Articles | 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.
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.
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 Giuseppe et al.
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Cited
13 citations as recorded by crossref.
- Characterisation of African biomass burning plumes and impacts on the atmospheric composition over the south-west Indian Ocean B. Verreyken et al. 10.5194/acp-20-14821-2020
- Fire Weather Index: the skill provided by the European Centre for Medium-Range Weather Forecasts ensemble prediction system F. Di Giuseppe et al. 10.5194/nhess-20-2365-2020
- Prediction and data mining of burned areas of forest fires: Optimized data matching and mining algorithm provides valuable insight D. Wood 10.1016/j.aiia.2021.01.004
- Fourier transform infrared time series of tropospheric HCN in eastern China: seasonality, interannual variability, and source attribution Y. Sun et al. 10.5194/acp-20-5437-2020
- Evaluation of Global Fire Weather Database reanalysis and short-term forecast products R. Field 10.5194/nhess-20-1123-2020
- Forecasting Daily Wildfire Activity Using Poisson Regression C. Graff et al. 10.1109/TGRS.2020.2968029
- Empirical estimates of regional carbon budgets imply reduced global soil heterotrophic respiration P. Ciais et al. 10.1093/nsr/nwaa145
- Detection and attribution of wildfire pollution in the Arctic and northern midlatitudes using a network of Fourier-transform infrared spectrometers and GEOS-Chem E. Lutsch et al. 10.5194/acp-20-12813-2020
- Status and future of numerical atmospheric aerosol prediction with a focus on data requirements A. Benedetti et al. 10.5194/acp-18-10615-2018
- The Global Fire Atlas of individual fire size, duration, speed and direction N. Andela et al. 10.5194/essd-11-529-2019
- Machine learning to predict final fire size at the time of ignition S. Coffield et al. 10.1071/WF19023
- Can Delhi's Pollution be Affected by Crop Fires in the Punjab Region? M. Takigawa et al. 10.2151/sola.2020-015
- Toward Global Mapping of Methane With TROPOMI: First Results and Intersatellite Comparison to GOSAT H. Hu et al. 10.1002/2018GL077259
11 citations as recorded by crossref.
- Characterisation of African biomass burning plumes and impacts on the atmospheric composition over the south-west Indian Ocean B. Verreyken et al. 10.5194/acp-20-14821-2020
- Fire Weather Index: the skill provided by the European Centre for Medium-Range Weather Forecasts ensemble prediction system F. Di Giuseppe et al. 10.5194/nhess-20-2365-2020
- Prediction and data mining of burned areas of forest fires: Optimized data matching and mining algorithm provides valuable insight D. Wood 10.1016/j.aiia.2021.01.004
- Fourier transform infrared time series of tropospheric HCN in eastern China: seasonality, interannual variability, and source attribution Y. Sun et al. 10.5194/acp-20-5437-2020
- Evaluation of Global Fire Weather Database reanalysis and short-term forecast products R. Field 10.5194/nhess-20-1123-2020
- Forecasting Daily Wildfire Activity Using Poisson Regression C. Graff et al. 10.1109/TGRS.2020.2968029
- Empirical estimates of regional carbon budgets imply reduced global soil heterotrophic respiration P. Ciais et al. 10.1093/nsr/nwaa145
- Detection and attribution of wildfire pollution in the Arctic and northern midlatitudes using a network of Fourier-transform infrared spectrometers and GEOS-Chem E. Lutsch et al. 10.5194/acp-20-12813-2020
- Status and future of numerical atmospheric aerosol prediction with a focus on data requirements A. Benedetti et al. 10.5194/acp-18-10615-2018
- The Global Fire Atlas of individual fire size, duration, speed and direction N. Andela et al. 10.5194/essd-11-529-2019
- Machine learning to predict final fire size at the time of ignition S. Coffield et al. 10.1071/WF19023
Latest update: 04 Mar 2021
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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