Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Hydrol. Earth Syst. Sci., 21, 4347-4361, 2017
https://doi.org/10.5194/hess-21-4347-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
05 Sep 2017
An assessment of the performance of global rainfall estimates without ground-based observations
Christian Massari et al.
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Interactive discussionStatus: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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RC1: 'Review', Anonymous Referee #1, 18 Apr 2017 Printer-friendly Version Supplement 
AC1: 'Responses to the comments of reviewer #1: An assessment of the accuracy of global rainfall estimates without ground-based observations', Christian Massari, 08 May 2017 Printer-friendly Version Supplement 
 
RC2: 'Anonymous Reviewer Comments', Anonymous Referee #2, 25 Apr 2017 Printer-friendly Version Supplement 
AC2: 'Responses to the comments of reviewer #2: An assessment of the accuracy of global rainfall estimates without ground-based observations', Christian Massari, 17 May 2017 Printer-friendly Version Supplement 
RC4: 'My comments have also been addressed.', Anonymous Referee #2, 19 May 2017 Printer-friendly Version 
 
RC3: 'Comments have been addressed', Anonymous Referee #1, 17 May 2017 Printer-friendly Version 
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
CC BY 4.0
Publications Copernicus
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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
The paper explores a method for the assessment of the performance of global rainfall estimates...
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