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 Using satellite observations, radar data, and interpretable machine learning, the work refines outdated cloud physics models, helping scientists better predict severe weather, hurricanes, and long-term climate behavior.

This study explored whether satellite remote sensing can estimate black truffle mycelium biomass. Optical vegetation indices showed limited results, while Sentinel-1 radar backscatter had significant correlations, especially in spring. Findings suggest radar data capture soil moisture dynamics linked to fungal activity, offering a promising tool for sustainable truffle orchard management.