Articles | Volume 21, issue 9
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


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to revisions (further review by Editor and Referees) (11 Jun 2017) by Lixin Wang
AR by Christian Massari on behalf of the Authors (10 Jul 2017)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (11 Jul 2017) by Lixin Wang
RR by Viviana Maggioni (12 Jul 2017)
RR by Anonymous Referee #2 (31 Jul 2017)
ED: Publish as is (01 Aug 2017) by Lixin Wang
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