Clouds?
Figure 1. A combined investigation approach using field observations (CAMP2Ex), theoretical scaling analysis, and LES with superdroplet scheme.
Image by Kamal Kant Chandrakar, NSF NCAR
Figure 2. Averaged drop size distributions at different altitudes (a: near cloud base to e: near cloud top) from observations in cumulus congestus clouds during CAMP2Ex (blue) and corresponding LES outputs at time = 7,500 s using the Lagrangian microphysics scheme with gravitational drop coalescence only (red) and with turbulence effects on coalescence (black). (f) Time series of the domain integrated rain water mass from various simulations with gravitational and turbulent collision kernels and using different giant CCN concentrations.
Image by Kamal Kant Chandrakar, NSF NCAR
Rain formation is a critical factor governing the lifecycle and radiative forcing of clouds, and therefore, it is a key process in Earth system models. Cloud microphysics–turbulence interactions occur across a wide range of scales and are challenging to represent in atmospheric models with limited resolution. This study improves understanding of the role of turbulence on rain formation through its influence on drop collision coalescence in cumulus clouds, with the broader goal of improving the representation of rain formation in Earth system models.
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.
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 the 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. This study highlights the importance of including turbulent coalescence in detailed microphysical models that serve as a basis for developing bulk schemes in Earth system models.