Surface-layer turbulence associated with a fast spreading grass fire

Abstract

A wildland fire experiment was conducted on a 40-ha tall grass prairie in Texas to study fire-atmosphere interactions. The experiment coincided with a Red Flag Warning, signifying specific weather conditions associated with an elevated risk of wildfire ignition and rapid spread. This provided a rare opportunity to observe wildland fire behavior and its impact on atmospheric flows under conditions deliberately avoided in similar experiments. This study analyzed the high frequency meteorological data collected during the experiment using threedimensional sonic anemometers mounted on a 43-m tower (at 5.8, 10 and 20 m) and on three 10-m towers (at 5.3 m) within the burn block. The tower placements were carefully chosen to capture the impact of both head and flank fires on the mean and turbulent flows. The hypothesis is that fire-induced perturbations in the lower atmosphere, quantified through parameters like turbulent kinetic energy (TKE) and vertical fluxes, would be substantially stronger than those observed in similar wildland fires under less fire-prone atmospheric conditions. While this hypothesis was validated for heat flux and TKE, it did not hold for momentum fluxes or friction velocity. Additionally, the observations failed to confirm the hypothesis that head fires would produce more intense perturbations than flank fires. Given the homogeneity of fuel, terrain and meteorological elements across the burn unit, this underscores the challenge of disentangling the effects of fire type from other natural factors in a real-world setting. Nevertheless, the finding holds promise for improving turbulence parameterizations in firebehavior and smoke dispersion models.

Citation

Zhong, Shiyuan; Gonzalez-Fuentes, Melissa; Clements, Craig B.; Bian, Xindi; Heilman, Warren E.; Charney, Joseph J.; Valero, Mario M.; Kochanski, Adam K.; Kiefer, Michael T. 2024. Surface-layer turbulence associated with a fast spreading grass fire. Agricultural and Forest Meteorology. 350: 110000. 14 p. https://doi.org/10.1016/j.agrformet.2024.110000.