Earth System Science Data
Earth System Science Data
Earth System Science Data
Articles | Volume 17, issue 11
Articles | Volume 17, issue 11
https://doi.org/10.5194/essd-17-6445-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-6445-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 11
Data description article
 | 
25 Nov 2025
Data description article |  | 25 Nov 2025

Multi-spatial scale assessment and multi-dataset fusion of global terrestrial evapotranspiration datasets

Yi Wu, Chiyuan Miao, Yiying Wang, Qi Zhang, Jiachen Ji, and Yuanfang Chai

Viewed

Total article views: 2,425 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,847 480 98 2,425 359 78 107
  • HTML: 1,847
  • PDF: 480
  • XML: 98
  • Total: 2,425
  • Supplement: 359
  • BibTeX: 78
  • EndNote: 107
Views and downloads (calculated since 24 Jan 2025)
Cumulative views and downloads (calculated since 24 Jan 2025)

Viewed (geographical distribution)

Total article views: 2,425 (including HTML, PDF, and XML) Thereof 2,403 with geography defined and 22 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 11 Feb 2026
Download
Short summary
Our study introduces BMA-ET, a novel multi-dataset fusion product. Spanning 1980 to 2020 with spatial resolution of 0.5° and 1°, BMA-ET uses Bayesian model averaging (BMA) to combine thirty evapotranspiration (ET) datasets. A key innovation is dynamic weighting scheme, which adjusts for vegetation types and non-common coverage years among ET datasets. BMA-ET provides a comprehensive resource for understanding global ET patterns and trends, addressing the limitation of prior ET fusion efforts.
Read more
Share
Altmetrics
Final-revised paper
Preprint