Met Office study finds probability forecasts improve weather decisions

“Just small changes in starting conditions can result in big changes to forecasts,” said Ken Mylne, Met Office Science Fellow and author of the study.

Probability-based weather forecasts can significantly improve decision-making by giving users a clearer picture of uncertainty, according to new peer-reviewed research from the UK Met Office.

Published in the Royal Meteorological Society’s journal Weather and funded by the Public Weather Service, the study brings together 25 years of Met Office research for the first time, making the case for probabilistic forecasting as a core pillar of modern weather prediction.

The findings challenge the long-held assumption that the public struggles to understand uncertainty in forecasts and show that probability-based information can, in fact, be more useful and empowering for people making weather-sensitive decisions.

Why probability matters in forecasting

Traditional TV weather forecasts usually show a single, deterministic outcome—one predicted version of future weather. In contrast, probability-based forecasts rely on ensemble forecasting, a technique that runs weather models 20–50 times using slightly different starting conditions.

These multiple simulations produce a range of possible outcomes, allowing forecasters to assess likelihoods and risks, rather than presenting weather as a single fixed prediction.

“Just small changes in starting conditions can result in big changes to forecasts,” said Ken Mylne, Met Office Science Fellow and author of the study. “Ensemble forecasting captures that uncertainty and turns it into actionable information.”

The Met Office has been a global pioneer in ensemble forecasting, with research dating back to 1986, initially for month-ahead outlooks. Evidence accumulated over decades now shows ensembles consistently deliver better predictive skill than single-run forecasts.

Public understanding is not the barrier once feared

A key finding of the study is that public understanding of probability is stronger than previously assumed.

While uncertainty has often been communicated informally—through presenters’ language or the familiar “percentage chance of rain” in apps—the research finds that people are capable of interpreting probabilistic information and using it effectively.

“Previous thinking assumed probabilities might confuse people or undermine trust,” Mylne said. “Our research suggests the opposite. People can understand probabilistic forecasts and often find them more useful for making decisions.”

The paper also explores clearer visual ways to present probabilities, such as combined weather symbols, pie charts or multiple icons, to improve rapid comprehension.

Shaping the future of UK forecasting

The findings align closely with the Met Office Research and Innovation Strategy, which places uncertainty-inclusive forecasting at the centre of future operations.

The Met Office has already begun rolling out this approach through:

• Blended Probabilistic Forecasts on its website and app

• In-depth YouTube forecasts such as Deep Dive and 10 Day Trend, which explain ensemble signals and uncertainty

According to Charles Ewen, Met Office Chief Information and Data Officer, the research bridges science and public value.

“These papers help people understand that every forecast has built-in uncertainty,” Ewen said. “Ensembles allow us to calculate and communicate that uncertainty in a practical way—helping the public, industry and government make better risk-based decisions.”

As extreme weather becomes more frequent and impactful, the Met Office says probability-based forecasting will be increasingly vital in supporting resilience, safety and informed choices across all sectors.