About the Project

Weather Generator is a pan-European initiative that fuses state-of-the-art machine-learning architectures with high-performance computing to build an open, kilometer-scale foundation model of the coupled Earth system.

The main idea behind the WeatherGenerator is the use streams of various different data products – from observations via reanalysis data to model output – and the use of masked token learning in a self-supervised training approach to learn how to translate between the different data streams.

Once this is done, a timestepping scheme in latent space is established to allow for the progression of the model state in time to perform forecasts of the physical fields.

Users can than bring their own data to the tool and provide the WeatherGenerator with whatever data they have available to generate meaningful outputs for their application.

Work Structure

The overall project is organised in four Themes. The first Theme puts the datasets that are needed together and makes them useable for machine learning in an efficient and scalable manner. The second theme is building the core WeatherGenerator model. The third Theme is working on twenty-two applications that are developed by the project partners. The fourth Theme coordinates the project, organises hackathons and dissemination workshops, and provides services to externals to get started using the WeatherGenerator for their application.
Explore Themes

Hackathons

The WeatherGenerator project is bringing together core and application developers, and external innovators through a series of internal and external hackathons. These collaborative coding events focus on embedding the WeatherGenerator into applications, testing data APIs, sharing development experiences, and enabling external users to integrate the system with their own weather-related projects.

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    Our partners

    A Europe-wide alliance of weather agencies, HPC centres, universities and industry pioneers driving an open next-generation climate model.

    About
    Météo-France, based in Toulouse, is the French National Weather Service, providing weather forecasts, alerts, and guidance while advancing research on weather and climate through its CNRM joint research unit.
    Role in WeatherGenerator
    • Applying the WeatherGenerator model to produce high-accuracy predictions for Western Europe
    • Contributing to the development of next-generation, AI-driven forecasting models
    • Integrating research into operational weather prediction for extreme events and public services
    • Collaborating with top-level partners to advance data-driven weather forecasting

    MPI for Biogeochemistry

    Max Planck Institute for Biogeochemistry

    Germany
    About
    The Max Planck Institute for Biogeochemistry in Jena, Germany, is a leading research institute studying Earth system and biogeochemical processes using advanced measurements and modeling.
    Role in WeatherGenerator
    • Building a foundation model of land ecosystems
    • Integrating measurements from experiments, in-situ stations, and Earth observations
    • Applying advanced modeling, including machine learning, to understand ecosystem-climate interactions
    • Supporting early warning systems for extreme climate events like droughts and heatwaves

    LT

    Latest Thinking

    Germany
    About
    Latest Thinking is a science communication company that helps institutions and funded projects make research accessible and engaging. They provide tailored communication strategies and produce high-quality content across multiple formats - including videos, animations, infographics, podcasts, reports, and interactive media - bridging the gap between science and society.
    Role in WeatherGenerator
    • Developing the project’s visual identity, including logo, color scheme, and website
    • Producing video content such as project intros, work package leader statements, science explainers, and researcher spotlights
    • Managing ongoing website updates and enhancements
    • Supporting communication, planning, coordination, reporting, and social media management

    FSJ

    Forschungszentrum Jülich

    Germany
    About
    Forschungszentrum Jülich is a leading German research center leveraging high-performance computing to tackle global scientific challenges.
    Role in WeatherGenerator
    • Developing the core models of WeatherGenerator through the ESDE group
    • Designing training protocols and maintaining the software framework
    • Optimizing computations for high-performance supercomputers
    • Fine-tuning models to handle diverse and complex datasets

    CMCC

    Centro Euro-Mediterrane sui Cambiamenti Climatici

    Italy
    About
    The CMCC Foundation (Euro-Mediterranean Center on Climate Change) is an international, independent, multidisciplinary research center that includes climate modelling and the interaction between climate change and society.
    Role in WeatherGenerator
    • Contributing to WeatherGenerator model architecture and development of applications for extreme events and sea-ice prediction
    • Improving Arctic sea ice predictions by correcting systematic errors using data assimilation
    • Providing cutting-edge machine learning solutions for model development
    • Leveraging high-performance computing to enhance WeatherGenerator models
    • Supporting the creation of a world-leading generative foundation model for the Earth system
    About
    The Netherlands eScience Center, based in Amsterdam, is the Dutch national center of expertise in research software, supporting academic research through innovative and sustainable software development.
    Role in WeatherGenerator
    • Connecting WeatherGenerator to the broader European geoscientific community
    • Embedding WeatherGenerator into existing scientific and operational workflows
    • Extending and improving data-driven solutions using the WeatherGenerator atmospheric foundation model

    KNMI

    The Royal Netherlands Meteorological Institute

    Netherlands
    About
    The Royal Netherlands Meteorological Institute (KNMI) in De Bilt provides research, forecasts, and warnings in meteorology, climate, and seismology to ensure a safe and livable Netherlands.
    Role in WeatherGenerator
    • Contributing to the development of the WeatherGenerator
    • Developing tail networks for improved forecasting
    • Enhancing high-resolution probabilistic extreme weather forecasts
    • Improving probabilistic sub-seasonal to seasonal forecasts

