ECMWF: “Our scientists have developed a new tool for improved wildfire prediction using machine learning (ML), as set out in a paper published on 1 April 2025 in Nature Communications. The paper describes how the collection and integration of higher-quality data can significantly improve the accuracy and reliability of wildfire predictions. It evaluates how our new data-driven fire danger forecasting model, the Probability of Fire (PoF), performed in 2023 and in recent extreme events. We have been producing fire danger forecasts since 2018 as part of the Copernicus Emergency Management Service (CEMS) led by the European Commission’s Joint Research Centre. In recent years, we have developed innovative approaches using ML methods. This has enabled us to move from predicting fire danger – a measure of landscape flammability – to forecasting fire activity. The new products, using the Probability of Fire model, are distributed to CEMS and are accessible to ECMWF Member States.”

• In addition to the Nature Communications paper, more details on the Probability of Fire model are contained in a recent ECMWF blog post and in a video explainer.