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Advancing data compression via noise detection

delete2021-11-25
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PRE
AI
D
Dorit Hammerling *
A
Allison H. Baker
DOI:10.1038/s43588-021-00167-zdelete
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摘要

摘要

En 中文
Compressing scientific data is essential to save on storage space, but doing so effectively while ensuring that the conclusions from the data are not affected remains a challenging task. A recent paper proposes a new method to identify numerical noise from floating-point atmospheric data, which can lead to a more effective compression.

期刊

Nature Computational Science 封面图
Nature Computational Science
IF:
18.3
论文数:
3.1K
被引数:
4.0K

机构

C
Colorado School of Mines
学者数:
5.6K
论文数: 5.5K
被引数: 1.0W
N
national center atmospheric research (ncar) - usa
学者数:
4.7K
论文数: 5.1K
被引数: 8
引用论文

引用论文

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A statistical analysis of lossily compressed climate model data
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errPoppick, Andrew; Nardi, Joseph; Feldman, Noah; Baker, Allison H.; Pinard, Alexander; Hammerling, Dorit M.
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Evaluating lossy data compression on climate simulation data within a large ensemble
err2016-12-07
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errOAAI
errBaker, Allison H.; Hammerling, Dorit M.; Mickelson, Sheri A.; Xu, Haiying; Stolpe, Martin B.; Naveau, Phillipe; Sanderson, Ben; Ebert-Uphoff, Imme; Samarasinghe, Savini; De Simone, Francesco; Carbone, Francesco; Gencarelli, Christian N.; Dennis, John M.; Kay, Jennifer E.; Lindstrom, Peter
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