INDIGO Case Study on climate models intercomparison data analysis: watch the video of the demo

Tuesday, March 8, 2016

This demo presents a preliminary implementation of a climate change experiment on precipitation trend analysis in the context of the INDIGO-DataCloud project. It has been presented at Cloudscape 2016, Brussels, March 8th.

More about the use case

The case study on Climate models intercomparison data analysis relates to the climate change domain and community (European Network for Earth System modelling - ENES). It is directly connected to the Coupled Model Intercomparison Project (CMIP), one of the most internationally relevant and large climate experiment as well as to the Earth System Grid Federation (ESGF) infrastructure in terms of existing eco-system and services. In the last three years, ESGF has been serving the Coupled Model Intercomparison Project Phase 5 (CMIP5) experiment, providing access to 2.5PB of data for the IPCC AR5. The test case focuses on a subset of this global data archive and proposes a common approach to perform three different scientific data analysis classes: (i) trend analysis, (ii) anomalies analysis, and (iii) climate change signal analysis. The first one will be specifically addressed by the demo. The test case demonstrates the INDIGO capabilities in terms of software framework deployed on heterogeneous infrastructures (e.g., HPC clusters and cloud environments), as well as workflow support to run distributed, parallel data analyses. While general-purpose WfMSs (in this case Kepler WfMS) are exploited in this use case to orchestrate multi-site tasks, the Ophidia framework is adopted at the single-site level to run scientific data analytics workflows consisting of tens/hundreds of data processing, analysis, and visualization operators. The demonstration will highlight: (i) the interoperability with the already existing community-based software ecosystem and infrastructure (IS-ENES/ESFG); (ii) the adoption of workflow management system solutions (both coarse and fine grained) for large-scale climate data analysis (e.g. Ophidia, Kepler); (iii) the exploitation of Cloud technologies/solutions from the INDIGO PaaS offering easy-to-deploy, flexible, isolated and dynamic big data analysis solutions; and (iv) the provisioning of interfaces, toolkits and libraries to develop high-level interfaces/applications integrated in a Science Gateway. With regard to the last point, the demo will show how the results of the experiments will be easily made available to the end user for inspection, download, and visualization. To this end, the user interface will provide specific/advanced support for data analytics and visualization.