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

Hassell, David; Gregory, Jonathan; Blower, Jon; Lawrence, Bryan N.; Taylor, Karl E.

doi:10.5194/gmd-10-4619-2017

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

Abstract

Abstract. 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:

;

Publication Date:: Tue Dec 19 00:00:00 EST 2017

Research Org.:: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Org.:: USDOE National Nuclear Security Administration (NNSA)

OSTI Identifier:: 1459768

Alternate Identifier(s):: OSTI ID: 1458637

Report Number(s):: LLNL-JRNL-744900
Journal ID: ISSN 1991-9603

Grant/Contract Number:: AC52-07NA27344

Resource Type:: Published Article

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:: Copernicus Publications, EGU

Country of Publication:: Germany

Language:: English

Subject:: 54 ENVIRONMENTAL SCIENCES

Citation Formats


                    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).  Germany: N. p., 2017. 
Web.  doi:10.5194/gmd-10-4619-2017.

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                    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).  Germany.  https://doi.org/10.5194/gmd-10-4619-2017

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                    Hassell, David, Gregory, Jonathan, Blower, Jon, Lawrence, Bryan N., and Taylor, Karl E. Tue .  
"A data model of the Climate and Forecast metadata conventions (CF-1.6) with a software implementation (cf-python v2.1)".  Germany.  https://doi.org/10.5194/gmd-10-4619-2017.

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@article{osti_1459768,

  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 = {Abstract. 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        = {Germany},

  year         = {Tue Dec 19 00:00:00 EST 2017},

  month        = {Tue Dec 19 00:00:00 EST 2017}

}

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Works referenced in this record:

Evaluating lossy data compression on climate simulation data within a large ensemble
journal, January 2016

Baker, Allison H.; Hammerling, Dorit M.; Mickelson, Sheri A.
Geoscientific Model Development, Vol. 9, Issue 12
DOI: 10.5194/gmd-9-4381-2016

NetCDF: an interface for scientific data access
journal, July 1990

Rew, R.; Davis, G.
IEEE Computer Graphics and Applications, Vol. 10, Issue 4
DOI: 10.1109/38.56302

Unidata’s Common Data Model mapping to the ISO 19123 Data Model
journal, July 2008

Nativi, Stefano; Caron, John; Domenico, Ben
Earth Science Informatics, Vol. 1, Issue 2
DOI: 10.1007/s12145-008-0011-6

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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)

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