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      "statement": "# Aardvark end-to-end observation-to-weather forecasting\n\nMaps heterogeneous weather observations through learned state estimation, autoregressive forecasting and local prediction modules, permitting end-to-end adaptation without numerical-model initial states at inference.\n\n## Scientific scope\n\nV1 ten-author UNet account differs from expanded v3 eleven-author ViT account; first two equal marks are explicit in v3. Independence from NWP at inference does not remove reanalysis dependence during pretraining. V1 abstract says one-degree while body reports1.41-degree grid; no unsupported exact resolution selected. Skill and baseline wins vary by variable/lead; spectral blurring and weak upper-level/short-range skill remain. No agricultural/public-health application claims.\n\n## Reading status\n\nThis is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.\n\n## People and systems\n\nAnna Vaughan; Stratis Markou; Will Tebbutt; James Requeima; Wessel P. Bruinsma; Tom R. Andersson; Michael Herzog; Nicholas D. Lane; J. Scott Hosking; Richard E. Turner; Matthew Chantry\n\nSource-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.\n\n\n\n## Original sources\n\n- [Aardvark Weather: end-to-end data-driven weather forecasting](https://arxiv.org/pdf/2404.00411v1)\n- [End-to-end data-driven weather prediction](https://arxiv.org/pdf/2404.00411v3)\n",
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