The model, "FuXi-Subseasonal," developed by scientists from the Shanghai Academy of Artificial Intelligence for Science (SAIS), Fudan University, and China's National Climate Center, has a thousand-fold increase in operational speed, and higher forecasting accuracy and longer forecasting period than existing international authoritative models, local English daily Global Times reported citing team members who have developed the model.
"Climate disaster warning is another important value of this FuXi-Subseasonal model," said Qi Yuan, in charge of the research team.
He said his team has significantly increased the prediction period for extreme weather from 30 days to 36 days, predicting potential climate disaster events as early as possible, and gaining more time for response and mitigation measures.
The model of "FuXi-Subseasonal" represents one of China's mushrooming AI models used for predicting extreme weather.
In July last year, when typhoon Doksuri hit China, Fengwu, a machine learning model developed by the Shanghai Artificial Intelligence Laboratory, surpassed European and American equivalents in predicting its moves, Qi claimed.
Bai Lei, a scientist at the Shanghai Artificial Intelligence Laboratory, explained that the Fengwu model focuses primarily on the forecasting stage. It utilizes data obtained from atmospheric reanalysis and obtain more accurate weather forecasts.
AI models such as Fengwu use artificial intelligence to analyze the elements provided by atmospheric data assimilation, such as wind speed, temperature and humidity in order to predict future weather. Artificial intelligence can utilize past meteorological elements, such as temperature, to forecast future weather and achieve more precise results, explained Ouyang Wanli, another scientist from the Shanghai lab.
Unlike the traditional physical models that mostly run on supercomputers, Fengwu only needs single graphics processing unit to generate high-precision global weather forecasts for the next 10 days in 30 seconds.
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