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Near-Term Fire Weather Forecasting in the Pacific Northwest using 500-hPa Map Types

Reed Humphrey , John Saltenberger, John abatzoglou, Alison Cullen

Abstract

[Background] Near-term forecasts of fire danger based on predicted surface weather and fuel dryness are widely used to support the decisions of wildfire managers. The incorporation of synoptic-scale upper-air patterns into predictive models may provide additional value in operational forecasting. [Aims] In this study, we assess the impact of synoptic-scale upper-air patterns on the occurrence of large wildfires and widespread fire outbreaks in the US Pacific Northwest. Additionally, we examine how discrete upper-air map types can augment subregional models of wildfire risk. [Methods] We assess the statistical relationship between synoptic map types, surface weather, and wildfire occurrence. Additionally, we compare subregional fire danger models to identify the predictive value contributed by upper-air map types. [Key Results] We find that these map types explain variation in wildfire occurrence not captured by fire danger indices based on surface weather alone, with specific map types associated with significantly higher expected daily ignition counts in half of the subregions. [Conclusions] We observe that incorporating upper-air map types enhances the explanatory power of subregional fire danger models. [Implications] Our approach provides value to operational wildfire management and provides a template for how these methods may be implemented in other regions.

WF23117  Accepted 13 April 2024

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