An Analysis of Vertical Plume Extent Forecasted with the WRFx System and WRF-SFIRE using MISR Plume Height Data

Wildland fire emissions pose a great risk to human health. Depending on plume top height, the height at which smoke is injected into the atmosphere, emissions may either undergo long-range transport and impact air quality on a regional scale in the instance of high plume heights, or in the instance of lower plumes emissions may travel shorter distances and impact air quality on a local scale. In order to effectively inform the public of smoke-related risks it is vital that the tools used to forecast air quality impacts of smoke realistically capture the smoke production, plume rise, and smoke dispersion. Classic air quality systems leverage satellite observations of air quality and project them to the future to generate an estimate of future emissions. These emission estimates along with the weather forecast (used to compute the smoke dispersion), and a plume rise parametrization used to estimate the vertical smoke extent, enable the prediction of smoke concentrations. However, this method may not be valid when fire activity changes rapidly due to weather conditions or heterogeneity in fuel characteristics.

Therefore, in this work, an alternative approach is evaluated, in which a coupled fire atmosphere model (WRF-SFIRE) is used to forecast fire behavior, fire emissions, plume rise, and smoke dispersion in an integrated system. WRF-SFIRE is a coupled fire-atmosphere model which consists of the WRF weather model coupled with the semi-empirical fire-spread model SFIRE. For each time step, the atmospheric component of the model drives fire propagation providing weather information to the integrated fuel moisture model and the fire model. The fire model resolves the fire propagation and estimates the fire heat and emission fluxes that are injected into the atmosphere. Therefore, the fire behavior driven by local winds and fuel moisture is dynamically linked to the plume dynamics and fire emissions, allowing the model to explicitly resolve plume rise. The coupled nature of this system, however, means that errors in the forecasted weather, fuel moisture, or fire progression can potentially degrade the overall quality of the smoke forecast. Specifically, errors in vertical smoke distribution can lead to unrealistic smoke transport and inaccurate predictions of smoke concentrations. Therefore, it is critical to assess whether an operational coupled fire-atmosphere model, like WRF-SFIRE, can provide realistic vertical smoke extent, when run in an operational 12h forecast cycle, including periodic assimilation of fire information.

The goal of this work is to assess to what degree coupled fire-atmosphere forecasts executed cyclically by assimilating fire observations can realistically forecast the vertical extent of smoke columns. To accomplish this goal, WRF-SFIRE output is compared to smoke heights from NASA’s Multi-angle Imaging SpectroRadiometer (MISR). The performance of WRF-SFIRE is analyzed, and errors in predicting the vertical plume extent are quantified for operational forecasts executed for selected California fires during the 2021 fire season. The presented work is one of the first attempts to rigorously validate the forecasting capability of a coupled fire-atmosphere model leveraging assimilation of fire observations, in the context of vertical plume extent, which is critical for the smoke transport forecasting, and potential adaptation of coupled models into air quality applications.