Forest Fire Aerosol – Weather Feedbacks over Western North America Using a High-Resolution, Fully Coupled, Air-Quality Model

Abstract

Abstract. The influence of both anthropogenic and forest fire emissions, and their and subsequent chemical and physical processing, on the accuracy of weather and air-quality forecasts, was studied using a high resolution, fully coupled air-quality model. Simulations were carried out for the period 4 July through 5 August 2019, at 2.5-km horizontal grid cell size, over a 2250 x 3425 km2 domain covering western Canada and USA, prior to the use of the forecast system as part of the FIREX-AQ ensemble forecast. Several large forest fires took place in the Canadian portion of the domain during the study period. A feature of the implementation was the incorporation of a new on-line version of the Canadian Forest Fire Emissions Prediction System (CFFEPSv4.0). This inclusion of thermodynamic forest fire plume-rise calculations directly into the on-line air-quality model allowed us to simulate the interactions between forest fire plume development and weather. Incorporating feedbacks resulted in improvements in most metrics of both air-quality and meteorological model forecast performance, through comparison of no-feedback and feedback simulations with surface, radiosonde, and satellite observations. For the meteorological simulations, these improvements occurred at greater than the 90 % confidence level. Relative to the climatological cloud condensation nuclei and aerosol optical properties used in the no-feedback simulations, the fully coupled model’s aerosol indirect and direct effects were shown to result in feedback loops characterized by increased surface temperatures, decreased lower troposphere temperatures, and increased lower troposphere cloud droplet and raindrop number densities. The aerosol direct and indirect effect reduced oceanic cloud droplet number densities and increased oceanic rain drop number densities, relative to the no-feedback climatological simulation. The aerosol direct and indirect effects were responsible for changes to the aerosol concentrations at greater than the 90 % confidence level throughout the model domain, and to NO2 and O3 concentrations within forest fire plumes. The simulations show that incorporating aerosol direct and indirect effect feedbacks can significantly improve the accuracy of weather and air quality forecasts, and that forest fire plume rise calculations within a fully coupled model changes the predicted fire plume dispersion and emissions, the latter through changing the meteorology driving fire behaviour and growth.

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