{"work":{"id":"70fb872c-054e-46dc-b24c-d5d21d6bd87e","openalex_id":"https://openalex.org/W4399401448","doi":"10.48550/arxiv.2406.01465","arxiv_id":"2406.01465","raw_key":null,"title":"AIFS -- ECMWF's data-driven forecasting system","authors":null,"authors_text":"URL https://arxiv","year":2024,"venue":"physics.ao-ph","abstract":"Machine learning-based weather forecasting models have quickly emerged as a promising methodology for accurate medium-range global weather forecasting. Here, we introduce the Artificial Intelligence Forecasting System (AIFS), a data driven forecast model developed by the European Centre for Medium-Range Weather Forecasts (ECMWF). AIFS is based on a graph neural network (GNN) encoder and decoder, and a sliding window transformer processor, and is trained on ECMWF's ERA5 re-analysis and ECMWF's operational numerical weather prediction (NWP) analyses. It has a flexible and modular design and supports several levels of parallelism to enable training on high-resolution input data. AIFS forecast skill is assessed by comparing its forecasts to NWP analyses and direct observational data. We show that AIFS produces highly skilled forecasts for upper-air variables, surface weather parameters and tropical cyclone tracks. AIFS is run four times daily alongside ECMWF's physics-based NWP model and forecasts are available to the public under ECMWF's open data policy.","external_url":"https://arxiv.org/abs/2406.01465","cited_by_count":70,"metadata_source":"pith","metadata_fetched_at":"2026-08-05T02:28:24.338817+00:00","pith_arxiv_id":"2406.01465","created_at":"2026-05-08T16:53:29.783885+00:00","updated_at":"2026-08-05T02:28:24.338817+00:00","title_quality_ok":true,"display_title":"arXiv, ://arxiv.org/abs/2406.01465, doi:10.48550/arXiv.2406.01465","render_title":"arXiv, ://arxiv.org/abs/2406.01465, doi:10.48550/arXiv.2406.01465"},"hub":{"state":{"work_id":"70fb872c-054e-46dc-b24c-d5d21d6bd87e","tier":"hub","tier_reason":"10+ Pith inbound or 1,000+ external citations","pith_inbound_count":33,"external_cited_by_count":70,"distinct_field_count":8,"first_pith_cited_at":"2024-12-01T19:02:03+00:00","last_pith_cited_at":"2026-07-08T19:30:17+00:00","author_build_status":"not_needed","summary_status":"needed","contexts_status":"needed","graph_status":"needed","ask_index_status":"not_needed","reader_status":"not_needed","recognition_status":"not_needed","updated_at":"2026-08-21T21:19:27.896423+00:00","tier_text":"hub"},"tier":"hub","role_counts":[{"context_role":"background","n":5},{"context_role":"method","n":1}],"polarity_counts":[{"context_polarity":"background","n":5},{"context_polarity":"use_method","n":1}],"runs":{},"summary":{},"graph":{},"authors":[]}}