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International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

Santa Ana winds and predictors of wildfire progression in southern California

Michael Billmire A D , Nancy H. F. French A , Tatiana Loboda B , R. Chris Owen A C and Marlene Tyner A
+ Author Affiliations
- Author Affiliations

A Michigan Tech Research Institute, 3600 Green Court Suite #100 Ann Arbor, MI 48105, USA

B Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA

C Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC 27711. USA

D Corresponding author. Email: michael.billmire@mtu.edu

International Journal of Wildland Fire 23(8) 1119-1129 https://doi.org/10.1071/WF13046
Submitted: 21 March 2013  Accepted: 14 July 2014   Published: 18 November 2014

Abstract

Santa Ana winds have been implicated as a major driver of large wildfires in southern California. While numerous anecdotal reports exist, there is little quantitative analysis in peer-reviewed literature on how this weather phenomenon influences fire progression rates. We analysed fire progression within 158 fire events in southern California as a function of meteorologically defined Santa Ana conditions between 2001 and 2009. Our results show quantitatively that burned area per day is 3.5–4.5 times larger on Santa Ana days than on non-Santa Ana days. Santa Ana definition parameters (relative humidity, wind speed) along with other predictor variables (air temperature, fuel temperature, 10-h fuel moisture, population density, slope, fuel loading, previous-day burn perimeter) were tested individually and in combination for correlation with subsets of daily burned area. Relative humidity had the most consistently strong correlation with burned area per day. Gust and peak wind speed had a strong positive correlation with burned area per day particularly within subsets of burned area representing only the first day of a fire, >500 ha burned areas, and on Santa Ana days. The suite of variables comprising the best-fit generalised linear model for predicting burned area (R2 = 0.41) included relative humidity, peak wind speed, previous-day burn perimeter and two binary indicators for first and last day of a fire event.

Additional keywords: chaparral, fire spread, generalised linear model, relative humidity, wind speed.


References

Anderson SAJ, Anderson WR (2010) Ignition and fire spread thresholds in gorse (Ulex europaeus). International Journal of Wildland Fire 19, 589–598.
Ignition and fire spread thresholds in gorse (Ulex europaeus).Crossref | GoogleScholarGoogle Scholar |

Baeza M, De Lu’ıs M, Ravent’os J, Escarr’e A (2002) Factors influencing fire behaviour in shrublands of different stand ages and the implications for using prescribed burning to reduce wildfire risk. Journal of Environmental Management 65, 199–208.
Factors influencing fire behaviour in shrublands of different stand ages and the implications for using prescribed burning to reduce wildfire risk.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD38vjvFKjtA%3D%3D&md5=98cea0573442f0b06ebf5d25cb959edfCAS | 12197080PubMed |

Bilgili E, Saglam B (2003) Fire behavior in maquis fuels in Turkey. Forest Ecology and Management 184, 201–207.
Fire behavior in maquis fuels in Turkey.Crossref | GoogleScholarGoogle Scholar |

Burrows N, Ward B, Robinson A (1991) Fire behavior in spinifex fuels on the Gibson Desert Nature Reserve, Western Australia. Journal of Arid Environments 20, 189–204.

Catchpole W, Bradstock R, Choate J, Fogarty L, Gellie N, McArthy G, McCaw L, Marsden-Smedley J, Pearce G (1998) Co-operative development of equations for heathland fire behaviour. In ‘Proceedings of the 3rd International Conference on Forest Fire Research and 14th Conference on Fire and Forest Meteorology’, 16–20 November 1998, Luso, Portugal. (Ed. DX Viegas) pp. 631–645. (ADAI, University of Coimbra: Coimbra, Portugal)

Cheney NP, Gould JS (1995) Fire growth in grassland fuels. International Journal of Wildland Fire 5, 237–247.
Fire growth in grassland fuels.Crossref | GoogleScholarGoogle Scholar |

Clark TL, Coen JL, Latham D (2004) Description of a coupled atmosphere–fire model. International Journal of Wildland Fire 13, 49–63.
Description of a coupled atmosphere–fire model.Crossref | GoogleScholarGoogle Scholar |

