Countries involved in the Belt and Road Initiative have expressed a strong willingness to participate in a meteorology project recently launched by China that uses artificial intelligence to improve weather forecasting amid increasingly frequent extreme weather conditions.

Kouam Magloire, head of the data processing office at Cameroon's meteorological services, said the project could provide a major opportunity for the country to strengthen its early warning systems and respond more effectively to extreme weather events.

The project, launched in March, is funded by the Ministry of Science and Technology and led by the China Meteorological Administration's Center for Earth System Modeling and Prediction.

It builds on China's MAZU early warning system, an open-source meteorological service platform already deployed in countries including Pakistan and Ethiopia to support real-time weather monitoring and disaster alerts.

Altansuvd Bold, an engineer with Mongolia's National Agency for Meteorology and Environmental Monitoring, said the country frequently experiences extreme weather events and urgently needs AI-powered nowcasting — forecasts from minutes to hours ahead — based on meteorological satellite and radar data.

Mongolia hopes to use the cooperation to build a more advanced long-term weather forecasting system, he said.

Leta Bekele Gudina, a senior expert at the Ethiopian Meteorological Institute, said China is at the forefront of meteorological forecasting and AI development.

"Ethiopia hopes to gain access to advanced technologies through the project, train local professionals and help fill the country's gap in nowcasting and early warning services," he said.

According to the China Meteorological Administration, many countries participating in the Belt and Road Initiative face rising risks from extreme weather and climate events. Between 1980 and 2022, direct economic losses from meteorological disasters in these countries averaged $214.7 billion annually, accounting for about 28.4 percent of global losses.

Many of these nations have limited meteorological infrastructure, including sparse observation networks and insufficient computing capacity. The meteorological gap has become a key constraint on disaster preparedness and sustainable development.

To address these challenges, the project aims to develop an integrated AI-based forecasting system capable of producing predictions from short-term to sub-seasonal time scales. The system combines physical atmospheric models with AI approaches and will be adapted for local conditions in partner countries.

An integrated intelligent forecasting device will be designed for flexible deployment in countries with different levels of technical infrastructure, according to the China Meteorological Administration.

Han Wei, the project leader, said the platform will operate for at least six months in more than six countries, with early warning services expected to reach about 10 million people.

The AI models developed through the project will be integrated into the MAZU early warning platform to provide a stable technological foundation for international services, he said.

Chen Deliang, an academician of the Chinese Academy of Sciences, said the project addresses urgent needs in Belt and Road countries while applying cutting-edge AI technology to meteorology.

Zhang Xiaoye, an academician of the Chinese Academy of Engineering, suggested further strengthening regional downscaling techniques to better meet the specific forecasting needs of partner countries.