China leads AI weather forecasting as extreme weather intensifies, Fengwu predicts typhoon within 30 minutes

China bets on AI weather forecasting as extreme weather intensifies

SHANGHAI, Aug 11 (Reuters) - As meteorologists tracked Typhoon Dolphin's, opens new tab path toward China in recent days, a new generation of artificial intelligence weather models worked alongside traditional forecasting systems, highlighting China's emergence as a leading player in the race to improve weather prediction. Chinese-developed systems, including Shanghai AI Laboratory-developed Fengwu, Huawei's Pangu and Fudan University's Fuxi, are among a handful of AI forecasting models that researchers say can generate forecasts much faster than conventional systems while matching or surpassing them on some measures of accuracy. For decades, weather prediction has relied on numerical models running on supercomputers that simulate atmospheric physics. AI models instead learn patterns from vast archives of ⁠historical weather observations and can produce forecasts in a fraction of the time. The technology is increasingly being tested during typhoon season in East Asia, where even small improvements in track forecasts can help authorities better prepare for flooding, organise evacuations and manage potential transport disruptions. The rise of AI weather forecasting has created a new arena of competition among technology companies, research institutes and meteorological agencies, with China emerging as one of the field's leading players. Among the best-known AI forecasting systems globally are Google's (GOOGL.O), opens new tab GraphCast and GenCast, Nvidia-backed (NVDA.O), opens new tab FourCastNet and the European Centre for Medium-Range Weather Forecasts' AI Forecasting System, known as AIFS. 'PEOPLE NEED INFORMATION' Fengwu attracted attention after developers reported it outperformed GraphCast across roughly 80% of evaluated weather variables and extended skilful global medium-range forecasts beyond 10 days. "With more extreme weather, people need information to make ⁠decisions, both local governments, the national government, also the average person, farmers and fisherman," said Sun Zhi, the CTO of Techwind, the company responsible for Fengwu's industrial applications. "So we want to help provide better information so people can make decisions." While AI systems are becoming an increasingly important complement to conventional forecasting because of their speed and lower computing costs, they are unlikely to fully replace traditional weather models in the near future. According to ⁠Techwind's Sun, AI models are already capable of predicting the path of typhoons -- five days out from Dolphin's landfall Fengwu predicted the time and place it would hit mainland China to within 30 minutes and 30 km (19 miles) -- but they still lag conventional weather forecasts in predicting the intensity of a ⁠storm and they are still untested predicting major climate developments. "If we predict a climate change event 18 months in advance, people won't believe it," Sun said. "They need to know it's reliable. We need to do years of scientific research before people trust us when we ⁠say there will be an El Nino event or we say the changing temperature on the sea's surface will affect the breeding cycle of fish." As the tech forecasters work to make their systems ever more sophisticated, the concurrent use of both methods is likely to continue for some time. Reporting by Casey Hall and Chenxi Yang in Shanghai; Editing by Kate Mayberry Our Standards: The Thomson Reuters Trust Principles., opens new tab * Suggested Topics: * Environment Casey Hall Thomson Reuters Casey is the Shanghai bureau chief and a senior correspondent covering companies in China, reporting on the biggest issues facing local and global businesses operating in the world's second largest economy. The Australian-born journalist has been based in Shanghai since 2007.

China bets on AI weather forecasting as extreme storms close in

Three Chinese models are closing the gap on Western labs, and one reportedly pinned a typhoon's landfall to within half an hour, though the hardest forecasts still elude them all. As Typhoon Dolphin bore down on China's coast this week, the country's bet on artificial intelligence to read the skies looked less like a research curiosity and more like national infrastructure. Extreme weather is intensifying, the cost of getting a forecast wrong is rising, and Beijing is pouring resources into models that promise to see storms coming sooner and cheaper than the supercomputers that have long done the job. Three home-grown systems lead the effort. Fengwu comes from the Shanghai AI Laboratory, Pangu from Huawei, and Fuxi from Fudan University, a spread that puts a state lab, a tech champion, and a leading university into the same race. It is a very Chinese arrangement, and a deliberate one, since forecasting has quietly become a field where AI supremacy carries real-world stakes. The headline claims are striking. Fengwu reportedly outperformed Google DeepMind's GraphCast across roughly 80% of the weather variables it was tested on, and pushed skilful forecasts beyond the ten-day mark that has traditionally marked the edge of usefulness. If the numbers hold up to independent scrutiny, they suggest the gap with the West is not merely narrowing but, on some measures, closing. Dolphin offered a vivid test. Five days before the storm made landfall on the mainland, Fengwu predicted the time and place of impact to within 30 minutes and 30km, or about 19 miles, according to Sun Zhi of the firm Techwind. That is the kind of precision that turns an evacuation order from guesswork into logistics, and it is precisely what governments want when a typhoon is still a working week away and every hour of warning buys another town the time to move people and boats out of harm. AI forecasters generate their predictions far faster than conventional numerical weather prediction, and they lean on a fraction of the computing power, which is why the approach has spread so quickly from research papers to operational trials. For a country that runs some of the world's most weather-exposed agriculture and coastline, speed and cost are not footnotes. "With more extreme weather, people need information to make decisions, both local governments, the national government, also the average person, farmers and fishermen," Sun said, framing the work less as a benchmark contest than as a public service for people whose livelihoods hinge on the next front coming in off the sea. Yet the caveats are real, and China's forecasters are candid about them. AI models still lag traditional methods at predicting storm intensity, which is the difference between a manageable blow and a genuine catastrophe, and they remain untested against major, longer-term climate developments that fall outside the historical data they learned from. A model brilliant at where a storm lands can still be shaky on how hard it hits, and a warming climate keeps serving up conditions no training set has seen before. The wider contest gives the effort its edge. China is chasing a Western field that has moved fast, from DeepMind's probabilistic GenCast system to Nvidia-backed FourCastNet and the European Centre for Medium-Range Weather Forecasts' AIFS, with well-funded startups piling in as well. One Swiss firm has even claimed its forecaster beats Microsoft and Google, a sign of how crowded and combative the space has become. What makes weather an unusually revealing arena for the AI rivalry is that the referee is physics. A chatbot can be graded on taste, but a typhoon forecast is either right or it is not, and the ground truth arrives on schedule. As the planet warms and the storms grow fiercer, China is wagering that the side which reads the atmosphere fastest will hold an advantage that is measured not in benchmarks but in lives.

