Weather and Climate: Applications of Machine Learning and Artificial Intelligence

We demonstrate software and tools for users to progress from machine learning theory, probabilistic methods, through to construction of AI models across environmental science. We span basic AI methods through to modern generative AI methods, physics informed techniques, as well as including a vast array of concrete applications such as river discharge modelling, ocean-wave emulation, environmental monitoring, AI foreasting and more. Throughout we place emphasis on how and when these methods should be used, as well as their limitations. This allows users to develop a non-naive understanding of AI and to engage with all themes of Machine Learning Across Earth System Modeling: Subgrid-Scale Parameterizations, Emulation and Hybrid Modeling.