A SciDB-based framework for efficient satellite data storage and query based on dynamic atmospheric event trajectory

Current research in climate informatics focuses mainly on the development of novel (machine learning, data mining, or statistical) techniques to analyze climate data (e.g. model, in-situ, or satellite) or to make prediction based on these climate data. One important component missing from this analysis workflow is data management that allows efficient and flexible data retrieval, (ease of) reproducibility, and the (ease of) techniques reuse on user-defined data subsets or other data. In this paper, we describe our preliminary investigation on the utilization of the distributed array-based database management system, SciDB, to support data-driven climate science research. We focus on modeling and generating indices that allow effective execution of various spatiotemporal queries on satellite data. Moreover, we demonstrate fast and accurate data retrieval based on user-specified trajectories from the SciDB database containing tropical cyclone trajectories and the complete ten-year QuikSCAT ocean surface wind fields satellite data. Our preliminary work indicates the feasibility of the array-based technology for multiple satellite data storage, query, and analysis. Towards this end, a successful deployment of SciDB-based data storage can facilitate the use of data from multiple satellites for climate and weather research.