A single researcher with a desktop computer will be able to deliver accurate weather forecasts using a new AI weather prediction approach that is tens of times faster and uses thousands of times less computing power than conventional systems.
Weather forecasts are currently generated through a complex set of stages, each taking several hours to run on bespoke supercomputers, requiring large teams of experts to develop, maintain and deploy them.
Aardvark Weather provides a blueprint to replace the entire process by training an AI on raw data from weather stations, satellites, weather balloons, ships and planes from around the world to enable it to make predictions.
This offers the potential for vast improvements in forecast speed, accuracy and cost, according to research published on Thursday in Nature from the University of Cambridge, the Alan Turing Institute, Microsoft Research and the European Centre for Medium-Range Weather Forecasts (ECMWF).
Richard Turner, a professor of machine learning at the University of Cambridge, said the approach could be used to quickly provide bespoke forecasts for specific industries or locations, for example predicting temperatures for African agriculture or wind speeds for a renewable energy company in Europe.
This contrasts to traditional weather prediction systems where creating a customised system takes years of work by large teams of researchers, while supercomputers take hours to process measurements from the real world in order to build forecasting models.
“This is a completely different approach to what people have done before. The writing’s on the wall that this is going to transform things, it’s going to be the new way of doing forecasting,” Turner said. He said the model would eventually be able to produce accurate eight-day forecasts, compared with five-day forecast at present, as well as hyper-localised predictions.
Dr Scott Hosking, the director of science and innovation for environment and sustainability at the Alan Turing Institute, said the breakthrough could “democratise forecasting” by making powerful technologies available to developing nations around the world, as well as assisting policymakers, emergency planners and industries that rely on accurate weather forecasts.
Dr Anna Allen, the lead author of the paper, from the University of Cambridge, noted that the findings paved the way for better forecasts of natural disasters such as hurricanes, wildfires and tornadoes, as well as other climatic issues such as air quality, ocean dynamics and sea ice predictions.
Aardvark builds on recent research by Huawei, Google, and Microsoft demonstrating that one step of the weather prediction process known as the numerical solver, which calculates how weather evolves over time, can be replaced with AI to produce faster and more accurate predictions. This approach is already being deployed by the ECMWF.
The researchers said that using just 10% of the input data that existing systems required, Aardvark could already outperform the US national GFS forecasting system in certain respects, and was competitive with United States Weather Service forecasts.