Coen JL, Douglas CC (2010) Computational modeling of large wildfires: a roadmap. In ‘Ninth International Symposium on Distributed Computing and Applications to Business, Engineering and Science’, 10–12 August 2010, Hong Kong, China, pp. 113–117. (IEEE Xplore Digital Library: Piscataway, NJ)

Conil S, Hall A (2006) Local regimes of atmospheric variability: a case study of southern California. Journal of Climate 19, 4308–4325.
Local regimes of atmospheric variability: a case study of southern California.Crossref | GoogleScholarGoogle Scholar |

Davis FW, Michaelsen J (1995) Sensitivity of fire regime in chaparral ecosystems to climate change. In ‘Global Change and Mediterranean-type Ecosystems’. (Eds J Moreno, WC Oechel) pp. 435–456. (Springer-Verlag: New York)

Edinger JG, Helvey RA, Baumhefner D (1964) Surface wind patterns in the Los Angeles basin during ‘Santa Ana’ conditions. USDA Forest Service, Part 1 of USDA Forest Service Research Project 2606, Pacific Southwest Forest and Range Experiment Station. (Los Angeles, CA)

Eidenshink J, Schwind B, Brewer K, Zhu Z, Quayle B, Howard S (2007) A project for monitoring trends in burn severity. Fire Ecology 3, 3–21.
A project for monitoring trends in burn severity.Crossref | GoogleScholarGoogle Scholar |

Fendell FE, Wolff MF (2001) Wind-aided fire spread. In ‘Forest Fires: Behavior and Ecological Effects’. (Eds EA Johnson, K Miyanishi) pp. 171–224. (Academic Press: San Diego, CA)

Fernandes PM (2001) Fire spread prediction in shrub fuels in Portugal. Forest Ecology and Management 144, 67–74.

Fernandes PM, Botelho HS, Lourerio C (2002) Models for the sustained ignition and behavior of low-to-moderately intense fires in maritime pine stands. In ‘Proceedings of IV International Conference on Forest Fire Research and 2002 Wildland Fire Safety Summit’, 19–21 June 1978, Lake Tahoe, CA. (Ed DX Viegas) (Millpress: Rotterdam, Netherlands)

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, South Lake Tahoe, NV. pp. 1–4.

Fovell RG (2012) Downslope windstorms of San Diego county: sensitivity to resolution and model physics. In ‘13th WRF Users’ Workshop’, 26–29 June 2012. (National Center for Atmospheric Research: Boulder, CO) Available at http://www2.mmm.ucar.edu/wrf/users/workshops/WS2012/WorkshopPapers.php [Verified 6 October 2014

Gelman A (2008) Scaling regression inputs by dividing by two standard deviations. Statistics in Medicine 27, 2865–2873.
Scaling regression inputs by dividing by two standard deviations.Crossref | GoogleScholarGoogle Scholar | 17960576PubMed |

Giglio L, Descloitres J, Justice CO, Kaufman YJ (2003) An enhanced contextual fire detection algorithm for MODIS. Remote Sensing of Environment 87, 273–282.
An enhanced contextual fire detection algorithm for MODIS.Crossref | GoogleScholarGoogle Scholar |

Giglio L, Loboda T, Roy DP, Quayle B, Justice CO (2009) An active-fire based burned area mapping algorithm for the MODIS sensor. Remote Sensing of Environment 113, 408–420.
An active-fire based burned area mapping algorithm for the MODIS sensor.Crossref | GoogleScholarGoogle Scholar |

Hughes M, Hall A (2010) Local and synoptic mechanisms causing southern California’s Santa Ana winds. Climate Dynamics 34, 847–857.
Local and synoptic mechanisms causing southern California’s Santa Ana winds.Crossref | GoogleScholarGoogle Scholar |

Keeley JE, Fotheringham CJ (2001) Historic fire regime in southern California shrublands. Conservation Biology 15, 1536–1548.
Historic fire regime in southern California shrublands.Crossref | GoogleScholarGoogle Scholar |

Keeley JE, Zedler PH (2009) Large, high-intensity fire events in southern California shrublands: debunking the fine-grain age patch model. Ecological Applications 19, 69–94.
Large, high-intensity fire events in southern California shrublands: debunking the fine-grain age patch model.Crossref | GoogleScholarGoogle Scholar | 19323174PubMed |

Keeley JE, Safford H, Fotheringham CJ, Franklin J, Moritz M (2009) The 2007 southern California wildfires: lessons in complexity. Journal of Forestry 107, 287–296.

