Articles | Volume 14, issue 6
https://doi.org/10.5194/essd-14-2681-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-2681-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
09 Jun 2022
Data description paper |
| 09 Jun 2022
| 09 Jun 2022
New gridded dataset of rainfall erosivity (1950–2020) on the Tibetan Plateau
Yueli Chen
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing, 100081, China
Xingwu Duan
CORRESPONDING AUTHOR
Institute of International Rivers and Eco-security, Yunnan University,
Kunming, 650091, China
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing, 100081, China
Wei Qi
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing, 100081, China
Ting Wei
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing, 100081, China
Jianduo Li
CMA Earth System Modeling and Prediction Centre, Beijing, 100081,
China
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing, 100081, China
Yun Xie
State Key Laboratory of Earth Surface Processes and Resources Ecology,
Faculty of Geographic Science, Beijing Normal University, Beijing, 100875,
China
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https://doi.org/10.1007/s00382-021-05653-8, 2021.
Short summary
We reconstructed the first annual rainfall erosivity dataset for the Tibetan Plateau in China. The dataset covers 71 years in a 0.25° grid. The reanalysis precipitation data are employed in combination with the densely spaced in situ precipitation observations to generate the dataset. The dataset can supply fundamental data for quantifying the water erosion, and extend our knowledge of the rainfall-related hazard prediction on the Tibetan Plateau.
We reconstructed the first annual rainfall erosivity dataset for the Tibetan Plateau in China....
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