The International Training Course on AI Empowered Early Warnings for All has officially begun in Shanghai, a significant location for showcasing the World Meteorological Organization's (WMO) multi-hazard warning systems. This program features 22 participants from 21 different countries and regions such as Jordan, Chad, and Mauritius, indicating a robust international interest in enhancing disaster preparedness and response.
Spanning over five days, the training employs a multifaceted approach that includes sharing technological innovations, analyzing case studies, and engaging in practical exercises. Participants are being guided by experts from the WMO, the China Meteorological Administration, academic institutions, and financial organizations. These experts are focusing on the integration of artificial intelligence in creating universal early warning systems and developing tools for urban multi-hazard early warnings. The curriculum also includes workshops aimed at using the urban multi-hazard early warning toolbox in real-world scenarios.
Cyrille Honoré, the deputy director of the WMO Services Department, emphasized the program's importance, especially in light of the increasing frequency of severe weather and climate-related incidents. He pointed out the urgent need for a people-centered early warning system and highlighted that international cooperation is vital for improving warning systems with AI technology.
Ra'ed Ahmad Subhi Rafid, the director of the Jordan Meteorological Department and one of the participants, expressed his eagerness to learn from China’s experiences to foster development prospects for other developing nations.
Shanghai has made strides in bolstering its disaster impact forecasting, risk warnings, and disaster mitigation efforts in recent years. Currently, the city is in the process of building an urban multi-hazard early warning center and is upgrading its warning toolbox to promote global sharing of early warning technologies and strengthen international collaboration.
Feng Lei, the director of the Shanghai Meteorological Service, expressed optimism for future partnerships to enhance the development of the enhanced urban multi-hazard early warning toolbox and the integration of AI technology in meteorology worldwide.
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