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ACP | Articles | Volume 20, issue 17
Atmos. Chem. Phys., 20, 10259–10277, 2020
https://doi.org/10.5194/acp-20-10259-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Atmos. Chem. Phys., 20, 10259–10277, 2020
https://doi.org/10.5194/acp-20-10259-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 04 Sep 2020

Research article | 04 Sep 2020

Inverse modeling of fire emissions constrained by smoke plume transport using HYSPLIT dispersion model and geostationary satellite observations

Hyun Cheol Kim et al.

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Cited articles

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), 23–28 July 2017, Fort Worth, TX, USA, 2806–2808, 2017. 
Andreae, M. O.: Emission of trace gases and aerosols from biomass burning – An updated assessment, Atmos. Chem. Phys., 19, 8523–8546, https://doi.org/10.5194/acp-19-8523-2019, 2019. 
Arya, S. P.: Air Pollution Meteorology and Dispersion, Oxford University Press, Oxford, 1998. 
Boichu, M., Clarisse, L., Khvorostyanov, D., and Clerbaux, C.: Improving volcanic sulfur dioxide cloud dispersal forecasts by progressive assimilation of satellite observations, Geophys. Res. Lett., 41, 2637–2643, https://doi.org/10.1002/2014GL059496, 2014. 
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Smoke forecasts have been challenged by high uncertainty in fire emission estimates. We develop an inverse modeling system, the HYSPLIT-based Emissions Inverse Modeling System for wildfires, that estimates wildfire emissions from the transport and dispersion of smoke plumes as measured by satellite observations. Using NOAA HYSPLIT and GOES Aerosol/Smoke Product (GASP), the system resolves smoke source strength as a function of time and vertical level and outperforms current operational system.
Smoke forecasts have been challenged by high uncertainty in fire emission estimates. We develop...
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