ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Archive > Volume 51 Issue 11 > 2025,51(11):1321-1334. DOI:10.7519/j.issn.1000-0526.2025.063003 Prev Next
Technological Advances in the Intelligent Digital Weather Forecasting Operational System of National Meteorological Centre
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Abstract:
Intelligent digital weather forecasting is a key means to support meteorological service. Countries around the world are actively developing new-generation seamless forecasting technology systems and promoting the application of artificial intelligence (AI) in the meteorological field. China has established a relatively complete intelligent digital weather forecasting operation system, achieving seamless forecasting for the near-surface and three-dimensional meteorological elements with a resolution of 1 km across China and 5 km around the globe, covering a time range of 0-30 days. By developing adaptable technologies through the strategy of implementing different strategies at different time scales and integrating multi-source forecasts, China has made remarkable achievements. A unified, standardized, and modularly expandable intelligent digital general technology framework has been constructed, with more than 30 types of algorithms constructed and the “low-code” deployment able to be supported. This is very important in major event support and extreme weather forecasting. The in-depth application of AI technology has significantly improved forecast performance in short-time, short-term and medium-term precipitation forecasting, severe convective weather forecasting, and disastrous gale forecasting by leveraging deep learning models. Progress has also been made in refined downscaling technology. At the same time, the data fusion and integration technology has continued to be developed, and the intelligent integration of objective and subjective forecasts has developed to enhance the ability to predict disastrous weather. China’s intelligent digital forecasting system has improved the forecast accuracy by 10%-31% compared with the EC_IFS and CMA models, and has been widely applied in many fields. However, it still faces challenges. In the future, breakthroughs will be made in the technologies related to the forecasting of disastrous and transitional weather, the low-altitude hundreds-meter-resolution refined downscaling forecasting, the industry-specific weather and risk forecasting, and the integrated platform with the meteorological “intelligent brain” as the core.
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