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dc.contributor.authorRichard M. Schulte
dc.contributor.authorChristian D. Kummerow
dc.contributor.authorChristian Klepp
dc.contributor.authorGerald G. Mace
dc.date.accessioned2023-04-12T18:26:10Z
dc.date.available2023-04-12T18:26:10Z
dc.date.copyright2022/09/01
dc.date.issued2022
dc.identifier.otherJAMC-D-21-0158.1.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4289661
dc.description.abstractA significant part of the uncertainty in satellite-based precipitation products stems from differing assumptions about drop size distributions (DSDs). Satellite radar-based retrieval algorithms rely on DSD assumptions that may be overly simplistic, whereas radiometers further struggle to distinguish cloud water from rain. We utilize the Ocean Rainfall and Ice-phase Precipitation Measurement Network (OceanRAIN), version 1.0, dataset to examine the impact of DSD variability on the ability of satellite measurements to accurately estimate rates of warm rainfall. We use the binned disdrometer counts and a simple model of the atmosphere to simulate observations for three satellite architectures. Two are similar to existing instrument combinations on the GPM
dc.publisherAmerican Meteorological Society
dc.titleHow Accurately Can Warm Rain Realistically Be Retrieved with Satellite Sensors? Part I: DSD Uncertainties
dc.typeJournal Paper
dc.journal.volume61
dc.journal.issue9
dc.journal.titleJournal of Applied Meteorology and Climatology
dc.identifier.doi10.1175/JAMC-D-21-0158.1
dc.journal.fristpage1087
dc.journal.lastpage1105
dc.page1087–1105
dc.treeJournal of Applied Meteorology and Climatology:;2022:;volume( 061 ):;issue: 009
dc.contenttypeFulltext


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