Earth System Science Data
Earth System Science Data
Earth System Science Data
Articles | Volume 17, issue 8
Articles | Volume 17, issue 8
https://doi.org/10.5194/essd-17-3987-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-3987-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 8
Data description paper
 | 
19 Aug 2025
Data description paper |  | 19 Aug 2025

An upgraded high-precision gridded precipitation dataset for the Chinese mainland considering spatial autocorrelation and covariates

Jinlong Hu, Chiyuan Miao, Jiajia Su, Qi Zhang, Jiaojiao Gou, and Qiaohong Sun

Viewed

Total article views: 2,266 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,990 237 39 2,266 59 19 48
  • HTML: 1,990
  • PDF: 237
  • XML: 39
  • Total: 2,266
  • Supplement: 59
  • BibTeX: 19
  • EndNote: 48
Views and downloads (calculated since 12 Feb 2025)
Cumulative views and downloads (calculated since 12 Feb 2025)

Viewed (geographical distribution)

Total article views: 2,266 (including HTML, PDF, and XML) Thereof 2,266 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 19 Aug 2025
Download
Short summary
We developed a high-precision daily precipitation dataset for the Chinese mainland called CHM_PRE V2. Using data from 3746 rain gauges, 11 precipitation-related variables, and advanced machine learning methods, we created a daily precipitation dataset spanning 1960–2023 with unprecedented accuracy. Compared to existing datasets, it better captures rainfall events while reducing false alarms. This work provides a reliable tool for studying water resources, climate change, and disaster management.
Read more
Share
Altmetrics
Final-revised paper
Preprint