EGU22-3051, updated on 09 Jan 2023
EGU General Assembly 2022
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Nowcasting Burn Probability for the Contiguous United States

Theodore Keeping1, Sandy P. Harrison1, Colin Prentice2, Ted Shepherd3, and John Wardman4
Theodore Keeping et al.
  • 1University of Reading, School of Archaeology, Geography and Environmental Science, Environmental Science, Reading, UK
  • 2Imperial College London, Faculty of Natural Sciences, Department of Life Sciences, London, UK
  • 3University of Reading, Department of Meteorology, Reading, UK
  • 4AXA XL, London, UK

The probability of wildfire occurrence has been successfully predicted on coarse spatial scales (~0.5°) based on empirical modelling of burned area. This method has limited scope for predicting thwildfire hazard at local scales and in the near-term, both necessary for wildfire management. high-resolution, practically applicable hazard model can be built through quantifying the probability of fire as a function of site-specific present and antecedent climate and vegetation variables.Here we apply the known Poisson and Pareto distributions of wildfire occurrence and fire size in a two-step hazard model, where the probability of a location being affected by wildfire is approximated using multiple climate and vegetation parameters. In addition, we examine other predictor variables that have been used for modelling fire at coarse resolution, e.g. road density, to determine at what spatial scale they lose predictive power. The study focuses exclusively on the contiguous United States, due to its comparatively long and high-resolution record of wildfire events. 

How to cite: Keeping, T., Harrison, S. P., Prentice, C., Shepherd, T., and Wardman, J.: Nowcasting Burn Probability for the Contiguous United States, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3051,, 2022.