Components Anemoi comprises several packages written in the Python programming language. These packages address different aspects of the artificial intelligence (AI) weather forecasting pipeline.

Weather forecasting is complex and challenging. The process entails three steps: observation, analysis and communication.

AI-powered forecasting models are trained on historical weather data that goes back decades, which means they are great at predicting events that are similar to the weather of the past.

Traditionally, weather forecasting relies on complex numerical weather prediction models which require vast amounts of data and supercomputers - like the ones used by the Met Office.

Aurora, an AI foundation model revolutionizes weather and environmental forecasting with accuracy, speed and efficiency.

Weather forecasting improves with AI, but we still need humans Advanced systems from Microsoft and Google are already outperforming traditional forecasting models.

The Aardvark Weather system will be several thousand times faster than current forecasting methods, and more accurate.

A Microsoft model can make accurate 10-day forecasts quickly, an analysis found. And, it’s designed to predict more than weather.