Advancing sub-seasonal to seasonal multi-model ensemble precipitation prediction in east asia: Deep learning-based post-processing for improved accuracy.
- DOI
- 10.1016/j.heliyon.2024.e35933
- Published
- 2024 Aug 30
- Container
- Heliyon
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1016/j.heliyon.2024.e35933,
title = {Advancing sub-seasonal to seasonal multi-model ensemble precipitation prediction in east asia: Deep learning-based post-processing for improved accuracy.},
author = {Chung U and Rhee J and Kim M and Sohn SJ},
year = {2024},
journal = {Heliyon},
doi = {10.1016/j.heliyon.2024.e35933},
url = {https://doi.org/10.1016/j.heliyon.2024.e35933}
}RIS
TY - JOUR TI - Advancing sub-seasonal to seasonal multi-model ensemble precipitation prediction in east asia: Deep learning-based post-processing for improved accuracy. AU - Chung U AU - Rhee J AU - Kim M AU - Sohn SJ PY - 2024 JO - Heliyon DO - 10.1016/j.heliyon.2024.e35933 UR - https://doi.org/10.1016/j.heliyon.2024.e35933 ER -
APA
U, C., J, R., M, K., & SJ, S. (2024). Advancing sub-seasonal to seasonal multi-model ensemble precipitation prediction in east asia: Deep learning-based post-processing for improved accuracy.. Heliyon. https://doi.org/10.1016/j.heliyon.2024.e35933
Source records
- pubmed · retrieved 2026-09-25T14:51:07.460Z