Research Projects

Thunderstorms are natural disasters that can significantly impact the economy, with approximately 2500 deaths in India annually due to lightning and thunderstorms. These storms cause damage to crops, aviation, communication, power, and socioeconomic sectors. The majority of these fatalities are people working in rural and coastal areas. Early detection of thunderstorms is challenging due to their small spatial and temporal scales and complex interactions of atmospheric motion. This study aims to identify thunderstorm occurrences and assess their prediction using thermodynamic stability indices, artificial intelligence (AI), and machine learning (ML) technologies. The primary objective is to analyze all available lightning observations at 16-km spatial and 4-minute temporal resolutions to identify thunderstorm occurrences. The second objective is to use recently available INSAT 3D and 3DR data at 10 km spatial and 30 minutes temporal resolutions to compute thermodynamic stability indices over Andhra Pradesh and Telangana regions. Regression equations will be developed to provide probabilistic predictions. The study proposes designing an early detection model based on deep learning modeling (AI & ML) strategies to detect thunderstorms at different lead times. The results will also be helpful for risk assessment of affected areas in Andhra Pradesh and Telangana regions, which would be crucial for thunderstorm-related disaster management.