Research on meteorological grid data processing based on spatiotemporal big data engine
Yang Cai1, Guo Yuefan2, Li Wenzhao1, Li Jingrui3, Xue Shuaining1, Shi Yan1
1. Chongqing Meteorological Information and Technology Support Center,Chongqing 401147; 2. Sichuan Meteorological Observation and Data Center,Chengdu 610000; 3. Wuxi County Meteorological Bureau,Wuxi 405800
Abstract：In order to effectively meet the demand for spatiotemporal services of massive meteorological grid data,precipitation elements from multi-source fused real-time grid data were selected as experimental data.Based on the spatiotemporal big data engine (GeoTrellis),a processing scheme for storing,retrieving,statistically analyzing,and visualizing massive meteorological grid data was proposed,and compared with traditional data storage schemes.Research has shown that this approach performs better than traditional grid data slicing storage methods,with time consumption reduced to seconds.The spatiotemporal retrieval of meteorological grid data can be shortened to milliseconds,which can support real-time statistics of massive meteorological grid data.The solution based on spatiotemporal big data engine can effectively support the efficient storage,retrieval,statistics and visualization of grid data,and can effectively enhance the spatiotemporal service capability of massive meteorological grid data.
杨才, 郭越凡, 李文钊, 黎景锐, 薛帅宁, 石焱. 基于时空大数据引擎的气象网格数据处理研究[J]. 气象水文海洋仪器, 2025, 42(3): 9-13.
Yang Cai, Guo Yuefan, Li Wenzhao, Li Jingrui, Xue Shuaining, Shi Yan. Research on meteorological grid data processing based on spatiotemporal big data engine. Meteorological Hydrological and Marine Instrument, 2025, 42(3): 9-13.
2025, Vol. 42 
