Foundation Models for Planetary-Scale Forecasting

Explore how foundation models can revolutionize planetary-scale forecasting in this conference talk by Aditya Grover from the International Centre for Theoretical Sciences. Discover the application of large-scale machine learning models to Earth system modeling and weather prediction, examining how these advanced AI approaches can address the computational challenges and accuracy limitations of traditional physics-based Earth System Models. Learn about the integration of foundation models with climate science, their potential for improving parameterizations of localized processes, and their role in developing efficient surrogate models for complex Earth system simulations. Understand how transformer-based architectures and other deep learning paradigms are being adapted for atmospheric and climate modeling, and examine the implications for operational weather forecasting and long-term climate projections. Gain insights into the intersection of artificial intelligence and Earth sciences, focusing on how foundation models can enhance our understanding of planetary-scale processes and improve forecasting capabilities across multiple temporal and spatial scales.