• Anderson, H., 1982: Aids to determining fuel models for estimating fire behavior. USDA Forest Service, Intermountain Forest and Range Experiment Station General Tech. Rep. INT-122, 28 pp. [Available online at http://www.fs.fed.us/rm/pubs_int/int_gtr122.pdf.]

  • Baughman, R. G., , and F. A. Albini, 1980: Estimating midflame windspeeds. Proc. Sixth Conf. on Fire and Forest Meteorology, Seattle, WA, Society of American Foresters, 8892.

  • Beezley, J., , A. Kochanski, , V. Kondratenko, , J. Mandel, , and B. Sousedik, cited 2010: Simulation of the Meadow Creek fire using WRF-Fire. [Available online at http://www.openwfm.org/w/images/a/ae/Agu10_jb.pdf.]

  • Billing, P., , and R. Rawson, 1982: A fire tornado in the sunset country, January 1981. Victoria, Australia, Department of Conservation and Environment, Fire Management Branch Research Rep. 11, 12 pp.

  • Clark, T. L., , M. A. Jenkins, , J. Coen, , and D. Packham, 1996: A coupled atmosphere–fire model: Convective feedback on fire-line dynamics. J. Appl. Meteor., 35, 875901, doi:10.1175/1520-0450(1996)035<0875:ACAMCF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Clark, T. L., , J. Coen, , and D. Latham, 2004: Description of a coupled atmosphere–fire model. Int. J. Wildland Fire, 13, 4963, doi:10.1071/WF03043.

    • Search Google Scholar
    • Export Citation
  • Coen, J., 2005: Simulation of the Big Elk Fire using coupled atmosphere–fire modeling. Int. J. Wildland Fire, 14, 4959, doi:10.1071/WF04047.

    • Search Google Scholar
    • Export Citation
  • Coen, J., , and P. J. Riggan, 2014: Simulation and thermal imaging of the 2006 Esperanza Wildfire in southern California: Application of a coupled weather–wildland fire model. Int. J. Wildland Fire, 23, 755770, doi:10.1071/WF12194.

    • Search Google Scholar
    • Export Citation
  • Coen, J., , M. Cameron, , J. Michalakes, , E. Patton, , P. Riggan, , and K. Yedinak, 2013: WRF-Fire: Coupled weather–wildland fire modeling with the Weather Research and Forecasting Model. J. Appl. Meteor. Climatol., 52, 1638, doi:10.1175/JAMC-D-12-023.1.

    • Search Google Scholar
    • Export Citation
  • Countryman, C. M., 1971: Fire whirls … why, when and where. USDA Forest Service, Pacific Southwest Forest and Range Experiment Station, 14 pp.

  • Cunningham, P., 2007: Idealized numerical simulations of the interactions between buoyant plumes and density currents. J. Atmos. Sci., 64, 21052115, doi:10.1175/JAS3947.1.

    • Search Google Scholar
    • Export Citation
  • Cunningham, P., , and M. Reeder, 2009: Severe convective storms initiated by intense wildfires: Numerical simulations of pyro-convection and pyro-tornadogenesis. Geophys. Res. Lett., 36, L12812, doi:10.1029/2009GL039262.

    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and et al. , 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, doi:10.1002/qj.828.

    • Search Google Scholar
    • Export Citation
  • Filippi, J.-B., , F. Bosseur, , X. Pialat, , P.-A. Santoni, , S. Strada, , and C. Mari, 2011: Simulation of coupled fire/atmosphere interaction with the MesoNH-ForeFire models. J. Combust., 540390, doi:10.1155/2011/540390.

    • Search Google Scholar
    • Export Citation
  • Finney, M., , J. Cohen, , S. McAllister, , and W. Jolley, 2013: On the need for a theory of wildland fire spread. Int. J. Wildland Fire, 22, 2536, doi:10.1071/WF11117.

    • Search Google Scholar
    • Export Citation
  • Forthofer, J., , and S. Goodrick, 2011: Review of vortices in wildland fire. J. Combust., 984363, doi:10.1155/2011/984363.

  • Hu, X.-M., , J. Neilsen-Gammon, , and F. Zhang, 2010: Evaluation of three planetary boundary layer schemes in the WRF Model. J. Appl. Meteor. Climatol., 49, 18311844, doi:10.1175/2010JAMC2432.1.

