Predicting Extreme Weather in the Central Himalayas Using Artificial Intelligence and Aerosol Dynamics
This research aims to evaluate the Central Himalayan aerosol properties and negative impacts on extreme meteorological conditions, like cloudburst and flash floods. In using secondary data, the study analyses the application of machine learning models such as Random Forest, XGBoost and LSTM in findings and forecasting the likelihood of extreme weather by the use of aerosol and meteorological factors. An early warning system, which is vital for disaster preparedness and environmental policy, can be developed using an AI-based predictive model. The results point to the importance of aerosols in weather and reveal the effectiveness of employing AI techniques for better decision-making and climate adaptation. The study describes how AI can be incorporated into conventional meteorological initiatives and offers policy advocacy and capacity-strengthening strategies for meteorological departments in the Central Himalayan region.