The second international training course on artificial intelligence empowering early warnings for all got underway on Monday at Donghua University in Songjiang district, Shanghai, aiming to foster in-depth exchanges and practical cooperation on leveraging AI technology to enhance disaster prevention in the meteorology sector.

The five-day training gathered meteorological representatives from over 30 countries across the world, including Asia, Africa, South America and the Pacific region. Sharing China's solutions in an open and inclusive approach, the program is set to contribute Chinese wisdom and Shanghai's experience to global meteorological governance.

"As climate change increases the frequency and intensity of extreme weather events, strengthening early warning systems has become more important than ever," said Yu Jun from Regional Office for Asia and the South-West Pacific at World Meteorological Organization at the opening ceremony.

Mariam Tidiga, director general of Burkina Faso's National Meteorological Agency, added that climate change is increasingly affecting societies, economies and food systems. Droughts, floods, heat waves and other extreme events continue to threaten lives, livelihoods and sustainable development, particularly in vulnerable regions.

To tackle global meteorological challenges, the United Nations launched the Early Warnings for All initiative in 2022. It aims to ensure universal protection from hazardous hydrometeorological, climatological and related environmental events through life-saving multi-hazard early warning systems, anticipatory action and resilience efforts by the end of 2027.

As a national response to the initiative, China came up with the MAZU solution last year, which is named after an ancient Chinese sea goddess known for protecting fishermen, and has seen its expanding international application to help cope with extreme weather and climate risks in developing countries.

At this year's training program, participants will explore into China's MAZU solution and weather radar-enabled early warnings, as well as participate in hands-on exercises on the MAZU-based AI agent for urban multi-hazard early warnings, which is spearheaded by the Shanghai Meteorological Service.