OceanUQ Summer School Lecture: ML for DA and Model Error Representation

Explore the fundamentals of machine learning in the context of data assimilation and ensemble forecasting. Learn about the two main sources of uncertainty and how they impact ensemble forecasts. Explore how machine learning can augment traditional data assimilation, and why stochastic parameterization is essential for effectively representing model uncertainty in weather simulations.