Articles | Volume 20, issue 17
https://doi.org/10.5194/acp-20-10259-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-20-10259-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Sep 2020
Research article |
| 04 Sep 2020
| 04 Sep 2020
Inverse modeling of fire emissions constrained by smoke plume transport using HYSPLIT dispersion model and geostationary satellite observations
Air Resources Laboratory, National Oceanic and Atmospheric
Administration, College Park, MD 20740, USA
Cooperative Institute for Satellite Earth System Studies, University of Maryland, College Park, MD 20740, USA
Air Resources Laboratory, National Oceanic and Atmospheric
Administration, College Park, MD 20740, USA
Cooperative Institute for Satellite Earth System Studies, University of Maryland, College Park, MD 20740, USA
Ariel Stein
Air Resources Laboratory, National Oceanic and Atmospheric
Administration, College Park, MD 20740, USA
Shobha Kondragunta
National Environmental Satellite, Data and Information Service,
National Oceanic and Atmospheric Administration, College Park, MD 20740, USA
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Cited
14 citations as recorded by crossref.
- Downwind Ozone Changes of the 2019 Williams Flats Wildfire: Insights From WRF‐Chem/DART Assimilation of OMI NO2, HCHO, and MODIS AOD Retrievals A. Pouyaei et al. 10.1029/2022JD038019
- An Investigation of Non‐Spherical Smoke Particles Using CATS Lidar N. Midzak et al. 10.1029/2023JD038805
- Biomass Burning Over the United States East Coast and Western North Atlantic Ocean: Implications for Clouds and Air Quality A. Mardi et al. 10.1029/2021JD034916
- Realistic large eddy and dispersion simulation experiments during project sagebrush phase 1 A. Thomas & R. Kurzeja 10.1016/j.atmosenv.2023.120030
- Simulating spatio-temporal dynamics of surface PM2.5 emitted from Alaskan wildfires D. Chen et al. 10.1016/j.scitotenv.2023.165594
- Impacts of Transboundary Dust Transport on Aerosol Pollution in the Western Yangtze River Delta Region, China: Insights Gained From Ground‐Based Lidar and Satellite Observations H. Yang et al. 10.1029/2020EA001533
- Estimation of power plant SO2 emissions using the HYSPLIT dispersion model and airborne observations with plume rise ensemble runs T. Chai et al. 10.5194/acp-23-12907-2023
- Moisture sources and paths associated with warm-season precipitation over the Sichuan Basin in southwestern China: Climatology and interannual variability S. Zhang et al. 10.1016/j.jhydrol.2021.127019
- Measurement report: Vehicle-based multi-lidar observational study of the effect of meteorological elements on the three-dimensional distribution of particles in the western Guangdong–Hong Kong–Macao Greater Bay Area X. Xu et al. 10.5194/acp-22-139-2022
- Spatiotemporal change of beneficiary area from wind erosion prevention service in the Ulan Buh Desert in 2008 and 2018 W. Hu et al. 10.1016/j.geosus.2022.04.002
- Wildfire Smoke Particulate Matter Concentration Measurements Using Radio Links From Cellular Communication Networks A. Guyot et al. 10.1029/2020AV000258
- Air quality changes in Ukraine during the April 2020 wildfire event M. Savenets et al. 10.5937/gp24-27436
- Temporal Solar Photovoltaic Generation Capacity Reduction From Wildfire Smoke D. Donaldson et al. 10.1109/ACCESS.2021.3084528
- Hybrid IFDMB/4D-Var inverse modeling to constrain the spatiotemporal distribution of CO and NO2 emissions using the CMAQ adjoint model J. Moon et al. 10.1016/j.atmosenv.2024.120490
14 citations as recorded by crossref.
- Downwind Ozone Changes of the 2019 Williams Flats Wildfire: Insights From WRF‐Chem/DART Assimilation of OMI NO2, HCHO, and MODIS AOD Retrievals A. Pouyaei et al. 10.1029/2022JD038019
- An Investigation of Non‐Spherical Smoke Particles Using CATS Lidar N. Midzak et al. 10.1029/2023JD038805
- Biomass Burning Over the United States East Coast and Western North Atlantic Ocean: Implications for Clouds and Air Quality A. Mardi et al. 10.1029/2021JD034916
- Realistic large eddy and dispersion simulation experiments during project sagebrush phase 1 A. Thomas & R. Kurzeja 10.1016/j.atmosenv.2023.120030
- Simulating spatio-temporal dynamics of surface PM2.5 emitted from Alaskan wildfires D. Chen et al. 10.1016/j.scitotenv.2023.165594
- Impacts of Transboundary Dust Transport on Aerosol Pollution in the Western Yangtze River Delta Region, China: Insights Gained From Ground‐Based Lidar and Satellite Observations H. Yang et al. 10.1029/2020EA001533
- Estimation of power plant SO2 emissions using the HYSPLIT dispersion model and airborne observations with plume rise ensemble runs T. Chai et al. 10.5194/acp-23-12907-2023
- Moisture sources and paths associated with warm-season precipitation over the Sichuan Basin in southwestern China: Climatology and interannual variability S. Zhang et al. 10.1016/j.jhydrol.2021.127019
- Measurement report: Vehicle-based multi-lidar observational study of the effect of meteorological elements on the three-dimensional distribution of particles in the western Guangdong–Hong Kong–Macao Greater Bay Area X. Xu et al. 10.5194/acp-22-139-2022
- Spatiotemporal change of beneficiary area from wind erosion prevention service in the Ulan Buh Desert in 2008 and 2018 W. Hu et al. 10.1016/j.geosus.2022.04.002
- Wildfire Smoke Particulate Matter Concentration Measurements Using Radio Links From Cellular Communication Networks A. Guyot et al. 10.1029/2020AV000258
- Air quality changes in Ukraine during the April 2020 wildfire event M. Savenets et al. 10.5937/gp24-27436
- Temporal Solar Photovoltaic Generation Capacity Reduction From Wildfire Smoke D. Donaldson et al. 10.1109/ACCESS.2021.3084528
- Hybrid IFDMB/4D-Var inverse modeling to constrain the spatiotemporal distribution of CO and NO2 emissions using the CMAQ adjoint model J. Moon et al. 10.1016/j.atmosenv.2024.120490
Latest update: 18 Apr 2024
Short summary
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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