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Training

CMA launches international training course on powering Early Warnings for All with AI

Elizabeth BakerBy Elizabeth BakerJune 16, 20253 Mins Read
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A room full of people sit facing a projector slide, which says "International Training Course on AI Empowered Early Warnings for All".
The WMO's Cyrille Honoré delivered a speech at the opening ceremony. Credit: Yang Yang
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Twenty-two people from 21 countries, including Jordan, Chad and Mauritius, gathered in Shanghai, China, last week for a five-day training course on AI-powered Early Warnings for All.

Course content

CMA launches international training course on powering Early Warnings for All with AI.
Mustafa Adiguzel, scientific officer in the Education and Training Office of the WMO’s Science and Innovation Department, gave the first lecture of the course. Credit: Yang Yang

Experts from WMO, the China Meteorological Administration (CMA), universities, and AI research and financial institutions gave lectures on the application of AI in early warnings, the development of an urban multi-hazard early warning toolbox, and green finance and disaster risk management. There was also a workshop on the practical operation of the toolbox.

With the main topics of AI+, Government+ and Finance+, the course focused on the shared exchange of technology, case studies and field experience. There was a range of technical topics and practical applications, including discussion of the WMO’s efforts to support the Early Warnings for All (EW4ALL) initiative, Shanghai’s experience in disaster mitigation, and the use of artificial intelligence (AI) in forecasting and warnings.

Ensuring effective early warning systems

CMA launches international training course on powering Early Warnings for All with AI.
The launch of the WMO Regional Association II (Asia) Pilot Project of the Centre on Urban Multi-Hazard Early Warning. Credit: Yang Yang

“This gathering is timely and vital,” said Cyrille Honoré, deputy director of the WMO’s member service department and director of disaster risk reduction and early warnings at the WMO. “In an era marked by escalating climate-related disasters and extreme weather events, the need for robust, inclusive and people-centered early warning systems has never been more urgent. This multi-stakeholder approach was essential to the success of the United Nations’ Early Warnings for All initiative, which was built on the principle of partnership. Only by working together could all address the full value chain of early warning systems, from observation and forecasting to communication and response.”

As a representative of the trainees, Raed Ahmad Subhi Rafid, director of the Jordan Meteorological Department (JMD) added, “This course comes at a time when the world is witnessing an increasing frequency and intensity of extreme weather events, underscoring the urgent need for more accurate and effective early warning systems.”

The future of the Shanghai Meteorological Service

During the opening ceremony, the WMO Regional Association II (Asia) Pilot Project of the Centre on Urban Multi-Hazard Early Warning and the Shanghai Meteorological Service and Shanghai Emergency Management Bureau jointly launched a multilingual early warning information service system covering 14 languages.

In related news, the China Meteorological Administration recently unveiled the Yushi and Fuyao artificial intelligence (AI) meteorological models. These two AI models are currently in trial operation and are scheduled for official operation during this year’s flood season

Previous ArticleUK Met Office and Environment Agency to construct radar for improved rainfall measurements
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