(untitled) (Journal of Scientific Research, 2025)
Cloud droplet evolution is influenced by microphysical processes such as nucleation, condensation, evaporation, and coalescence, all of which impact precipitation. Models simulating droplet growth help improve rainfall predictions by providing insight into these processes. In this study, we investigate the coalescence time of droplets, using ground truth data from Disdrometer Observations with a size range of 156.5 to 2800.25 µm, applying the Python Super Droplet Model (PySDM) to simulate the evolution of droplet size over time. Focusing on the coalescence process, we analyzed the time-dependent progression of droplet formation. Our results revealed a relationship between coalescence time (CT) and drop size distribution (DSD). Larger droplets were found to coalesce rapidly upon impact, quickly reaching a precipitation-ready state, while smaller droplets experienced more frequent bouncing, requiring more time for coalescence. The mean coalescence time was estimated to be approximately 12,550 sec.