Evaluate state-of-the art fine-scale atmospheric dispersion modeling systems using existing data sets from previous prescribed fires and new data sets to be collected during prescribed fires in the New Jersey Pine Barrens and in the North Carolina Calloway Forest/Sandhills Preserve.
Develop a modeling system for use in predictions of smoke from low-intensity fires by modifying the model and taking advantage of the existing modules for fire information, fuel loading, consumption, smoke emissions, user interface, and display.
Validate the modeling system using field observations to understand the performance of the models for a variety of fire types, environmental settings, and atmospheric conditions.
Develop web-based, user friendly smoke management decision supporting tools that are based on a solid understanding of the errors and uncertainties of the model predictions.
In achieving these objectives, a number of science questions will be answered, including:
What are the effects of forest canopies on smoke transport and dispersion?
What role do near-surface circulations play in the dispersion and transport of smoke from low-intensity fires?
What are the uncertainties and limitations of current models in predicting smoke dispersion from low-intensity fires?
What data sets are necessary for effective model validation?