A deep-learning-based consistency test approach for Earth system models on HPC systems.

Yu Y, Zhang S, Fu H, Chen D, Gao Y, Lin X, Liu Z, Lv X

DOI: 10.1016/j.isci.2024.111574
Published: 2025 Jan 17
Container: iScience
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1016/j.isci.2024.111574,
  title = {A deep-learning-based consistency test approach for Earth system models on HPC systems.},
  author = {Yu Y and Zhang S and Fu H and Chen D and Gao Y and Lin X and Liu Z and Lv X},
  year = {2025},
  journal = {iScience},
  doi = {10.1016/j.isci.2024.111574},
  url = {https://doi.org/10.1016/j.isci.2024.111574}
}

RIS

TY  - JOUR
TI  - A deep-learning-based consistency test approach for Earth system models on HPC systems.
AU  - Yu Y
AU  - Zhang S
AU  - Fu H
AU  - Chen D
AU  - Gao Y
AU  - Lin X
AU  - Liu Z
AU  - Lv X
PY  - 2025
JO  - iScience
DO  - 10.1016/j.isci.2024.111574
UR  - https://doi.org/10.1016/j.isci.2024.111574
ER  -

APA

Y, Y., S, Z., H, F., D, C., Y, G., X, L., Z, L., & X, L. (2025). A deep-learning-based consistency test approach for Earth system models on HPC systems.. iScience. https://doi.org/10.1016/j.isci.2024.111574

Source records

pubmed · retrieved 2026-09-26T06:30:50.720Z