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Understanding the past, present, and changing behavior of the climate requires close collaboration of a large number of researchers from many scientific domains. At present, the necessary interdisciplinary collaboration is greatly limited by the difficulties in discovering, sharing, and integrating climatic data due to the tremendously increasing data size. This paper discusses the methods and techniques for solving the inter-related problems encountered when transmitting, processing, and serving metadata for heterogeneous Earth System Observation and Modeling (ESOM) data. A cyberinfrastructure-based solution is proposed to enable effective cataloging and two-step search on big climatic datasets by leveraging state-of-the-art web service technologies and crawling the existing data centers. To validate its feasibility, the big dataset served by UCAR THREDDS Data Server (TDS), which provides Petabyte-level ESOM data and updates hundreds of terabytes of data every day, is used as the case study dataset. A complete workflow is designed to analyze the metadata structure in TDS and create an index for data parameters. A simplified registration model which defines constant information, delimits secondary information, and exploits spatial and temporal coherence in metadata is constructed. The model derives a sampling strategy for a high-performance concurrent web crawler bot which is used to mirror the essentialmore »