The RODEO project responds to the requirements of the EU Directive (2019/1024) on Open Data and the Reuse of Public-sector Information and its Implementing Regulation in order to boost the re-use and combination of open public data across the EU. The Implementing Regulation defines High Value Datasets (HVD) for six thematic categories of public data of which weather observation data, climate data, warnings, weather radar data and Numerical Weather Prediction (NWP) data are defined as meteorological High Value Datasets. These HVDs shall be shared free of charge, under the conditions of the Creative Commons BY 4.0 licence or a less restrictive open licence, and will be openly accessible via Application Programming Interfaces (APIs), machine-readable and bulk downloadable.

The three-year RODEO project is a joint effort by 11 European meteorological institutions, the European Centre for Medium-Range Weather Forecasts (ECMWF) and the network of 31 European National Meteorological and Hydrological Services, EUMETNET. The project strengthens the capacity of the European meteorological data providers by

• Developing a user interface and a data catalogue for making data discoverable;
• Developing APIs, using open licences, for accessing weather observation data, climate data, weather radar data, warnings, and AI datasets;
• Engaging with the data owners and user communities; and
• Supporting the deployment of national data portals and APIs.
• Implementing a comprehensive user engagement strategy involving
  • A Project External Advisory Board, composed of public and private sector partners
  • Frequent communications updates through several channels

The project contributes not only to the overall EU and Digital Europe Programme (DEP) objectives but also to objectives of the global meteorological community. The World Meteorological Organization (WMO) Unified Data Policy commits WMO Member Nations to supporting free and open exchange of meteorological data. The RODEO project builds upon the WMO and EUMETNET long-term plans for exchange of meteorological data under the WMO Information System 2.0 (WIS 2.0).

The project, which started on 1^st January 2023, will finish on 31^st December 2025, having delivered a one-stop-shop infrastructure linking APIs developed within the project with APIs developed by European NMHSs and a host of community components enabling users to find and retrieve the data they need that will all be free and open. As a result, this will vastly increase the amount of European-wide real-time meteorological data available for the public, business, and other governmental institutions, opening business opportunities for several sectors and application areas.

How to cite: McCairns, W.: RODEO Project – bringing meteorological data open for all users, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-706, https://doi.org/10.5194/ems2025-706, 2025.

How to cite: Kuilman, M., Bennett, V., Couglan, R., Modigliani, U., Parodi, I., Pidduck, E., Rootham, L., Gomez Segura, A., and Yang, X.: Final step of the ECMWF Open Data Programme , EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-374, https://doi.org/10.5194/ems2025-374, 2025.

The Swiss government introduced an Open Government Data (OGD) policy for all its federal offices starting on January 1^st, 2024, with a deadline for implementation at the end of 2026. For MeteoSwiss, the OGD policy took effect with the revised Ordinance for Meteorology and Climatology, entering into force on April 1^st, 2025. Building on the experience of several European countries, MeteoSwiss started the project for implementation already in 2022, before the governing law was finalized. The objective was to have API interfaces in place at the start of the revised ordinance, in order to prevent overloading of the current push delivery system for meteorological and climatological data.

The project was divided into the sub-projects ‘Legal’, ‘Data Policy’, ‘Technical Implementation, and ‘Organization and Customer Orientation’. It involved the management, customer support and data production units from the beginning in order to draw from the full know-how of the organization as well as to create awareness of the broad effects of OGD on the service. MeteoSwiss teamed up with the Federal Office of Topography swisstopo and the Swiss National Supercomputing Centre CSCS for the hosting and data distribution. Furthermore, the experience of many European met services and the work of the RODEO project were an invaluable help.

This presentation will focus on the course of action regarding the interface design for different user groups of data literacy, the layout of the documentation, the strategy for sequencing the implementation steps as well as the design of the support organization. It will present the lessons learned during the project and the first months of operation, and the challenges of setting up a mixed infrastructure including a public cloud, having only vague assumptions of usage and a limited budget at hand. Finally, it will highlight the benefits of cooperating with partners and the community to design and speed up the introduction of open data.

How to cite: Lukasczyk, C., Amsler, A., Fuhrer, O., and Biegger, S.: The Introduction of Open Data at MeteoSwiss: Development, Set up, and Lessons Learned, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-620, https://doi.org/10.5194/ems2025-620, 2025.

The "Artificial Intelligence and Machine Learning for Weather, Climate, and Environmental Applications" (E-AI) Optional Programme

The E-AI is a strategic initiative adopted by the EUMETNET General Assembly and is set to run for a period of five years. It aims to strengthen collaboration among European National Meteorological and Hydrological Services (NMHSs) and external partners, with a specific focus on AI and ML in weather, climate, and environmental domains. A key objective is to disseminate the advancements achieved under the E-AI programme through widely accepted permissive open-source licenses, fostering a culture of openness and collaboration. The Deutsche Wetterdienst (DWD) has been designated as the Coordinating Member of E-AI, responsible for overseeing the programme's progress and ensuring alignment with its foundational goals. E-AI is structured around several working groups, covering topics such as data curation, large language models, nowcasting, local area modelling, ethics, regional downscaling, and more.

