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    Variational Assimilation of Global Microwave Rainfall Retrievals: Physical and Dynamical Impact on GEOS Analyses

    Source: Monthly Weather Review:;2007:;volume( 135 ):;issue: 008::page 2931
    Author:
    Lin, Xin
    ,
    Zhang, Sara Q.
    ,
    Hou, Arthur Y.
    DOI: 10.1175/MWR3434.1
    Publisher: American Meteorological Society
    Abstract: Global microwave rainfall retrievals from a five-satellite constellation, including the Tropical Rainfall Measuring Mission Microwave Imager, Special Sensor Microwave Imager from the Defense Meteorological Satellite Program F13, F14, and F15, and the Advanced Microwave Scanning Radiometer from the Earth Observing System Aqua, are assimilated into the NASA Goddard Earth Observing System (GEOS) Data Assimilation System using a 1D variational continuous assimilation (VCA) algorithm. The physical and dynamical impact of rainfall assimilation on GEOS analyses is examined at various temporal and spatial scales. This study demonstrates that the 1D VCA algorithm, which was originally developed and evaluated for rainfall assimilations over tropical oceans, can effectively assimilate satellite microwave rainfall retrievals and improve GEOS analyses over both the Tropics and the extratropics where the atmospheric processes are dominated by different large-scale dynamics and moist physics, and also over land, where rainfall estimates from passive microwave radiometers are believed to be less accurate. Results show that rainfall assimilation renders the GEOS analysis physically and dynamically more consistent with the observed precipitation at the monthly mean and 6-h time scales. Over regions where the model precipitation tends to misbehave in distinctly different rainy regimes, the 1D VCA algorithm, by compensating for errors in the model?s moist time tendency in a 6-h analysis window, is able to bring the rainfall analysis closer to the observed. The radiation and cloud fields also tend to be in better agreement with independent satellite observations in the rainfall?assimilation run especially over regions where rainfall analyses indicate large improvements. Assimilation experiments with and without rainfall data for a midlatitude frontal system clearly indicate that the GEOS analysis is improved through changes in the thermodynamic and dynamic fields that respond to the rainfall assimilation. The synoptic structures of temperature, moisture, winds, divergence, and vertical motion, as well as vorticity, are more realistically captured across the front.
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      Variational Assimilation of Global Microwave Rainfall Retrievals: Physical and Dynamical Impact on GEOS Analyses

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4229486
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    • Monthly Weather Review

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    contributor authorLin, Xin
    contributor authorZhang, Sara Q.
    contributor authorHou, Arthur Y.
    date accessioned2017-06-09T17:28:38Z
    date available2017-06-09T17:28:38Z
    date copyright2007/08/01
    date issued2007
    identifier issn0027-0644
    identifier otherams-85980.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4229486
    description abstractGlobal microwave rainfall retrievals from a five-satellite constellation, including the Tropical Rainfall Measuring Mission Microwave Imager, Special Sensor Microwave Imager from the Defense Meteorological Satellite Program F13, F14, and F15, and the Advanced Microwave Scanning Radiometer from the Earth Observing System Aqua, are assimilated into the NASA Goddard Earth Observing System (GEOS) Data Assimilation System using a 1D variational continuous assimilation (VCA) algorithm. The physical and dynamical impact of rainfall assimilation on GEOS analyses is examined at various temporal and spatial scales. This study demonstrates that the 1D VCA algorithm, which was originally developed and evaluated for rainfall assimilations over tropical oceans, can effectively assimilate satellite microwave rainfall retrievals and improve GEOS analyses over both the Tropics and the extratropics where the atmospheric processes are dominated by different large-scale dynamics and moist physics, and also over land, where rainfall estimates from passive microwave radiometers are believed to be less accurate. Results show that rainfall assimilation renders the GEOS analysis physically and dynamically more consistent with the observed precipitation at the monthly mean and 6-h time scales. Over regions where the model precipitation tends to misbehave in distinctly different rainy regimes, the 1D VCA algorithm, by compensating for errors in the model?s moist time tendency in a 6-h analysis window, is able to bring the rainfall analysis closer to the observed. The radiation and cloud fields also tend to be in better agreement with independent satellite observations in the rainfall?assimilation run especially over regions where rainfall analyses indicate large improvements. Assimilation experiments with and without rainfall data for a midlatitude frontal system clearly indicate that the GEOS analysis is improved through changes in the thermodynamic and dynamic fields that respond to the rainfall assimilation. The synoptic structures of temperature, moisture, winds, divergence, and vertical motion, as well as vorticity, are more realistically captured across the front.
    publisherAmerican Meteorological Society
    titleVariational Assimilation of Global Microwave Rainfall Retrievals: Physical and Dynamical Impact on GEOS Analyses
    typeJournal Paper
    journal volume135
    journal issue8
    journal titleMonthly Weather Review
    identifier doi10.1175/MWR3434.1
    journal fristpage2931
    journal lastpage2957
    treeMonthly Weather Review:;2007:;volume( 135 ):;issue: 008
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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