{"slug":"ai-weather-climate","topic":"ai-weather-climate","title":"AI Weather & Climate Modeling: State of the Field (October 2026)","summary":"This dossier covers learned global medium-range weather models, probabilistic and ensemble systems, hybrid learned-physics climate components and kilometre-scale emulators as of October 2026. Its main takeaway is that data-driven global forecasts now match or beat operational baselines on most headline verification targets, while extremes, uncertainty and climate-scale reliability remain contested.","version":1,"published_at":"2026-10-30","updated_at":"2026-10-30","stats":{"words":3012,"citations":45,"claims":30,"timeline":17,"benchmarks":8,"open_problems":6,"key_papers":12,"glossary":11},"verification":{"status":"verified","method":"automated figure and citation-relevance triage against cited abstracts, targeted AI review with web checks of flagged statements, and an editorial close-out; automated citation resolution","claims_checked":30,"issues_fixed":2,"verified_at":"2026-10-30","notes":["Coverage gap (not an error): AIFS ENS operational start (1 July 2025), AIFS version 2 (12 May 2026) and the October 2026 Nature subseasonal bias-correction paper are not yet covered."]},"ai_assisted":true,"price":{"usd":"0.20","protocol":"x402","network":"eip155:84532","asset":"USDC"},"url":"https://space-kitty.com/dossiers/ai-weather-climate","preview_url":"https://space-kitty.com/api/v1/dossiers/ai-weather-climate/preview","purchase_url":"https://space-kitty.com/api/v1/dossiers/ai-weather-climate","toc":[{"level":2,"text":"Executive summary","anchor":"executive-summary"},{"level":2,"text":"Background and core concepts","anchor":"background-and-core-concepts"},{"level":2,"text":"Timeline of key milestones","anchor":"timeline-of-key-milestones"},{"level":2,"text":"State of the art","anchor":"state-of-the-art"},{"level":3,"text":"Deterministic global forecasts","anchor":"deterministic-global-forecasts"},{"level":3,"text":"Probabilistic and ensemble forecasting","anchor":"probabilistic-and-ensemble-forecasting"},{"level":3,"text":"Operational systems and industrial models","anchor":"operational-systems-and-industrial-models"},{"level":3,"text":"Hybrid and climate models","anchor":"hybrid-and-climate-models"},{"level":3,"text":"Kilometre-scale and regional emulation","anchor":"kilometre-scale-and-regional-emulation"},{"level":3,"text":"Foundation models","anchor":"foundation-models"},{"level":3,"text":"Quantitative benchmarks","anchor":"quantitative-benchmarks"},{"level":2,"text":"Open problems and active debates","anchor":"open-problems-and-active-debates"},{"level":2,"text":"Major programs and players","anchor":"major-programs-and-players"},{"level":2,"text":"Outlook: what to watch (November 2026 to April 2028)","anchor":"outlook-what-to-watch-november-2026-to-april-2028"},{"level":2,"text":"Key papers","anchor":"key-papers"},{"level":2,"text":"Glossary","anchor":"glossary"}],"sample_claims":["Data-driven global medium-range models trained on reanalysis data, including GraphCast, now match or exceed the operational ECMWF deterministic forecast on most verification targets.","GraphCast produces a 10-day global forecast at 0.25 degree resolution in under one minute, and reports better scores than the operational deterministic baseline on 90% of 1,380 verification targets."],"includes":["markdown","claims","timeline","benchmarks","open_problems","key_papers","glossary","bibliography"],"citation_count":45,"how_to_buy":"GET https://space-kitty.com/api/v1/dossiers/ai-weather-climate with an x402 client ($0.20, USDC on Base Sepolia (testnet))."}