Turbulent kinetic energy during wildfires in the north central and north-eastern US
Warren E. Heilman A B and Xindi Bian AA Northern Research Station, USDA Forest Service, East Lansing, MI 48823, USA.
B Corresponding author. Email: wheilman@fs.fed.us
International Journal of Wildland Fire 19(3) 346-363 https://doi.org/10.1071/WF08076
Submitted: 17 May 2008 Accepted: 30 July 2009 Published: 13 May 2010
Abstract
The suite of operational fire-weather indices available for assessing the atmospheric potential for extreme fire behaviour typically does not include indices that account for atmospheric boundary-layer turbulence or wind gustiness that can increase the erratic behaviour of fires. As a first step in testing the feasibility of using a quantitative measure of turbulence as a stand-alone fire-weather index or as a component of a fire-weather index, simulations of the spatial and temporal patterns of turbulent kinetic energy during major recent wildfire events in the western Great Lakes and north-eastern US regions were performed. Simulation results indicate that the larger wildfires in these regions of the US were associated with episodes of significant boundary-layer ambient turbulence. Case studies of the largest recent wildfires to occur in these regions indicate that the periods of most rapid fire growth were generally coincident with occurrences of the product of the Haines Index and near-surface turbulent kinetic energy exceeding a value of 15 m2 s–2, a threshold indicative of a highly turbulent boundary layer beneath unstable and dry atmospheric layers, which is a condition that can be conducive to erratic fire behaviour.
Acknowledgements
The authors thank Dr Kenneth Clark, USDA Forest Service, for providing observational turbulence data collected at the Silas Little Experimental Forest in New Jersey. Funding for this research was provided by the US National Fire Plan.
Byun D , Schere KL (2006) Review of the governing equations, computational algorithms, and other components of the Models-3 Community Multiscale Air Quality (CMAQ) Modeling System. Applied Mechanics Reviews 59, 51–77.
| Crossref | GoogleScholarGoogle Scholar |
Gerrity JP, Black TL , Treadon RE (1994) The numerical solution of the Mellor-Yamada level 2.5 turbulent kinetic energy equation in the Eta model. Monthly Weather Review 122, 1640–1646.
| Crossref | GoogleScholarGoogle Scholar |
Haines DA (1988) A lower atmospheric severity index for wildland fires. National Weather Digest 13, 23–27.
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, 213–232.
| Crossref | GoogleScholarGoogle Scholar |
Reisner J, Rasmussen RJ , Bruintjes RT (1998) Explicit forecasting of supercooled liquid water in winter storms using the MM5 mesoscale model. Quarterly Journal of the Royal Meteorological Society 124, 1071–1107.
| Crossref | GoogleScholarGoogle Scholar |
Zhong S , Fast J (2003) An evaluation of the MM5, RAMS, and Meso-Eta models at subkilometer resolution using VTMX field campaign data in the Salt Lake Valley. Monthly Weather Review 131, 1301–1322.
| Crossref | GoogleScholarGoogle Scholar |
Zhong S, In H-J, Bian X, Charney J, Heilman W , Potter B (2005) Evaluation of real-time high-resolution MM5 predictions over the Great Lakes region. Weather and Forecasting 20, 63–81.
| Crossref | GoogleScholarGoogle Scholar |
