Demonstrations are sought of tools that forecast wildfire activities and prescribed fire opportunities at Department of Defense (DoD) Installation-relevant spatial scales for time horizons of 1-10 years. Demonstrating the accuracy and efficacy of wildfire and prescribed fire forecasts beyond the current operational year is necessary for improving the management of wildfire risks and optimizing the application of prescribed fires to meet military mission needs. Specific objectives include:

• Incorporating fire environmental conditions from weather-to-climate forecasting to assess wildfire exposure and prescribed burn windows.
• Demonstrating proficiency in forecasting wildfire conditions for extremes in fire weather, such as drought, extreme thresholds of energy release components, excessive heat, etc., at 1-10 year time horizons.
• Demonstrating accuracy of modeling against past fire activities.
• Demonstrating accuracy of modeling prescribed burning windows using 1-10 year weather-to-climate forecasting tools.
• At no less than annually, incorporating high spatial resolution inputs of past fuel and vegetation conditions to forecasting future hazards.

Enhanced, actionable assessments of potential exposure to wildfire hazards and concomitant assessment of prescribed fire opportunities will contribute to the sustainment of the military test and training mission at many installations. Improved interannual forecasting of fire activities in the 1 – 10-year timescale will allow resource managers to more effectively optimize fuel treatments that sustain mission activities.

Wildfire risk and assessment tools provide essential evaluations of wildfire hazards at a variety of time and spatial scales for general prioritization of resources across many agencies (e.g, https://www.usgs.gov/tools/usgs-wildfire-hazard-and-risk-assessment-clearinghouse). These approaches use a variety of environmental data and methods for analyzing wildfire risk, but few have been validated at installation scales for operational application. Moreover, few if any current approaches show dynamic skill for projecting fire activities and fire environmental conditions at 1–10-year time horizons, which would allow for budget planning for resources or mission planning for risks. Many also are either static or infrequently updated for fuel or vegetation data used to make the assessment.

Equally important is the forecasting of prescribed burning opportunity. The DoD applies nearly 800,000 acres of prescribed fire annually across all Services to reduce ordnance-caused wildfires and manage fire dependent threatened or endangered species habitat. Tools to project prescribed burning opportunities are increasing, but are currently needed at time horizons that budgets and staffing can adjust to projected conditions. Since prescribed fire is the primary treatment on DoD lands for wildfire risk reduction, interannual optimization of treatments would greatly benefit from skilled projections of fire-relevant environmental conditions in the 1-10-year “weather-to-climate” continuum.

Forecasting in this weather-to-climate continuum has received considerable investment in recent years, including artificial intelligence approaches. Demonstrating and evaluating these emerging tools for their ability to assess wildfire activity or prescribed fire opportunities will dramatically improve the options available to natural resource managers, mission planners, and DoD partners.