Articles | Volume 17, issue 23
https://doi.org/10.5194/gmd-17-8593-2024
https://doi.org/10.5194/gmd-17-8593-2024
Development and technical paper
 | 
05 Dec 2024
Development and technical paper |  | 05 Dec 2024

Software sustainability of global impact models

Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke

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Cited articles

Abernathey, R. P., Augspurger, T., Banihirwe, A., Blackmon-Luca, C. C., Crone, T. J., Gentemann, C. L., Hamman, J. J., Henderson, N., Lepore, C., McCaie, T. A., Robinson, N. H., and Signell, R. P.: Cloud-Native Repositories for Big Scientific Data, Comput. Sci. Eng., 23, 26–35, https://doi.org/10.1109/MCSE.2021.3059437, 2021. 
Alexander, K. and Easterbrook, S. M.: The software architecture of climate models: a graphical comparison of CMIP5 and EMICAR5 configurations, Geosci. Model Dev., 8, 1221–1232, https://doi.org/10.5194/gmd-8-1221-2015, 2015. 
Arafat, O. and Riehle, D.: The comment density of open source software code, in: 2009 31st International Conference on Software Engineering – Companion Volume, 16–24 May 2009, Vancouver, BC, Canada, 195–198, https://doi.org/10.1109/ICSE-COMPANION.2009.5070980, 2009. 
Azmi, E., Ehret, U., Weijs, S. V., Ruddell, B. L., and Perdigão, R. A. P.: Technical note: “Bit by bit”: a practical and general approach for evaluating model computational complexity vs. model performance, Hydrol. Earth Syst. Sci., 25, 1103–1115, https://doi.org/10.5194/hess-25-1103-2021, 2021. 
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Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
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