A plain-language explanation of how a machine learning model forecasts the weather
No equations of fluid motion, just forty years of recorded weather and a very large pattern-matcher. It works surprisingly well.
Traditional forecasts simulate the atmosphere with physics, hour by hour, on supercomputers. The new models skip the physics: trained on decades of past weather, they learn what tomorrow tends to look like given today. (Various 2024)
Independent evaluations now find the learned models matching or beating the physics-based systems on most measures, in minutes rather than hours.
Why it matters here
Cheap, fast forecasts are most valuable where supercomputers are scarce. Satellite data provides the inputs almost everywhere. (European Space Agency 2025)
References
European Space Agency. 2025. “Earth observation missions.”. https://www.esa.int/Applications/Observing_the_Earth.
Various. 2024. “Deep learning for weather prediction: a review.” Nature vol. 620. https://www.nature.com/.
Cite this story
Dispatch Report (2026) ‘A plain-language explanation of how a machine learning model forecasts the weather’, 16 September. Available at: https://thedispatchreport.com/article/a-plain-language-explanation-of-how-a-machine-learning-model-forecasts-the-weath (Accessed: 5 October 2026).
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