Empirical Evidence of Reduced Wildfire Ignition Risk in the Presence of Strong Winds

Assaf Shmuel*, Eyal Heifetz

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Anyone who has tried lighting a campfire on a windy day can appreciate how difficult it could be. However, despite real-life experience and despite laboratory experiments which have demonstrated that fire ignition risk dramatically decreases beyond a certain wind threshold, current fire weather indices (FWIs) do not take this effect into account and assume a monotonic relation between wind velocity and ignition risk. In this paper, we perform a global analysis which empirically quantifies the probability of ignition as a function of wind velocity. Using both traditional methods (a logistic regression and a generalized additive model) and machine learning techniques, we find that beyond a threshold of approximately 3–4 m/s, the ignition risk substantially decreases. The effect holds when accounting for additional factors such as temperature and relative humidity. We recommend updating FWIs to account for this issue.

Original languageEnglish
Article number338
Issue number9
StatePublished - Sep 2023


  • fire weather indices
  • forest management
  • machine learning
  • wind velocity


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