For decades, weather ⁠prediction ⁠has relied on numerical models running on supercomputers, now AI can produce forecasts in a fraction of the time. Will it be accurate? Here's what experts are saying

While AI systems are becoming an increasingly important complement to conventional forecasting because of their speed and lower computing costs, they are unlikely to fully replace traditional weather models in the near future, as per Reuters report. Chinese-developed systems, including Shanghai AI Laboratory-developed Fengwu, Huawei's Pangu and Fudan University's Fuxi, are among a handful of AI forecasting models that researchers say can generate forecasts much faster than conventional systems while matching or surpassing them on some measures of accuracy. For decades, weather ⁠prediction ⁠has relied on numerical models running on supercomputers that simulate atmospheric physics. AI models instead learn patterns from vast archives of historical weather observations and can produce forecasts in a fraction of the time. The technology is increasingly being tested during typhoon season in East Asia, where even small improvements in track forecasts can help authorities better prepare for flooding, organise evacuations and manage potential transport disruptions. The rise of AI weather forecasting has created a new arena of competition among technology companies, research institutes and meteorological agencies, with China emerging as one of ⁠the field's leading players. Among the best-known AI forecasting systems globally are Google's GraphCast and GenCast, Nvidia-backed FourCastNet and the European Centre for Medium-Range Weather Forecasts' AI Forecasting System, known as AIFS. You Might Also Like: In 1950, world witnessed strongest El Nino but weather forecasters warn of more powerful climate phenomenon that will push nearly 49 million people ⁠into acute food insecurity Weather Forecast Fengwu attracted ⁠attention after developers reported it outperformed GraphCast across roughly 80% of evaluated weather variables and extended skilful global medium-range forecasts beyond 10 days. "With more extreme weather, people need information to make decisions, both local governments, the national government, also the average person, farmers and fisherman," said Sun Zhi, the CTO of Techwind, the company responsible for Fengwu's industrial applications. "So we want to help provide better information so people can make decisions." While AI systems are becoming an increasingly important complement to conventional forecasting because of their speed and lower computing costs, they are unlikely to fully replace traditional weather models in the near future, as per Reuters report. According to Techwind's Sun, AI models are already capable of predicting the path of typhoons -- five days out from Dolphin's landfall Fengwu predicted the time and place it would hit mainland China to within 30 ⁠minutes and 30 km (19 miles) -- but they still lag conventional weather forecasts in predicting the intensity of a storm and they are still untested predicting major climate developments. "If we predict a climate change event 18 months in advance, people won't believe it," Sun said. "They need to know it's reliable. We need to do years of scientific research before people trust us when we say there will be an El Nino event or we say the changing temperature on the sea's surface will affect the breeding cycle of fish." As the tech forecasters work to make their systems ever more sophisticated, the concurrent use of both methods is likely to continue for some time.

