×

Fire-spotting generated fires. I: The role of atmospheric stability. (English) Zbl 1481.86014

Summary: This is the first part of two papers concerning fire-spotting generated fires. In this part we deal with the impact of macroscale factors, such as the atmospheric stability, and in the second part we deal with mesoscale factors, such as the flame geometry. For this study we adopt an approach where the motion of the front is split into a drifting part and a fluctuating part. The drifting part, that can be provided by choosing an existing operational model, is here based on the level-set method in analogy with WRF-SFIRE model. The fluctuating part, that is the result of a comprehensive statistical description of the physics of the system and includes the random effects, is here physically parametrized to include turbulent hot-air transport and firebrand landing distance. In order to highlight the net effects of the random contributions due to turbulence and firebrand flying, a simplified model without fire-atmosphere coupling is considered. Numerical simulations show that the atmospheric stability is an important factor for wildfire propagation. In particular, unstable conditions boost the number of fire-spotting generated fires at small elapsed times as well as the strength of turbulence leading to rapid merging and the formation of unburned islands surrounded by the fire. Stability conditions have then an effect on the risk and the management associated to fire-spotting generated fires. In fact, with stable conditions (corresponding for example to the night-time) the turbulence is not strong enough to merge the fires and, at large elapsed times, this results into a higher number of independent fires but lower burned area with respect to unstable conditions (corresponding for example to the day-time) when the push of turbulence leads to faster merging resulting into a lower number of independent fires but higher burned area. Finally, with stable conditions less fire fronts need to be managed at short time, but more fire fronts need to be managed than with unstable conditions that however show a higher risk because of the merging of independent fires.

MSC:

86A10 Meteorology and atmospheric physics
76E20 Stability and instability of geophysical and astrophysical flows
PDFBibTeX XMLCite
Full Text: DOI

References:

