Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 9, issue 12
Articles | Volume 9, issue 12
https://doi.org/10.5194/gmd-9-4381-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-4381-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Articles | Volume 9, issue 12
Development and technical paper
 | 
07 Dec 2016
Development and technical paper |  | 07 Dec 2016

Evaluating lossy data compression on climate simulation data within a large ensemble

Allison H. Baker, Dorit M. Hammerling, Sheri A. Mickelson, Haiying Xu, Martin B. Stolpe, Phillipe Naveau, Ben Sanderson, Imme Ebert-Uphoff, Savini Samarasinghe, Francesco De Simone, Francesco Carbone, Christian N. Gencarelli, John M. Dennis, Jennifer E. Kay, and Peter Lindstrom

Data sets

CESM Models and Supported Releases CESM http://www.cesm.ucar.edu/models/current.html

Climate Data at the National Center for Atmospheric Research Earth System Grid https://www.earthsystemgrid.org

CESM-LE data Large Ensemble Community Project http://www.cesm.ucar.edu/projects/community-projects/LENS/

Floating Point Compression zfp & fpzip http://computation.llnl.gov/projects/floating-point-compression

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Short summary
We apply lossy data compression to output from the Community Earth System Model Large Ensemble Community Project. We challenge climate scientists to examine features of the data relevant to their interests and identify which of the ensemble members have been compressed, and we perform direct comparisons on features critical to climate science. We find that applying lossy data compression to climate model data effectively reduces data volumes with minimal effect on scientific results.
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