Seasonal climate forecasting aims to estimate how likely it is for a particular geographical region to experience warmer or colder and wetter or drier than average conditions in the coming months. This is crucial information for weather-sensitive sectors like agriculture. Despite the chaos in the atmosphere, getting such a glimpse into the future is possible due to the presence of slowly evolving fields (e.g., sea surface temperature, soil moisture, snow cover) and phenomena (e.g., El Niño-Southern Oscillation) in the Earth system.

Given the pronounced and unavoidable uncertainty in predicting the long-term evolution of the Earth system, seasonal forecasts have to be probabilistic. To that end, probabilistic estimates about the average weather conditions in the months ahead are derived by running one or, ideally, several different models multiple times to produce an ensemble of equiprobable outcomes. Despite the ever-growing availability and accessibility of seasonal forecasts, it has to be emphasised that these long-term forecasts are characterised by significant uncertainty and aim to estimate the tendency in the monthly and seasonal evolution of average weather conditions. Daily and local weather conditions may differ significantly from the monthly average conditions in a broader region. Therefore, a seasonal forecasting system is neither built nor able to foresee extreme weather episodes, like heat waves and tropical cyclones, months in advance.

Explore the 2026 monthly seasonal outlooks conducted as part of the Augures! project below.

Agronomists at Wikifarmer are using Augures! seasonal outlooks to make data-driven predictions about how conditions might affect crops across Europe during the forecast period. They identify potential risks and advise farmers on management measures. See how farming stakeholders are applying our findings to make real-world recommendations!