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    Source: Monthly Weather Review:;2017:;volume( 145 ):;issue: 012::page 4937
    Author:
    Mueller, Kevin J.;Liu, Junjie;McCarty, Will;Gelaro, Ron
    DOI: 10.1175/MWR-D-17-0047.1
    Publisher: American Meteorological Society
    Abstract: AbstractThis study examines the benefit of assimilating cloud motion vector (CMV) wind observations obtained from the Multiangle Imaging SpectroRadiometer (MISR) within a Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), configuration of the Goddard Earth Observing System-5 (GEOS-5) model data assimilation system (DAS). Available in near?real time (NRT) and with a record dating back to 1999, MISR CMVs boast pole-to-pole coverage and geometric height assignment that is complementary to the suite of atmospheric motion vectors (AMVs) included in the MERRA-2 standard. Experiments spanning September?November of 2014 and March?May of 2015 estimated relative MISR CMV impact on the 24-h forecast error reduction with an adjoint-based forecast sensitivity method. MISR CMV were more consistently beneficial and provided twice as large a mean forecast benefit when larger uncertainties were assigned to the less accurate component of the CMV oriented along the MISR satellite ground track, as opposed to when equal uncertainties were assigned to the eastward and northward components as in previous studies. Assimilating only the cross-track component provided 60% of the benefit of both components. When optimally assimilated, MISR CMV proved broadly beneficial throughout the Earth, with the greatest benefit evident at high latitudes where there is a confluence of more frequent CMV coverage and gaps in coverage from other MERRA-2 wind observations. Globally, MISR represented 1.6% of the total forecast benefit, whereas regionally that percentage was as large as 3.7%.
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    contributor authorMueller, Kevin J.;Liu, Junjie;McCarty, Will;Gelaro, Ron
    date accessioned2018-01-03T11:03:06Z
    date available2018-01-03T11:03:06Z
    date copyright11/7/2017 12:00:00 AM
    date issued2017
    identifier othermwr-d-17-0047.1.pdf
    identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4246590
    description abstractAbstractThis study examines the benefit of assimilating cloud motion vector (CMV) wind observations obtained from the Multiangle Imaging SpectroRadiometer (MISR) within a Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), configuration of the Goddard Earth Observing System-5 (GEOS-5) model data assimilation system (DAS). Available in near?real time (NRT) and with a record dating back to 1999, MISR CMVs boast pole-to-pole coverage and geometric height assignment that is complementary to the suite of atmospheric motion vectors (AMVs) included in the MERRA-2 standard. Experiments spanning September?November of 2014 and March?May of 2015 estimated relative MISR CMV impact on the 24-h forecast error reduction with an adjoint-based forecast sensitivity method. MISR CMV were more consistently beneficial and provided twice as large a mean forecast benefit when larger uncertainties were assigned to the less accurate component of the CMV oriented along the MISR satellite ground track, as opposed to when equal uncertainties were assigned to the eastward and northward components as in previous studies. Assimilating only the cross-track component provided 60% of the benefit of both components. When optimally assimilated, MISR CMV proved broadly beneficial throughout the Earth, with the greatest benefit evident at high latitudes where there is a confluence of more frequent CMV coverage and gaps in coverage from other MERRA-2 wind observations. Globally, MISR represented 1.6% of the total forecast benefit, whereas regionally that percentage was as large as 3.7%.
    publisherAmerican Meteorological Society
    typeJournal Paper
    journal volume145
    journal issue12
    journal titleMonthly Weather Review
    identifier doi10.1175/MWR-D-17-0047.1
    journal fristpage4937
    journal lastpage4947
    treeMonthly Weather Review:;2017:;volume( 145 ):;issue: 012
    contenttypeFulltext
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