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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 10, issue 1
Geosci. Model Dev., 10, 413–423, 2017
https://doi.org/10.5194/gmd-10-413-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 10, 413–423, 2017
https://doi.org/10.5194/gmd-10-413-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Development and technical paper 27 Jan 2017

Development and technical paper | 27 Jan 2017

The compression–error trade-off for large gridded data sets

Jeremy D. Silver and Charles S. Zender
Data sets

Sample CAM SE model output C. S. Zender https://doi.org/10.4225/49/576ca64db2a14

Sample output of the mineral Dust Entrainment And Deposition (DEAD) model C. S. Zender https://doi.org/10.4225/49/576c95f254b67

Sample MERRA analysis C. S. Zender https://doi.org/10.4225/49/576c934f73be7

Sample output from the Weather, Research and Forecasting model J. D. Silver https://doi.org/10.4225/49/576c900f7d289

Sample MOZART model output J. D. Silver https://doi.org/10.4225/49/576c8ba706ac9

Publications Copernicus
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Short summary
Many modern scientific research projects generate large amounts of data. Storage space is valuable and may be limited; hence compression is vital. We tested different compression methods for large gridded data sets, assessing the space savings and the amount of precision lost. We found a general trade-off between precision and compression, with compression well-predicted by the entropy of the data set. A method introduced here proved to be a competitive archive format for gridded numerical data.
Many modern scientific research projects generate large amounts of data. Storage space is...
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