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 article
 | 
19 Aug 2025
Data description article |  | 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: 6,460 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
5,436 914 110 6,460 255 99 152
  • HTML: 5,436
  • PDF: 914
  • XML: 110
  • Total: 6,460
  • Supplement: 255
  • BibTeX: 99
  • EndNote: 152
Views and downloads (calculated since 12 Feb 2025)
Cumulative views and downloads (calculated since 12 Feb 2025)

Viewed (geographical distribution)

Total article views: 6,460 (including HTML, PDF, and XML) Thereof 6,460 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 10 Feb 2026
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