Requirements for a global data infrastructure in support of CMIP6

Author:

Balaji VenkatramaniORCID,Taylor Karl E.ORCID,Juckes MartinORCID,Lawrence Bryan N.ORCID,Durack Paul J.ORCID,Lautenschlager Michael,Blanton Chris,Cinquini Luca,Denvil SébastienORCID,Elkington Mark,Guglielmo Francesca,Guilyardi EricORCID,Hassell DavidORCID,Kharin Slava,Kindermann StefanORCID,Nikonov Sergey,Radhakrishnan AparnaORCID,Stockhause MartinaORCID,Weigel TobiasORCID,Williams Dean

Abstract

Abstract. The World Climate Research Programme (WCRP)'s Working Group on Climate Modelling (WGCM) Infrastructure Panel (WIP) was formed in 2014 in response to the explosive growth in size and complexity of Coupled Model Intercomparison Projects (CMIPs) between CMIP3 (2005–2006) and CMIP5 (2011–2012). This article presents the WIP recommendations for the global data infrastructure needed to support CMIP design, future growth, and evolution. Developed in close coordination with those who build and run the existing infrastructure (the Earth System Grid Federation; ESGF), the recommendations are based on several principles beginning with the need to separate requirements, implementation, and operations. Other important principles include the consideration of the diversity of community needs around data – a data ecosystem – the importance of provenance, the need for automation, and the obligation to measure costs and benefits.This paper concentrates on requirements, recognizing the diversity of communities involved (modelers, analysts, software developers, and downstream users). Such requirements include the need for scientific reproducibility and accountability alongside the need to record and track data usage. One key element is to generate a dataset-centric rather than system-centric focus, with an aim to making the infrastructure less prone to systemic failure.With these overarching principles and requirements, the WIP has produced a set of position papers, which are summarized in the latter pages of this document. They provide specifications for managing and delivering model output, including strategies for replication and versioning, licensing, data quality assurance, citation, long-term archiving, and dataset tracking. They also describe a new and more formal approach for specifying what data, and associated metadata, should be saved, which enables future data volumes to be estimated, particularly for well-defined projects such as CMIP6.The paper concludes with a future facing consideration of the global data infrastructure evolution that follows from the blurring of boundaries between climate and weather, and the changing nature of published scientific results in the digital age.

Publisher

Copernicus GmbH

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