Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Geosci. Model Dev., 10, 4619-4646, 2017
https://doi.org/10.5194/gmd-10-4619-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
19 Dec 2017
A data model of the Climate and Forecast metadata conventions (CF-1.6) with a software implementation (cf-python v2.1)
David Hassell et al.
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Interactive discussionStatus: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version      Supplement - Supplement
 
SC1: 'Executive Editor Comment on "A CF data model and implementation"', Astrid Kerkweg, 18 Jul 2017 Printer-friendly Version 
AC1: 'Reply to short comment 1 (SC1)', David Hassell, 21 Jul 2017 Printer-friendly Version 
 
RC1: 'Review of GMD-2017-154 CF data model and implementation David Hassell, Jonathan Gregory, Jon Blower, Bryan N. Lawrence, and Karl E. Taylor', V. Balaji, 04 Aug 2017 Printer-friendly Version 
 
RC2: 'Review of gmd-2017-154', Brian Eaton, 17 Aug 2017 Printer-friendly Version 
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision
AR by David Hassell on behalf of the Authors (31 Oct 2017)  Author's response  Manuscript
ED: Publish subject to technical corrections (02 Nov 2017) by Steve Easterbrook  
CC BY 4.0
Publications Copernicus
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Short summary
We present a formal data model for version 1.6 of the CF (Climate and Forecast) metadata conventions that provide a description of the physical meaning of geoscientific data and their spatial and temporal properties. We describe the CF conventions and how they lead to our CF data model, and compare it other data models for storing data and metadata. We present cf-python version 2.1: a software implementation of the CF data model capable of manipulating any CF-compliant dataset.
We present a formal data model for version 1.6 of the CF (Climate and Forecast) metadata...
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