The Cryosphere
The Cryosphere
TC
Articles | Volume 18, issue 9
Articles | Volume 18, issue 9
https://doi.org/10.5194/tc-18-4089-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-18-4089-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 9
Research article
 | 
10 Sep 2024
Research article |  | 10 Sep 2024

Which global reanalysis dataset has better representativeness in snow cover on the Tibetan Plateau?

Shirui Yan, Yang Chen, Yaliang Hou, Kexin Liu, Xuejing Li, Yuxuan Xing, Dongyou Wu, Jiecan Cui, Yue Zhou, Wei Pu, and Xin Wang

Viewed

Total article views: 2,457 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,006 364 87 2,457 137 68 150
  • HTML: 2,006
  • PDF: 364
  • XML: 87
  • Total: 2,457
  • Supplement: 137
  • BibTeX: 68
  • EndNote: 150
Views and downloads (calculated since 23 Feb 2024)
Cumulative views and downloads (calculated since 23 Feb 2024)

Viewed (geographical distribution)

Total article views: 2,457 (including HTML, PDF, and XML) Thereof 2,417 with geography defined and 40 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 19 Dec 2025
Download
Short summary
The snow cover over the Tibetan Plateau (TP) plays a role in climate and hydrological systems, yet there are uncertainties in snow cover fraction (SCF) estimations within reanalysis datasets. This study utilized the Snow Property Inversion from Remote Sensing (SPIReS) SCF data to assess the accuracy of eight widely used reanalysis SCF datasets over the TP. Factors contributing to uncertainties were analyzed, and a combined averaging method was employed to provide optimized SCF simulations.
Read more
Share