Articles | Volume 25, issue 22
https://doi.org/10.5194/acp-25-16347-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-16347-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Impact of cloud vertical structure perturbations on the retrieval of cloud optical thickness and effective radius from FY4A/AGRI
Jing Sun
College of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, China
China Meteorological Administration Basin Heavy Rainfall Key Laboratory/Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research, Institute of Heavy Rain, China Meteorological Administration, Wuhan 430205, China
Yunying Li
CORRESPONDING AUTHOR
College of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, China
Key Laboratory of High Impact Weather(special), China Meteorological Administration, Changsha 410073, China
Hao Hu
State Key Laboratory of Severe Weather Meteorological Science and Technology, CMA Earth System Modeling and Prediction Centre, Beijing 100081, China
Qian Li
College of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, China
Key Laboratory of High Impact Weather(special), China Meteorological Administration, Changsha 410073, China
Chengzhi Ye
Institute of Meteorological Sciences of Hunan Province, Hunan Meteorological Bureau, Changsha 410118, China
Yining Shi
State Key Laboratory of Severe Weather Meteorological Science and Technology, CMA Earth System Modeling and Prediction Centre, Beijing 100081, China
Zitong Chen
College of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, China
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Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
Short summary
Short summary
Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
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Short summary
Clouds strongly affect how sunlight and heat move through the atmosphere, but their vertical layers make them hard to study. We examined how different cloud layers influence satellite estimates of cloud thickness and droplet size using observations and computer simulations over China. We found that high ice clouds can hide lower water clouds, causing large errors. This shows satellites need to consider cloud layers to improve accuracy.
Clouds strongly affect how sunlight and heat move through the atmosphere, but their vertical...
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