Articles | Volume 15, issue 14
Geosci. Model Dev., 15, 5829–5856, 2022
Geosci. Model Dev., 15, 5829–5856, 2022
Methods for assessment of models
27 Jul 2022
Methods for assessment of models | 27 Jul 2022

Cloud-based framework for inter-comparing submesoscale-permitting realistic ocean models

Takaya Uchida et al.

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Cited articles

Abernathey, R. P.: Petabytes of Ocean Data, Part I: NASA ECCO Data Portal, (last access: 8 July 2022), 2019. a, b
Abernathey, R. P.: fastjmd95: Numba implementation of Jackett & McDougall (1995) ocean equation of state, Zenodo [code],, 2020. a
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,, 2021a. a, b
Abernathey, R. P., Busecke, J., Smith, T., et al.: xgcm: General Circulation Model Postprocessing with xarray, Zenodo [code],, 2021b. a, b
Abernathey, R. P., Dougie, S., Nicholas, T., Bourbeau, J., Joseph, G., Yunyi, Y., Bailey, S., Bell, R., and Spring, A.: xhistogram: Fast, flexible, label-aware histograms for numpy and xarray, Zenodo [code],, 2021c. a
Short summary
Ocean and climate scientists have used numerical simulations as a tool to examine the ocean and climate system since the 1970s. Since then, owing to the continuous increase in computational power and advances in numerical methods, we have been able to simulate increasing complex phenomena. However, the fidelity of the simulations in representing the phenomena remains a core issue in the ocean science community. Here we propose a cloud-based framework to inter-compare and assess such simulations.