Accurate predictions of how weather may affect a wildfire’s behavior are needed to protect crews on the line and efficiently allocate firefighting resources. Since 1988, fire meteorologists have used a tool called the Haines Index to predict days when the weather will exacerbate a wildfire. Although the Haines Index is widely believed to have value, it never received rigorous testing on the line. Even Don Haines, the U.S. Forest Service meteorologist who developed the index, has said the Haines Index needs further refinement.
Recognizing that a new fire weather prediction tool was needed, a team composed of meteorologists with the U.S. Forest Service and St. Cloud State University developed the Hot-Dry-Windy Index. The index is based upon the three weather conditions—hot, dry, and windy—that significantly affect a wildfire’s behavior.
When the Hot-Dry-Windy Index and the Haines Index were evaluated on four wildfires that burned in the United States between 2002 and 2011, the Hot-Dry-Windy Index proved better at identifying days when weather contributed to dangerous wildfire conditions. Because of the positive feedback received during subsequent field testing, the National Weather Service has recommended that fire meteorologists evaluate the Hot-Dry-Windy Index as a fire weather tool for use on wildfires.
Wildfire is an ever present, natural process shaping landscapes. Having the ability to accurately measure and predict wildfire occurrence and impacts to ecosystem goods and services, both retrospectively and prospectively, is critical for adaptive management of landscapes. Landscape vulnerability is a concept widely utilized in the ecosystem management literature that has not been explicitly defined, particularly with regard to wildfire. Vulnerability more broadly is defined by three primary components: exposure to the stressor, sensitivity to a range of stressor variability, and resilience following exposure. In this synthesis, we define vulnerability in the context of wildfire. We first identify the components of a guiding framework for a vulnerability assessment with respect to wildfire. We then address retrospective assessments of wildfire vulnerability and the data that have been developed and utilized to complete these assessments. Finally, we review the modeling efforts that allow for predictive and probabilistic assessment of future vulnerability. Throughout the synthesis, we highlight gaps in the research, data availability, and models used to complete vulnerability assessments.