This research investigates tropical atmospheric waves that influence rainfall, storms, and seasonal weather patterns. Using satellite observations and machine learning, the study shows that wave propagation depends on geographic location, upper-level winds, and topography. The findings can improve weather forecasting models and help communities better prepare for extreme rainfall events.

This research improves weather and climate forecasting by studying how dry air mixes into thunderstorm clouds, a process called entrainment. Using satellite observations, radar data, and interpretable machine learning, the work refines outdated cloud physics models, helping scientists better predict severe weather, hurricanes, and long-term climate behavior.