Regimes of Scale in AI Meteorology
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866911573938798592 |
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| author | Martin, Anya Lin, Cindy |
| author_facet | Martin, Anya Lin, Cindy |
| contents | HCI work has explored the effective integration of AI/ML tools across "application domains" from healthcare to finance to transportation. We add to this literature with an analysis of AI/ML tools in meteorology, a domain that already uses "big data" and massive physics-based models. Drawing from 12 interviews with forecasters and meteorologists with varied connections to AI/ML weather modeling, we trace tensions in AI/ML weather application arising from what we call "regimes of scale," different ways that AI/ML and meteorological regimes make observations, data, and models scale. Rather than seeing AI/ML as a domain-agnostic tool, we argue that AI/ML methods were born from specific platform and internet infrastructures, and so they can struggle to integrate with very different (in this case meteorological) ways of organizing data pipelines. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_06000 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Regimes of Scale in AI Meteorology Martin, Anya Lin, Cindy Human-Computer Interaction HCI work has explored the effective integration of AI/ML tools across "application domains" from healthcare to finance to transportation. We add to this literature with an analysis of AI/ML tools in meteorology, a domain that already uses "big data" and massive physics-based models. Drawing from 12 interviews with forecasters and meteorologists with varied connections to AI/ML weather modeling, we trace tensions in AI/ML weather application arising from what we call "regimes of scale," different ways that AI/ML and meteorological regimes make observations, data, and models scale. Rather than seeing AI/ML as a domain-agnostic tool, we argue that AI/ML methods were born from specific platform and internet infrastructures, and so they can struggle to integrate with very different (in this case meteorological) ways of organizing data pipelines. |
| title | Regimes of Scale in AI Meteorology |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2604.06000 |