Earth System Science Data
Earth System Science Data
Earth System Science Data
Articles | Volume 14, issue 5
Articles | Volume 14, issue 5
https://doi.org/10.5194/essd-14-2315-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-2315-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 5
Data description paper
 | 
13 May 2022
Data description paper |  | 13 May 2022

A global long-term (1981–2019) daily land surface radiation budget product from AVHRR satellite data using a residual convolutional neural network

Jianglei Xu, Shunlin Liang, and Bo Jiang

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Short summary
Land surface all-wave net radiation (Rn) is a key parameter in many land processes. Current products have drawbacks of coarse resolutions, large uncertainty, and short time spans. A deep learning method was used to obtain global surface Rn. A long-term Rn product was generated from 1981 to 2019 using AVHRR data. The product has the highest accuracy and a reasonable spatiotemporal variation compared to three other products. Our product will play an important role in long-term climate change.
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