Koo E, Pagni P, Stephens S, Huff J, Woycheese J, Weise DR (2005) A simple physical model for forest fire spread rate. Fire Safety Science 8, 851–862.
A simple physical model for forest fire spread rate.Crossref | GoogleScholarGoogle Scholar |

Lindenmuth AW, Davis JR (1973) Predicting fire spread in Arizona’s oak chaparral. USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, RM-101. (Fort Collins, CO)

Linn RR, Winterkamp JL, Weise DR, Edminster C (2010) A numerical study of slope and fuel structure effects on coupled wildfire behaviour. International Journal of Wildland Fire 19, 179–201.
A numerical study of slope and fuel structure effects on coupled wildfire behaviour.Crossref | GoogleScholarGoogle Scholar |

Loboda TV, Csiszar IA (2007) Reconstruction of fire spread within wildland fire events in Northern Eurasia from the MODIS active fire product. Global and Planetary Change 56, 258–273.
Reconstruction of fire spread within wildland fire events in Northern Eurasia from the MODIS active fire product.Crossref | GoogleScholarGoogle Scholar |

Marsden-Smedley JB, Catchpole WR (1995) Fire behaviour modeling in Tasmanian buttongrass moorlands: I. fuel characteristics. International Journal of Wildland Fire 5, 203–214.
Fire behaviour modeling in Tasmanian buttongrass moorlands: I. fuel characteristics.Crossref | GoogleScholarGoogle Scholar |

McCaw L (1997) Predicting fire spread in Western Australian mallee–heath shrubland. PhD thesis, University of New South Wales, Canberra.

Miller NL, Schlegel NJ (2006) Climate change projected fire weather sensitivity: California Santa Ana wind occurrence. Geophysical Research Letters 33, L15711
Climate change projected fire weather sensitivity: California Santa Ana wind occurrence.Crossref | GoogleScholarGoogle Scholar |

Moritz MA (1997) Analyzing extreme disturbance events: fire in Los Padres National Forest. Ecological Applications 7, 1252–1262.
Analyzing extreme disturbance events: fire in Los Padres National Forest.Crossref | GoogleScholarGoogle Scholar |

Moritz MA, Moody TJ, Krawchuk MA, Hughes M, Hall A (2010) Spatial variation in extreme winds predict large wildfire locations in chaparral ecosystems. Geophysical Research Letters 37, L04801
Spatial variation in extreme winds predict large wildfire locations in chaparral ecosystems.Crossref | GoogleScholarGoogle Scholar |

Morvan D, Tauleigne V, Dupuy JL (2002) Wind effects on wildfire propagation through a Mediterranean shrub. In ‘Forest Fire Research and Wildland Fire Safety: Proceedings of IVth International Conference on Forest Fire Research/2002 Wildland Fire Safety Summit’, 18–23 November 2002, Coimbra, Portugal. (Ed. DX Viegas) pp. 116–130 (Millpress: Rotterdam, Netherlands)

NWCG (2011) Historical Incident ICS-209 Reports. (National Wildlife Coordinating Group) Available at http://fam.nwcg.gov/fam-web/hist_209/report_list_209 [Verified 23 September 2014]

Ottmar RD, Sandberg DV, Riccardi CL, Prichard SJ (2007) An overview of the Fuel Characteristic Classification System – quantifying, classifying, and creating fuelbeds for resource planning. Canadian Journal of Forest Research 37, 2383–2393.
An overview of the Fuel Characteristic Classification System – quantifying, classifying, and creating fuelbeds for resource planning.Crossref | GoogleScholarGoogle Scholar |

