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2020 | OriginalPaper | Buchkapitel

8. The Goddard Profiling (GPROF) Precipitation Retrieval Algorithm

verfasst von : David L. Randel, Christian D. Kummerow, Sarah Ringerud

Erschienen in: Satellite Precipitation Measurement

Verlag: Springer International Publishing

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Abstract

Early in the 1990s, the Goddard Profiling Algorithm (GPROF) was created to retrieve both surface rainfall and hydrometeor vertical profiles from satellite passive microwave sensors. Over the last 25 years it has been the primary algorithm for the TRMM Microwave Imager (TMI) and the follow-on sensor – the Global Precipitation Measurement (GPM) Microwave Imager (GMI). To meet the objectives of these missions, GPROF has been designed not just for single sensors, but to consistently retrieve rainfall from the full suite of passive sensors in the GPM constellation. These include Advanced Microwave Scanning Radiometer-2 (AMSR2), Special Sensor Microwave Imager/Sounder (SSMIS), Microwave Humidity Sounder (MHS), Advanced Technology Microwave Sounder (ATMS), and the historical sensors, Special Sensor Microwave Imager (SSM/I), and the Advanced Technology Microwave Sounder (AMSR-E).

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Vorheriges Kapitel Introduction to Passive Microwave Retrieval Methods

Nächstes Kapitel Precipitation Estimation from the Microwave Integrated Retrieval System (MiRS)

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Brown, P. J., Kummerow, C. D., & Randel, D. L. (2016). Hurricane GPROF: An optimized ocean microwave rainfall retrieval for tropical cyclones. Journal of Atmospheric and Oceanic Technology, 33, 1539–1556. https://doi.org/10.1175/JTECH-D-15-0234.1.CrossRef

Duncan, D. I., & Kummerow, C. D. (2016). A 1DVAR retrieval applied to GMI: Algorithm description, validation, and sensitivities. Journal of Geophysical Research, 121, 7415–7429. https://doi.org/10.1002/2016JD024808.CrossRef

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Titel: The Goddard Profiling (GPROF) Precipitation Retrieval Algorithm
verfasst von: David L. Randel
Christian D. Kummerow
Sarah Ringerud
Verlag: Springer International Publishing
Buch: Satellite Precipitation Measurement
Print ISBN: 978-3-030-24567-2

Electronic ISBN: 978-3-030-24568-9

Copyright-Jahr: 2020
DOI: https://doi.org/10.1007/978-3-030-24568-9_8