Earth System Science Data
Earth System Science Data
Earth System Science Data
Articles | Volume 14, issue 5
Articles | Volume 14, issue 5
https://doi.org/10.5194/essd-14-2259-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/essd-14-2259-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 5
Data description paper
 | 
12 May 2022
Data description paper |  | 12 May 2022

A global drought dataset of standardized moisture anomaly index incorporating snow dynamics (SZIsnow) and its application in identifying large-scale drought events

Lei Tian, Baoqing Zhang, and Pute Wu

Viewed

Total article views: 12,104 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
10,993 988 123 12,104 267 94 113
  • HTML: 10,993
  • PDF: 988
  • XML: 123
  • Total: 12,104
  • Supplement: 267
  • BibTeX: 94
  • EndNote: 113
Views and downloads (calculated since 26 Nov 2021)
Cumulative views and downloads (calculated since 26 Nov 2021)

Viewed (geographical distribution)

Total article views: 12,104 (including HTML, PDF, and XML) Thereof 10,098 with geography defined and 2,006 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 30 Jun 2025
Download
Short summary
We propose a global monthly drought dataset with a resolution of 0.25° from 1948 to 2010 based on a multitype and multiscalar drought index, the standardized moisture anomaly index adding snow processes (SZIsnow). The consideration of snow processes improved its capability, and the improvement is prominent over snow-covered high-latitude and high-altitude areas. This new dataset is well suited to monitoring, assessing, and characterizing drought and is a valuable resource for drought studies.
Read more
Share
Special issue
Extreme environment datasets for the three poles
Altmetrics
Final-revised paper
Preprint