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A Diagnosis of Oceanic Precipitation in IMERG-GMIDiagnosing errors in spaceborne oceanic precipitation estimates is difficult due to complicated multi-satellite algorithms and limited surface-based measurements. The Global Precipitation Measurement (GPM) mission helps to alleviate these challenges with NASA’s Integrated Multi-satellitE Retrievals for GPM (IMERG) product, which is transparently designed to encourage community validation activities, and the GPM Validation Network, which collects observations across global precipitation regimes from over 100 ground-based weather radars to serve as reference datasets for the GPM precipitation products. This study uses the GPM Validation Network’s oceanic precipitation observations from 32 island and coastal radars to diagnose the performance of IMERG V06B & V07B Final Run products during GPM Microwave Imager (GMI) overpasses (i.e., IMERG-GMI) in the period June 2014 – September 2021. Errors are traced from the input Level-2 (satellite footprint) Goddard Profiling Algorithm climate (GPROF-CLIM) GMI product through the successive gridding, calibration and precipitation distribution restoration steps of IMERG’s Level-3 (gridded) algorithm. Results highlight that IMERG-GMI V07B outperforms V06B in detecting and quantifying oceanic precipitation, with a significant improvement over high-latitude ocean (V06B: +143%; V07B: +50%). Furthermore, there is a clear oceanic latitudinal trend in the mean relative bias of IMERG-GMI V07B (high-latitude: +50%; mid-latitude: +10%; tropical: −41%), which largely traces back to GPROF-CLIM V07 (high-latitude: +22%; mid-latitude: −8%; tropical: −44%), with bias differences driven by IMERG’s passive microwave calibration scheme. This error tracing approach supports future IMERG algorithm developments by disentangling how algorithm steps enhance or mitigate errors.
Document ID
20250002249
Acquisition Source
Marshall Space Flight Center
Document Type
Accepted Manuscript (Version with final changes)
Authors
Daniel C Watters
(Universities Space Research Association Columbia, United States)
George J Huffman
(Goddard Space Flight Center Greenbelt, United States)
Patrick N Gatlin
(Marshall Space Flight Center Redstone Arsenal, United States)
Pierre-Emmanuel Kirstetter ORCID
(University of Oklahoma Norman, United States)
David T Bolvin
(Goddard Space Flight Center Greenbelt, United States)
Robert Joyce
(Science Systems and Applications (United States) Lanham, Maryland, United States)
Eric J Nelkin
(Science Systems & Applications, Inc. Hampton, VA, USA)
Jackson Tan
(University of Maryland, Baltimore County Baltimore, Maryland, United States)
David B Wolff
(Goddard Space Flight Center Greenbelt, United States)
Date Acquired
March 3, 2025
Publication Date
March 6, 2025
Publication Information
Publication: Journal of Hydrometeorology
Publisher: American Meteorological Society (AMS-HQ)
ISSN: 1525-755X
e-ISSN: 1525-7541
Subject Category
Meteorology and Climatology
Funding Number(s)
CONTRACT_GRANT: 80NSSC19K0681
CONTRACT_GRANT: 80NSSC21K2045
WBS: 378289.04.05.10
Distribution Limits
Public
Copyright
Use by or on behalf of the US Gov. Permitted.
Technical Review
External Peer Committee
Keywords
remote sensing
precipitation
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