Emerging energy signals advance early warnings of extreme precipitation
Year: 2026
Type: article
Abstract: The increasing frequency and intensity of extreme precipitation events pose growing societal risks, underscoring the urgent need for effective early warning systems. Forecasting such events at subseasonal-to-seasonal timescales, however, remains a major scientific challenge. Utilizing Seasonal Forecast System version 5 from the European Centre for Medium-Range Weather Forecasts, here we show that introducing a total atmospheric energy proxy into forecasts substantially improves extreme precipitation prediction at subseasonal and longer timescales. This approach extends the effective forecast lead times from about one month by conventional methods to six months, and achieves more than tenfold increases in global prediction accuracy over the past two decades. The added predictive value of total energy has increased substantially in recent years, reflecting a strengthening relationship between total energy and extreme precipitation. These findings highlight the emerging energy signals that enhance predictability, offering promising opportunities for developing more reliable early warning systems in a warming future. This study introduces a total atmospheric energy proxy into precipitation forecasts, improving extreme precipitation prediction at sub-seasonal and longer timescales. Moreover, it shows that the predictive value added by total energy has grown substantially in recent years.
Source: Nature Communications
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $6,990
OpenAlex ID: W7141947053
