Numerical Weather Prediction

Numerical weather prediction (NWP) aims to forecast atmospheric conditions using mathematical models and observational data. Current research emphasizes improving forecast accuracy, particularly for extreme weather events, through the development and application of advanced machine learning models, including transformers, convolutional neural networks, and graph neural networks, often integrated with or replacing aspects of traditional physics-based NWP systems. This involves exploring novel data assimilation techniques, efficient model architectures, and improved post-processing methods to enhance forecast reliability and reduce uncertainties. The advancements in NWP have significant implications for various sectors, including disaster preparedness, resource management, and energy production.