Articles | Volume 21, issue 18
https://doi.org/10.5194/acp-21-14427-2021
https://doi.org/10.5194/acp-21-14427-2021
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

Related authors

A Lagrangian approach towards extracting signals of urban CO2 emissions from satellite observations of atmospheric column CO2 (XCO2): X-Stochastic Time-Inverted Lagrangian Transport model (“X-STILT v1”)
Dien Wu, John C. Lin, Benjamin Fasoli, Tomohiro Oda, Xinxin Ye, Thomas Lauvaux, Emily G. Yang, and Eric A. Kort
Geosci. Model Dev., 11, 4843–4871, https://doi.org/10.5194/gmd-11-4843-2018,https://doi.org/10.5194/gmd-11-4843-2018, 2018
Short summary
Constraining fossil fuel CO2 emissions from urban area using OCO-2 observations of total column CO2
Xinxin Ye, Thomas Lauvaux, Eric A. Kort, Tomohiro Oda, Sha Feng, John C. Lin, Emily Yang, and Dien Wu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-1022,https://doi.org/10.5194/acp-2017-1022, 2017
Revised manuscript not accepted
Short summary

Related subject area

Subject: Aerosols | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
Unveiling the optimal regression model for source apportionment of the oxidative potential of PM10
Vy Dinh Ngoc Thuy, Jean-Luc Jaffrezo, Ian Hough, Pamela A. Dominutti, Guillaume Salque Moreton, Grégory Gille, Florie Francony, Arabelle Patron-Anquez, Olivier Favez, and Gaëlle Uzu
Atmos. Chem. Phys., 24, 7261–7282, https://doi.org/10.5194/acp-24-7261-2024,https://doi.org/10.5194/acp-24-7261-2024, 2024
Short summary
Investigating the contribution of grown new particles to cloud condensation nuclei with largely varying preexisting particles – Part 2: Modeling chemical drivers and 3-D new particle formation occurrence
Ming Chu, Xing Wei, Shangfei Hai, Yang Gao, Huiwang Gao, Yujiao Zhu, Biwu Chu, Nan Ma, Juan Hong, Yele Sun, and Xiaohong Yao
Atmos. Chem. Phys., 24, 6769–6786, https://doi.org/10.5194/acp-24-6769-2024,https://doi.org/10.5194/acp-24-6769-2024, 2024
Short summary
Technical note: Influence of different averaging metrics and temporal resolutions on the aerosol pH calculated by thermodynamic modeling
Haoqi Wang, Xiao Tian, Wanting Zhao, Jiacheng Li, Haoyu Yu, Yinchang Feng, and Shaojie Song
Atmos. Chem. Phys., 24, 6583–6592, https://doi.org/10.5194/acp-24-6583-2024,https://doi.org/10.5194/acp-24-6583-2024, 2024
Short summary
Dual roles of the inorganic aqueous phase on secondary organic aerosol growth from benzene and phenol
Jiwon Choi, Myoseon Jang, and Spencer Blau
Atmos. Chem. Phys., 24, 6567–6582, https://doi.org/10.5194/acp-24-6567-2024,https://doi.org/10.5194/acp-24-6567-2024, 2024
Short summary
Global source apportionment of aerosols into major emission regions and sectors over 1850–2017
Yang Yang, Shaoxuan Mou, Hailong Wang, Pinya Wang, Baojie Li, and Hong Liao
Atmos. Chem. Phys., 24, 6509–6523, https://doi.org/10.5194/acp-24-6509-2024,https://doi.org/10.5194/acp-24-6509-2024, 2024
Short summary

Cited articles

Abatzoglou, J. T. and Williams, A. P.: Impact of anthropogenic climate change on wildfire across western US forests, P. Natl. Acad. Sci. USA, 113, 11770–11775, https://doi.org/10.1073/pnas.1607171113, 2016. 
Ahmadov, R., Grell, G., James, E., Csiszar, I., Tsidulko, M., Pierce, B., McKeen, S., Benjamin, S., Alexander, C., Pereira, G., Freitas, S., and Goldberg, M.: Using VIIRS fire radiative power data to simulate biomass burning emissions, plume rise and smoke transport in a real-time air quality modeling system, in: 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2806–2808, 2017. 
Ahmadov, R., James, E., Grell, G. A., Alexander, C., Olson, J., Benjamin, S., McKeen, S. A., Bela, M., Hamilton, J., and Wong, K. Y.: High-resolution (3 km) forecasting of smoke and visibility for the US by ingesting the VIIRS and MODIS FRP data into HRRR-Smoke during August 2018, in: AGU Fall Meeting Abstracts, A51F-08, 2019. 
Albayrak, A., Wei, J., Petrenko, M., Lynnes, C., and Levy, R. C.: Global bias adjustment for MODIS aerosol optical thickness using neural network, J. Appl. Remote Sens., 7, 073514, https://doi.org/10.1117/1.JRS.7.073514, 2013. 
Anderson, K., Pankratz, A., and Mooney, C.: A thermodynamic approach to estimating smoke plume heights, in: Proceedings of Ninth Symposium on Fire and Forest Meteorology, Palms Springs, CA, American Meteorological Society, 17–21, 2011. 
Download
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.
Altmetrics
Final-revised paper
Preprint