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Fire and Emergency Management Agencies

Next-Generation Forecasting Tools

Pyregence is creating next-generation models to forecast fire risk in the coming week—and for the rest of the century. We are pioneering new research into weather, fuels, and wildfire, and feeding this data into both near- and long-term risk models.

Thanks to these innovations, Pyregence’s near-term wildfire forecasting models will provide the fastest and most accurate forecasts available, ensuring that decision-makers have the critical forecasts they need as quickly as possible. And our long-term climate change and fire projection models provide a range of projections of wildfire risk in coming decades, promoting effective policy, planning, and risk mitigation.

Wildfire Forecasting

We provide the forecasts fire and emergency management agencies need to get ahead of the curve. Understand risk and take action. Protect workers and the public.

Identify which segments of the electric grid are vulnerable to wind-caused ignitions or damage from active fires.

Make decisions regarding when and where to deploy firefighting crews and undertake suppression efforts.

Create plans for wildfire response based on varying risks faced by different areas.

Decide how to manage wildland fuel loads using controlled burns and mechanical treatments.

Forecast Application: PyreCast™

Our web tool provides several forecasts, including active fire spread, fire weather danger, and fire risk

Fire Forecasting
User’s Guide
Guide provides instructions on using the near-term risk forecast outputs
Fire Forecasting Data
Datasets include input and output data from near-term forecast models
Fire Forecasting Code
Repository contains programming code used to run near-term spread and risk forecast models

Learn more about the Wildfire Forecasting tool on the team page.

Climate Change & Fire Projection

Draw on fire-risk projections for coming decades to manage fuels, write building codes, and adjust policy.

Know where to conduct fuel-reduction operations through prescribed burns or mechanical treatments.

Assess the public health threats posed by smoke emissions from wildfires.

Require risk reduction measures such as minimum street width, secondary access routes, and adequate water supplies in new developments.

Use building codes and other incentives to require use of ignition-resistant construction materials and removal of flammable materials around structures.

Encourage agricultural lands, athletic fields, and recreational paths on the outskirts of cities to serve as firebreaks and buffers between wildland fires and developed areas.

Wildfire Projection-Related Research Papers

This web page hosts peer-reviewed research papers and other publications based on the work of the Climate Change and Fire Projections team.

Long-Term Wildfire Projection Datasets

Datasets will include input and output data from long-term projection models.

Learn more about the Climate Change Projection tool on the team page.


The ability to assess and forecast wildfire risk based on weather conditions and other environmental factors such as fuel load is critical. Want to learn more about the research we’re advancing in these areas? Visit the following pages.

Extreme Weather and Wildfire

This team will ensure that utility companies and government agencies have the fire weather forecasts they need to make life-saving decisions. Using machine learning and wildfire simulation techniques, our scientists are evolving our understanding of the relationship between weather conditions and wildfires.

Forest Fuels and Fire Behavior

To understand fire behavior, you must first understand fuel loads. We’re improving the accuracy of fire behavior forecasting by increasing our understanding of the fuels available on the forest floor. Our scientists will map the current amount, types, and distribution of fuels, and project future fuel loads over the next 10–20 years. We’re also conducting laboratory experiments to better understand how different sizes and types of fuels burn under varying weather conditions.


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