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

Data sets


Distributed Regional Aerosol Gridded Observation Networks (DRAGON)- FIREX-AQ 2019 B. Holben, T. Eck, and D. Giles

MODIS/Terra+Aqua MAIAC Land Aerosol Optical Depth Daily L2G 1 km SIN Grid (MCD19A2 v006) Alexei Lyapustin and Yujie Wang

Air Quality Data Collected at Outdoor Monitors Across the US U.S. EPA

Air Quality Data Collected by OpenAQ platfrom OpenAQ

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