Articles | Volume 21, issue 9
https://doi.org/10.5194/hess-21-4347-2017
https://doi.org/10.5194/hess-21-4347-2017
Research article
 | 
05 Sep 2017
Research article |  | 05 Sep 2017

An assessment of the performance of global rainfall estimates without ground-based observations

Christian Massari, Wade Crow, and Luca Brocca

Viewed

Total article views: 5,909 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
3,971 1,807 131 5,909 504 111 127
  • HTML: 3,971
  • PDF: 1,807
  • XML: 131
  • Total: 5,909
  • Supplement: 504
  • BibTeX: 111
  • EndNote: 127
Views and downloads (calculated since 10 Apr 2017)
Cumulative views and downloads (calculated since 10 Apr 2017)

Viewed (geographical distribution)

Total article views: 5,909 (including HTML, PDF, and XML) Thereof 5,639 with geography defined and 270 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 21 Feb 2025
Download
Short summary
The paper explores a method for the assessment of the performance of global rainfall estimates without relying on ground-based observations. Thanks to this method, different global correlation maps are obtained (for the first time without relying on a benchmark dataset) for some of the most used globally available rainfall products. This is central for hydroclimatic studies within data-scarce regions, where ground observations are scarce to evaluate the relative quality of a rainfall product
Share