HQ Team
April 1, 2025: Aardvark Weather, an artificial intelligence weather predicting system, can deliver accurate forecasts tens of times faster and using thousands of times less computing power than current AI and physics-based forecasting systems, according to researchers.
The researchers at the University of Cambridge jointly developed the system with the help of the Alan Turing Institute, Microsoft Research and the European Centre for Medium Range Weather Forecasting, according to a statement.
The weather forecasts that people rely upon are currently generated through a complex set of stages, each taking several hours to run on powerful supercomputers.
Aside from daily usage, the development, maintenance and deployment of these complex systems require significant time and large teams of experts.
Cheaper forecasts
“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.”
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.
Simple design
One of the key aspects of Aardvark is its flexibility and simple design. Because it learns directly from data, it can be quickly adapted to produce bespoke forecasts for specific industries or locations, be that predicting temperatures for African agriculture or wind speeds for a renewable energy company in Europe.
This contrasts with traditional weather prediction systems where creating a customised system takes years of work by large teams of researchers.
This capability has the potential to transform weather prediction in developing countries where access to the expertise and computational resources required to develop conventional systems is not typically available, according to the statement.
“These results are just the beginning of what Aardvark can achieve. This end-to-end learning approach can be easily applied to other weather forecasting problems, for example, hurricanes, wildfires, and tornadoes,” said Anna Allen, lead author from the University of Cambridge.
“Beyond weather, its applications extend to broader Earth system forecasting, including air quality, ocean dynamics, and sea ice prediction.”
‘Democratise forecasting’
When using just 10% of the input data of existing systems, Aardvark already outperforms the United States national GFS forecasting system on many variables, and it is also competitive with United States Weather Service forecasts that use input from dozens of weather models and analysis by expert human forecasters.
“Unleashing AI’s potential will transform decision-making for everyone from policymakers and emergency planners to industries that rely on accurate weather forecasts. Aardvark’s breakthrough is not just about speed, it’s about access,” said Dr Scott Hosking, Director of Science and Innovation for Environment and Sustainability at The Alan Turing Institute.
“By shifting weather prediction from supercomputers to desktop computers, we can democratise forecasting, making these powerful technologies available to developing nations and data-sparse regions around the world.”
The team of researchers are exploring the potential to deploy Aardvark in the global south and integrating the technology into the Institute’s wider work to develop high-precision environmental forecasting for weather, oceans and sea ice.
