Articles | Volume 24, issue 12
https://doi.org/10.5194/nhess-24-4225-2024
https://doi.org/10.5194/nhess-24-4225-2024
Research article
 | 
29 Nov 2024
Research article |  | 29 Nov 2024

Statistical calibration of probabilistic medium-range Fire Weather Index forecasts in Europe

Stephanie Bohlmann and Marko Laine

Viewed

Total article views: 2,734 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,921 685 128 2,734 286 124 159
  • HTML: 1,921
  • PDF: 685
  • XML: 128
  • Total: 2,734
  • Supplement: 286
  • BibTeX: 124
  • EndNote: 159
Views and downloads (calculated since 31 May 2024)
Cumulative views and downloads (calculated since 31 May 2024)

Viewed (geographical distribution)

Total article views: 2,734 (including HTML, PDF, and XML) Thereof 2,626 with geography defined and 108 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 21 Jul 2026
Download
Short summary
Probabilistic ensemble forecasts of the Canadian Forest Fire Weather Index (FWI) can be used to estimate the possible wildfire risk but require post-processing to provide accurate and reliable predictions. This article presents a calibration method using non-homogeneous Gaussian regression to statistically post-process FWI forecasts up to 15 d. Calibration improves the forecast especially at short lead times and in regions with high fire risk.
Share
Altmetrics
Final-revised paper
Preprint