Articles | Volume 10, issue 12
https://doi.org/10.5194/gmd-10-4619-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-10-4619-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
19 Dec 2017
Methods for assessment of models |
| 19 Dec 2017
| 19 Dec 2017
A data model of the Climate and Forecast metadata conventions (CF-1.6) with a software implementation (cf-python v2.1)
National Centre for Atmospheric Science, Department of
Meteorology, University of Reading, Reading, UK
Jonathan Gregory
National Centre for Atmospheric Science, Department of
Meteorology, University of Reading, Reading, UK
Met Office Hadley Centre, Exeter, Exeter, UK
Jon Blower
Institute for Environmental Analytics, University of Reading, Reading, UK
Bryan N. Lawrence
National Centre for Atmospheric Science, Department of
Meteorology, University of Reading, Reading, UK
Karl E. Taylor
Program for Climate Model Diagnosis and Intercomparison,
Lawrence Livermore National Laboratory, Livermore, CA, USA
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- The CMIP6 Data Request (DREQ, version 01.00.31) M. Juckes et al. 10.5194/gmd-13-201-2020
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- The 3D Elliptical Parcel-In-Cell (EPIC) method M. Frey et al. 10.1016/j.jcpx.2023.100136
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Latest update: 20 Nov 2024
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...
