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Optimizing Smoke and Plume Rise Modeling Approaches at Local Scales

Department of Atmospheric Sciences, University of Utah, Salt Lake City, UT 84112, USA
Missoula Fire Science Laboratory, U.S. Forest Service, Missoula, MT 59808, USA
Author to whom correspondence should be addressed.
Atmosphere 2018, 9(5), 166;
Received: 9 April 2018 / Revised: 23 April 2018 / Accepted: 25 April 2018 / Published: 1 May 2018
(This article belongs to the Special Issue Fire and the Atmosphere)
Heating from wildfires adds buoyancy to the overlying air, often producing plumes that vertically distribute fire emissions throughout the atmospheric column over the fire. The height of the rising wildfire plume is a complex function of the size of the wildfire, fire heat flux, plume geometry, and atmospheric conditions, which can make simulating plume rises difficult with coarser-scale atmospheric models. To determine the altitude of fire emission injection, several plume rise parameterizations have been developed in an effort estimate the height of the wildfire plume rise. Previous work has indicated the performance of these plume rise parameterizations has generally been mixed when validated against satellite observations. However, it is often difficult to evaluate the performance of plume rise parameterizations due to the significant uncertainties associated with fire input parameters such as fire heat fluxes and area. In order to reduce the uncertainties of fire input parameters, we applied an atmospheric modeling framework with different plume rise parameterizations to a well constrained prescribed burn, as part of the RxCADRE field experiment. Initial results found that the model was unable to reasonably replicate downwind smoke for cases when fire emissions were emitted at the surface and released at the top of the plume. However, when fire emissions were distributed below the plume top following a Gaussian distribution, model results were significantly improved. View Full-Text
Keywords: smoke modeling; fires; fire plume rise; atmospheric modeling smoke modeling; fires; fire plume rise; atmospheric modeling
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MDPI and ACS Style

Mallia, D.V.; Kochanski, A.K.; Urbanski, S.P.; Lin, J.C. Optimizing Smoke and Plume Rise Modeling Approaches at Local Scales. Atmosphere 2018, 9, 166.

AMA Style

Mallia DV, Kochanski AK, Urbanski SP, Lin JC. Optimizing Smoke and Plume Rise Modeling Approaches at Local Scales. Atmosphere. 2018; 9(5):166.

Chicago/Turabian Style

Mallia, Derek V., Adam K. Kochanski, Shawn P. Urbanski, and John C. Lin. 2018. "Optimizing Smoke and Plume Rise Modeling Approaches at Local Scales" Atmosphere 9, no. 5: 166.

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