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Improving Wildfire Emissions Transport Modeling and Emissions Estimation

We have recently started this project and have no results to display. We will post results to this location as they become available. However, this project is based on the idea that non-aerosol satellite observations in an ensemble Kalman filter can take advantage of the correlations between the non-aerosol observations and aerosol state variables to improve wildfire (WF) emissions and initial conditions. Figure 3 is based on results from our collaboration with the University of Houston. We are applying WRF-Chem/DART to the FIREX-AQ Williams Flats WF with assimilation of OMI NO2 and formaldehyde (HCHO). The results show that assimilation of NO2 and HCHO improves the smoke AOD (sAOD) forecast. This result is significant because it illustrates that correlations between non-aerosol observations and aerosol state variable in WRF-Chem can improve sAOD forecasts. This suggests that they can be used to improve WF emssions.

Maps of smoke AOD (sAOD)
Figure 1. Maps of smoke AOD (sAOD) for the Williams Flats WF using WRF-Chem/DART with the assimilation of OMI NO2 and HCHO.