Science Explainer #2: Can weather models predict power prices?

What is representation learning and how does it support smarter weather forecasting?

Sophie Xhonneux from ECMWF explores exactly that in the second WeatherGenerator Science Explainer.

The atmosphere is measured continuously by satellites, weather stations, and balloons, producing vast, overlapping datasets. Rather than training separate models on all of this data, WeatherGenerator learns a compressed, unified representation that captures the underlying physics of the atmosphere, enabling more efficient and powerful forecasting across applications.

Watch the video to hear Sophie explain the principles behind representation learning and its role in the WeatherGenerator project: