The Prithvi WxC Foundation Model for Weather and Climate

Explore the Prithvi WxC Foundation Model, a cutting-edge machine learning approach for weather and climate applications, in this 45-minute conference talk by Manikandan Padmanabhan. Discover how this foundation model leverages advanced AI techniques to address challenges in weather forecasting and climate modeling, representing a significant advancement in the intersection of artificial intelligence and Earth system sciences. Learn about the model's architecture, training methodologies, and practical applications in meteorological and climatological contexts. Understand how foundation models are transforming traditional approaches to weather prediction and climate analysis by providing more efficient and accurate computational frameworks. Gain insights into the technical innovations that enable the Prithvi WxC model to process complex atmospheric data and generate reliable forecasts. Examine the potential impact of this technology on operational weather services and climate research, including its role in improving parameterizations and reducing computational costs compared to traditional physics-based models. This presentation is part of the Advanced Machine Learning for Earth System Modeling program at the International Centre for Theoretical Sciences, which focuses on exploring how machine learning can enhance Earth System Models and make them more accurate and efficient.