Atmospheric Dynamic

Atmospheric dynamics research focuses on understanding and predicting atmospheric behavior, primarily through numerical weather prediction (NWP) and increasingly, data-driven machine learning (ML) approaches. Current research emphasizes developing efficient and accurate ML models, such as transformers, convolutional neural networks, and Fourier neural operators, to improve forecast accuracy, particularly for long-range predictions and high-resolution details, while addressing challenges like error accumulation and model interpretability. These advancements have significant implications for various sectors, including renewable energy, aviation, and disaster preparedness, by providing more accurate and timely weather forecasts.