Integrating wildfire plume rises within atmospheric transport models

Wildfires can generate significant pyro-convection that is responsible for releasing pollutants, greenhouse gases, and trace species into the free troposphere, which are then transported a significant distance downwind from the fire. Oftentimes, atmospheric transport and chemistry models have a difficult time resolving the transport of smoke from these wildfires, primarily due to deficiencies in estimating the plume injection height, which has been highlighted in previous work as the most important aspect of simulating wildfire plume transport. As a result of the uncertainties associated with modeled wildfire plume rise, researchers face difficulties modeling the impacts of wildfire smoke on air quality and constraining fire emissions using inverse modeling techniques. Currently, several plume rise parameterizations exist that are able to determine the injection height of fire emissions; however, the success of these parameterizations has been mixed. With the advent of WRF-SFIRE, the wildfire plume rise and injection height can now be explicitly calculated using a fire spread model (SFIRE) that is dynamically linked with the atmosphere simulated by WRF. However, this model has only been tested on a limited basis due to computational costs. Here, we will test the performance of WRF-SFIRE in addition to several commonly adopted plume parameterizations (Freitas, Sofiev, and Briggs) for the 2013 Patch Springs (Utah) and 2012 Baker Canyon (Washington) fires, for both of which observations of plume rise heights are available. These plume rise techniques will then be incorporated within a Lagrangian atmospheric transport model (STILT) in order to simulate CO and CO2 concentrations during NASA's CARVE Earth Science Airborne Program over Alaska during the summer of 2012. Initial model results showed that STILT model simulations were unable to reproduce enhanced CO concentrations produced by Alaskan fires observed during 2012. Near-surface concentrations were drastically overestimated while free tropospheric concentrations of CO were underestimated, likely a result of STILT injecting the fire emissions strictly into the PBL. We show in this study to what degree coupling the STILT model with an external plume rise model can help mitigate these problems.