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

Related authors

Application and Evaluation of CRACMM V1.0 Mechanism in PM2.5 Simulation Over China
Qingfang Su, Yifei Chen, Yangjun Wang, David C. Wong, Havala O. T. Pye, Ling Huang, Golam Sarwar, Benjamin Murphy, Bryan Place, and Li Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-3627,https://doi.org/10.5194/egusphere-2025-3627, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Accounting for the black carbon aging process in a two-way coupled meteorology–air quality model
Yuzhi Jin, Jiandong Wang, Chao Liu, David C. Wong, Golam Sarwar, Kathleen M. Fahey, Shang Wu, Jiaping Wang, Jing Cai, Zeyuan Tian, Zhouyang Zhang, Jia Xing, Aijun Ding, and Shuxiao Wang
Atmos. Chem. Phys., 25, 2613–2630, https://doi.org/10.5194/acp-25-2613-2025,https://doi.org/10.5194/acp-25-2613-2025, 2025
Short summary
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024,https://doi.org/10.5194/gmd-17-7855-2024, 2024
Short summary
Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3: performance evaluation and benefits for the user community
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024,https://doi.org/10.5194/gmd-17-7001-2024, 2024
Short summary
The pathway of impacts of aerosol direct effects on secondary inorganic aerosol formation
Jiandong Wang, Jia Xing, Shuxiao Wang, Rohit Mathur, Jiaping Wang, Yuqiang Zhang, Chao Liu, Jonathan Pleim, Dian Ding, Xing Chang, Jingkun Jiang, Peng Zhao, Shovan Kumar Sahu, Yuzhi Jin, David C. Wong, and Jiming Hao
Atmos. Chem. Phys., 22, 5147–5156, https://doi.org/10.5194/acp-22-5147-2022,https://doi.org/10.5194/acp-22-5147-2022, 2022
Short summary

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. 
Download
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.
Share