Explainable AI for Climate Science - Opening the Black Box to Reveal Planet Earth

Join a comprehensive webinar presentation where Elizabeth A. Barnes from Colorado State University explores the intersection of Artificial Intelligence and Climate Science. Learn how explainable AI techniques can revolutionize climate data analysis by sifting through complex information to identify meaningful patterns in Earth's chaotic climate system. Discover the applications of machine learning in various climate-related challenges, from predicting rainfall and hurricane trajectories to understanding Arctic ice melt patterns and human impacts on the planet's surface. Gain insights into how XAI empowers scientists to not only make predictions but also understand the underlying reasons behind climate phenomena, combining the analytical power of machine learning with scientific inquiry. Part of the SIAM MPE Community Meetings series organized by the SIAM Activity Group on Mathematics of Planet Earth, this presentation bridges the gap between advanced computational methods and practical climate science applications.