The AI Revolution in Climate Modeling

Explore a comprehensive webinar presentation from the SIAM Activity Group on Mathematics of Planet Earth where University of Chicago's Pedram Hassanzadeh delves into the transformative impact of artificial intelligence on weather and climate modeling. Learn about the implementation of deep neural networks in enhancing weather forecasting accuracy and climate change predictions, examining both achievements and limitations in current approaches. Discover how data-driven models and hybrid weather-climate methodologies are revolutionizing atmospheric science, while understanding the challenges in interpreting AI learning processes and predicting extreme weather events. Gain insights into innovative solutions, including applications of Fourier analysis and rare-event sampling techniques, that are advancing the integration of AI in climate science and improving our ability to forecast atmospheric phenomena.