{
  "abstract": "Artificial-intelligence weather prediction (AIWP) models have made it possible to produce high-quality tailored forecasts with limited computational resources. This advance has the potential to benefit hundreds of millions of farmers in low- and middle-income countries who lack access to forecasts of critical weather phenomena. However, it can be difficult for key stakeholders to evaluate forecast quality, risking a \"race to the bottom\" as cheap but low-quality forecasts crowd out forecasts that would benefit farmers. We propose a set of principles and protocols for evaluating agriculturally-relevant forecasts as a starting point for standards that would let forecasters credibly convey their forecasts' quality.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.00782",
  "author_total": 12,
  "authors": [
    {
      "name": "Colin Aitken"
    },
    {
      "name": "Michael K. Tippett"
    },
    {
      "name": "Pedram Hassanzadeh"
    },
    {
      "name": "Katherine Kowal"
    },
    {
      "name": "Rendani Mbuvha"
    },
    {
      "name": "John H. Marsham"
    },
    {
      "name": "Shruti Nath"
    },
    {
      "name": "Ousmane Ndiaye"
    },
    {
      "name": "Douglas J. Parker"
    },
    {
      "name": "Caroline M Wainwright"
    },
    {
      "name": "Michael Kremer"
    },
    {
      "name": "William R. Boos"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6geet0pqazemq.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.00782",
  "fulltext_url": null,
  "id": "6geet0pqazemq",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.00782",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "econ.GN"
    ],
    [
      "arxiv",
      "physics.ao-ph"
    ],
    [
      "arxiv",
      "q-fin.EC"
    ],
    [
      "openalex",
      "1105|Climate change impacts on agriculture"
    ]
  ],
  "openalex": "W7215774796",
  "pdf_url": "https://arxiv.org/pdf/2610.00782",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-07",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/6geet0pqazemq.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:27:37Z",
      "native_id": "2610.00782",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.00782"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "arxiv:physics.ao-ph",
      "subfield": "atmospheric"
    }
  ],
  "title": "Can we create a `race to the top' for weather forecasts to inform smallholder farmer decisions?",
  "title_text": "Can we create a `race to the top' for weather forecasts to inform smallholder farmer decisions?",
  "type": "preprint",
  "updated_at": "2026-10-30T12:27:37Z",
  "url": "https://research.draconitic.com/paper/6geet0pqazemq",
  "venue": "arXiv",
  "versions": []
}