A fine-resolution soil moisture dataset for China in 2002–2018

Meng, Xiangjin; Mao, Kebiao; Meng, Fei; Shi, Jiancheng; Zeng, Jiangyuan; Shen, Xinyi; Cui, Yaokui; Jiang, Lingmei; Guo, Zhonghua

doi:https://doi.org/10.5194/essd-13-3239-2021

Articles | Volume 13, issue 7

https://doi.org/10.5194/essd-13-3239-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-13-3239-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 13, issue 7

Data description paper

|

07 Jul 2021

Data description paper |

| 07 Jul 2021

A fine-resolution soil moisture dataset for China in 2002–2018

Xiangjin Meng, Kebiao Mao, Fei Meng, Jiancheng Shi, Jiangyuan Zeng, Xinyi Shen, Yaokui Cui, Lingmei Jiang, and Zhonghua Guo

Data sets

A fine-resolution soil moisture dataset for China in 2002~2018 Xiangjin Meng, Kebiao Mao, Fei Meng, Jiancheng Shi, Jiangyuan Zeng, Xinyi Shen, Yaokui Cui, Lingmei Jiang, and Zhonghua Guo https://doi.org/10.5281/zenodo.4738556

Model code and software

reconstruction model-based downscaling techniques Xiangjin Meng, Kebiao Mao, Fei Meng, Jiancheng Shi, Jiangyuan Zeng, Xinyi Shen, Yaokui Cui, Lingmei Jiang, and Zhonghua Guo https://doi.org/10.5281/zenodo.4922393

Short summary

In order to improve the accuracy of China's regional agricultural drought monitoring and climate change research, we produced a long-term series of soil moisture products by constructing a time and depth correction model for three soil moisture products with the help of ground observation data. The spatial resolution is improved by building a spatial weight decomposition model, and validation indicates that the new product can meet application needs.