摘要
随着大数据产业的蓬勃发展和全社会对气象服务需求的日益增长,气象大数据与各行各业数据平台的融合应用越来越广泛。而传统气象数据的存储和运算方式,难以同时高效支撑多个行业、高时空分辨率的气象数据生产和传输要求。因此该方案基于Hadoop技术建设河北省行业气象服务大数据平台,通过分布式存储、分布式计算,快速接收原始气象数据、通过插值等方法对气象数据进行时空降尺度、通过行业专项预报指标和模型快速计算相关气象服务产品,最终生成支撑能源电力、交通运输等多领域气象监测预报服务产品,得到了很好的应用。为河北省构建气象大数据产业发展生态环境、提升气象信息产业化发展以及保障地方经济社会发展提供了有力支撑。
With the vigorous development of big data industry and the growing demand of the whole society for meteorological services,the integration and application of meteorological big data and data platforms of all walks of life are more and more extensive.However,the traditional storage and operation methods of meteorological data are difficult to efficiently support the production and transmission requirements of meteorological data with high spatial and temporal resolution in multiple industries at the same time.Therefore,the scheme is based on Hadoop technology to build a big data platform for industry meteorological services in Hebei Province.Through distributed storage and distributed computing,the scheme can quickly receive original meteorological data,conduct time-space downscaling of meteorological data through interpolation and other methods,quickly calculate relevant meteorological service products through industry specific forecast indicators and models,and finally generate meteorological monitoring and forecasting service products supporting energy,electricity,transportation and other fields,it has been applied well.It provides strong support for Hebei Province to build the ecological environment for the development of meteorological big data industry,promote the industrialization of meteorological information,and ensure the local economic and social development.
作者
张中杰
李飞
曲晓黎
周朔
ZHANG Zhongjie;LI Fei;QU Xiaoli;ZHOU Shuo(Meteorological Institute of Hebei Province,Shijiazhuang Hebei 050021;Key Laboratory of Weather and Meteorological and Ecological Environment of Hebei Province,Shijiazhuang Hebei 050021;Hebei Province Meteorological Service Centre,Shijiazhuang Hebei 050021)
出处
《软件》
2023年第1期24-28,共5页
Software
基金
河北省重点研发计划项目资助(导线覆冰和风偏气象灾害精准预警技术研究:22375405D)。