China's AI weather forecasting takes a major step forward

Models deliver faster, cheaper forecasts and earlier typhoon warnings China's push into AI weather forecasting just took a big step forward. Models built in China, including Shanghai AI Laboratory's Fengwu, Huawei's Pangu-Weather, and Fudan University's Fuxi, can produce forecasts in minutes and at a fraction of the computing cost of traditional physics-based models that run on supercomputers, at least according to the teams behind them. That matters more as extreme weather keeps showing up more often. The biggest shift is speed. Chinese researchers say that if forecasts come back faster, you can run more scenarios, update warnings more frequently, and maybe get alerts out earlier for typhoons, floods, and heatwaves. Those same researchers point to one Typhoon Dolphin forecast that put landfall within 30 minutes and 30 kilometers, five days in advance. China is also moving hard against Western rivals such as Google's GraphCast and GenCast, Nvidia-backed FourCastNet, the European Centre for Medium-Range Weather Forecasts, and new global models from the US National Oceanic and Atmospheric Administration. Chinese teams say Fengwu outperformed GraphCast on about 80% of the variables they tested, and they think it could eventually extend useful forecasting past the 10-day mark. If weather alerts affect how you travel, farm, price insurance, or just plan your day, this is something to keep an eye on. Even so, experts say the older models still tend to do a better job with storm intensity and the rare, record-breaking events, and a lot of the splashier claims still need independent, peer-reviewed testing at scale. You can't download most of these systems yet. Still, the Chinese teams behind them are pushing open-source tools and outside partnerships, including projects with Thailand and Djibouti.

China bets on AI weather forecasting as extreme weather intensifies

As meteorologists tracked Typhoon Dolphin's path toward China in recent days, a new generation of artificial intelligence weather models worked alongside traditional forecasting systems, highlighting China's emergence as a leading player in the race to improve weather prediction. Chinese-developed systems, including Shanghai AI Laboratory-developed Fengwu, Huawei's Pangu and Fudan University's Fuxi, are among a handful of AI forecasting models that researchers say can generate forecasts much faster than conventional systems while matching or surpassing them on some measures of accuracy. For decades, weather prediction has relied on numerical models running on supercomputers that simulate atmospheric physics. AI models instead learn patterns from vast archives of ⁠historical weather observations and can produce forecasts in a fraction of the time. The technology is increasingly being tested during typhoon season in East Asia, where even small improvements in track forecasts can help authorities better prepare for flooding, organize evacuations and manage potential transport disruptions. The rise of AI weather forecasting has created a new arena of competition among technology companies, research institutes and meteorological agencies, with China emerging as one of the field's leading players. Among the best-known AI forecasting systems globally are Google's, GraphCast and GenCast, Nvidia-backed, FourCastNet and the European Centre for Medium-Range Weather Forecasts' AI Forecasting System, known as AIFS. 'People need information' Fengwu attracted attention after developers reported it outperformed GraphCast across roughly 80% of evaluated weather variables and extended skilful global medium-range forecasts beyond 10 days. "With more extreme weather, people need information to make ⁠decisions, both local governments, the national government, also the average person, farmers and fisherman," said Sun Zhi, the CTO of Techwind, the company responsible for Fengwu's industrial applications. "So we want to help provide better information so people can make decisions." While AI systems are becoming an increasingly important complement to conventional forecasting because of their speed and lower computing costs, they are unlikely to fully replace traditional weather models in the near future. According to ⁠Techwind's Sun, AI models are already capable of predicting the path of typhoons -- five days out from Dolphin's landfall Fengwu predicted the time and place it would hit mainland China to within 30 minutes and 30 km (19 miles) -- but they still lag conventional weather forecasts in predicting the intensity of a ⁠storm and they are still untested predicting major climate developments. "If we predict a climate change event 18 months in advance, people won't believe it," Sun said. "They need to know it's reliable. We need to do years of scientific research before people trust us when we ⁠say there will be an El Nino event or we say the changing temperature on the sea's surface will affect the breeding cycle of fish." As the tech forecasters work to make their systems ever more sophisticated, the concurrent use of both methods is likely to continue for some time.

How is China using AI for weather forecasting during typhoon season?

STORY: :: Why is China betting on AI-powered weather forecasts? "China has been using these AI weather prediction models to help track the progress of typhoons during the typhoon season. :: Shanghai, China / August 11, 2026 :: Casey Hall, Shanghai Bureau Chief "The way these AI models work is that they can use vast historical weather pattern data and be able to predict what's going to happen next. And they have proven to be very accurate, especially at tracking the flight paths of typhoons. The recent Typhoon Dolphin that made landfall in China over the weekend, five days out from that landfall, they were able to predict it to within 30 minutes and 30 kilometers." :: How does AI forecasting differ from traditional methods? :: CSU/CIRA & JMA/JAXA "So the way that traditional forecasting works is that the numerical models that are run through supercomputers to predict what's gonna happen with the weather. AI models are basically much, much faster and they use much less computing power than the traditional models do. They do have their strengths and weaknesses though. AI modules, for example, are very, very good at predicting the track of a typhoon, but they're still not as good as the traditional models at predicting the intensity of a storm." "Globally, I think people will know that there's huge companies like Google, like Nvidia, that have their own AI weather prediction models. In China, big companies like Huawei are also getting into this kind of AI weather-prediction game//Some of the leading Chinese players are very, very competitive, and they have been shown to be able to have accurate forecasts beyond 10 days, which even globally is quite impressive." "I don't think these AI weather predicting models are going to replace the traditional ways that we predict weather. I think they're probably going to be used concurrently for quite some time, just because the strengths and weaknesses are quite different."