{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/aurora-a-foundation-model-of-the-atmosphere","title":"A Foundation Model for the Earth System","arxiv_id":"2405.13063","date":"2024-05-20","proceeding":null,"authors":["Cristian Bodnar","Wessel P. Bruinsma","Ana Lucic","Megan Stanley","Anna Vaughan","Johannes Brandstetter","Patrick Garvan","Maik Riechert","Jonathan A. Weyn","Haiyu Dong","Jayesh K. Gupta","Kit Thambiratnam","Alexander T. Archibald","Chun-Chieh Wu","Elizabeth Heider","Max Welling","Richard E. Turner","Paris Perdikaris"],"abstract":"Reliable forecasts of the Earth system are crucial for human progress and safety from natural disasters. Artificial intelligence offers substantial potential to improve prediction accuracy and computational efficiency in this field, however this remains underexplored in many domains. Here we introduce Aurora, a large-scale foundation model for the Earth system trained on over a million hours of diverse data. Aurora outperforms operational forecasts for air quality, ocean waves, tropical cyclone tracks, and high-resolution weather forecasting at orders of magnitude smaller computational expense than dedicated existing systems. With the ability to fine-tune Aurora to diverse application domains at only modest computational cost, Aurora represents significant progress in making actionable Earth system predictions accessible to anyone.","url_abs":"https://arxiv.org/abs/2405.13063v3","url_pdf":"https://arxiv.org/pdf/2405.13063v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"aurora-a-foundation-model-of-the-atmosphere","repo_url":"https://github.com/openclimatefix/graph_weather","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"computational-efficiency","task_name":"Computational Efficiency"},{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"weather-forecasting","task_name":"Weather Forecasting"},{"task_slug":"model","task_name":"model"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2405.13063","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2405.13063"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/openclimatefix/graph_weather","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"unverified":1},"by_repo_kind":{"listed":{"samples":1,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"1b7d3be2af7ec7fa","entry":"regional_weighted_mse","repo":"openclimatefix/graph_weather","repo_kind":"listed","path":"graph_weather/models/losses.py","file_url":"https://github.com/openclimatefix/graph_weather/blob/HEAD/graph_weather/models/losses.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"1b7d3be2af7ec7fa"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}