Uncertainties in modeling smoke impacts from wildland fire

Smoke model predictions increasingly are being used for land management and fire management decision support work. Inherent in such projections are significant model parameterizations, process unknowns, empirical fits, and grid scale issues involved in the underlying models utilized in creating smoke predictions. To understand where the most significant issues lie, recent work through the Smoke and Emissions Model Intercomparison Project has focused on quantifying variability and uncertainty in model choices at each modeling step using a succession of test cases. Variations between different fire reporting systems, fuel loading maps, fire consumption models, fire emissions factors, plume rise algorithms, meteorological models, and smoke transport and dispersion models have been found to have significant impacts on the final calculated smoke impacts. We cross compare these results to determine the biggest remaining uncertainties and issues in creating accurate smoke impact predictions.