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The GPM Combined AlgorithmIn this paper, the operational Global Precipitation Measurement (GPM) mission combined radar-radiometer algorithm is thoroughly described. The operational combined algorithm is designed to reduce uncertainties in GPM Core Observatory precipitation estimates by effectively integrating complementary information from the GPM Dual-Frequency Precipitation Radar (DPR) and the GPM Microwave Imager (GMI) into an optimal, physically consistent precipitation product. Although similar in many respects to previously developed combined algorithms, the GPM combined algorithm has several unique features that are specifically designed to meet the GPM objectives of deriving, based on GPM Core Observatory information, accurate and physically consistent precipitation estimates from multiple spaceborne instruments, and ancillary environmental data from reanalyses. The algorithm features an optimal estimation framework based on a statistical formulation of the Gauss-Newton method, a parameterization for the nonuniform distribution of precipitation within the radar fields of view, a methodology to detect and account for multiple scattering in Ka-band DPR observations, and a statistical deconvolution technique that allows for an efficient sequential incorporation of radiometer information into DPR precipitation retrievals.
Document ID
20180000748
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
Authors
Grecu, Mircea
(Morgan State Univ. Baltimore, MD, United States)
Olson, William S.
(Maryland Univ. Greenbelt, MD, United States)
Munchak, Stephen Joseph
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Ringerud, Sarah
(Maryland Univ. Greenbelt, MD, United States)
Liao, Liang
(Morgan State Univ. Baltimore, MD, United States)
Haddad, Ziad
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Kelley, Bartie L.
(Science Systems and Applications, Inc. Lanham, MD, United States)
Mclaughlin, Steven F.
(Science Systems and Applications, Inc. Lanham, MD, United States)
Date Acquired
January 25, 2018
Publication Date
October 12, 2016
Publication Information
Publication: Journal of Atmospheric and Oceanic Technology
Publisher: American Meteorological Society
Volume: 33
Issue: 10
ISSN: 0739-0572
e-ISSN: 1520-0426
Subject Category
Meteorology And Climatology
Report/Patent Number
GSFC-E-DAA-TN51634
E-ISSN: 1520-0426
Report Number: GSFC-E-DAA-TN51634
ISSN: 0739-0572
Funding Number(s)
CONTRACT_GRANT: NNX13AF85G
CONTRACT_GRANT: NNN12AA01C
CONTRACT_GRANT: NNG12HP08C
CONTRACT_GRANT: NNG11HP16A
CONTRACT_GRANT: NNG17HP01C
CONTRACT_GRANT: NNX17AE79A
CONTRACT_GRANT: NNX15AT34A
Distribution Limits
Public
Copyright
Other

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