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<p>The Canadian Fire Weather Index (FWI), widely used to assess wildfire danger, typically relies on noon-specific meteorological data. However, climate models often provide only daily aggregated values, posing a challenge for accurate FWI calculations. We evaluated daily approximations for FWI95d—the annual count of extreme fire-weather days—against the standard noon-based method (1980–2023). Our findings reveal that noon-based FWI95d show a global increase of ~65% (11.66 days over 44 years). In contrast, daily approximations tend to overestimate these trends by 5–10%, with combinations involving minimum relative humidity showing the largest divergences. Globally, up to 15 million km²—particularly in the western United States, southern Africa, and parts of Asia—exhibit significant overestimations. We recommend (i) prioritizing the inclusion of sub-daily meteorological data in future climate model intercomparison projects to enhance FWI accuracy, and (ii) adopting daily mean approximations as the least-biased alternative if noon-specific data are unavailable.</p>

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Challenges in assessing Fire Weather changes in a warming climate

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月28日

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  • Aurora Matteo,
  • Ginés Garnés-Morales,
  • Alberto Moreno,
  • Andreia F. S. Ribeiro,
  • Cesar Azorin-Molina,
  • Joaquín Bedia,
  • Francesca Di Giuseppe,
  • Robert J. H. Dunn,
  • Sixto Herrera,
  • Antonello Provenzale,
  • Yann Quilcaille,
  • Miguel Ángel Torres-Vázquez,
  • Marco Turco

摘要

The Canadian Fire Weather Index (FWI), widely used to assess wildfire danger, typically relies on noon-specific meteorological data. However, climate models often provide only daily aggregated values, posing a challenge for accurate FWI calculations. We evaluated daily approximations for FWI95d—the annual count of extreme fire-weather days—against the standard noon-based method (1980–2023). Our findings reveal that noon-based FWI95d show a global increase of ~65% (11.66 days over 44 years). In contrast, daily approximations tend to overestimate these trends by 5–10%, with combinations involving minimum relative humidity showing the largest divergences. Globally, up to 15 million km²—particularly in the western United States, southern Africa, and parts of Asia—exhibit significant overestimations. We recommend (i) prioritizing the inclusion of sub-daily meteorological data in future climate model intercomparison projects to enhance FWI accuracy, and (ii) adopting daily mean approximations as the least-biased alternative if noon-specific data are unavailable.