All-day global cloud physical properties products with 0.07° resolution retrieved from geostationary satellite imagers covering the period from 2000 to 2022

Zhao, Lingxiao; Zhang, Feng; Zhao, Zhijun; Lu, Feng; Li, Jingwei; Guo, Bin; Li, Wenwen

doi:10.5194/essd-18-1813-2026

Articles | Volume 18, issue 3

https://doi.org/10.5194/essd-18-1813-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-18-1813-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 3

Data description article

|

10 Mar 2026

Data description article |

| 10 Mar 2026

All-day global cloud physical properties products with 0.07° resolution retrieved from geostationary satellite imagers covering the period from 2000 to 2022

Lingxiao Zhao, Feng Zhang, Zhijun Zhao, Feng Lu, Jingwei Li, Bin Guo, and Wenwen Li

Supplement

https://doi.org/10.5194/essd-18-1813-2026-supplement

Data sets

DaYu-GCP: DaYu all-day global cloud physical properties products with 0.07° resolution retrieved from geostationary satellite imagers covering the period from 2000 to 2022 Lingxiao Zhao et al. https://doi.org/10.57760/sciencedb.26292

IRBT2CPP: A training and testing dataset for machine learning training, ranging from infrared brightness temperature to cloud physical properties Lingxiao Zhao https://doi.org/10.57760/sciencedb.27171

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Short summary

Clouds strongly influence Earth's energy balance and water cycle, yet global cloud datasets cannot provide both long time coverage and high detail in space and time. We created an open dataset of continuous, high-resolution cloud physical properties every three hours from 2000 to 2022. Independent evaluation shows stable accuracy over years, no clear day–night bias, and continuous spatiotemporal coverage. This dataset supports more reliable studies of clouds' roles in radiation and hydrology.