[1] Bowman, D. M.J. S.; Balch, J. K.; Artaxo, P.; Bond, W. J.; Carlson, J. M.; Cochrane, M. A.; D’Antonio, C. M.; DeFries, R. S.; Doyle, J. C.; Harrison, S. P.; Johnston, F. H.; Keeley, J. E.; Krawchuk, M. A.; Kull, C. A.; Marston, J. B.; Moritz, M. A.; Prentice, I. C.; Roos, C. I.; Scott, A. C.; Swetnam, T. W.; van der Werf, G. R.; Pyne, S. J., Fire in the earth system, Science, 324, 5926, 481-484 (2009)
[2] 72 pages, CODEN: NSPUE2, doi:10.6028/NIST.SP.1215.
[3] Sullivan, A. L., Inside the inferno: fundamental processes of wildland fire behaviour. Part 1: combustion chemistry and heat release, Curr. For. Rep., 3, 132-149 (2017)
[4] Sullivan, A. L., Inside the inferno: fundamental processes of wildland fire behaviour. Part 2: heat transfer and interaction, Curr. For. Rep., 3, 150-171 (2017)
[5] Fernandez-Pello, A. C., Wildland fire spot ignition by sparks and firebrands, Fire Saf. J., 91, 2-10 (2017)
[6] Pagnini, G.; Mentrelli, A., Modelling wildland fire propagation by tracking random fronts, Nat. Hazards Earth Syst. Sci., 14, 8, 2249-2263 (2014)
[7] Kaur, I.; Mentrelli, A.; Bosseur, F.; Filippi, J.-B.; Pagnini, G., Turbulence and fire-spotting effects into wild-land fire simulators, Commun. Nonlinear Sci. Numer. Simul., 39, 300-320 (2016) · Zbl 1461.76367
[8] Sethian, J. A.; Smereka, P., Level set methods for fluid interfaces, Annu. Rev. Fluid Mech., 35, 341-372 (2003) · Zbl 1041.76057
[9] Mallet, V.; Keyes, D.; Fendell, F., Modeling wildland fire propagation with level set methods, Comput. Math. Appl., 57, 7, 1089-1101 (2009) · Zbl 1186.65140
[10] Mandel, J.; Beezley, J. D.; Kochanski, A. K., Coupled atmosphere-wildland fire modeling with WRF 3.3 and SFIRE 2011, Geosci. Model. Dev., 4, 591-610 (2011)
[11] Tarifa, C.; del Notario, P.; Moreno, F., On flight paths and lifetimes of burning particles of wood, Proceedings of the Tenth Symposium on Combustion, 1721 August 1964, Cambridge, UK, 1021-1037 (1965), The Combustion Institute: Pittsburgh, PA
[12] Albini, F. A., Spot fire distance from burning trees: a predictive model, Technical Report (1979), U.S. Department of Agriculture Forest Service Intermountain Forest and Range Experiment Station
[13] Albini, F. A., Potential spotting distance from wind-driven surface fires, Research Paper (1983), U.S. Department of Agriculture Forest Service Intermountain Forest and Range Experiment Station
[14] Finney, M., FARSITE: fire area simulator-model development and evaluation, Research Paper (1998), USDA Forest Service, Rocky Mountain Research Station: USDA Forest Service, Rocky Mountain Research Station Ogden, Utah
[15] Tymstra, C.; Bryce, R.; Wotton, B.; Taylor, S.; Armitage, O., Development and structure of Prometheus: the Canadian wild land fire growth simulation model, Information Report (2010), Canadian Forest Service, Northern Forestry Centre
[16] Wang, H. H., Analysis on downwind distribution of firebrands sourced from a wildland fire, Fire Technol., 47, 321-340 (2011)
[17] Sardoy, N.; Consalvi, J. L.; Porterie, B.; Fernandez-Pello, A. C., Modeling transport and combustion of firebrands from burning trees, Combust. Flame, 150, 151-169 (2007)
[18] Sardoy, N.; Consalvi, J.; Kaiss, A.; Fernandez-Pello, A.; Porterie, B., Numerical study of ground-level distribution of firebrands generated by line fires, Combust. Flame, 154, 3, 478-488 (2008)
[19] Tohidi, A.; Kaye, N.; Bridges, W., Statistical description of firebrand size and shape distribution from coniferous trees for use in Monte Carlo simulations of firebrand flight distance, Fire Saf. J., 77, 21-35 (2015)
[20] Tohidi, A.; Kaye, N. B., Stochastic modeling of firebrand shower scenarios, Fire Saf. J., 91, 91-102 (2017)
[21] Martin, J.; Hillen, T., The spotting distribution of wildfires, Appl. Sci., 6, 177, 1-34 (2016)
[22] Kaur, I.; Pagnini, G., Fire-spotting modelling and parametrisation for wild-land fires, (Sauvage, S.; Sánchez-Pérez, J. M.; Rizzoli, A. E., Proceedings of the Eighth International Congress on Environmental Modelling and Software (iEMSs); Toulouse, France, 10-14 July (2016)), 384-391
[23] Sofiev, M.; Ermakova, T.; Vankevich, R., Evaluation of the smoke-injection height from wild-land fires using remote-sensing data, Atmos. Chem. Phys., 12, 4, 1995-2006 (2012)
[24] Alexander, M. E., Calculating and interpreting forest fire intensities, Can. J. Bot., 60, 349-357 (1982)
[25] Himoto, K.; Tanaka, T., Transport of disk-shaped firebrands in a turbulent boundary layer, (Gottuk, D.; Lattimer, B., Proceedings of the Eighth International Symposium on Fire Safety Science, 18-23 September, Beijing, China (2005)), 433-444
[26] Wang, H.-H., Analysis on downwind distribution of firebrands sourced from a wildland fire, Fire Technol., 47, 2, 321-340 (2011)
[27] Stull, R. B., An Introduction to Boundary Layer Meteorology (1988), Kluwer Academic Publishers · Zbl 0752.76001
[28] Dupuy, J. L.; Marechal, J.; Portier, D.; Morvan, D., Fires from a cylindrical forest fuel burner: combustion dynamics and flame properties, Combust. Flame, 135, 2029-2036 (2003)
[29] Mphale, K.; Heron, M., Microwave measurement of electron density and collision frequency of a pine fire, J. Phys. D Appl. Phys., 40, 2818-2825 (2007)
[30] Niemela, J. J.; Skrbek, L.; Sreenivasan, K. R.; Donnelly, R. J., Turbulent convection at very high Rayleigh numbers, Nature, 404, 837-840 (2000)
[31] Niemela, J. J.; Sreenivasan, K. R., Turbulent convection at high Rayleigh numbers and aspect ratio 4, J. Fluid Mech., 557, 411-422 (2006) · Zbl 1093.76515
[32] Wu, X.-Z.; Libchaber, A., Scaling relations in thermal turbulence: the aspect-ratio dependence, Phys. Rev. A, 45, 842-845 (1992)
[33] Rehm, R. G.; McDermott, R. J., Fire-front propagation using the level set method, Technical note (2009), National Institute of Standard Technology
[34] ISBN 978-88-904409-7-7.
[35] Revised version: August 2014, available at: http://publications.crs4.it/pubdocs/2012/PM12a/pagnini_massidda-levelset.pdf and arXiv:1408.6129.
[36] Shiryaev, A. N., Probability-1, Graduate Texts in Mathematics (2016), Springer · Zbl 1390.60002
[37] McGrath-Spangler, E. L.; Molod, A., Comparison of GEOS-5 AGCM planetary boundary layer depths computed with various definitions, Atmos. Chem. Phys., 14, 13, 6717-6727 (2014)
[38] Wilson, J. D., Trajectory models for heavy particles in atmospheric turbulence: comparison with observations, J. Appl. Meteor., 39, 1894-1912 (2000)
[39] Bouvet, T.; Wilson, J. D.; Tuzet, A., Observations and modeling of heavy particle deposition in a windbreak flow, J. Appl. Meteorol. Climatol., 45, 1332-1349 (2006)
[40] K.T. Chu, M. Prodanović, Level set method library (LSMLIB)(2009). http://ktchu.serendipityresearch.org/software/lsmlib/.
[41] https://www.frames.gov/catalog/935.
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.