The work began in late 2024, with an initial focus on producing a gap analysis of available and missing data for AI/ML applications relevant to E-AI. This analysis compiles AI/ML use case descriptions, including information on data used and missing, data preparation processes, and shortcomings in available data (such as insufficient quality, resolution, irregular time steps, etc.), as well as challenges encountered during development. Following this, the use cases will be mapped to available data sources and tools to derive a comprehensive gap analysis of the current ecosystem deficiencies. The goal is to complete the first iteration of this analysis by the end of 2025.

In addition to the gap analysis, the Data Curation Working Group is also exploring best practices for using Zarr in AI/ML applications. The group is collecting experiences to develop a "Zarr Best Practices" document, which may eventually evolve into a Zarr profile tailored for E-AI applications, aligned with broader standardization efforts such as GeoZarr [1].

Future plans include the development of a catalogue and mechanisms for data exchange within the E-AI framework, as well as the collection of examples and tutorials related to data preparation and pipelines. While the focus is strongly on E-AI applications, the work is conducted publicly via the https://github.com/eumetnet-e-ai/wg1_data_curation.

[1] https://github.com/zarr-developers/geozarr-spec

How to cite: Tervo, R., Valmassoi, A., Siemen, S., and Jacob, M.: EUMETNET E-AI Data Curation working group activities, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-183, https://doi.org/10.5194/ems2025-183, 2025.

How to cite: Visa, M. and Rauhala, M.: Current technology developments at Finnish Meteorological Institute , EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-474, https://doi.org/10.5194/ems2025-474, 2025.

Monitorization of climate change is of utmost importance, especially as some trends observed are not fully (or at all) captured by climate projections. In order to do this, the State of the Climate reports are a great resource. However, most of the reports published do not fully follow FAIR principles, and  are focused on large areas (countries or whole continents). To improve this situation, the Regional State of the Climate (RSOTC) project is implementing a web-based dashboard providing near-real-time climate data (time series, maps and diagrams) for the Nomenclature of territorial units for statistics (NUTS) European regions. This dashboard shows the evolution of climate indicators as those used in the State of the climate reports, aggregated over these smaller socio-political regions, enabling in this way a policy-ready source of climate information. It allows users to visualise climate trends, such as rainfall and temperature, as they emerge from short term variability, and to easily access the underlying data, so they can compare it with the large amount of environmental and socio-economical data available for these regions. Users are also able to interact with the data to apply a toolbox for quick in-place  statistical analysis. It implements FAIR principles as a core requirement, to ensure open access, reproducibility, and transparency, including releasing the source code. The dashboard, and its underlying REST API, will be contributed to the ENVRI Catalogue of Services as a Science Demonstrator, being a complementary service similar to the ENVRI Dashboard for the State of the Environment. Finally integration with the European Open Science Cloud (EOSC) is also planned. This project is funded by the 1st OSCARS project open call (EU’s HorizonEurope programme, grant agreement No. 101129751).

How to cite: Pérez, A., Garcia-Diez, M., and San Martin, D.: RSOTC - The Regional State of the Climate dashboard, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-632, https://doi.org/10.5194/ems2025-632, 2025.

Air pollution poses a substantial threat to public health, thus lawmakers, regulators, authorities and planners take measures to improve or at least maintain air quality. Atmospheric dispersion modelling represents a vital component of these measures. In Germany, the model AUSTAL serves as the reference implementation of such a model and is freely provided by Umweltbundesamt (UBA) under an open source licence. However, beyond the pure model, AUSTAL lacks tools for pre-processing, post-processing, and visualisation, in contrast to several other modelling systems provided by public authorities. The absence of free tools and the prohibitive high costs for most necessary input data have historically restricted its application.

Recent advances in the transformation of geoscientific information into open data have contributed to the reduction of these barriers. Specifically, substantial weather and national terrain datasets have become freely available. Nevertheless, in the absence of appropriate processing tools for the AUSTAL model, these data are still not usable.

For this purpose, AustalTools has been developed as a software solution with the aim of improving the usability and accessibility of the AUSTAL model. AustalTools has been implemented in Python with as few as possible dependencies for cross-platform compatibility. AustalTools facilitates the acquisition of weather and terrain input data by integrating sources such as the German Weather Service (DWD) and the Copernicus Climate Change Service (C3S), Copernicus Data Space, the US National Aeronautics and Space Administration (NASA) and the sixteen German state surveying offices.

AustalTools not only expedites data handling, but also supports the creation of time-dependent emission scenarios through simple weekly patterns or a versatile mini-language. It assists users in preparing AUSTAL configurations, including determining substitute anemometer positions (EAP) as defined by VDI 3783(16) and facilitating the import of building data from Geographic Information Systems (GIS). To assist with meeting quality assurance guidelines and checking output quality, AustalTools includes several simple plotting tools to visualise terrain steepness, concentration fields, wind fields and windroses.

The implementation of a variety of preprocessing schemes has the potential to offer supplementary insight into the methods themselves and their consequences for modelling results. Nevertheless, even the software's inherent functionality, which encompasses data acquisition, pre- and post-processing for AUSTAL, can be regarded as an advancement since it democratises access to professional-grade dispersion modelling, in particular for academic and amateur researchers and educators.

How to cite: Drüe, C.: AustalTools: Enhancing Accessibility and Functionality of the AUSTAL Dispersion Model, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-301, https://doi.org/10.5194/ems2025-301, 2025.