Articles | Volume 9, issue 9
Geosci. Model Dev., 9, 3199–3211, 2016
https://doi.org/10.5194/gmd-9-3199-2016
Geosci. Model Dev., 9, 3199–3211, 2016
https://doi.org/10.5194/gmd-9-3199-2016

Development and technical paper 19 Sep 2016

Development and technical paper | 19 Sep 2016

Bit Grooming: statistically accurate precision-preserving quantization with compression, evaluated in the netCDF Operators (NCO, v4.4.8+)

Charles S. Zender

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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Charles Zender on behalf of the Authors (22 Aug 2016)  Author's response    Manuscript
ED: Publish subject to minor revisions (Editor review) (30 Aug 2016) by David Ham
AR by Charles Zender on behalf of the Authors (01 Sep 2016)  Author's response    Manuscript
ED: Publish as is (02 Sep 2016) by David Ham
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Short summary
We introduce Bit Grooming, a lossy compression algorithm that removes the bloat due to false precision, those bits and bytes beyond the meaningful precision of the data. Bit Grooming is statistically unbiased, applies to all floating-point numbers, and is easy to use. Bit Grooming reduces data storage requirements by 25–80 %. Unlike its best-known competitor Linear Packing, Bit Grooming imposes no software overhead on users, and guarantees its precision throughout the whole floating-point range.