A data model of the Climate and Forecast metadata conventions (CF-1.6) with a software implementation (cf-python v2.1)

Hassell, D. ORCID: https://orcid.org/0000-0001-5106-7502, Gregory, J. ORCID: https://orcid.org/0000-0003-1296-8644, Blower, J., Lawrence, B. N. ORCID: https://orcid.org/0000-0001-9262-7860 and Taylor, K. E. (2017) A data model of the Climate and Forecast metadata conventions (CF-1.6) with a software implementation (cf-python v2.1). Geoscientific Model Development, 10 (12). pp. 4619-4646. ISSN 1991-9603 doi: 10.5194/gmd-10-4619-2017

Abstract/Summary

The CF (Climate and Forecast) metadata conventions are designed to promote the creation, processing, and sharing of climate and forecasting data using Network Common Data Form (netCDF) files and libraries. The CF conventions provide a description of the physical meaning of data and of their spatial and temporal properties, but they depend on the netCDF file encoding which can currently only be fully understood and interpreted by someone familiar with the rules and relationships specified in the conventions documentation. To aid in development of CF-compliant software and to capture with a minimal set of elements all of the information contained in the CF conventions, we propose a formal data model for CF which is independent of netCDF and describes all possible CF-compliant data. Because such data will often be analysed and visualised using software based on other data models, we compare our CF data model with the ISO 19123 coverage model, the Open Geospatial Consortium CF netCDF standard, and the Unidata Common Data Model. To demonstrate that this CF data model can in fact be implemented, we present cf-python, a Python software library that conforms to the model and can manipulate any CF-compliant dataset.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/74998
Item Type	Article
Refereed	Yes
Divisions	Interdisciplinary centres and themes > Institute for Environmental Analytics (IEA) Science > School of Mathematical, Physical and Computational Sciences > NCAS
Publisher	European Geosciences Union
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