Abstract
Meteorological observational data is collected from many stations around the country at the same time, and immediately submitted to the national meteorological data center-NMIC. NMIC aggregates national data and carries out effective processing and rapid service. This paper describes a high performance computing model in cluster environment to process massive meteorological data, which employs parallel computing and distributed computing frameworks focused on task division, task scheduling management, load balancing methods on various types of meteorological data in the Master-Slave operation environment. Within implementation of this architecture, high ability to efficiently handle large amount of content and good usability and stability of the data management and date service are achieved.
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