Distributed and cloud-based multi-model analytics experiments on large volumes of climate change data in the earth system grid federation eco-system
Sandro Fiore, Marcin Płóciennik, Charles M. Doutriaux, Cosimo Palazzo, Jason Boutte, Tomasz Żok, Donatello Elia, M. Owsiak, Alessandro D’Anca, Z. Shaheen, Rodrigo Bruno, Marco Fargetta, Miguel Caballer, Germán Moltó, Ignácio Blanquer, R. Barbera, M. David, Giacinto Donvito, Dean N. Williams, Valentine G. Anantharaj · 2016
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).