Title: Intelligent big data service for meteorological cloud platform

Authors: Jie Zhang; Shengjun Xue; Tao Huang

Addresses: Shanghai Meteorological Information and Technical Support Center, Shanghai Meteorological Bureau, No. 166, Puxi Road, Shanghai 200030, China ' School of Computer Science and Technology, Silicon Lake College, Suzhou, China ' School of Computer Science and Technology, Silicon Lake College, Suzhou, China

Abstract: With the acceleration of meteorological informationisation, meteorological data has gradually become a typical industry big data. In view of the challenge of storage, index and processing, cloud computing technology provides the technical support for meteorological big data. We design a framework of meteorological big data service in the cloud computing environment which contains meteorological services, meteorological scientific research services and public meteorological services. As the most popular distributed processing technology, MapReduce is effectively used for distributed processing of meteorological big data. Finally, based on MapReduce, the daily meteorological data of Baoshan Station in Shanghai is analysed, and the statistical results and corresponding examples are provided. The application research of meteorological big data in the cloud environment can not only improve the overall meteorological service level, but also play a significant role in accelerating the meteorological informatisation process in the big data era.

Keywords: cloud computing; meteorological mata; meteorological mervices; Hadoop; MapReduce.

DOI: 10.1504/IJIITC.2019.104719

International Journal of Intelligent Internet of Things Computing, 2019 Vol.1 No.1, pp.23 - 31

Received: 23 Jan 2019
Accepted: 24 Feb 2019
Published online: 29 Jan 2020 *