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Title: 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 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.
Authors:
ORCiD logo [1] ; ORCiD logo [2] ; ORCiD logo [1] ; ORCiD logo [1] ;  [3]
  1. Univ. of Reading (United Kingdom)
  2. Univ. of Reading (United Kingdom); Met Office Hadley Centre, Exeter (United Kingdom)
  3. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Publication Date:
Report Number(s):
LLNL-JRNL-744900
Journal ID: ISSN 1991-9603; 896058
Grant/Contract Number:
AC52-07NA27344
Type:
Accepted Manuscript
Journal Name:
Geoscientific Model Development (Online)
Additional Journal Information:
Journal Name: Geoscientific Model Development (Online); Journal Volume: 10; Journal Issue: 12; Journal ID: ISSN 1991-9603
Publisher:
European Geosciences Union
Research Org:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org:
USDOE National Nuclear Security Administration (NNSA)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES
OSTI Identifier:
1458637

Hassell, David, Gregory, Jonathan, Blower, Jon, Lawrence, Bryan N., and Taylor, Karl E.. A data model of the Climate and Forecast metadata conventions (CF-1.6) with a software implementation (cf-python v2.1). United States: N. p., Web. doi:10.5194/gmd-10-4619-2017.
Hassell, David, Gregory, Jonathan, Blower, Jon, Lawrence, Bryan N., & Taylor, Karl E.. A data model of the Climate and Forecast metadata conventions (CF-1.6) with a software implementation (cf-python v2.1). United States. doi:10.5194/gmd-10-4619-2017.
Hassell, David, Gregory, Jonathan, Blower, Jon, Lawrence, Bryan N., and Taylor, Karl E.. 2017. "A data model of the Climate and Forecast metadata conventions (CF-1.6) with a software implementation (cf-python v2.1)". United States. doi:10.5194/gmd-10-4619-2017. https://www.osti.gov/servlets/purl/1458637.
@article{osti_1458637,
title = {A data model of the Climate and Forecast metadata conventions (CF-1.6) with a software implementation (cf-python v2.1)},
author = {Hassell, David and Gregory, Jonathan and Blower, Jon and Lawrence, Bryan N. and Taylor, Karl E.},
abstractNote = {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.},
doi = {10.5194/gmd-10-4619-2017},
journal = {Geoscientific Model Development (Online)},
number = 12,
volume = 10,
place = {United States},
year = {2017},
month = {12}
}