A coupled atmospheric/wildfire behavior model is described that utilizes physics-based process models to represent wildfire behavior. Five simulations are presented, four of which are highly idealized situations that are meant to illustrate some of the dependencies of the model on environmental conditions. The fifth simulation consists of a fire burning in complex terrain with non-homogeneous vegetation and realistic meteorological conditions. The simulated fire behavior develops out of the coupling of a set of very complex processes and not from prescribed rules based on empirical data. This represents a new direction in wildfire modeling that we believe will eventually help decision makers and land managers do their jobs more effectively.

Multiscale modeling of a diurnal cycle of real‐world conditions is presented for the first time, validated using data from the CWEX‐13 field experiment. Dynamical downscaling from synoptic‐scale down to resolved three‐dimensional eddies in the atmospheric boundary layer (ABL) was performed, spanning 4 orders of magnitude in horizontal grid resolution: from 111 km down to 8.2 m (30 m) in stable (convective) conditions. Computationally efficient mesoscale‐to‐microscale transition was made possible by the generalized cell perturbation method with time‐varying parameters derived from mesoscale forcing conditions, which substantially reduced the fetch to achieve fully developed turbulence. In addition, careful design of the simulations was made to inhibit the presence of under‐resolved convection at convection‐resolving mesoscale resolution and to ensure proper turbulence representation in stably‐stratified conditions. Comparison to in situ wind‐profiling lidar and near‐surface sonic anemometer measurements demonstrated the ability to reproduce the ABL structure throughout the entire diurnal cycle with a high degree of fidelity. The multiscale simulations exhibit realistic atmospheric features such as convective rolls and global intermittency. Also, the diurnal evolution of turbulence was accurately simulated, with probability density functions of resolved turbulent velocity fluctuations nearly identical to the lidar measurements. Explicit representation of turbulence in the stably‐stratified ABL was found to provide the right balance with larger scales, resulting in the development of intra‐hour variability as observed by the wind lidar; this variability was not captured by the mesoscale model. Moreover, multiscale simulations improved mean ABL characteristics such as horizontal velocity, vertical wind shear, and turbulence.

The Fire and Smoke Model Evaluation Experiment (FASMEE) is designed to collect integrated observations from large wildland fires and provide evaluation datasets for new models and operational systems. Wildland fire, smoke dispersion, and atmospheric chemistry models have become more sophisticated, and next-generation operational models will require evaluation datasets that are coordinated and comprehensive for their evaluation and advancement. Integrated measurements are required, including ground-based observations of fuels and fire behavior, estimates of fire-emitted heat and emissions fluxes, and observations of near-source micrometeorology, plume properties, smoke dispersion, and atmospheric chemistry. To address these requirements the FASMEE campaign design includes a study plan to guide the suite of required measurements in forested sites representative of many prescribed burning programs in the southeastern United States and increasingly common high-intensity fires in the western United States. Here we provide an overview of the proposed experiment and recommendations for key measurements. The FASMEE study provides a template for additional large-scale experimental campaigns to advance fire science and operational fire and smoke models.

Ten simulations were performed with the HIGRAD/FIRETEC wildfire behaviour model in order to explore its utility in studying wildfire behaviour in inhomogeneous topography. The goal of these simulations is to explore the potential extent of the coupling between the fire, atmosphere, and topography. The ten simulations described in this paper include five different topographies, each run with two different ambient wind speeds of 6 and 12 m s–1. The five topologies explored are: an idealised hill (which serves as the base centerline for the other topographies), two variations of the hill with lateral gradients downwind from the ignition line (one sloping up from the ‘hill’ at the centerline to form an upward sloping canyon parallel to the ambient wind, and the other sloping down from the centerline to form a ridge parallel to the ambient flow), one with a second hill upwind of the ignition line such that the fire is ignited in the bottom of a canyon that runs perpendicular to the ambient wind, and finally a flat terrain. The four non-trivial topographies have the same profile along the centerline downwind of the ignition line to help assess the impacts of topographic gradients that are perpendicular to the ambient wind. It is hoped that analysis of these simulations will help reveal where point-functional models are sufficient, where topographically modified wind fields are needed, and where fully coupled fire and transport models are necessary to properly describe wildfire behaviour.

In this text we describe an initial attempt to incorporate discrete porous element fuel beds into the coupled atmosphere–wildfire behavior model HIGRAD/FIRETEC. First we develop conceptual models for use in translating measured tree data (in this case a ponderosa pine forest) into discrete fuel elements. Then data collected at experimental sites near Flagstaff, Arizona are used to create a discontinuous canopy fuel representation in HIGRAD/FIRETEC. Four simulations are presented with different canopy and understory configurations as described in the text. The results are discussed in terms of the same two discrete locations within the canopy for each simulation. The canopy structure had significant effects on the balance between radiative and convective heating in driving the fire and indeed sometimes determined whether a specific tree burned or not. In our simulations the ground fuel density was the determining factor in the overall spread rate of the fire, even when the overstory was involved in the fire. This behavior is well known in the fire meteorology community. In the future, simulations of this type could help land managers to better understand the role of canopy and understory structure in determining fire behavior, and thus help them decide between the different thinning and fuel treatment strategies available to them.