    • Search Google Scholar
    • Export Citation
  • Jordanov, G., , J. Beezley, , N. Dobrinkova, , A. Kochanski, , J. Mandel, , and B. Sousedik, 2012: Simulation of the 2009 Harmanli fire (Bulgaria). Eighth Int. Conf., Large-Scale Scientific Computing 2011, Sozopol, Bulgaria, 291–298. [Available online at http://arxiv.org/abs/1106.4736.]

  • Kochanski, A., , M. Jenkins, , S. Kruger, , J. Mandel, , and J. Beezley, 2013a: Real time simulation of the 2007 Santa Ana fires. For. Ecol. Manage., 294, 136149, doi:10.1016/j.foreco.2012.12.014.

    • Search Google Scholar
    • Export Citation
  • Kochanski, A., , M. Jenkins, , J. Mandel, , J. Beezley, , C. Clements, , and S. Krueger, 2013b: Evaluation of WRF-SFIRE performance with field observations from the FireFlux experiment. Geosci. Model Dev. Discuss., 6, 121169, doi:10.5194/gmdd-6-121-2013.

    • Search Google Scholar
    • Export Citation
  • Kochanski, A., , M. Jenkins, , R. Sun, , S. Krueger, , S. Abedi, , and J. Charney, 2013c: The importance of low-level environmental wind shear to wildfire propagation: Proof of concept. J. Geophys. Res. Atmos., 118, 8238–8252, doi:10.1002/jgrd.50436.

    • Search Google Scholar
    • Export Citation
  • Linn, R., , J. Riesner, , J. J. Colman, , and J. Winterkamp, 2002: Studying wildfire behaviour using FIRETEC. Int. J. Wildland Fire, 11, 233246, doi:10.1071/WF02007.

    • Search Google Scholar
    • Export Citation
  • Mandel, J., , J. D. Beezley, , and A. K. Kochanski, 2011: Coupled atmosphere–wildland fire modeling with WRF 3.3 and SFIRE 2011. Geosci. Model Dev., 4, 591610, doi:10.5194/gmd-4-591-2011.

    • Search Google Scholar
    • Export Citation
  • McCaw, L., 1998: Research as a basis for fire management in mallee heath shrublands of south-western Australia. Proc. Third Int. Conf. on Forest Fire Research/14th Conf. on Fire and Forest Meteorology, Coimbra, Portugal, ADAI, 2335–2348.

  • McRae, R., , J. Sharples, , S. Wilkes, , and A. Walker, 2013: An Australian pyro-tornadogenesis event. Nat. Hazards, 65, 18011811, doi:10.1007/s11069-012-0443-7.

    • Search Google Scholar
    • Export Citation
  • Mell, W. E., , R. J. McDermott, , and G. P. Forney, 2010: Wildland fire behaviour modeling: Perspectives, new approaches and applications. Proc. Third Fire Behaviour and Fuels Conf., Spokane, WA, International Association of Wildland Fire, 17 pp. [Available online at https://www.firescience.gov/projects/07-1-5-08/project/07-1-5-08_Mell_FireBehaveModeling_3rdFireFuelsConf_2010.pdf.]

  • Ogawa, S., , W. Sha, , and T. Iwasaki, 2003: A numerical study on the interaction of a sea-breeze front with convective cells in the daytime boundary layer. J. Meteor. Soc. Japan, 81, 635651, doi:10.2151/jmsj.81.635.

    • Search Google Scholar
    • Export Citation
  • Peace, M., , and G. Mills, 2012: A case study of the 2007 Kangaroo Island bushfires. CAWCR Tech. Rep. 53, 58 pp. [Available online at http://www.cawcr.gov.au/publications/technicalreports/CTR_053.pdf.]

  • Peace, M., , L. McCaw, , and G. Mills, 2012: Meteorological dynamics in a fire environment; a case study of the Layman prescribed burn in Western Australia. Aust. Meteor. Oceanogr. J., 62 (3), 127141.

    • Search Google Scholar
    • Export Citation
  • Potter, B., 2005: The role of released moisture in the atmospheric dynamics associated with wildland fires. Int. J. Wildland Fire, 14, 7784, doi:10.1071/WF04045.

    • Search Google Scholar
    • Export Citation
  • Rothermel, R., 1972: A mathematical model for predicting fire spread in wildland fires. USDA Forest Service Research Paper INT-115, 48 pp.

