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Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

Turbulent kinetic energy during wildfires in the north central and north-eastern US

Warren E. Heilman A B and Xindi Bian A
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- Author Affiliations

A 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.


References


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 | de Arellano JVG, Vellinga OS, Holtlag AAM, Bosveld FC, Baltink HK (2001) Observational evaluation of PBL parameterizations modeled by MM5. In ‘Proceedings of the 11th PSU/NCAR Mesoscale Model User’s Workshop’, 25–27 June 2001, Boulder, CO. pp. 102–104. (National Center for Atmospheric Research: Boulder, CO)

Ferguson SA, McKay S, Nagel D, Piepho T, Rorig M, Anderson C (2001) The potential for smoke to ventilate from wildland fires in the United States. In ‘Fourth Symposium on Fire and Forest Meteorology’, 12–15 November 2001, Reno, NV. (American Meteorological Society: Boston, MA) Available at http://ams.confex.com/ams/4FIRE/techprogram/meeting_4FIRE.htm [Verified 13 March 2010]

Fosberg MA (1978) Weather in wildland fire management: the fire weather index. In ‘Proceedings of the Conference on Sierra Nevada Meteorology’, 19–21 June 1978, Lake Tahoe, CA. pp. 1–4. (American Meteorological Society: Boston, MA)

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 | Grell GA, Dudhia J, Stauffer DR (1994) A description of the fifth-generation Penn State/NCAR mesoscale model (MM5). National Center for Atmospheric Research, NCAR Technical Note NCAR/TN-398+STR. (Boulder, CO)

Haines DA (1988) A lower atmospheric severity index for wildland fires. National Weather Digest  13, 23–27.
Heilman WE, Bian X (2007) Combining turbulent kinetic energy and Haines Index predictions for fire-weather assessments. In ‘Proceedings of the 2nd Fire Behavior and Fuels Conference’, 26–30 March 2007, Destin, FL. (Eds BW Butler, W Cook) USDA Forest Service, Rocky Mountain Research Station, Proceedings RMRS-P-46CD, pp. 159–172. (Fort Collins, CO)

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 | Potter BE, Heilman WE (2001) Atmospheric research needs and issues. In ‘Northern Minnesota Independence Day Storm: a Research Needs Assessment’. (Eds WJ Mattson, DS Shriner) USDA Forest Service, North Central Research Station, General Technical Report NC-216, pp. 9–11. (Saint Paul, MN)

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 | Stull RB (1988) ‘An Introduction to Boundary Layer Meteorology.’ (Kluwer Academic Publishers: Dordrecht, the Netherlands)

Sun R, Krueger SK, Zulauf MA, Jenkins MA, Charney JJ (2006) Wildfire evolution in the convective boundary layer. In ‘Proceedings of the 17th Symposium on Boundary Layers and Turbulence’, 21–25 May 2006, San Diego, CA. (American Meteorological Society: Boston, MA)

US Air Force (2007) United States Air Force Aircraft Accident Investigation Board Report. (New Jersey Air National Guard: Atlantic City International Airport, NJ)

USDA Forest Service (2002) National Fire Plan research and development – 2001 business summary. USDA Forest Service, North Central Research Station. (Saint Paul, MN)

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 |