Nonlinear Processes in Geophysics
Nonlinear Processes in Geophysics
NPG
Articles | Volume 33, issue 3
Articles | Volume 33, issue 3
https://doi.org/10.5194/npg-33-347-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-33-347-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 33, issue 3
Research article
 | 
14 Jul 2026
Research article |  | 14 Jul 2026

Formulation of parametric uncertainty forecasts towards operational wildfire smoke assimilation

Annika Vogel, Richard Ménard, James Abu, and Jack Chen

Viewed

Total article views: 1,880 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,188 544 148 1,880 427 459
  • HTML: 1,188
  • PDF: 544
  • XML: 148
  • Total: 1,880
  • BibTeX: 427
  • EndNote: 459
Views and downloads (calculated since 30 Dec 2025)
Cumulative views and downloads (calculated since 30 Dec 2025)

Viewed (geographical distribution)

Total article views: 1,880 (including HTML, PDF, and XML) Thereof 1,866 with geography defined and 14 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 14 Jul 2026
Download
Short summary
Recent wildfire activity in Canada has been rising the public demand for fast, yet accurate operational air quality forecasts along with related forecast uncertainties. This study explores the potential of an efficient process-based approach to estimate forecast uncertainties of operational air quality models. Our results show its potential for understanding how uncertainties of operational forecast evolve over time and an improved use of sparse observation signals at remote wildfire regions.
Read more
Share