Technical note: Applicability of physics-based and machine-learning-based algorithms of a geostationary satellite in retrieving the diurnal cycle of cloud base height
- DOI
- 10.5194/acp-24-14239-2024
- Published
- 2024-12-20
- Container
- Atmospheric Chemistry and Physics
- Publisher
- Copernicus GmbH
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.5194/acp-24-14239-2024,
title = {Technical note: Applicability of physics-based and machine-learning-based algorithms of a geostationary satellite in retrieving the diurnal cycle of cloud base height},
author = {Mengyuan Wang and Min Min and Jun Li and Han Lin and Yongen Liang and Binlong Chen and Zhigang Yao and Na Xu and Miao Zhang},
year = {2024},
journal = {Atmospheric Chemistry and Physics},
doi = {10.5194/acp-24-14239-2024},
url = {https://doi.org/10.5194/acp-24-14239-2024}
}RIS
TY - JOUR TI - Technical note: Applicability of physics-based and machine-learning-based algorithms of a geostationary satellite in retrieving the diurnal cycle of cloud base height AU - Mengyuan Wang AU - Min Min AU - Jun Li AU - Han Lin AU - Yongen Liang AU - Binlong Chen AU - Zhigang Yao AU - Na Xu AU - Miao Zhang PY - 2024 JO - Atmospheric Chemistry and Physics DO - 10.5194/acp-24-14239-2024 UR - https://doi.org/10.5194/acp-24-14239-2024 ER -
APA
Wang, M., Min, M., Li, J., Lin, H., Liang, Y., Chen, B., Yao, Z., Xu, N., & Zhang, M. (2024). Technical note: Applicability of physics-based and machine-learning-based algorithms of a geostationary satellite in retrieving the diurnal cycle of cloud base height. Atmospheric Chemistry and Physics. https://doi.org/10.5194/acp-24-14239-2024
Source records
- crossref · retrieved 2026-09-26T15:28:17.386Z