Novel 3-D and AI-based weather forecast products based on open data

Recent developments in open data policies of meteorological agencies have much expanded the set of up-to-date forecast, reanalysis, and observational data that is publicly available to meteorological research and education. To make use of this open data, we have developed a set of 3-D and AI-based visualization products that extract and display meteorological information in novel ways. In this presentation, we present visualization products derived from publicly available data from operational agencies including the German Weather Service (DWD) and the European Centre for Medium-Range Weather Forecasts (ECMWF). All our visualizations are created using open-source software, mostly using the interactive 3-D visualization tool Met.3D. Met.3D has primarily been developed for rapid exploration of gridded atmospheric data by interactive means, and has recently been extended with capabilities for batch-creation of visualizations and animations. Met.3D supports a variety of visual displays from traditional 2-D maps to novel 3-D visualizations of, for example, clouds, jet streams, and weather fronts. In recent work, we also investigated explainable-AI-based feature identification algorithms to detect meteorological structures including fronts and tropical cyclones. We provide comprehensive documentation and ensure straightforward installation processes for easy adoption and use of the presented visualization products by the community, e.g., for use in weather forecasting courses at universities. In addition, we are currently developing a near-real-time website that comprehensively showcases our visualizations using current forecast and observation data. For reproducibility and further interactive visual analysis of the data, the website provides scripts and configurations that enable users to replicate the visualizations using a local Met.3D installation, thus providing additional benefit to users.