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Journal Article

Citation

Lannom KO, Tinkham WT, Smith AMS, Abatzoglou JT, Newingham BA, Hall TE, Morgan P, Strand EK, Paveglio TB, Anderson JW, Sparks AM. Int. J. Wildland Fire 2014; 23(3): 322-337.

Copyright

(Copyright © 2014, International Association of Wildland Fire, Fire Research Institute, Publisher CSIRO Publishing)

DOI

10.1071/WF13065

PMID

unavailable

Abstract

There is a growing professional and public perception that 'extreme' wildland fires are becoming more common due to changing climatic conditions. This concern is heightened in the wildland-urban interface where social and ecological effects converge. 'Mega-fires', 'conflagrations', 'extreme' and 'catastrophic' are descriptors interchangeably used increasingly to describe fires in recent decades in the US and globally. It is necessary to have consistent, meaningful and quantitative metrics to define these perceived 'extreme' fires, given studies predict an increased frequency of large and intense wildfires in many ecosystems as a response to climate change. Using the Monitoring Trends in Burn Severity dataset, we identified both widespread fire years and individual fires as potentially extreme during the period 1984-2009 across a 91.2 × 106-ha area in the north-western United States. The metrics included distributions of fire size, fire duration, burn severity and distance to the wildland-urban interface. Widespread fire years for the study region included 1988, 2000, 2006 and 2007. When considering the intersection of all four metrics using distributions at the 90th percentile, less than 1.5% of all fires were identified as potentially extreme fires. At the more stringent 95th and 99th percentiles, the percentage reduced to <0.5% and 0.05%. Correlations between area burnt and climatic measures (Palmer drought severity index, temperature, energy release component, duff moisture code and potential evapotranspiration) were observed. We discuss additional biophysical and social metrics that could be included and recommend both the need for enhanced visualisation approaches and to weigh the relative strength or importance of each metric.

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