Latest news with #AardvarkWeather
The Guardian
09-05-2025
- Climate
- The Guardian
Weatherwatch: How AI could offer faster, affordable weather forecasting
Weather forecasting has gradually been getting more and more sophisticated. It has also got far more important as the climate gets more unpredictable and extreme events threaten to cause massive economic damage and loss of life. So an early warning system is vital. Ever larger computer systems making millions of calculations over many hours are now part of the daily forecasting in most developed countries. Sadly large parts of the world, many very vulnerable to dangerous climate events, do not have the money, personnel or computing power to develop the 10-day forecasting system they need. But researchers at Cambridge University think they have found a solution by harnessing artificial intelligence. They use AI to create advanced weather forecasts which they claim outperform supercomputers and are thousands of times faster, needing only the power of a laptop. Sign up to Down to Earth The planet's most important stories. Get all the week's environment news - the good, the bad and the essential after newsletter promotion Aardvark Weather, which has the backing of the Alan Turing Institute, Microsoft Research and the European Centre for Medium-Range Weather Forecasts, claims its system could replace current weather forecasting methods altogether. It would be able to give local forecasts, for example temperature extremes for African crops or wind speeds for European windfarms. Most importantly, it would give every developing country and thinly populated region a reliable forecast and an early warning system of potential disasters.
Axios
24-03-2025
- Science
- Axios
AI weather forecasting just took a big step forward
The field of AI-driven weather modeling is advancing at a rapid pace, as illustrated by a new model that has critical advantages over other approaches. Why it matters: Applying artificial intelligence to weather prediction holds the promise of significantly advancing forecast precision, reliability and delivery to the developing world. It could augment the role of human weather forecasters, providing them with another tool for forecasting extreme weather events as well as routine conditions. Driving the news: The new model is the result of an international effort among the University of Cambridge, Alan Turing Institute, Microsoft Research and European Centre for Medium-Range Weather Forecasts (ECMWF). Zoom in: The new model, detailed in a study in the journal Nature, is known as Aardvark Weather. It offers what its creators call an "end-to-end AI forecasting system." Previous AI models developed by technology giants like Nvidia and Google take in real-world observations and apply AI methods to predict how weather conditions would unfold over time. These models don't require supercomputers and can be run at a fraction of the time of regular physics-based numerical models like the U.S. Global Forecast System, or GFS. Yes, but: The AI models developed to date are still somewhat dependent on the work of traditional numerical systems at the initial step of incorporating vast amounts of weather data. What sets Aardvark Weather apart — and may usher in a new era in AI-driven models — is that it uses a single machine-learning model that takes in observations from satellites, weather stations, ships and other sensors, and yields high-resolution global and local forecasts. It doesn't involve traditional numerical weather models at any step of the process, setting it apart from other new AI systems. In other words, it's a purely AI-driven weather play. Aardvark also uses far fewer observations as inputs compared to both traditional models in use and other AI-driven ones. For this reason and others, it may not yet be suitable for government forecast agencies. Those agencies are generally responsible for producing forecasts with more variables, using models that assist with issuing extreme weather watches and warnings. The intrigue: The researchers tout Aardvark's ability to result in specially-tailored forecasts while being run on a desktop computer, providing results that are available within minutes. Importantly, they claim that even with just a fraction of the input data from current weather observations, the system outperforms the GFS model on particular variables and competes with National Weather Service forecasts made using a combination of modeling and human forecast expertise. Perhaps the biggest breakthrough of the new model is that its simplicity and the way it's designed to learn from input data can provide a means for tailoring forecasts for specific applications and regions. These could include forecasting wind speeds for renewable energy installations or predicting rainfall for agricultural interests. Currently, such hyper-focused models can take many months to years to develop and require supercomputers to run. Between the lines: The new, experimental model doesn't eliminate the need for real-world weather data gathering, conventional modeling or human forecasters. In fact, the study underlined the importance of real-time weather data gathered from satellites to ensure forecast accuracy, for example. It also couldn't have been developed without abundant training data that came in the form of a dataset ECMWF developed, known as the ERA5 reanalysis. While ECMWF has been at the forefront of developing and implementing AI models, NOAA is only beginning to travel down this road in the U.S., with the American private sector moving faster to capitalize on new technologies. The suitability of the new model to specific forecast circumstances could benefit the Global South, where high-performance computing is lacking. What they're saying: "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 Richard Turner, a study coauthor and researcher at the Alan Turing Institute and Cambridge University, in a statement.
Yahoo
20-03-2025
- Science
- Yahoo
AI breakthrough is ‘revolution' in weather forecasting
Cambridge scientists have made a major breakthrough in weather forecasting after developing a new AI prediction model that is tens of times better than current systems. The new model, called Aardvark Weather, replaces the supercomputers and human experts used by forecasting agencies with a single artificial intelligence model that can run on a standard desktop computer. This turns a multi-stage process that takes hours to generate a forecast into a prediction model that takes just seconds. 'Aardvark reimagines current weather prediction methods, offering the potential to make weather forecasts faster, cheaper, more flexible and more accurate than ever before,' said Richard Turner, a professor of machine learning in the Department of Engineering at the University of Cambridge. Tests of the Aardvark model revealed that it is able to outperform the United States national GFS forecasting system using just 10 per cent of the input data, leading researchers to say it could offer a 'revolution in forecasting'. The researchers noted that its simple design and ability to run on standard computers means it has the potential to be used to create bespoke forecasts for a huge range of industries – from predicting wind speeds for offshore European wind farms, to rainfall and temperature predictions for farmers in developing countries. '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." Anna Allen from the University of Cambridge, who led the research, added: '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. 'Beyond weather, its applications extend to broader Earth system forecasting, including air quality, ocean dynamics, and sea ice prediction.' The new AI weather model was detailed in a study, titled 'End-to-end data-driven weather prediction', published in the journal Nature. Sign in to access your portfolio
Yahoo
20-03-2025
- Science
- Yahoo
AI breakthrough is ‘revolution' in weather forecasting
Cambridge scientists have made a major breakthrough in weather forecasting after developing a new AI prediction model that is tens of times better than current systems. The new model, called Aardvark Weather, replaces the supercomputers and human experts used by forecasting agencies with a single artificial intelligence model that can run on a standard desktop computer. This turns a multi-stage process that takes hours to generate a forecast into a prediction model that takes just seconds. 'Aardvark reimagines current weather prediction methods, offering the potential to make weather forecasts faster, cheaper, more flexible and more accurate than ever before,' said Richard Turner, a professor of machine learning in the Department of Engineering at the University of Cambridge. Tests of the Aardvark model revealed that it is able to outperform the United States national GFS forecasting system using just 10 per cent of the input data, leading researchers to say it could offer a 'revolution in forecasting'. The researchers noted that its simple design and ability to run on standard computers means it has the potential to be used to create bespoke forecasts for a huge range of industries – from predicting wind speeds for offshore European wind farms, to rainfall and temperature predictions for farmers in developing countries. '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." Anna Allen from the University of Cambridge, who led the research, added: '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. 'Beyond weather, its applications extend to broader Earth system forecasting, including air quality, ocean dynamics, and sea ice prediction.' The new AI weather model was detailed in a study, titled 'End-to-end data-driven weather prediction', published in the journal Nature. Sign in to access your portfolio
The Guardian
20-03-2025
- Science
- The Guardian
AI-driven weather prediction breakthrough reported
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. Sign up to Headlines UK Get the day's headlines and highlights emailed direct to you every morning after newsletter promotion 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.
