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The overall architecture and operation flow of the high-frequency refined meteorological grid data real-time processing system are designed and implemented taking high-frequency massive meteorological grid data as the research object, focusing on the low data processing efficiency of the traditional real-time processing system. Based on the analysis of the characteristics of massive high-frequency meteorological grid data, a distributed storage model is designed and implemented to meet the needs of the meteorological service. Multi-channel dynamic sensing technology is used to implement dynamic multi-channel file processing and fast sensing triggers of file arrival. The fast data block positioning algorithm based on accurate location addressing is implemented using real-time data fast processing technology to realize the accurate positioning of data blocks. The data on-demand real-time interception technology is used to realize the interception algorithm, which can intercept the data on-demand, and then realize the data ondemand extraction. The practical application shows that the system can effectively improve the real-time processing efficiency of unstructured meteorological data.