4:15 PM - 4:30 PM
[ACG43-10] A Content-Based Database System for Large Ensemble Future Climate Simulations
Keywords:Climate Change, Relational Database
simulations and regional downscaling simulations around Japan. Considering that those data volumes are too large, i.e. a few petabytes, to download to a local computer of users,
a user-friendly system is required to search and download data which satisfy requests of the users.
In order to provide functions to extract necessary data from +2K future climate simulations to the users, we developed “System for Efficient content-based retrieval to Analyze Large volume climate data (SEAL)”. Existing web-based search systems for climate simulations are designed to find data files using metadata associated with a data file itself. On the other hand, the SEAL allows the users to extract necessary data using metadata associated with contents of a data file such as physical values. The SEAL mainly consists of a relational database, a data download function and web-based user interface. Among the three main features, a key role is provided by the relational database using PostgreSQL which is designed to be registered temporally and spatially compressed data. The data download function allows the users to download temporally and spatially extracted data based on search results obtained by the relational database. In addition, the web-based user interface allows the users to easily use the relational database without knowledge about PostgreSQL. We also prepare a guidebook for usage of the SEAL. The SEAL is currently in test operation on our local server for SI-CAT members.
The SEAL and the guidebook will be released on Data Integration and Analysis System Program (DIAS) after end of fiscal year 2018. Techniques of the SEAL might be quite useful for simulation, experimental and observational data in other research fields. We report functions and some case studies of the SEAL.