  • Simpson, C. C., , J. J. Sharples, , J. P. Evans, , and M. F. McCabe, 2013: Large eddy simulation of atypical wildland fire spread on leeward slopes. Int. J. Wildland Fire, 22, 599614, doi:10.1071/WF12072.

    • Search Google Scholar
    • Export Citation
  • Simpson, J. E., 1997: Gravity Currents in the Environment and the Laboratory. 2nd ed. Cambridge University Press, 244 pp.

  • Skamarock, W., and et al. , 2008: A description of the Advanced Research WRF version 3. NCAR Tech. Note NCAR/TN-475+STR, 113 pp. [Available online at http://www.mmm.ucar.edu/wrf/users/docs/arw_v3_bw.pdf.]

  • Umscheid, M., , J. Monteverdi, , and J. Davies, 2006: Photographs and analysis of an unusually large and long-lived firewhirl. Electron. J. Severe Storms Meteor.,1 (2). [Available online at http://www.ejssm.org/ojs/index.php/ejssm/article/viewArticle/6/11.]

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Fire-Modified Meteorology in a Coupled Fire–Atmosphere Model

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  • 1 Bushfire Cooperative Research Centre, Melbourne, Victoria, and Applied Mathematics, Adelaide University, and Bureau of Meteorology, Adelaide, South Australia, Australia
  • | 2 Applied Mathematics, Adelaide University, South Australia, Australia
  • | 3 Bureau of Meteorology, Adelaide, South Australia, and Bushfire Cooperative Research Centre, Melbourne, Victoria, Australia
  • | 4 Department of Parks and Wildlife, Manjimup, Western Australia, Australia
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Abstract

The coupled fire–atmosphere model consisting of the Weather and Forecasting (WRF) Model coupled with the fire-spread model (SFIRE) module has been used to simulate a bushfire at D’Estrees Bay on Kangaroo Island, South Australia, in December 2007. Initial conditions for the simulations were provided by two global analyses: the GFS operational analysis and ERA-Interim. For each NWP initialization, the simulations were run with and without feedback from the fire to the atmospheric model. The focus of this study was examining how the energy fluxes from the simulated fire modified the local meteorological environment. With feedback enabled, the propagation speed of the sea-breeze frontal line was faster and vertical motion in the frontal zone was enhanced. For one of the initial conditions with feedback on, a vortex developed adjacent to the head fire and remained present for over 5 h of simulation time. The vortex was not present without fire–atmosphere feedback. The results show that the energy fluxes released by a fire can effect significant changes on the surrounding mesoscale atmosphere. This has implications for the appropriate use of weather parameters extracted from NWP and used in prediction for fire operations. These meteorological modifications also have implications for anticipating likely fire behavior.

Corresponding author address: Mika Peace, Bureau of Meteorology South Australia Regional Office, 25 College Rd., Kent Town, Adelaide, SA 5071, Australia. E-mail: m.peace@bom.gov.au

Abstract

The coupled fire–atmosphere model consisting of the Weather and Forecasting (WRF) Model coupled with the fire-spread model (SFIRE) module has been used to simulate a bushfire at D’Estrees Bay on Kangaroo Island, South Australia, in December 2007. Initial conditions for the simulations were provided by two global analyses: the GFS operational analysis and ERA-Interim. For each NWP initialization, the simulations were run with and without feedback from the fire to the atmospheric model. The focus of this study was examining how the energy fluxes from the simulated fire modified the local meteorological environment. With feedback enabled, the propagation speed of the sea-breeze frontal line was faster and vertical motion in the frontal zone was enhanced. For one of the initial conditions with feedback on, a vortex developed adjacent to the head fire and remained present for over 5 h of simulation time. The vortex was not present without fire–atmosphere feedback. The results show that the energy fluxes released by a fire can effect significant changes on the surrounding mesoscale atmosphere. This has implications for the appropriate use of weather parameters extracted from NWP and used in prediction for fire operations. These meteorological modifications also have implications for anticipating likely fire behavior.

Corresponding author address: Mika Peace, Bureau of Meteorology South Australia Regional Office, 25 College Rd., Kent Town, Adelaide, SA 5071, Australia. E-mail: m.peace@bom.gov.au
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