Estimating biomass burning emissions with HYSPLIT-based emission inverse modeling system and GOES Advanced Baseline Imager (ABI) observations

Abstract:

The HYSPLIT-based Emissions Inverse Modeling System for wildfire (HEIMS-fire) is an emission inverse modeling system to estimate wildfire smoke source strength, vertical distribution, and temporal variations by assimilating satellite observations with the HYSPLIT dispersion model for smoke forecasting. This system defines a cost function to quantify the differences between the satellite smoke products and their model counterparts, weighted by the model and observation uncertainties. Smoke sources that minimize this cost function provide the optimal smoke emission estimates. This system has been successfully applied to hindcast smoke distribution during a Southeast US wildfire event in 2016 using GOES GASP products. A new Advanced Baseline Imager (ABI) sensor onboard GOES-16 has become fully operational since December 2017. The ABI smoke products have better spatial and temporal resolutions than those from its predecessors. In this study, the HEIMS-fire inverse modeling system is updated to assimilate the ABI observations. A case study for the 2018 Camp Fire event in California USA is presented. Comparison with other biomass burning emission estimates will be conducted. Hindcasts using the estimated emissions by the HEIMS-fire system are also presented.