This research examines how atmospheric aerosols influence cloud formation and rainfall, particularly under turbulent conditions. Using a laboratory cloud chamber and computer modeling, the study investigates how particle size and concentration affect droplet growth. The findings aim to improve climate models and weather forecasting in both polluted and clean environments.

This research quantifies the uncertainty in chaotic systems, showing why long-term predictions — from planetary motion to weather patterns — become unreliable. By developing mathematical models that capture chaotic behaviour, the work supports applications in traffic flow, wireless communication, climate forecasting, and disease spread, revealing why some systems are inherently more predictable than others.