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.
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.
the Creative Commons Attribution 4.0 License.
Data description article
| 
10 Mar 2026
Data description article |
| 10 Mar 2026
| 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
Key Laboratory of Polar Atmosphere-Ocean-Ice System for Weather and Climate of Ministry of Education/Shanghai Key Laboratory of Ocean-Land-Atmosphere Boundary Dynamics and Climate Change, Department of Atmospheric and Oceanic Sciences & Institutes of Atmospheric Sciences, Fudan University, Shanghai, China
Feng Zhang
CORRESPONDING AUTHOR
Key Laboratory of Polar Atmosphere-Ocean-Ice System for Weather and Climate of Ministry of Education/Shanghai Key Laboratory of Ocean-Land-Atmosphere Boundary Dynamics and Climate Change, Department of Atmospheric and Oceanic Sciences & Institutes of Atmospheric Sciences, Fudan University, Shanghai, China
Zhijun Zhao
Key Laboratory of Polar Atmosphere-Ocean-Ice System for Weather and Climate of Ministry of Education/Shanghai Key Laboratory of Ocean-Land-Atmosphere Boundary Dynamics and Climate Change, Department of Atmospheric and Oceanic Sciences & Institutes of Atmospheric Sciences, Fudan University, Shanghai, China
Feng Lu
Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), Innovation Center for Feng Yun Meteorological Satellite (FYSIC), China Meteorological Administrations, Beijing, China
Jingwei Li
Key Laboratory of Polar Atmosphere-Ocean-Ice System for Weather and Climate of Ministry of Education/Shanghai Key Laboratory of Ocean-Land-Atmosphere Boundary Dynamics and Climate Change, Department of Atmospheric and Oceanic Sciences & Institutes of Atmospheric Sciences, Fudan University, Shanghai, China
College of Physics and Electronic Information Engineering, Zhejiang Normal University, Jinhua, China
Wenwen Li
Engineering Research Center of Optical Instrument and System, the Ministry of Education, Shanghai Key Laboratory of Modern Optical System, University of Shanghai for Science and Technology, Shanghai, China
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Xiaoli Wei, Qian Cui, Leiming Ma, Feng Zhang, Wenwen Li, and Peng Liu
Atmos. Chem. Phys., 24, 5025–5045, https://doi.org/10.5194/acp-24-5025-2024, https://doi.org/10.5194/acp-24-5025-2024, 2024
Short summary
Short summary
A new aerosol-type classification algorithm has been proposed. It includes an optical database built by Mie scattering and a complex refractive index working as a baseline to identify different aerosol types. The new algorithm shows high accuracy and efficiency. Hence, a global map of aerosol types was generated to characterize aerosol types across the five continents. It will help improve the accuracy of aerosol inversion and determine the sources of aerosol pollution.
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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.
Clouds strongly influence Earth's energy balance and water cycle, yet global cloud datasets...
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