--- title: README emoji: 🌍 colorFrom: blue colorTo: indigo sdk: static pinned: false --- ![Destination Earth](./banner.jpg) ## Welcome to Destination Earth on Hugging Face! [Destination Earth (DestinE)](https://destine.ecmwf.int) is a flagship initiative of the European Commission to develop a highly accurate digital model of the Earth. It is implemented by [ECMWF](https://www.ecmwf.int), [ESA](https://www.esa.int) and [EUMETSAT](https://www.eumetsat.int). This organisation hosts the artificial intelligence (AI) and machine learning (ML) work led by ECMWF and its partners within DestinE. AI and ML play an increasingly central role in DestinE: ML-driven models and AI-based software boost the ability to quantify uncertainty in digital twin simulations and make the DestinE system more interactive, using the supercomputing infrastructure of the [EuroHPC Joint Undertaking](https://eurohpc-ju.europa.eu). This work builds on ECMWF's own ML efforts with its Member States, in particular: - [Anemoi](https://anemoi.readthedocs.io), the open-source ML framework now powering several state-of-the-art data-driven forecasting models in Europe. - The [Artificial Intelligence Forecasting System (AIFS)](https://huggingface.co/ecmwf), ECMWF's operational AI-based weather forecasting system. - [AIFL (AI for Flood Forecasting)](https://huggingface.co/ecmwf), ECMWF's global deep learning model for daily streamflow at catchment scale, including in ungauged basins. ## Objectives In Phase II of DestinE, AI activities focus on: - Developing ML-based Earth system model components, working towards a European ML-based Earth system model. - Enhancing the [Digital Twin Engine](https://destine.ecmwf.int/digital-twin-engine/) to support training and running ML models on EuroHPC systems. - Applying AI to support uncertainty quantification of digital twin simulations. - Using AI to make the system more interactive and digital twin data easier to use. ## ML Earth system components ECMWF is developing [ML-based Earth system components](https://destine.ecmwf.int/ml-earth-system-components/) that will be coupled with the AIFS to form a fully AI-driven Earth system model: | Component | Description | | --- | --- | | [Land](https://destine.ecmwf.int/news/destine-blog-towards-an-ml-based-earth-system-model-land/) | **aiLand**, a global deep learning emulator of land surface processes, trained on ECMWF's physical land model. | | [Waves](https://destine.ecmwf.int/news/destine-blog-towards-an-ml-based-earth-system-model-waves/) | An AI wave model trained on over 40 years of ECMWF physical wave model output, driven by the AIFS. | | [Hydrology](https://destine.ecmwf.int/news/destine-blog-towards-an-ml-based-earth-system-model-hydrology/) | Builds on ECMWF's [AIFL](https://huggingface.co/ecmwf) model, developed as part of ECMWF's wider ML activities. | | [Sea ice](https://destine.ecmwf.int/news/destine-blog-towards-an-ml-based-earth-system-model-sea-ice/) | Learns sea ice and surface ocean evolution from decades of reanalysis data, capturing seasonal cycles and ice-edge behaviour. | | [Ocean](https://destine.ecmwf.int/news/destine-blog-towards-an-ml-based-earth-system-model-oceans/) | Models the full-depth ocean: temperature, salinity, currents and sea surface height anomaly. | ## Learn more - [AI in DestinE](https://destine.ecmwf.int/ai-in-destination-earth/): news, videos and podcasts on AI and ML in DestinE. - [AI in DestinE: the explainer](https://destine.ecmwf.int/artificial-intelligence-in-destine-the-explainer/) - [Forecast-in-a-Box](https://destine.ecmwf.int/news/forecast-in-a-box-portable-ai-forecasting-workflows-within-the-destine-digital-twin-engine/): portable AI forecasting workflows within the Digital Twin Engine. - [AIFS blog series](https://www.ecmwf.int/en/about/media-centre/aifs-blog) ## Get involved - **Training**: ECMWF offers advanced ML and AI training, including the Machine Learning for Earth System Modelling course series. See the [ML training page](https://destine.ecmwf.int/ml-training/). - **AI Weather Quest**: an international competition to advance weather forecasting with AI and ML. See the [AI Weather Quest](https://destine.ecmwf.int/ai-weather-quest/). - **Tenders**: ECMWF regularly opens invitations to tender for AI and ML development in DestinE. See [DestinE procurement](https://www.ecmwf.int/en/about/suppliers/destine-procurement/update-destine-itts) and the [opportunities to be involved](https://destine.ecmwf.int/opportunities-to-be-involved/). ## Support For questions about DestinE, please use the [DestinE contact page](https://destine.ecmwf.int/contact/). For the ECMWF tools behind this work: - To follow announcements and discuss with other users and ECMWF staff, visit the [ECMWF User Forum](https://forum.ecmwf.int/). - To report a bug or contribute to Anemoi, open a GitHub issue in line with the [contribution guidelines](https://anemoi.readthedocs.io/en/latest/contributing/contributing.html). If you spot an issue specific to our entries on Hugging Face, you may raise it through Hugging Face discussions. Please note that we do not guarantee support through Hugging Face. --- Destination Earth is funded by the European Union and implemented by ECMWF, ESA and EUMETSAT.