A global classification dataset of daytime and nighttime marine low-cloud mesoscale morphology based on deep-learning methods
<p>Marine low clouds tend to organize into larger mesoscale patterns with distinct morphological appearances over the ocean, referred to as mesoscale morphology. While previous studies have mainly examined the fundamental characteristics and shortwave radiative effects of these mesoscale morph...
Saved in:
| Main Authors: | Y. Wu, J. Liu, Y. Zhu, Y. Zhang, Y. Cao, K.-E. Huang, B. Zheng, Y. Wang, Y. Li, Q. Wang, C. Zhou, Y. Liang, J. Sun, M. Wang, D. Rosenfeld |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2025-07-01
|
| Series: | Earth System Science Data |
| Online Access: | https://essd.copernicus.org/articles/17/3243/2025/essd-17-3243-2025.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
On the Choice of Training Data for Machine Learning of Geostrophic Mesoscale Turbulence
by: F. E. Yan, et al.
Published: (2024-02-01) -
Subgrid-scale aerosol–cloud interaction in the atmospheric chemistry model CMA_Meso5.1/CUACE and its impacts on mesoscale meteorology prediction
by: W. Zhang, et al.
Published: (2025-08-01) -
The Hourly Apnea-Hypopnea Duration Better Correlates with OSA-Related Nocturnal Hypoxemia and Excessive Daytime Sleepiness Rather Than AHI
by: Wang Y, et al.
Published: (2025-05-01) -
Daytime and Nighttime Image of Cities
by: Düriye Dilan Öner, et al.
Published: (2025-07-01) -
Associations Among Obstructive Sleep Apnea, Thyroid Function and Morphology Changes
by: Xie Y, et al.
Published: (2025-07-01)