Articles | Volume 16, issue 17
https://doi.org/10.5194/amt-16-4067-2023
https://doi.org/10.5194/amt-16-4067-2023
Research article
 | 
11 Sep 2023
Research article |  | 11 Sep 2023

Long-term multi-source precipitation estimation with high resolution (RainGRS Clim)

Anna Jurczyk, Katarzyna Ośródka, Jan Szturc, Magdalena Pasierb, and Agnieszka Kurcz

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2023-98', Anonymous Referee #1, 22 Jun 2023
    • AC1: 'Reply on RC1', Jan Szturc, 26 Jun 2023
  • RC2: 'Comment on amt-2023-98', Anonymous Referee #2, 02 Jul 2023
    • AC2: 'Reply on RC2', Jan Szturc, 05 Jul 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Jan Szturc on behalf of the Authors (30 Jul 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (02 Aug 2023) by Gianfranco Vulpiani
AR by Jan Szturc on behalf of the Authors (02 Aug 2023)
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Short summary
A data-processing algorithm, RainGRS Clim, has been developed to work on precipitation accumulations such as daily or monthly totals. The algorithm makes the most of additional opportunities: access to high-quality data that are not operationally available and greater efficiency of the algorithms for data quality control and merging for longer accumulations. Monthly accumulations estimated by RainGRS Clim were found to be significantly more reliable than accumulations generated operationally.