Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 17, issue 2
Articles | Volume 17, issue 2
https://doi.org/10.5194/amt-17-515-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-17-515-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 2
Research article
 | Highlight paper
 | 
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

Data sets

GPM GMI (GPROF) Climate-based Radiometer Precipitation Profiling L2A 1.5 hours 4 km x 4 km V07 GPM Science Team https://doi.org/10.5067/GPM/GMI/GPROFCLIM/2A/07

GPM AMSR-2 on GCOM-W1 (GPROF) Climate-based Radiometer Precipitation Profiling L2A 1.5 hours 10 km V07 GPM Science Team https://doi.org/10.5067/GPM/AMSR2/GCOMW1/GPROFCLIM/2A/07

GPM MHS on NOAA-19 (GPROF) Radiometer Precipitation Profiling L2A 1.5 hours 17 km V07 GPM Science Team https://doi.org/10.5067/GPM/MHS/NOAA19/GPROFCLIM/2A/07

GPM ATMS on SUOMI-NPP (GPROF) Radiometer Precipitation Profiling L2 1.5 hours 16 km V07 GPM Science Team https://doi.org/10.5067/GPM/ATMS/NPP/GPROFCLIM/2A/07

GPM SSMIS on F17 (GPROF) Climate-based Radiometer Precipitation Profiling 1.5 hours 12 km V07 GPM Science Team https://doi.org/10.5067/GPM/SSMIS/F17/GPROFCLIM/2A/07

GPM DPR and GMI Combined Precipitation L2B 1.5 hours 5 km V07 William Olson https://doi.org/10.5067/GPM/DPRGMI/CMB/2B/07

Precipitation Measurements Missions Ground Validation Data David B. Wolff https://pmm-gv.gsfc.nasa.gov/

Model code and software

GPROF-NN: A neural network based implementation of the Goddard Profiling Algorithm Simon Pfreundschuh https://doi.org/10.5281/zenodo.10257786

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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).
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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.
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