Coursera Flash Sale
40% Off Coursera Plus for 3 Months!
Grab it
Explore the fundamentals of Earth System and Ocean Modeling in this 59-minute lecture delivered by Gokhan Danabasoglu as part of the Advanced Machine Learning for Earth System Modeling program at the International Centre for Theoretical Sciences. Delve into the complexities of Earth System Models (ESMs) and their crucial role in understanding Earth's future climate scenarios under various anthropogenic emissions and socio-economic policies. Learn how these sophisticated models simulate global-scale climate, hydrology, ecology, biogeochemistry, and human activities while examining their applications to local and regional dynamics. Understand the physics-based differential equations that govern these models and discover the computational challenges and parameterization limitations that affect simulation accuracy, particularly for localized processes. Examine how Machine Learning approaches, including Physics-Inspired Neural Networks (PINN) and Generative Modeling, are being integrated to develop low-cost surrogate models and improve parameterization accuracy. Gain insights into the carbon cycle simulation capabilities of ESMs and their vital role in modeling environmental conditions that influence climate-ecosystem variability and change. This lecture forms part of a comprehensive workshop exploring the intersection of advanced AI techniques and Earth system modeling, designed for early career researchers, PhD students, and industry professionals working in Earth Sciences or Machine Learning.
