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A process-based validation of GPM IMERG and its sources using a mesoscale rain gauge network in the West African forest zone

Maranan, Marlon 1; Fink, Andreas H. 1; Knippertz, Peter ORCID iD icon 1; Amekudzi, Leonard K.; Atiah, Winifred A.; Stengel, Martin
1 Karlsruher Institut für Technologie (KIT)


Using a two-year dataset (2016–17) from 17 one-minute rain gauges located in the moist forest region of Ghana, the performance of Integrated Multisatellite Retrievals for GPM, version 6b (IMERG), is evaluated based on a subdaily time scale, down to the level of the underlying passive microwave (PMW) and infrared (IR) sources. Additionally, the spaceborne cloud product Cloud Property Dataset Using SEVIRI, edition 2 (CLAAS-2), available every 15 min, is used to link IMERG rainfall to cloud-top properties. Several important issues are identified: 1) IMERG’s proneness to low-intensity false alarms, accounting for more than a fifth of total rainfall; 2) IMERG’s overestimation of the rainfall amount from frequently occurring weak convective events, while that of relatively rare but strong mesoscale convective systems is underestimated, resulting in an error compensation; and 3) a decrease of skill during the little dry season in July and August, known to feature enhanced low-level cloudiness and warm rain. These findings are related to 1) a general oversensitivity for clouds with low ice and liquid water path and a particular oversensitivity for low cloud optical thickness, a problem which is slightly reduced for direct PMW overpasses; 2) a pronounced negative bias for high rain intensities, strongest when IR data are included; and 3) a large fraction of missed events linked with rainfall out of warm clouds, which are inherently misinterpreted by IMERG and its sources. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000117601
Veröffentlicht am 13.12.2021
DOI: 10.1175/JHM-D-19-0257.1
Zitationen: 39
Zitationen: 40
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2020
Sprache Englisch
Identifikator ISSN: 1525-755X, 1525-7541
KITopen-ID: 1000117601
HGF-Programm 12.01.02 (POF III, LK 01) Proc.res.f.multisc.predictab.of weather
Erschienen in Journal of hydrometeorology
Verlag American Meteorological Society
Band 21
Heft April 2020
Seiten 729-749
Vorab online veröffentlicht am 05.03.2020
Schlagwörter Athmosphere; Africa; Deep convection; Precipitation; Cloud microphysics; Remote sensing
Nachgewiesen in Scopus
Web of Science
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