The importance of fire–atmosphere coupling and boundary-layer turbulence to wildfire spread
Ruiyu Sun A D , Steven K. Krueger A , Mary Ann Jenkins B , Michael A. Zulauf A and Joseph J. Charney CA Department of Meteorology, University of Utah, Salt Lake City, UT 84112-0110, USA.
B Department of Earth and Space Science and Engineering, Faculty of Pure and Applied Science, York University, Toronto, ON, M3J 1P3, Canada.
C United States Forest Service, North Central Research Station, East Landsing, MI, USA.
D Corresponding author. Email: ruiyu.sun@noaa.gov
International Journal of Wildland Fire 18(1) 50-60 https://doi.org/10.1071/WF07072
Submitted: 18 May 2007 Accepted: 26 March 2008 Published: 17 February 2009
Abstract
The major source of uncertainty in wildfire behavior prediction is the transient behavior of wildfire due to changes in flow in the fire’s environment. The changes in flow are dominated by two factors. The first is the interaction or ‘coupling’ between the fire and the fire-induced flow. The second is the interaction or ‘coupling’ between the fire and the ambient flow driven by turbulence due to wind gustiness and eddies in the atmospheric boundary layer (ABL). In the present study, coupled wildfire–atmosphere large-eddy simulations of grassland fires are used to examine the differences in the rate of spread and area burnt by grass fires in two types of ABL, a buoyancy-dominated ABL and a roll-dominated ABL. The simulations show how a buoyancy-dominated ABL affects fire spread, how a roll-dominated ABL affects fire spread, and how fire lines interact with these two different ABL flow types. The simulations also show how important are fire–atmosphere couplings or fire-induced circulations to fire line spread compared with the direct impact of the turbulence in the two different ABLs. The results have implications for operational wildfire behavior prediction. Ultimately, it will be important to use techniques that include an estimate of uncertainty in wildfire behavior forecasts.
Additional keywords: atmospheric boundary layer, coupled atmosphere–wildfire numerical model, fire-induced convection, grassland fire, probabilistic wildfire prediction, rate of fire spread.
Acknowledgements
The present research was supported by the United States Department of Agriculture Forest Service Research Joint Venture Agreement 03-JV-11231300 08. A gratis grant of computer time from the Center for High Performance Computing, University of Utah, is gratefully acknowledged. We thank three anonymous reviewers for suggestions on how to improve a previous version of the paper. The first author would like to thank Dr Chin-Hoh Moeng, Dr Peter Sullivan, Dr Margaret LeMone, and Dr Tammy Weckworth for their useful discussions about the simulation results.
Albini FA (1982) Response of free-burning fires to non-steady wind. Combustion Science and Technology 29, 225–241.
| Crossref | GoogleScholarGoogle Scholar |
Anderson DH, Catchpole EA, de Mestre NJ , Parkes T (1982) Modelling the spread of grass fires. Journal of the Australian Mathematical Society Series B – Applied Mathematics 23, 451–466.
Cheney NP , Gould JS (1995) Fire growth in grassland fuels. International Journal of Wildland Fire 5(4), 237–247.
| Crossref | GoogleScholarGoogle Scholar |
Fons WL (1946) Analysis of fire spread in light forest fuels. Journal of Agricultural Research 72(3), 93–121.
Jenkins MA (2002) An examination of the sensitivity of numerically simulated wildfires to low-level atmospheric stability and moisture, and the consequences for the Haines Index. International Journal of Wildland Fire 11(4), 213–232.
| Crossref | GoogleScholarGoogle Scholar |
Mell W, Jenkins MA, Gould J , Cheney P (2007) A physically based approach to modelling grassland fires. International Journal of Wildland Fire 16, 1–22.
| Crossref | GoogleScholarGoogle Scholar |
Pitts WM (1991) Wind effects on fires. Progress in Energy and Combustion Science 17, 83–134.
| Crossref | GoogleScholarGoogle Scholar |
Stevens DE , Bretherton CS (1996) A forward-in-time advection scheme and adaptive multilevel flow solver for nearly incompressible atmospheric flow. Journal of Computational Physics 129, 284–295.
| Crossref | GoogleScholarGoogle Scholar |
Sun R, Jenkins MA, Krueger SK , Charney J (2006) An evaluation of fire plume properties simulated with the FDS and Clark coupled wildfire model. Canadian Journal of Forest Research 36, 2894–2908.
| Crossref | GoogleScholarGoogle Scholar |