* Researchers say Chinese AI models match or surpass

conventional forecasts on some measures

* AI models deliver forecasts far faster than physics-based

supercomputer systems

* AI still lags conventional models in predicting storm

intensity

By Casey Hall and Chenxi Yang

SHANGHAI, Aug 11 (Reuters) - 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,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 ( NVDA )-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.