AI Beats Traditional Weather Models in Forecasting Wildfires
The European Centre for Medium-Range Weather Forecasts has incorporated AI into its fire danger forecasting system. The use of AI technology has led to more precise and timely predictions of fire risks. This advancement is crucial in helping authorities prepare for and mitigate the impact of wildfires. The implementation of AI is an example of how technology can enhance traditional forecasting methods.
Artificial intelligence is improving the accuracy of fire forecasts made by Europe’s top intergovernmental weather center. Traditional fire forecasts are largely based on weather models that predict temperature, humidity, wind speed, and precipitation. By contrast, the Probability of Fire model used by the European Centre for Medium-Range Weather Forecasts is powered by AI algorithms that analyze fire patterns, potential fuel sources, and human activity.
Improved Accuracy and Holistic Approach
The AI forecast more accurately predicts high-risk regions and can more closely pinpoint hotspots where fires are likely to ignite, researchers found. The AI model is also better at factoring in human activity — the primary spark of most wildfires. It takes a more holistic approach, as stated by Francesca Di Giuseppe, who co-wrote the research and leads a division at the center that evaluates forecasts.
Increasing Need for Accurate Forecasting
As the planet heats up and weather whiplash spreads, compound weather events are raising risks across the globe, increasing the need to accurately forecast extreme weather events as wildfires threaten countries from South Korea to Greece.
AI Improvements in Data Analysis
The biggest AI improvement comes from better data on potential fuel sources, which are hard to observe and account for in weather-based forecasts like the Fire Weather Index. The AI model uses weather information and draws from 19 different datasets, including satellite images that can distinguish between living and dead plants, while also identifying population and road density, and proximity to urban areas.
Forecast Accuracy and Climate Change
Researchers found that the AI models were able to improve forecasts by 30% by adding in more detailed fuel data. The AI model also better predicts how climate change is altering fire conditions, including the distinct pattern of increased flammability created by anomalies such as wet periods followed by hot, dry periods.
Testing and Validation
Researchers tested the AI model by comparing forecasts for wildfires, including the January 2025 blaze that ravaged Southern California. The AI model better predicted specific areas where fires eventually ignited, showcasing its effectiveness in providing accurate fire forecasts.
Development and Implementation
The AI fire forecast was developed in 2023 by the center’s meteorologists, who believed that machine learning techniques would eventually surpass conventional methods and deliver crucial weather predictions with greater accuracy and speed. The center released a general AI model in February, the first from a major forecast agency, which is already being utilized by regional met offices and traders seeking an edge in Europe’s volatile energy market.