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Jeanne L. Hoadley, Ken Westrick, Sue A. Ferguson, Scott L. Goodrick, Larry Bradshaw, and Paul Werth


Previous studies of model performance at varying resolutions have focused on winter storms or isolated convective events. Little attention has been given to the static high pressure situations that may lead to severe wildfire outbreaks. This study focuses on such an event so as to evaluate the value of increased model resolution for prediction of fire danger. The results are intended to lay the groundwork for using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) as input to the National Fire Danger Rating System to provide gridded predictions of fire danger indices. Predicted weather parameters were derived from MM5 and evaluated at three different resolutions (36, 12, and 4 km). Model output was compared with observations during the 2000 fire season in western Montana and northern Idaho to help to determine the model's skill in predicting fire danger. For application in fire danger rating, little significant improvement was found in skill with increased model resolution using standard forecast verification techniques. Diurnal bias of modeled temperature and relative humidity resulted in errors larger than the differences between resolutions. Significant timing and magnitude errors at all resolutions could jeopardize accurate prediction of fire danger.

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Craig B. Clements, Shiyuan Zhong, Scott Goodrick, Ju Li, Brian E. Potter, Xindi Bian, Warren E. Heilman, Joseph J. Charney, Ryan Perna, Meongdo Jang, Daegyun Lee, Monica Patel, Susan Street, and Glenn Aumann

Grass fires, although not as intense as forest fires, present a major threat to life and property during periods of drought in the Great Plains of the United States. Recently, major wildland grass fires in Texas burned nearly 1.6 million acres and destroyed over 730 homes and 1320 other buildings. The fires resulted in the death of 19 people, an estimated loss of 10,000 head of livestock, and more than $628 million in damage, making the 2005/06 fire season the worst on record for the state of Texas.

As an aid to fire management, various models have been developed to describe fire behavior. However, these models strongly emphasize fuels and fail to adequately consider the role of convective dynamics within the atmosphere and its interaction with the fire due to the lack of observational data. To fill this gap, an intensive field measurement campaign called FireFlux was conducted during February 2006 near Houston, Texas. The campaign employed a variety of instrument platforms to collect turbulence data at multiple levels within and immediately downwind of a 155 acre tall-grass prairie burn unit. This paper presents some first-time observations of atmospheric turbulent structures/fluxes associated with intense grass fires and provides a basis to further our understanding of the dynamics of grass fires and their interactions with the atmosphere.

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