Peterson SH, Moritz MA, Morais ME, Dennison PE, Carlso JM (2011) Modelling long-term fire regimes of southern California shrublands. International Journal of Wildland Fire 20, 1–16.
Modelling long-term fire regimes of southern California shrublands.Crossref | GoogleScholarGoogle Scholar |

Price OF, Bradstock RA, Keeley JA, Syphard AD (2012) The impact of antecedent fire area on burned area in southern California coastal ecosystems. Journal of Environmental Management 113, 301–307.
The impact of antecedent fire area on burned area in southern California coastal ecosystems.Crossref | GoogleScholarGoogle Scholar | 23064248PubMed |

Raffuse SM, Sullivan DC, Larkin NK, Gilliland EK, Chinkin LR, Solomon R, Pace TG (2008) Development and sensitivity analysis of wildland fire emission inventories for 2002–2006. In ‘17th International Emissions Inventory Conference’, 2–5 June 2008, Portland, OR. pp. 2–5.

Raphael MN (2003) The Santa Ana winds of California. Earth Interactions 7, 1–13.
The Santa Ana winds of California.Crossref | GoogleScholarGoogle Scholar |

Richardson RT (1973) The continental contribution to the climate of southern California. PhD thesis, University of Oregon, Eugene.

Rothermel RC (1972) A mathematical model for predicting fire spread in wildland fuels. USDA Forest Service, Intermountain Forest and Range Experiment Station, INT-115.

Schroeder MJ, Glovinsky M, Henricks VF, Hood FC, Hull MK (1964) Synoptic weather types associated with critical fire. USDA Forest Service, Pacific Southwest Range and Experiment Station. (Berkeley, CA).

Sergius LA, Huntoon JK (1956) An objective method for forecasting the Santa Ana. In ‘Forecaster’s Handbook’. (US Fleet Weather Central: San Diego, CA).

Sullivan AL (2009) Wildland surface fire spread modeling, 1990–2007. International Journal of Wildland Fire 18, 369–386.
Wildland surface fire spread modeling, 1990–2007.Crossref | GoogleScholarGoogle Scholar |

Turner MG, Hargrove WW, Gardner RH, Romme WH (1994) Effects of fire on landscape heterogeneity in Yellowstone National Park, Wyoming. Journal of Vegetation Science 5, 731–742.
Effects of fire on landscape heterogeneity in Yellowstone National Park, Wyoming.Crossref | GoogleScholarGoogle Scholar |

US CENSUS Bureau (2002) Census 2000 Summary File 3 – California. (US Census Bureau: Washington, DC).

US Geological Survey (1999) USGS National Elevation Dataset. (EROS Data Center: Sioux Falls, SD).

US Geological Survey (2010) LANDFIRE Refresh 2008 Fuel Characterization Classification System Fuelbeds. Available at http://landfire.cr.usgs.gov/viewer/ [Verified 23 September 2014]

Weise DR, Zhou X, Sun L, Mahalingam S (2005) Fire spread in chaparral – ‘go or no-go?’. International Journal of Wildland Fire 14, 99–106.
Fire spread in chaparral – ‘go or no-go?’.Crossref | GoogleScholarGoogle Scholar |

Westerling AL, Cayan DR, Brown TJ, Hall BL, Riddle LG (2004) Climate, Santa Ana winds and autumn wildfires in southern California. American Geophysical Union EOS Transactions 85, 289–300.
Climate, Santa Ana winds and autumn wildfires in southern California.Crossref | GoogleScholarGoogle Scholar |

Zhou X, Mahalingam S, Weise D (2005) Modelling of marginal burning state of fire spread in live chaparral shrub fuel bed. Combustion and Flame 143, 183–198.
Modelling of marginal burning state of fire spread in live chaparral shrub fuel bed.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2MXhtFarsr7E&md5=99d9bb4d3359ff3a75ccfbcaefca9526CAS |