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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- Complex Virtual Instrument Model for Ocean Sensor Networks K. Hu et al. 10.1109/ACCESS.2018.2828322
- CMCC Metadata Agreement F. Sandro et al. 10.2139/ssrn.1370350
- cfdm: A Python reference implementation of the CF data model D. Hassell & S. Bartholomew 10.21105/joss.02717
- Theoretical Assessment for Weather Nowcasting Using Deep Learning Methods A. Upadhyay et al. 10.1007/s11831-024-10096-5
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- Data formats and standards for opportunistic rainfall sensors M. Fencl et al. 10.12688/openreseurope.16068.2
- Canadian historical Snow Water Equivalent dataset (CanSWE, 1928–2020) V. Vionnet et al. 10.5194/essd-13-4603-2021
- nctoolkit: A Python package for netCDF analysis and post-processing R. Wilson & Y. Artioli 10.21105/joss.05494
- Best Practice Data Standards for Discrete Chemical Oceanographic Observations L. Jiang et al. 10.3389/fmars.2021.705638
- Why don't we share data and code? Perceived barriers and benefits to public archiving practices D. Gomes et al. 10.1098/rspb.2022.1113
- A prototype field-to-publication data system for a multi-variable permafrost observation network N. Brown et al. 10.1016/j.envsoft.2024.106006
- GlobSim (v1.0): deriving meteorological time series for point locations from multiple global reanalyses B. Cao et al. 10.5194/gmd-12-4661-2019
- UniFHy v0.1.1: a community modelling framework for the terrestrial water cycle in Python T. Hallouin et al. 10.5194/gmd-15-9177-2022
- Data formats and standards for opportunistic rainfall sensors M. Fencl et al. 10.12688/openreseurope.16068.1
- A community convention for ecological forecasting: Output files and metadata version 1.0 M. Dietze et al. 10.1002/ecs2.4686
- Users of open Big Earth data – An analysis of the current state J. Wagemann et al. 10.1016/j.cageo.2021.104916
- Climate projections over the Antarctic Peninsula region to the end of the 21st century. Part III: clouds and extreme precipitation A. Chyhareva & S. Krakovska 10.33275/1727-7485.2.2022.699
- The METACLIP semantic provenance framework for climate products J. Bedia et al. 10.1016/j.envsoft.2019.07.005
- Profiling heliophysics data in the pythonic cloud A. Antunes et al. 10.3389/fspas.2022.1006839
- CHESS-SCAPE: high-resolution future projections of multiple climate scenarios for the United Kingdom derived from downscaled United Kingdom Climate Projections 2018 regional climate model output E. Robinson et al. 10.5194/essd-15-5371-2023
- The Common Community Physics Package (CCPP) Framework v6 D. Heinzeller et al. 10.5194/gmd-16-2235-2023
- Satellite-based time-series of sea-surface temperature since 1980 for climate applications O. Embury et al. 10.1038/s41597-024-03147-w
- The Mission Support System (MSS v7.0.4) and its use in planning for the SouthTRAC aircraft campaign R. Bauer et al. 10.5194/gmd-15-8983-2022
- The CMIP6 Data Request (DREQ, version 01.00.31) M. Juckes et al. 10.5194/gmd-13-201-2020
- Global Downscaled Projections for Climate Impacts Research (GDPCIR): preserving quantile trends for modeling future climate impacts D. Gergel et al. 10.5194/gmd-17-191-2024
- The 3D Elliptical Parcel-In-Cell (EPIC) method M. Frey et al. 10.1016/j.jcpx.2023.100136
- Reviews and syntheses: The promise of big diverse soil data, moving current practices towards future potential K. Todd-Brown et al. 10.5194/bg-19-3505-2022
- Global Surface Ocean Acidification Indicators From 1750 to 2100 L. Jiang et al. 10.1029/2022MS003563
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Latest update: 19 Apr 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...
