Articles | Volume 16, issue 4
https://doi.org/10.5194/gmd-16-1179-2023
https://doi.org/10.5194/gmd-16-1179-2023
Development and technical paper
 | 
20 Feb 2023
Development and technical paper |  | 20 Feb 2023

The impact of altering emission data precision on compression efficiency and accuracy of simulations of the community multiscale air quality model

Michael S. Walters and David C. Wong

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Cited articles

Burrows, M. and Wheeler, D. J.: A Block Sorting Data Compression Algorithm, Tech. report, Digital Systems Research Center, Digital Equipment Corporation, Palo Alto, CA, http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.37.6774 (last access: 30 September 2021), 1994. 
Byun, D. and Schere, K. L.: Review of the governing equations, computational algorithms, and other components of the Models-3 Community Multiscale Air Quality (CMAQ) modeling system, Appl. Mech. Rev., 59, 51–77, https://doi.org/10.1115/1.2128636, 2006. 
CMAS: CMAQ Model Version 5.3 Input Data – 1/1/2016–12/31/2016 12 km CONUS, Dataverse [data set], https://doi.org/10.15139/S3/MHNUNE, 2023. 
Deutsch, L. P.: DEFLATE compressed data format specification version 1.3, Tech. Rep. IETF RFC1951, Internet Engineering Task Force, Menlo Park, CA, USA, https://doi.org/10.17487/RFC1951, 1996. 
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Short summary
A typical numerical simulation that associates with a large amount of input and output data, applying popular compression software, gzip or bzip2, on data is one good way to mitigate data storage burden. This article proposes a simple technique to alter input, output, or input and output by keeping a specific number of significant digits in data and demonstrates an enhancement in compression efficiency on the altered data but maintains similar statistical performance of the numerical simulation.