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Volume 18, issue 8
Atmos. Chem. Phys., 18, 5359-5370, 2018
https://doi.org/10.5194/acp-18-5359-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Atmos. Chem. Phys., 18, 5359-5370, 2018
https://doi.org/10.5194/acp-18-5359-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 20 Apr 2018

Research article | 20 Apr 2018

Using the Fire Weather Index (FWI) to improve the estimation of fire emissions from fire radiative power (FRP) observations

Francesca Di Giuseppe1, Samuel Rémy2, Florian Pappenberger1, and Fredrik Wetterhall1 Francesca Di Giuseppe et al.
  • 1European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
  • 2Institut Pierre-Simon Laplace (IPSL), CNRS/UPMC, Paris, France

Abstract. The atmospheric composition analysis and forecast for the European Copernicus Atmosphere Monitoring Services (CAMS) relies on biomass-burning fire emission estimates from the Global Fire Assimilation System (GFAS). The GFAS is a global system and converts fire radiative power (FRP) observations from MODIS satellites into smoke constituents. Missing observations are filled in using persistence, whereby observed FRP values from the previous day are progressed in time until a new observation is recorded. One of the consequences of this assumption is an increase of fire duration, which in turn translates into an increase of emissions estimated from fires compared to what is available from observations. In this study persistence is replaced by modelled predictions using the Canadian Fire Weather Index (FWI), which describes how atmospheric conditions affect the vegetation moisture content and ultimately fire duration. The skill in predicting emissions from biomass burning is improved with the new technique, which indicates that using an FWI-based model to infer emissions from FRP is better than persistence when observations are not available.

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Short summary
Fire emissions injected into the atmosphere are crucial input for air quality models. This information is available globally using fire radiative power (FRP) observations, converted into smoke constituents. In case of a missing observation after ignition, a practical choice is to assume persistence. As an improvement we propose the use of the Canadian Fire Weather Index (FWI) to predict the FRP evolution. We show that the FWI is able to capture weather-related changes in fire activity well.
Fire emissions injected into the atmosphere are crucial input for air quality models. This...
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