Convection Nowcasting

Convection nowcasting focuses on rapidly predicting short-term (e.g., up to 4 hours) thunderstorm development and movement, crucial for mitigating weather-related hazards. Recent research emphasizes the use of machine learning, particularly deep learning models like diffusion models and transformers, often incorporating multiple data modalities (satellite imagery, meteorological sensors) to improve forecast accuracy and efficiency. These advancements aim to enhance lead times and spatial coverage, ultimately improving disaster preparedness and renewable energy grid management by providing more accurate and timely predictions of severe weather and renewable energy generation. Optimization efforts focus on balancing computational cost with forecast accuracy, exploring techniques like adaptive data reduction and performance-based retraining to improve efficiency without sacrificing predictive power.