A new AI weather prediction system, Aardvark Weather, promises to deliver accurate forecasts tens of times faster and using thousands of times less computing power than current AI and physics-based forecasting systems.
The system, developed by researchers from the University of Cambridge, has been supported by the Alan Turing Institute, Microsoft Research and the European Centre for Medium Range Weather Forecasts.
It provides a blueprint for a new approach to weather forecasting with the potential to transform current practices. The results are reported in the journal Nature.
The current weather forecasts are generated through a complex set of stages, each taking several hours to run on powerful supercomputers. The system require significant time and large teams of experts.
More recently, research by Huawei, Google, and Microsoft has demonstrated that one component of this pipeline, the numerical solver (which calculates how weather evolves over time), can be replaced with AI resulting in faster and more accurate predictions. This combination of AI and traditional approaches is now being deployed by the European Centre for Medium Range Weather Forecasts.
But with Aardvark, researchers have replaced the entire weather prediction pipeline with a single, simple machine learning model. The new model takes in observations from satellites, weather stations and other sensors and outputs both global and local forecasts. This fully AI driven approach means that predictions are now achievable in minutes on a desktop computer.
“Aardvark reimagines current weather prediction methods offering the potential to make weather forecasts faster, cheaper, more flexible and more accurate than ever before, helping to transform weather prediction in both developed and developing countries,” said Professor Richard Turner from Cambridge’s Department of Engineering, who led the research. “Aardvark is thousands of times faster than all previous weather forecasting methods.”