Recent increases in the frequency and extent of wildland fires assert a critical need for improved forecast of fire-weather models as an essential element of mitigating the risks to public health,…

Recent increases in the frequency and extent of wildland fires assert a critical need for improved forecast of fire-weather models as an essential element of mitigating the risks to public health, civil infrastructure, and terrestrial ecosystem function. Despite advances in the spatial resolution and data assimilation capabilities of noaas rapid refresh forecast system (rrfs; next generation regional version of the unified forecast system (UFS)), such advances are yet to be complemented with model development towards improved physical parameterization of coupling between the fire, atmospheric boundary-layer (ABL) turbulence emission rates, and vegetation structure, all of which are sub-grid scale processes at the current 3-KM model resolution. The absence of this fire-ABL feedback leads to the model of deficiencies including: 1) limited influence of fire-induced secondary flows associated with convective heat and moisture exchange between the fire and ambient air on fire rate of spread and ABL mixing; and 2) biased estimates of fire emission rates resulting in inaccurate predictions of fire plume dynamics and downwind air quality impacts.