As world leaders begin their discussions at the COP30 conference in Brazil the launch of a new system claims to have created the ability to forecast deadly heatwaves weeks and months before they arise.
With heatwaves among Europe’s deadliest climate hazards, a team of scientists led by CMCC has developed a prediction system capable of providing helpful information 4 to 7 weeks before summer, which gives valuable time to improve preparedness.

Trained on data from centuries of climate analysis up to recent years, the machine learning system has demonstrated an increase in forecast efficiency by drastically reducing the computational resources required, making these techniques accessible to a broader number of researchers and institutions.

Key benefits include:

• Enhanced prediction capability: Machine learning-based system matches and, in some cases, outperforms traditional forecasting systems, with particular improvements in northern Europe where conventional methods struggle.
• Critical timing insights: Greatest forecast skill comes from atmospheric predictors 4-7 weeks before summer (mid-March), providing optimal lead time for preparation measures.
• Lives and livelihoods at stake: Early warning capability could help the agricultural industry and health services implement effective strategies against heatwaves, which cause increased mortality and economic losses across Europe.
• Cost-effective innovation: The new approach requires far less computational power when compared to traditional systems, making seasonal forecasting far more accessible.
• Successful model-to-reality transfer: The system accurately forecasts real-world heatwaves from 1993-2016, including extreme events like 2003 and 2015.

The study Seasonal forecasting of European heatwaves using a feature selection framework, highlights how machine learning (ML) and artificial intelligence (AI) techniques are revolutionising climate science by enabling more accurate, cost-effective predictions than traditional approaches. Furthermore, where conventional dynamical forecasting systems require massive computational resources and struggle with reliability in northern European regions, this data-driven approach offers an alternative.

“ML will become a fundamental part of how we study climate variability,” said CMCC scientists Ronan McAdam. “This study has demonstrated the usefulness of ML in extreme event prediction, but it is only a first step in defining how we do that to receive interpretable and physically meaningful results.”

The team added heatwaves cause devastating impacts across Europe, including agricultural losses, energy usage spikes, health crises, and increased mortality. Recent deadly events in 2003, 2010, and 2022 underscore the urgent need for early warning systems that can help dampen the impacts of heatwaves. This is particularly important as climate projections suggest further intensification of heatwaves in the coming decades, making accurate seasonal forecasting crucial for saving lives.

“Early warning of extremely hot summers could help society prepare to mitigate against economic losses and reduce risk to life,” McAdam explained. “Seasonal forecasts made in spring can, in principle, state whether a summer will be warmer than average.”

“Our research has successfully extended data-driven ML-based forecasting to the seasonal timescale using a tiny fraction of the computational resources of traditional approaches,” McAdam noted.

The team explained by providing reliable seasonal forecasts of extreme heat months in advance, the system enables proactive measures to reduce heatwave impacts on society and the economy. This opens new possibilities for climate services across sectors including agriculture, public health, energy management and emergency planning, as well as creating an opportunity to combine ML approaches with the dynamical system produced by CMCC and therefore leverage the strengths of both approaches.

The framework also has the potential to be adapted for other extreme events, start dates and target seasons, representing a significant milestone in CMCC’s mission to advance climate science through innovative methodologies, and establish new standards for seasonal forecasting and climate risk assessment.

Heatwaves cause devastating impacts across Europe, including agricultural losses, energy usage spikes, health crises, and increased mortality. Recent deadly events in 2003, 2010, and 2022 underscore the urgent need for early warning systems that can help dampen the impacts of heatwaves. This is particularly important as climate projections suggest further intensification of heatwaves in the coming decades, making accurate seasonal forecasting crucial for saving lives.