A GLOBAL REPOSITORY FOR PLANET-SIZED EXPERIMENTS AND OBSERVATIONS

Working across U.S. federal agencies, international agencies, and multiple worldwide data centers, and spanning seven international network organizations, the Earth System Grid Federation (ESGF) allows users to access, analyze, and visualize data using a globally federated collection of networks, co...

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Bibliographic Details
Published in:Bulletin of the American Meteorological Society 2016-05, Vol.97 (5), p.803-816
Main Authors: Williams, Dean N., Balaji, V., Cinquini, Luca, Denvil, Sébastien, Duffy, Daniel, Evans, Ben, Ferraro, Robert, Hansen, Rose, Lautenschlager, Michael, Trenham, Claire
Format: Article
Language:English
Subjects:
Archives & records
Astronomy
Climate change
Climate models
Climate science
Climatic changes
Collaboration
Earth
Environmental protection
Experiments
Global climate
Information technology
Laboratories
Mathematical And Computer Sciences (General)
Political aspects
Researchers
Scientists
Studies
Trends
Working groups
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Description
Summary:Working across U.S. federal agencies, international agencies, and multiple worldwide data centers, and spanning seven international network organizations, the Earth System Grid Federation (ESGF) allows users to access, analyze, and visualize data using a globally federated collection of networks, computers, and software. Its architecture employs a system of geographically distributed peer nodes that are independently administered yet united by common federation protocols and application programming interfaces (APIs). The full ESGF infrastructure has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the Coupled Model Intercomparison Project (CMIP)—output used by the Intergovernmental Panel on Climate Change assessment reports. Data served by ESGF not only include model output (i.e., CMIP simulation runs) but also include observational data from satellites and instruments, reanalyses, and generated images. Metadata summarize basic information about the data for fast and easy data discovery.
ISSN:0003-0007
1520-0477
DOI:10.1175/BAMS-D-15-00132.1