    Startkraft

    Norway
    About
    Statkraft is Europe’s largest producer of renewable energy, specializing in the development, operation, and ownership of hydropower, wind, solar, gas, and biomass assets, while also supplying district heating and trading energy across more than 20 countries.
    Role in WeatherGenerator
    • Applying and validating WeatherGenerator results in real-world operations
    • Using weather forecasts for multi-year price forecasting, intraday production planning, and trading
    • Leveraging large models and reference data to integrate WeatherGenerator outputs
    • Supporting the project with practical energy sector applications

    MetNor

    Norwegian Meteorological Institute

    Norway
    About
    MetNor is Norway’s national meteorological service, providing weather information to support public safety, economic activity, and environmental protection, with offices in Oslo, Bergen, and Tromsø.
    Role in WeatherGenerator
    • Leading Theme 3 on applications
    • Developing two applications (AP7 and AP11) for the project
    • Integrating research advances into operational weather products
    • Enhancing public weather forecasts, including for the Yr app with over 14 million users
    • Collaborating with partners to share expertise and develop innovative applications

    KAJO

    Slovakia
    About
    KAJO is a Slovak-based consultancy that develops AI- and data-driven solutions for disaster risk management, environmental monitoring, and climate resilience.
    Role in WeatherGenerator
    • Leading the global flood forecasting use case
    • Integrating AI-driven meteorological data into models for improved flood accuracy, depth estimation, and delineation
    • Combining predictive analytics with real-time satellite data
    • Feeding outputs into the GLOFAS system under Copernicus EMS for long-term adoption
    • Advancing rapid risk assessment tools to strengthen global resilience, including support for the UN’s Early Warnings for All initiative

    SMHI

    Swedish Meteorological and Hydrological Institute

    Sweden
    About
    SMHI, the Swedish Meteorological and Hydrological Institute, provides science-based weather, water, and climate forecasts while conducting research in meteorology, hydrology, oceanography, and climate, with offices in Norrköping, Gothenburg, and Uppsala.
    Role in WeatherGenerator
    • Contributing to WP5 and WP6 with expertise in nowcasting from satellite and radar data
    • Applying machine learning and generative methods for precipitation forecasting
    • Bringing experience in generative numerical weather prediction techniques
    • Exploring AI/ML applications to enhance operational decision support for society

    MeteoSwiss

    Switzerland
    About
    MeteoSwiss is Switzerland’s federal meteorology and climatology office, providing weather and climate data, forecasts, warnings, and research-driven services.
    Role in WeatherGenerator
    • Developing the core WeatherGenerator model
    • Working on two applications: high-resolution weather forecasting over the Alps and downscaling re-analysis to finer resolution
    • Generating a new km-scale dataset with the ICON model for training and improving applications
    • Integrating advanced physical modeling to enhance weather and climate predictions

    ETH Zurich

    Eidgenössische Technische Hochschule Zürich

    Switzerland
    About
    ETH Zurich is a world-leading research university in Switzerland, advancing climate science and scalable computing to tackle complex Earth system challenges.
    Role in WeatherGenerator
    • CSCS: Developing a data transfer service to efficiently move large datasets between supercomputing centers
    • SPCL: Creating compression schemes for weather and climate data
    • Supporting scalable computing solutions and high-performance data handling
    • Leveraging expertise in parallel computing, storage, and data access for the project

    Buluttan

    Turkey
    About
    Buluttan is Turkey’s first private meteorology-technology company delivering AI-powered, ultra-local weather intelligence to enhance decision-making across sectors like renewable energy, aviation, logistics, and utilities.
    Role in WeatherGenerator
    • Developing robust AI-driven weather models to support Europe’s sustainability strategies
    • Delivering reliable energy production forecasts to reduce operational costs and support renewable energy investment
    • Demonstrating the financial impact of models in renewable energy and increasing grid stability
    • Contributing to Europe’s transition to sustainable energy solutions

    Met Office

    United Kingdom
    About
    The Met Office, based in Exeter, UK, is the national meteorological service providing weather and climate services to support public safety, business, and policy decisions, with 160 years of expertise in global weather science.
    Role in WeatherGenerator
    • Evaluating WeatherGenerator outputs using scientific expertise in forecast model assessment
    • Applying eXplainable AI (XAI) to understand and build trust in model outputs
    • Contributing to data compression and dataset optimization for efficient model training
    • Enhancing the handling of very large and diverse datasets for WeatherGenerator

    ECMWF

    European Centre for Medium Range Weather Forecasting

    United Kingdom
    About
    ECMWF is an international organization providing world-leading weather forecasts and climate data, while advancing innovation in Earth system science.
    Role in WeatherGenerator
    • Coordinating the entire project across all partners
    • Exploring the potential of foundation models for weather and climate applications
    • Bringing expertise from operational forecasting and climate science
    • Leveraging resources and collaborations for maximum project impact