Assimilation of Doppler Radial Velocity Measurements of Biomass Burning Debris into the Warn-on-Forecast System

Forecasting the impacts of wildfires has taken on more importance in recent years due to their increased frequency and significant human impacts. Wildfires often generate large smoke plumes which can loft aerosols deep into the atmosphere, which are then transported far downstream by the prevailing environment. Convection allowing models such as the HRRR-Smoke currently forecast the evolution of smoke plumes, but many uncertainties in these forecasts remain. A smoke enabled version of the Warn-on-Forecast System (WoFS) has been developed to combine the existing smoke injection algorithms into a short-term (0 – 6-h) probabilistic forecast system. WoFS cycles at 15 minute intervals, allowing for continuous updates of rapidly changing wildfire characteristics derived from geostationary satellite data. However, neither system assimilates any observations associated with the actual smoke plume. Few real-time, high density observations of smoke aerosol concentrations are currently available. Precipitation radars, such as the WSR-88D, can detect biomass burning debris (BBD) lofted by wildfires. Smoke aerosols themselves are too small to be readily detectable from these radars, but the larger lofted debris are. Returned radar reflectivity and radial velocity provide an estimate on the spatial distribution of smoke and its movement within the environment. Radial velocity observations can be assimilated with minimal modifications to the existing system. This work explores the impact of assimilating radial velocity observations of BBD for three large wildfires in 2024. Assimilating these data has a large impact on the forecast smoke plume characteristics. Comparisons of forecast smoke with visible satellite imagery and radar reflectivity shows that the forecasted spatial extent of wildfire smoke is improved.