Learn about sources of error in NWP, how they are quantified, and how ensembles are evaluated.
Six modules introducing the main topics in machine learning in the context of weather and climate.
Five modules covering decision trees, deep learning, uncertainty and generative models, and physics-guided approaches.
Learn about the unique role of snow in forecasting, from short-range to seasonal time scales.
Learn about the ways in which forecast jumpiness can appear and how it can be mitigated.
Learn about the role of satellite observations and measurements, and how these are assimilated and monitored for NWP.
