Janice Coen is a Scientist VI in the Mesoscale and Microscale Meteorology Laboratory, where her research focuses on the dynamics and prediction of wildland fires, with particular emphasis on two-way coupling between fires and the atmosphere.
Her work centers on the CAWFE coupled weather–wildland fire model , which links a microscale numerical weather prediction model (hundreds to thousands of meters grid spacing) with a wildland fire behavior and fuel consumption module. This framework enables explicit simulation of fire-induced winds, plume dynamics, fire phenomena, and feedbacks that control wildfire spread rate and direction.
Complementary observational studies use high-resolution thermal infrared imagery to analyze combustion-zone structure and motion. These data reveal the organization and variability of flow within and near the fire line, providing insight into processes such as fire-induced inflow, convective bursts, fire whirls, fingering of the fire front, and forward-projecting flame structures that pose significant hazards to firefighters.
Together, modeling and infrared analyses are used to investigate how fires generate their own weather and why fire behavior often organizes along sharp interfaces between burning and unburned fuel. While the initial focus of this work was on understanding fundamental fire–atmosphere interactions, more recent efforts have applied CAWFE to reproduce major historical wildfire events; forecast fire expansion, transient behavior, and phenomena; and communicate probabilistic predictions through ensembles.
These case studies, combined with infrared observations, have been used in collaborative research to examine fatality incidents and improve firefighter safety. Current work includes the assimilation of active fire detection data from satellites, aircraft, and uncrewed aerial systems to better constrain modeled fire growth.
These capabilities are now being applied in pre-operational and applied settings to anticipate wind extremes associated with ignition and early fire growth in recent wind-driven California fire events, and to support wildfire behavior forecasting.
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