Faster and More Efficient Weather Predictions using AI and Acceleration - Lecture 2

Explore advanced artificial intelligence techniques for accelerating weather prediction systems in this 42-minute lecture from the Advanced Machine Learning for Earth System Modeling program. Learn how AI and acceleration technologies can dramatically improve the speed and efficiency of weather forecasting models compared to traditional physics-based approaches. Discover the computational challenges facing current Earth System Models and understand how machine learning paradigms, including Physics-Inspired Neural Networks and deep learning architectures like Transformers and Graph Neural Networks, are revolutionizing meteorological predictions. Examine real-world applications of data-driven weather models such as FourCastNet, DLWP, Pangu, and GraphCast that are now being adopted by national meteorological agencies for operational forecasting. Gain insights into how these AI-powered approaches address the computational expense and parameterization inaccuracies of conventional Earth System Models while maintaining scientific rigor. Understand the broader implications of these technological advances for climate science research and practical weather forecasting applications.