Skillful forecasts of weather phenomena in numerical models begin with the most accurate set of initial conditions achievable from observational datasets. The process of combining observations with numerical model predictions is called data assimilation. This chapter describes the types of observations available for data assimilation in models that predict the transport, fate, and impacts of smoke pollution. Observation properties needed for effective data assimilation are identified based on experiences with a variety of observation types in data assimilation experiments, compiled from the published literature. The second half of the chapter surveys the data assimilation methodologies that have been applied to smoke aerosols, and describes specific problems associated with the smoke observations that require innovative techniques in data assimilation. The chapter concludes by providing an outlook for future research and development in data assimilation for smoke prediction models. Data assimilation for prediction of smoke is an emerging area of development that promises to greatly improve forecast skill as new datasets and techniques are applied.

Naturally occurring ozone rich Stratosphere-to-Troposphere Transport (STT) intrusions and biomass burning (BB) plumes reaching the surface can contribute to exceedances of the U.S. National Ambient Air Quality Standards for ground-level ozone (70 ppbv implemented in 2015). Additionally, fires can inject significant pollution into the free troposphere where it can be transported long distances. The combined air quality impacts from these sources on ozone has only been analyzed in a few case studies for the Midwest U.S. Here we study ozone impacts in a Midwestern city, for the first time in St. Louis, Missouri, using a series of ozonesonde profiles taken during the SEAC4RS (Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) field campaign in August-September 2013. All ozonesondes showed enhancements above the background profile levels (~55 ppbv) throughout each tropospheric column. Two models were used to estimate ozone origins in columns. A chemical transport model identified STT enhancements equivalent to 10 to 15 ppbv over the background with a 10 to 15% contribution overall to the column. Two FLEXPART-WRF simulations, one with smoke in the boundary layer and another with smoke above, identified BB enhancements equivalent to 10 to 80 ppbv. Overall, the total BB contribution is 15 to 30% of the total column. Five ozonesondes showed signatures of mixed BB plumes and STT intrusions. During this study period, BB in the western U.S. contributed 70% to ozone enhancements in the total column compared to 3% from the central U.S and 27% from other areas.