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.
Six modules giving ML applications in observations, forecasting, data assimilation, post-processing, ocean and more.
How to access, read and use Greenhouse Gas atmospheric carbon dioxide and methane data: temporal and spatial variation
Spatial and temporal ozone distribution of the total ozone columns. Retrieval of the data and analysis.
