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Distributed and cloud-based multi-model analytics experiments on large volumes of climate change data in the earth system grid federation eco-system | IEEE Conference Publication | IEEE Xplore

Distributed and cloud-based multi-model analytics experiments on large volumes of climate change data in the earth system grid federation eco-system


Abstract:

A case study on climate models intercomparison data analysis addressing several classes of multi-model experiments is being implemented in the context of the EU H2020 IND...Show More

Abstract:

A case study on climate models intercomparison data analysis addressing several classes of multi-model experiments is being implemented in the context of the EU H2020 INDIGO-DataCloud project. Such experiments require the availability of large amount of data (multi-terabyte order) related to the output of several climate models simulations as well as the exploitation of scientific data management tools for large-scale data analytics. More specifically, the paper discusses in detail a use case on precipitation trend analysis in terms of requirements, architectural design solution, and infrastructural implementation. The experiment has been tested and validated on CMIP5 datasets, in the context of a large scale distributed testbed across EU and US involving three ESGF sites (LLNL, ORNL, and CMCC) and one central orchestrator site (PSNC).
Date of Conference: 05-08 December 2016
Date Added to IEEE Xplore: 06 February 2017
ISBN Information:
Conference Location: Washington, DC, USA

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