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: 5,469 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
3,648 1,703 118 5,469 482 96 115
  • HTML: 3,648
  • PDF: 1,703
  • XML: 118
  • Total: 5,469
  • Supplement: 482
  • BibTeX: 96
  • EndNote: 115
Views and downloads (calculated since 10 Apr 2017)
Cumulative views and downloads (calculated since 10 Apr 2017)

Viewed (geographical distribution)

Total article views: 5,469 (including HTML, PDF, and XML) Thereof 5,214 with geography defined and 255 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 29 Jun 2024
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