United Nations initiative - using artificial intelligence technology to respond to meteorological disasters

2024-08-27

Recently, the United Nations launched the Global Initiative to Enhance Resilience to Climate Disasters through Artificial Intelligence Solutions, aiming to utilize advanced technologies in fields such as artificial intelligence to strengthen human resilience to natural disasters and reduce disaster risks. This initiative is jointly participated by multiple institutions such as the International Telecommunication Union, the United Nations Environment Programme, the Universal Postal Union, and the International Meteorological Organization. It is a continuation of the previous "Focus Group on Artificial Intelligence and Natural Disaster Management" mechanism and will promote the application of artificial intelligence technology in disaster management, as well as provide professional guidance and support for related research innovation and standard setting. The global initiative launched this time focuses on achieving early warning of meteorological disasters through artificial intelligence technology and closely coordinating with other relevant mechanisms of the United Nations. The initiative belongs to the "Artificial Intelligence for Early Warning for All" working group, which was established by the World Meteorological Organization's "Early Warning for All" initiative and reports to its cross disciplinary technology coordination group. The "Early Warning for All" initiative was launched by the United Nations Secretary General in March 2022, with the goal of ensuring that by 2027, everyone worldwide can be covered and protected by early warning systems. In the National Early Warning Action Plan, the application of artificial intelligence technology is highly anticipated. The main task of the "Artificial Intelligence for National Early Warning" working group is to strengthen institutional construction and enhance the contribution of artificial intelligence technology applications to national early warning. Its key members include the International Meteorological Organization, the United Nations Office for Disaster Risk Reduction, the International Telecommunication Union, and the International Federation of the Red Cross. The "National Early Warning" includes four pillar areas: disaster knowledge sharing and popularization, disaster observation, monitoring and prevention, early warning information dissemination and exchange, and disaster response capacity building. According to the initiative plan, the application of artificial intelligence technology will be strengthened synchronously in the above areas. While strengthening early warning of meteorological disasters, this initiative will also focus on standardization work. The International Telecommunication Union pointed out in its report "Roadmap for Standardization of Natural Disaster Management: Trends and gaps" that, according to time stages, disaster management includes prevention, preparedness, response, reconstruction and other aspects. Existing standards have insufficient coverage of early stages, including natural disasters such as biological disasters and man-made disasters, which also have similar shortcomings. Although artificial intelligence technology is used in many application scenarios, the lack of standardization leads to issues such as data discrimination, resulting in insufficient reliability of the final results. In order to address relevant issues, the working group responsible for the application of artificial intelligence technology should not only focus on establishing standards for open source data acquisition and stakeholder participation during the modeling phase, but also strengthen the standardization of decision support systems during the application phase. Overall, the characteristics of artificial intelligence technology give it strong capability advantages and broad application prospects in the field of meteorology, especially in dealing with meteorological disasters. With super computing power, artificial intelligence can directly calculate and output forecast results from meteorological observation data; Under self-learning, artificial intelligence can proficiently master the theory of weather and climate mechanisms, improving prediction accuracy. It is precisely because of its outstanding potential that the World Meteorological Organization has attached great importance to the application of artificial intelligence technology in recent years. In its strategic plan for 2024-2027, it regards artificial intelligence technology as an important force to promote the development of meteorological technology, especially planning to launch a short-term forecasting demonstration project based on artificial intelligence technology to support early warning for the whole population. China is at the forefront of using artificial intelligence technology for weather forecasting internationally. In June of this year, the China Meteorological Administration released three artificial intelligence meteorological big model systems, namely the AI global short - and medium-term forecasting system "Fengqing", the AI proximity forecasting system "Fenglei", and the AI global sub seasonal seasonal forecasting system "Fengshun". In the first half of this year, the China Meteorological Administration also utilized artificial intelligence technology to generate global weather forecasts for the next 10 days within 30 seconds, significantly improving the accuracy of severe convective weather forecasts and typhoon path forecasts. As demonstrated at the Global Summit on Artificial Intelligence for Good held in May this year, "for good" has become a consensus attitude of the international community towards the development and application of artificial intelligence technology. Multiple United Nations organizations have stated that extreme weather is becoming one of the biggest threats facing the world, undermining the achievement of almost all sustainable development goals. The use of artificial intelligence technology to better respond to meteorological disasters is the most intuitive manifestation of its "goodness oriented" application. In the future, it is expected to gather more countries' cooperation and help all mankind better cope with the challenges of meteorological disasters. (New Society)

Edit:Xiong Dafei    Responsible editor:Li Xiang

Source:Econnmic Daily

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