Articles | Volume 16, issue 10
https://doi.org/10.5194/essd-16-4655-2024
https://doi.org/10.5194/essd-16-4655-2024
Data description paper
 | 
16 Oct 2024
Data description paper |  | 16 Oct 2024

A 10 km daily-level ultraviolet-radiation-predicting dataset based on machine learning models in China from 2005 to 2020

Yichen Jiang, Su Shi, Xinyue Li, Chang Xu, Haidong Kan, Bo Hu, and Xia Meng

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Latest update: 22 May 2025
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Short summary
Limited ultraviolet (UV) measurements hindered further investigation of its health effects. This study used a machine learning algorithm to predict UV radiation with a daily and 10 km resolution of high accuracy in mainland China in 2005–2020. Then, uneven spatial distribution and population exposure risks as well as increased temporal trend of UV radiation were found in China. The long-term and high-quality UV dataset could further facilitate health-related research in the future.
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