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Deconstructing the King megafire
Abstract
Hypotheses that megafires, very large, high-impact fires, are caused by either climate effects such as drought or fuel accumulation due to fire exclusion with accompanying changes to forest structure have long been alleged and guided policy, but their physical basis remains untested. Here, unique airborne observations and microscale simulations using a coupled weather-wildland-fire-behavior model allowed a recent megafire, the King Fire, to be deconstructed and the relative impacts of forest structure, fuel load, weather, and drought on fire size, behavior, and duration to be separated. Simulations reproduced observed details including the arrival at an inclined canyon, a 25-km run, and later slower growth and features. Analysis revealed that fire-induced winds that equaled or exceeded ambient winds and fine-scale airflow undetected by surface weather networks were primarily responsible for the fire's rapid growth and size. Sensitivity tests varied fuel moisture and amount across wide ranges and showed that both drought and fuel accumulation effects were secondary, limited to sloped terrain where they compounded each other, and, in this case, unable to significantly impact the final extent. Compared to standard data, fuel models derived solely from remote sensing of vegetation type and forest structure improved simulated fire progression, notably in disturbed areas, and the distribution of burn severity. These results point to self-reinforcing internal dynamics rather than external forces as a means of generating this and possibly other outlier fire events. Hence, extreme fires need not arise from extreme fire environment conditions. Kinematic models used in operations do not capture fire-induced winds and dynamic feedbacks so can underestimate megafire events. The outcomes provided a nuanced view of weather, forest structure, fuel accumulation, and drought impacts on landscape-scale fire behavior-roles that can be misconstrued using correlational analyses between area burned and macroscale climate data or other exogenous factors. A practical outcome is that fuel treatments should be focused on sloped terrain, where factors multiply, for highest impact.
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“Further, coupled weather-fire models now capture the unfolding of complex landscape-scale events over a period of days (Coen, Stavros, & Fites-Kaufman, 2018), while global models continue to improve their representation of fire frequency, burned area and seasonality across years to decades (Forkel et al., 2019;Hantson et al., 2016).”
From Fire as a fundamental ecological process: Research advances and frontiers (2020) · cites this paper as Coen et al., 2018
Citations
Cites
Warming and earlier spring increase western U.S. forest wildfire activity.
Westerling, A. L., Hidalgo, H. G., Cayan, D. R., & Swetnam, T. W. (2006) · Science · doi:10.1126/science.1128834 · Cited by 5,176
A Description of the Advanced Research WRF Version 2
Skamarock, W., Klemp, J., Dudhia, J., Gill, D., Barker, D., & Wang, W. (2005) · NSF National Center for Atmospheric Research · doi:10.5065/d6dz069t · Cited by 2,504
A mathematical model for predicting fire spread in wildland fuels
Rothermel, R. C. (1972) · doi:10.2737/int-rp-115 · Cited by 2,247
Research works printed but not linked: 55
- 10.1071/WF10046 · DOI
- Albini F. A., 1976, Estimating wildfire behavior and effects
- Albini F. A., 1994, PROGRAM BURNUP: a simulation model of the burning of large woody natural fuels
- Alvarado E., 1998, Modeling large forest fires as extreme events, Northwest Science, 72, 66
- 10.2737/INT-GTR-122 · DOI
- 10.1088/1748-9326/9/12/124009 · DOI
- 10.1016/j.tree.2005.04.025 · DOI · Paper page
- Bowman D. M. J. S. G. J.Williamson J. T.Abatzoglou C. A.Kolden M. A.Cochrane andA. M. S.Smith.2017.Nature Ecology & Evolution1:0058. · DOI · Paper page
- 10.1111/j.1466-8238.2009.00512.x · DOI · Paper page
- 10.1175/1520-0450(1977)016<0867:AIOTSS>2.0.CO;2 · DOI
- 10.1071/WF03043 · DOI
