Articles | Volume 17, issue 2
https://doi.org/10.5194/amt-17-515-2024
https://doi.org/10.5194/amt-17-515-2024
Research article
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25 Jan 2024
Research article | Highlight paper |  | 25 Jan 2024

GPROF V7 and beyond: assessment of current and potential future versions of the GPROF passive microwave precipitation retrievals against ground radar measurements over the continental US and the Pacific Ocean

Simon Pfreundschuh, Clément Guilloteau, Paula J. Brown, Christian D. Kummerow, and Patrick Eriksson

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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 egusphere-2023-1310', Anonymous Referee #1, 27 Sep 2023
    • AC1: 'Reply on RC1', Simon Pfreundschuh, 23 Oct 2023
  • RC2: 'Comment on egusphere-2023-1310', Anonymous Referee #2, 02 Oct 2023
    • AC2: 'Reply on RC2', Simon Pfreundschuh, 23 Oct 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Simon Pfreundschuh on behalf of the Authors (24 Oct 2023)  Author's response   Manuscript 
EF by Sarah Buchmann (25 Oct 2023)  Author's tracked changes 
ED: Referee Nomination & Report Request started (30 Oct 2023) by Domenico Cimini
RR by Anonymous Referee #1 (02 Nov 2023)
RR by Anonymous Referee #2 (15 Nov 2023)
ED: Publish subject to technical corrections (17 Nov 2023) by Domenico Cimini
AR by Simon Pfreundschuh on behalf of the Authors (04 Dec 2023)  Author's response   Manuscript 
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Executive editor
This work validates retrievals from the latest operational version of the NASA Goddard Profiling Algorithm (GPROF), currently version 7, and it quantitatively demonstrates the performance improvements with respect to previous versions (GPROF v05) at various spatial and temporal resolutions. It also presents new, not yet operationally implemented, machine learning based versions of GPROF (GPROF-NN).
Short summary
The latest version of the GPROF retrieval algorithm that produces global precipitation estimates using observations from the Global Precipitation Measurement mission is validated against ground-based radars. The validation shows that the algorithm accurately estimates precipitation on scales ranging from continental to regional. In addition, we validate candidates for the next version of the algorithm and identify principal challenges for further improving space-borne rain measurements.