OSA1.5 | Machine Learning in Weather and Climate
Machine Learning in Weather and Climate
Conveners: Richard Müller, Bernhard Reichert, Dennis Schulze, Gert-Jan Steeneveld, Roope Tervo | Co-convener: Angela Meyer

Artificial Intelligence (AI) is revolutionizing the weather-prediction value chain and is becoming a key technology for all climate-related sciences. This session focuses on machine learning techniques and aims at bringing together research with weather and climate-related background with relevant contributions from computer sciences using these techniques.

Contributions from all kinds of machine learning studies in weather and climate are encouraged, including but not limited to:

* Global, regional and local weather prediction, including both NWP emulators and training the model directly from observations, data driven models
* ECMWF Anemoi Framework contributions, relevant Destination Earth contributions
* Postprocessing of Numerical Weather Prediction (NWP) output
* Nowcasting studies, studies using satellite data, radar data, and observational weather data
* Seasonal forecasts
* Climate-related studies, including dimensionality reduction of weather and climate data, extraction of relevant features
* Operational frameworks (MLOps), cloud ecosystems, and data flows related to AI
* AI/ML projects in the European Weather Cloud (EWC)
* Benchmark datasets and validation of the model outputs
* Quantifying the impacts of weather and climate, connecting meteorological data with non-meteorological datasets
* Human aspect -- how AI changes our work, organisations, and culture?