New Model Predicts Mega-Wildfires Before They Merge

Imagine knowing where lightning might spark the next mega-wildfire before it happens. Scientists just made that future possible.

Researchers at Lawrence Livermore National Laboratory developed a powerful new model that predicts when multiple small wildfires will merge into devastating super-fires. These rare but catastrophic events account for only 7% of California's fires but destroy 31% of burned land in the state.

The breakthrough centers on understanding fire-triggered thunderstorms called pyrocumulonimbus. When wildfires grow hot enough, they create massive updrafts that lift moisture into the sky, forming powerful storms that can spark new fires miles away from the original blaze.

"Although they are quite rare, their influence is large compared to single-ignition fires," said LLNL scientist Qi Tang. The model tracks these storm systems at kilometer-scale detail, showing exactly where new lightning strikes might ignite secondary fires.

California's August Complex fire in 2020 demonstrates the stakes. Ten separate ignition points merged into the largest fire in state history. In Siberia in 2021, 27 separate blazes converged into a single monster fire.

The research team used NASA satellite data to track past multi-ignition fires, then built simulations using the Department of Energy's flagship climate model. The system connects fire behavior with regional weather patterns to predict where convergence events might occur.

The Ripple Effect

This prediction tool could transform firefighting strategy. When multiple fire fronts develop, crews face deadly situations where new flames can suddenly surround them. Knowing where secondary ignitions might spark gives firefighters crucial time to position resources and evacuate safely.

The model's benefits extend beyond fire lines. Tang's team is already working to integrate predictions with power grid planning, helping utilities shut down equipment before fires start. NASA's 2026 field campaign will collect new data to make the model even more accurate.

California, Canada, and Siberia face the highest risk for these fire-triggered thunderstorms. The same atmospheric conditions that create summer afternoon storms can turn a manageable wildfire into an uncontrollable disaster when flames provide the initial heat source.

With climate change increasing wildfire frequency and intensity, this prediction tool arrives at a critical moment. Early warnings could help communities evacuate sooner, protect infrastructure before flames arrive, and give firefighters the information they need to stay safe while protecting others.

The research appears in Science Advances, offering firefighters and emergency managers a powerful new weapon against one of nature's most unpredictable threats.