Abstract
Research Highlights: Our results suggest that weather is a primary driver of resource orders over the course of extended attack efforts on large fires. Incident Management Teams (IMTs) synthesize information about weather, fuels, and order resources based on expected fire growth rather than simply reacting to observed fire growth. Background and Objectives: Weather conditions are a well-known determinant of fire behavior and are likely to become more erratic under climate change. Yet, there is little empirical evidence demonstrating how IMTs respond to observed or expected weather conditions. An understanding of weather-driven resource ordering patterns may aid in resource prepositioning as well as forecasting suppression costs. Our primary objective is to understand how changing weather conditions influence resource ordering patterns. Our secondary objective is to test how an additional risk factor, evacuation, as well as a constructed risk metric combining fire growth and evacuation, influences resource ordering. Materials and Methods: We compile a novel dataset on over 1100 wildfires in the western US from 2007–2013, integrating data on resource requests, detailed weather conditions, fuel and landscape characteristics, values at risk, fire behavior, and IMT expectations about future fire behavior and values at risk. We develop a two-step regression framework to investigate the extent to which IMTs respond to realized or expected weather-driven fire behavior and risks. Results: We find that IMTs’ expectations about future fire growth are influenced by observed weather and that these expectations influence resource ordering patterns. IMTs order nearly twice as many resources when weather conditions are expected to drive growth events in the near future. However, we find little evidence that our other risk metrics influence resource ordering behavior (all else being equal). Conclusion: Our analysis shows that incident management teams are generally forward-looking and respond to expected rather than recently observed weather-driven fire behavior. These results may have important implications for forecasting resource needs and costs in a changing climate.
Highlights
Extreme, erratic, and unpredictable are all words used to describe the behavior of some of the most devastating fires in recent decades
While our results suggest that Incident Management Teams (IMTs) order resources based on expected fire growth, we do not know how the resources are used or whether they were effective in achieving their objective
We develop a two-step regression framework to estimate the pathways through which weather effects resource ordering patterns
Summary
Erratic, and unpredictable are all words used to describe the behavior of some of the most devastating fires in recent decades. Do fire managers request resources in anticipation of weather-driven growth events, or do they wait to see if the consequences materialize? The objective of this study is to understand how fire managers respond to weather- and value-driven fire risk. We develop a two-step approach wherein we estimate the effect of weather conditions on observed wildfire growth and expected near term fire growth; we estimate the effect of observed and expected wildfire growth on suppression resource orders. This approach allows us to identify the channel through which weather conditions impact resource orders. We investigate how this response to observed and expected fire growth depends on the presence of values at risk
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