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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2019-63
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-63
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Model description paper 25 Mar 2019

Model description paper | 25 Mar 2019

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This discussion paper is a preprint. A revision of the manuscript is under review for the journal Geoscientific Model Development (GMD).

The FireWork v2.0 air quality forecast system with biomass burning emissions from the Canadian Forest Fire Emissions Prediction System v2.03

Jack Chen1, Kerry Anderson2,*, Radenko Pavlovic3, Michael D. Moran1, Peter Englefield2, Dan K. Thompson2, Rodrigo Munoz-Alpizar3, and Hugo Landry3 Jack Chen et al.
  • 1Air Quality Research Division, Environment and Climate Change Canada, Ontario, Canada
  • 2Canadian Forest Service, Natural Resources Canada, Alberta, Canada
  • 3Air Quality Modelling Applications Section, Environment and Climate Change Canada, Quebec, Canada
  • *Emeritus

Abstract. Biomass burning activities can produce large quantities of smoke and result in adverse air quality conditions in regional environments. In Canada, Environment and Climate Change Canada's (ECCC) operational FireWork air quality forecast system incorporates near-real-time biomass burning emissions to forecast smoke plumes from fire events. The system is based on the ECCC operational Regional Air Quality Deterministic Prediction System (RAQDPS) augmented with near-real-time wildfire emissions using inputs from the Canadian Forest Service's (CFS) Canadian Wildland Fire Information System (CWFIS). Recent improvements to the representation of fire behaviour and fire emissions have been incorporated into the CFS Canadian Forest Fire Emissions Prediction System (CFFEPS). This is a bottom-up system linked to CWFIS in which hourly changes in biomass fuel consumption are parameterized with hourly forecasted meteorology at fire locations. CFFEPS has now also been connected to FireWork. In addition, a plume-rise parameterization based on fire energy thermodynamics is used to define the smoke injection height and the distribution of emissions within a model vertical column. The new system, FireWork-CFFEPS, has been evaluated over North America for July–September 2017 and June–August 2018, both periods when western Canada experienced historical levels of fire activity with poor air quality conditions in several cities as well as other fires affecting northern Canada and Ontario. Forecast results were evaluated against hourly surface measurements for the three pollutant species used to calculate the Canadian Air Quality Health Index (AQHI), namely PM2.5, O3, and NO2, and benchmarked against the operational FireWork system (FireWork-Ops). This comparison shows improved forecast performance and predictive skills for the FireWork-CFFEPS system. Modelled fire plume injection heights from CFFEPS based on fire energy thermodynamics show higher plume injection heights and larger variability. The changes in predicted fire emissions and injection height reduced the consistent over-predictions of PM2.5 and O3 seen in FireWork-Ops. On the other hand, there were minimal fire emission contributions to surface NO2, and results from FireWork-CFFEPS do not degrade NO2 forecast skill compared to the RAQDPS. Model performances statistics are slightly better for Canada than for the U.S., with lower errors and biases. The new system is still unable to capture the hourly variability of the observed values for PM2.5, but it captured the observed hourly variability for O3 concentration adequately. FireWork-CFFEPS also improves upon FireWork-Ops categorical scores for forecasting the occurrence of elevated air pollutant concentrations in terms of false alarm ratio (FAR), and critical success index (CSI).

Jack Chen et al.
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Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Jack Chen et al.
Model code and software

CFFEPS v2.03 K. Anderson and cast of thousands anadian Forest Service, Natural Resources Canada https://doi.org/10.5281/zenodo.2579383

GEM-MACH atmospheric chemistry module for the GEM numerical weather prediction model J. Chen and GEM-MACH development team Environment and Climate Change Canada https://doi.org/10.5281/zenodo.2579386

Jack Chen et al.
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Latest update: 18 Jun 2019
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Short summary
Emissions from wildland fires can cause significant impacts to regional air quality. In this work, we introduce a new wild fire emissions modelling system and demonstrate its integration with an operational air quality forecast system to provide near-real-time guidance of surface air pollutants concentrations (PM2.5, O3 and NO2) from the impacts of regional wildland fires across the North American model domain.
Emissions from wildland fires can cause significant impacts to regional air quality. In this...
Citation