China Deploys Homegrown AI Chips to Power High-Resolution Global Weather Forecasting

China says it has developed a weather forecasting system capable of producing global forecasts up to 10 days ahead at a 5-kilometre resolution, using a domestically developed computing system powered entirely by Chinese-made AI chips.

The system was developed by the China Meteorological Administration and Beijing-based computing company Sugon, which announced the results on Tuesday. The companies said the model can generate a 10-day global forecast in about one hour on the Sugon 8,000 computing platform.

The claimed resolution places the system at the finer end of the range used by major operational forecasting systems. The China Meteorological Administration and Sugon said many global systems operate at roughly 5km to 10km resolution, while the U.S. National Weather Service's Global Forecast System operates at a maximum resolution of about 13km.

This development matters because higher-resolution forecasting requires substantially more computing power. Numerical weather models divide the atmosphere into a three-dimensional grid and calculate changes in variables including wind, temperature, pressure, and moisture. Smaller grid cells allow models to represent weather systems in greater detail, but the computational burden rises sharply.

Halving the distance between grid points, for example, can require roughly eight times as much computing power.

The Chinese team has already tested the forecasting model, known as the Mesoscale Convective Vortex, at a global resolution of 3km, according to Sugon. That work brings the system closer to targets outlined in China's latest five-year meteorological plan, which calls for 1km nationwide forecasts and resolutions as fine as 100 meters in key areas by 2030.

The model runs on Sugon 8,000, a computing cluster unveiled in July that links about 100,000 computing units capable of carrying out calculations simultaneously.

Sugon says the system differs from conventional supercomputers because it is designed to handle both traditional high-precision scientific calculations and AI workloads. Conventional supercomputers are generally optimized for precise numerical simulations, while AI systems are designed to process large quantities of data efficiently, often using lower numerical precision.

Sugon 8,000 combines the two approaches and uses domestically developed chips, storage, and networking technology. The weather forecasting test also serves as a demonstration of China's effort to build large-scale computing infrastructure without relying on foreign semiconductor technology.

The one-hour processing time is not, by itself, a global speed record. Sugon said the U.S. Global Forecast System has completed a 10-day forecast in roughly 45 minutes during testing. China's claim is instead that its system can deliver the higher-resolution forecast within a timeframe suitable for routine forecasting operations.

That is considered a feat because operational forecasting is not simply about producing the most detailed model possible. A forecast that arrives too late can have limited practical value. Completing the calculation within roughly an hour can give meteorologists additional time to assess developing threats and issue warnings.

Sugon said the system could help forecasters monitor typhoons, heavy rainfall and other severe weather events by providing more detailed information on atmospheric conditions.

The computing platform has applications beyond meteorology. According to Sugon, Sugon 8,000 has been adapted for nearly 200 applications and more than 500 mainstream AI models across more than 30 research and industrial fields. Those applications include protein research, molecular dynamics, and turbulence simulations.

The broader significance is the combination of AI computing and numerical simulation on domestically produced infrastructure. Weather forecasting is one of the most computationally demanding scientific applications, requiring enormous quantities of calculations to be repeated as new observations become available.

But some analysts believe that China's push toward finer resolution depends not only on improvements in forecasting models but also on access to sufficient computing capacity. That means its 2030 targets would require another substantial increase in processing capability, particularly for forecasts covering the entire country at 1km resolution and selected areas at 100 meters.

The reported results also indicate that the competition in AI computing has extended beyond commercial chatbots and generative models. Scientific computing, weather prediction and other simulation-heavy workloads are becoming another arena in which countries are seeking greater domestic control over chips, computing systems and software.

The Chinese announcement does not establish that its forecasting system is more accurate than the leading operational systems. Resolution measures the size of the model's grid cells, while forecast skill depends on factors including the underlying model, observations, data assimilation and the ability to represent atmospheric processes.

However, the reported ability to produce a 10-day global forecast at 5km resolution within about an hour, on domestically produced chips, represents a substantial computing exercise and marks another step in China's push toward high-resolution, domestically powered scientific computing.