On 7 January 2025, a series of devastating wildfires started in Los Angeles. Aided by extensive drought conditions and Santa Ana winds, the fires quickly spiralled out of control. The fires had significant impacts in the wildland–urban interface, where human development meets natural vegetation. The flames devastated thousands of buildings. Lives were tragically lost, and nearly 200,000 residents were forced to evacuate. The Palisades and Eaton fires burned for weeks, overwhelming firefighting efforts. With economic losses projected at $150 billion, this disaster ranks among the costliest in modern United States history.
ECMWF has been producing fire danger forecasts since 2018 as part of the Copernicus Emergency Management Service (CEMS). In recent years, ECMWF has been exploring new approaches to fire forecasting by leveraging advances in machine learning and ECMWF’s own weather prediction model, shifting from predicting fire danger to forecasting fire activity. In this analysis, we evaluate how the new kind of fire forecasting performed during these extraordinary events.
Dry vegetation
To fully understand why the Los Angeles fires were so extreme, we need to rewind to spring 2023. This was the start of an unusually wet period that lasted until late summer 2024, facilitating rapid vegetation growth. This wet period was followed by the exceptionally dry autumn and early winter of 2024 (Figure 1). An alternating pattern of wet and dry conditions – termed ‘hydroclimate whiplash’ – is not new in California but is being amplified by climate change and is likely to become more common. The sequence of wet and dry spells is visible in the Standardised Precipitation Evapotranspiration Index (SPEI), which is based on ECMWF’s ERA5 reanalysis. In southern California, this whiplash effect led to an abundance of dry and very flammable vegetation (Figure 1).
