This simulation research was conducted in order to develop a large-fire risk assessment system for the contiguous land area of the United States. The modeling system was applied to each of 134 Fire Planning Units (FPUs) to estimate burn probabilities and fire size distributions. To obtain stable estimates of these quantities, fire ignition and growth was simulated for 10,000 to 50,000 ''years'' of artificial weather. The fire growth simulations, when run repeatedly with different weather and ignition locations, produce burn probabilities and fire behavior distributions at each landscape location (e.g., number of times a ''cell'' burns at a given intensity divided by the total years). The artificial weather was generated for each land unit using (1) a fire danger rating index known as the Energy Release Component (ERC) which is a proxy for fuel moisture contents, (2) a time-series analysis of ERC to represent daily and seasonal variability, and (3) distributions of wind speed and direction from weather records. Large fire occurrence was stochastically modeled based on historical relationships to ERC. The simulations also required spatial data on fuel structure and topography which were acquired from the LANDFIRE project (http://www.landfire.gov). Fire suppression effects were represented by a statistical model that yields a probability of fire containment based on independent predictors of fire growth rates and fuel type. The simulated burn probabilities were comparable to observed patterns across the U.S. over the range of four orders of magnitude, generally falling within a factor of 3 or 4 of historical estimates. Close agreement between simulated and historical fire size distributions suggest that fire sizes are determined by the joint distributions of spatial opportunities for fire growth (dependent on fuels and ignition location) and the temporal opportunities produced by conducive weather sequences. The research demonstrates a practical approach to using fire simulations at very broad scales for purposes of operational planning and perhaps ecological research.

Performance of fuel treatments in modifying behavior and effects of the largest wildfires has rarely been evaluated, because the necessary data on fire movement, treatment characteristics, and fire severity were not obtainable together. Here we analyzed satellite imagery and prescribed fire records from two Arizona wildfires that occurred in 2002, finding that prescribed fire treatments reduced wildfire severity and changed its progress. Prescribed burning in ponderosa pine forests 1–9 years before the Rodeo and Chediski fires reduced fire severity compared with untreated areas, despite the unprecedented 1860-km2 combined wildfire sizes and record drought. Fire severity increased with time since treatment but decreased with unit size and number of repeated prescribed burn treatments. Fire progression captured by Landsat 7 enhanced thematic mapper plus (ETM+) clearly showed the fire circumventing treatment units and protecting areas on their lee side. This evidence is consistent with model predictions that suggest wildland fire size and severity can be mitigated by strategic placement of treatments.

The relationship between large fire occurrence and drought has important implications for fire prediction under current and future climates. This study’s primary objective was to evaluate correlations between drought and fire-danger-rating indices representing short- and long-term drought, to determine which had the strongest relationships with large fire occurrence at the scale of the western United States during the years 1984–2008. We combined 4–8-km gridded drought and fire-danger-rating indices with information on fires greater than 404.7ha (1000acres). To account for differences in indices across climate and vegetation assemblages, indices were converted to percentile conditions for each pixel. Correlations between area burned and short-term indices Energy Release Component and monthly precipitation percentile were strong (R2=0.92 and 0.89), as were correlations between number of fires and these indices (R2=0.94 and 0.93). As the period of time tabulated by indices lengthened, correlations with fire occurrence weakened: Palmer Drought Severity Index and 24-month Standardised Precipitation Index percentile showed weak correlations with area burned (R2=0.25 and –0.01) and number of large fires (R2=0.3 and 0.01). These results indicate associations between short-term indices and moisture content of dead fuels, the primary carriers of surface fire.

An ensemble simulation system that accounts for uncertainty in long-range weather conditions and twodimensional wildland fire spread is described. Fuel moisture is expressed based on the energy release component, a US fire danger rating index, and its variation throughout the fire season is modeled using time series analysis of historical weather data. This analysis is used to characterize the seasonal trend in ERC, autocorrelation of residuals, and daily standard deviation and stochastically generate artificial time series of afternoon fuel moisture. Daily wind speed and direction are sampled stochastically from joint probabilities of historical wind speed and direction for the date range of the fire simulation period. Hundreds or thousands of fire growth simulations are then performed using the synthetic fire weather sequences. The performance of these methods is evaluated in terms of the number of ensemble member simulations, one-versus twodimensional fire spread simulations, and comparison with results from 91 fires occurring from 2007 to 2009. Simulations were found to be in consistent agreement with observations, but trends indicate that the ensemble average of simulated fire sizes were consistently larger than actual fires whereas the farthest extent burned by fires was underestimated.