Toward Trustworthy Short-Range Forecasts with AFNO: From Skill Metrics to Conservation Checks
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2026
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| _version_ | 1866912840517943296 |
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| author | Sunil, Akshay Deepthi, B. Rashid, Muhammed |
| author_facet | Sunil, Akshay Deepthi, B. Rashid, Muhammed |
| contents | Data driven weather models now approach traditional numerical weather prediction (NWP) skill at short to medium lead times, but their dynamical consistency during autoregressive rollout remains uncertain. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_15660 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Toward Trustworthy Short-Range Forecasts with AFNO: From Skill Metrics to Conservation Checks Sunil, Akshay Deepthi, B. Rashid, Muhammed Atmospheric and Oceanic Physics Data driven weather models now approach traditional numerical weather prediction (NWP) skill at short to medium lead times, but their dynamical consistency during autoregressive rollout remains uncertain. |
| title | Toward Trustworthy Short-Range Forecasts with AFNO: From Skill Metrics to Conservation Checks |
| topic | Atmospheric and Oceanic Physics |
| url | https://arxiv.org/abs/2601.15660 |