- 10.1016/0021-9991(91)90218-A · DOI
- 10.1175/1520-0469(1997)054<1795:TITOLI>2.0.CO;2 · DOI
- 10.1071/WF04047 · DOI
- 10.1071/WF12194 · DOI
- 10.1002/2013GL057868 · DOI
- 10.1002/2014JD021993 · DOI
- Coen J. L., 2017, Coupled weather‐fire modeling: from research to operational forecasting, Fire Management Today, 75, 39
- 10.1641/0006-3568(2001)051[0723:CCAFD]2.0.CO;2 · DOI
- 10.1002/2014GL059576 · DOI · Paper page
- 10.1071/WF08055 · DOI
- Dimitrakopoulos A., 2011, Statistical analysis of the fire environment of large forest fires (>1000 ha) in Greece, Polish Journal of Environmental Studies, 20, 327
- 10.1071/WF06063 · DOI
- 10.1071/WF08187 · DOI · Paper page
- 10.1002/2014GL062433 · DOI
- 10.1002/ecs2.2019 · DOI
- Hook S. J., 2001, The MODIS/ASTER airborne simulator (MASTER)—a new instrument for earth science studies, Canadian Journal of Forest Research, 76, 93
- 10.1038/nplants.2016.24 · DOI
- 10.2737/RMRS-GTR-91 · DOI · Paper page
- 10.1071/WF07049 · DOI
- LaCroix J. J., 2006, Simulating fire spread with landscape management scenarios, Forest Science, 52, 522, 10.1093/forestscience/52.5.522 · DOI
- 10.1016/j.rse.2015.06.012 · DOI
- 10.1890/07-1183.1 · DOI
- 10.1016/j.foreco.2014.06.005 · DOI · Paper page
- 10.1016/j.foreco.2011.04.016 · DOI
- 10.1016/j.rse.2016.06.018 · DOI
- 10.1175/BAMS-D-14-00060.1 · DOI
- 10.1080/2150704X.2015.1029086 · DOI
- 10.1175/JCLI-D-12-00727.1 · DOI
- Pyne S. J., 2015, Between two fires: a fire history of contemporary America, 10.2307/j.ctt183gxsr · DOI
- 10.1071/WF12149 · DOI
- 10.2737/INT-RP-438 · DOI
- 10.1641/0006-3568(2004)054[0661:TIOFFA]2.0.CO;2 · DOI · Paper page
- 10.1016/j.rse.2013.12.008 · DOI
- 10.1071/WF13169 · DOI
- 10.1016/j.rsase.2018.04.010 · DOI
- 10.1002/ecy.1577 · DOI
- 10.1029/2001JD000484 · DOI
- Strauss D., 1989, Do one percent of forest fires cause ninety‐nine percent of the damage?, Forest Science, 35, 319, 10.1093/forestscience/35.2.319 · DOI
- 10.1071/WF09125 · DOI
- Tedim F., 2014, Wildfire. Hazards, risks, and disasters, 77
- 10.1890/10-0097.1 · DOI
- 10.1139/x77-004 · DOI
- 10.1111/gcb.12590 · DOI
- 10.1016/j.foreco.2012.06.030 · DOI · Paper page
Cited by
Sorted by citations
Fire as a fundamental ecological process: Research advances and frontiers
McLauchlan, K. K., Higuera, P. E., Miesel, J., Rogers, B. M., Schweitzer, J., Shuman, J. K., Tepley, A. J., Varner, J. M., Veblen, T. T., Adalsteinsson, S. A., et al. (2020) · Journal of Ecology · doi:10.1111/1365-2745.13403 · Cited by 729
Self-citation
Metadata
- Authors
- Coen, J. L., Stavros, E. N., & Fites‐Kaufman, J. A.
- Affiliations
- NSF National Center for Atmospheric Research (US)
- California Institute of Technology (US)
- US Forest Service (US)
- Corresponding author
- Coen, Janice L.
- Venue
- Ecological Applications
- Publisher
- Wiley
- Published
- 2018-06-29
- Volume
- 28
- Issue
- 6
- Pages
- 1565-1580
- ISSN
- 1051-0761 (ISSN-L)
- 1939-5582
- OpenAlex
- W2804602498
- Cited by
- 92
- References
- 3
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 21 · 2023: 6 · 2022: 16 · 2021: 10 · 2020: 15 · 2019: 9 · 2018: 3
- FWCI
- 5.41
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Ecological Applications (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Aeronautics and Space Administration (NNX12AQ87G, NNN12AA01C)
- Federal Emergency Management Agency (EMW‐2011‐FP‐01124)
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Fire effects on ecosystems
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Fire dynamics and safety research
- Physical Sciences › Environmental Science › Ecology › Rangeland and Wildlife Management
- Keywords
- megafires, fire behavior, fire-induced airflow, fuel moisture content, fuel accumulation, drought, forest structure, fuel models, burn severity, fire growth rate, fire duration, fuel treatment, sloping land
- MeSH terms
- Wildfires, California, Models, Theoretical, Weather, Wind, Droughts
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- Coen, J. L., Stavros, E. N., & Fites‐Kaufman, J. A. (2018). Deconstructing the King megafire. Ecological Applications. https://doi.org/10.1002/eap.1752