Articles | Volume 21, issue 18
Research article
29 Sep 2021
Research article |  | 29 Sep 2021

Evaluation and intercomparison of wildfire smoke forecasts from multiple modeling systems for the 2019 Williams Flats fire

Xinxin Ye, Pargoal Arab, Ravan Ahmadov, Eric James, Georg A. Grell, Bradley Pierce, Aditya Kumar, Paul Makar, Jack Chen, Didier Davignon, Greg R. Carmichael, Gonzalo Ferrada, Jeff McQueen, Jianping Huang, Rajesh Kumar, Louisa Emmons, Farren L. Herron-Thorpe, Mark Parrington, Richard Engelen, Vincent-Henri Peuch, Arlindo da Silva, Amber Soja, Emily Gargulinski, Elizabeth Wiggins, Johnathan W. Hair, Marta Fenn, Taylor Shingler, Shobha Kondragunta, Alexei Lyapustin, Yujie Wang, Brent Holben, David M. Giles, and Pablo E. Saide


Total article views: 4,382 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
3,063 1,265 54 4,382 160 50 63
  • HTML: 3,063
  • PDF: 1,265
  • XML: 54
  • Total: 4,382
  • Supplement: 160
  • BibTeX: 50
  • EndNote: 63
Views and downloads (calculated since 12 Apr 2021)
Cumulative views and downloads (calculated since 12 Apr 2021)

Viewed (geographical distribution)

Total article views: 4,382 (including HTML, PDF, and XML) Thereof 4,687 with geography defined and -305 with unknown origin.
Country # Views %
  • 1


Latest update: 23 Jun 2024
Short summary
Wildfire smoke has crucial impacts on air quality, while uncertainties in the numerical forecasts remain significant. We present an evaluation of 12 real-time forecasting systems. Comparison of predicted smoke emissions suggests a large spread in magnitudes, with temporal patterns deviating from satellite detections. The performance for AOD and surface PM2.5 and their discrepancies highlighted the role of accurately represented spatiotemporal emission profiles in improving smoke forecasts.
Final-revised paper