A data model of the Climate and Forecast metadata conventions (CF-1.6) with a software implementation (cf-python v2.1)
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 spati...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-12-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://www.geosci-model-dev.net/10/4619/2017/gmd-10-4619-2017.pdf |
| 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. |
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| ISSN: | 1991-959X 1991-9603 |