Severe weather causes human disasters. The most useful way to decrease a national disaster is by building more atmospheric sensing equipments to monitor the climate change. The data produced by these sensing equipments are of a huge amount and play an important role for weather prediction. Moreover, new sensing equipments enrich weather data. Everyday terabyte and petabyte-scale data are collected. Retrieval of such information requires access to large volumes of data; thus an efficient organisation is necessary both to reduce access time and to allow for efficient knowledge extraction. A new class of `data grid` infrastructure is efficient to support management, transportation, distributed access and analysis of these data sets by thousands of potential users. Intelligent agents can play an important role in helping achieve the `data grid` vision. In this study, the authors present a multi-agent-based framework to implement manage, share and query weather data in a geographical distributed environment, named weather data sharing system (WDSS). In each node, some services are designed for querying and accessing data sets based on agent environment. Information retrieval can be conducted locally, by considering portions of weather data, or in a distributed scenario, by exploiting global metadata. The agents` local and remote search is evaluated. The transfer speeds for different file types are also evaluated. From the presented platform, the system extensibility is analysed. The authors believe that this will be a useful platform for research on WDSS in a national area.