Articles | Volume 17, issue 6
https://doi.org/10.5194/essd-17-2405-2025
https://doi.org/10.5194/essd-17-2405-2025
Data description paper
 | 
06 Jun 2025
Data description paper |  | 06 Jun 2025

Estimation of long-term gridded cloud radiative kernel and radiative effects based on cloud fraction

Xinyan Liu, Tao He, Qingxin Wang, Xiongxin Xiao, Yichuan Ma, Yanyan Wang, Shanjun Luo, Lei Du, and Zhaocong Wu

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Short summary
This study addresses the challenge of how clouds affect the Earth's energy balance, which is vital for understanding climate change. We developed a new method to create long-term cloud radiative kernels to improve the accuracy of measurements of sunlight reaching the surface, which significantly reduces errors. Findings suggest that prior estimates of cloud cooling effects may have been overstated, emphasizing the need for better strategies to manage climate change impacts in the Arctic.
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