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    Optimization of a Radiative Transfer Forward Operator for Simulating SMOS Brightness Temperatures over the Upper Mississippi Basin

    Source: Journal of Hydrometeorology:;2015:;Volume( 016 ):;issue: 003::page 1109
    Author:
    Lievens, H.
    ,
    Al Bitar, A.
    ,
    Verhoest, N. E. C.
    ,
    Cabot, F.
    ,
    De Lannoy, G. J. M.
    ,
    Drusch, M.
    ,
    Dumedah, G.
    ,
    Hendricks Franssen, H.-J.
    ,
    Kerr, Y.
    ,
    Tomer, S. K.
    ,
    Martens, B.
    ,
    Merlin, O.
    ,
    Pan, M.
    ,
    van den Berg, M. J.
    ,
    Vereecken, H.
    ,
    Walker, J. P.
    ,
    Wood, E. F.
    ,
    Pauwels, V. R. N.
    DOI: 10.1175/JHM-D-14-0052.1
    Publisher: American Meteorological Society
    Abstract: he Soil Moisture Ocean Salinity (SMOS) satellite mission routinely provides global multiangular observations of brightness temperature TB at both horizontal and vertical polarization with a 3-day repeat period. The assimilation of such data into a land surface model (LSM) may improve the skill of operational flood forecasts through an improved estimation of soil moisture SM. To accommodate for the direct assimilation of the SMOS TB data, the LSM needs to be coupled with a radiative transfer model (RTM), serving as a forward operator for the simulation of multiangular and multipolarization top of the atmosphere TBs. This study investigates the use of the Variable Infiltration Capacity model coupled with the Community Microwave Emission Modelling Platform for simulating SMOS TB observations over the upper Mississippi basin, United States. For a period of 2 years (2010?11), a comparison between SMOS TBs and simulations with literature-based RTM parameters reveals a basin-averaged bias of 30 K. Therefore, time series of SMOS TB observations are used to investigate ways for mitigating these large biases. Specifically, the study demonstrates the impact of the LSM soil moisture climatology in the magnitude of TB biases. After cumulative distribution function matching the SM climatology of the LSM to SMOS retrievals, the average bias decreases from 30 K to less than 5 K. Further improvements can be made through calibration of RTM parameters related to the modeling of surface roughness and vegetation. Consequently, it can be concluded that SM rescaling and RTM optimization are efficient means for mitigating biases and form a necessary preparatory step for data assimilation.
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      Optimization of a Radiative Transfer Forward Operator for Simulating SMOS Brightness Temperatures over the Upper Mississippi Basin

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4225158
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    • Journal of Hydrometeorology

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    contributor authorLievens, H.
    contributor authorAl Bitar, A.
    contributor authorVerhoest, N. E. C.
    contributor authorCabot, F.
    contributor authorDe Lannoy, G. J. M.
    contributor authorDrusch, M.
    contributor authorDumedah, G.
    contributor authorHendricks Franssen, H.-J.
    contributor authorKerr, Y.
    contributor authorTomer, S. K.
    contributor authorMartens, B.
    contributor authorMerlin, O.
    contributor authorPan, M.
    contributor authorvan den Berg, M. J.
    contributor authorVereecken, H.
    contributor authorWalker, J. P.
    contributor authorWood, E. F.
    contributor authorPauwels, V. R. N.
    date accessioned2017-06-09T17:15:55Z
    date available2017-06-09T17:15:55Z
    date copyright2015/06/01
    date issued2015
    identifier issn1525-755X
    identifier otherams-82083.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4225158
    description abstracthe Soil Moisture Ocean Salinity (SMOS) satellite mission routinely provides global multiangular observations of brightness temperature TB at both horizontal and vertical polarization with a 3-day repeat period. The assimilation of such data into a land surface model (LSM) may improve the skill of operational flood forecasts through an improved estimation of soil moisture SM. To accommodate for the direct assimilation of the SMOS TB data, the LSM needs to be coupled with a radiative transfer model (RTM), serving as a forward operator for the simulation of multiangular and multipolarization top of the atmosphere TBs. This study investigates the use of the Variable Infiltration Capacity model coupled with the Community Microwave Emission Modelling Platform for simulating SMOS TB observations over the upper Mississippi basin, United States. For a period of 2 years (2010?11), a comparison between SMOS TBs and simulations with literature-based RTM parameters reveals a basin-averaged bias of 30 K. Therefore, time series of SMOS TB observations are used to investigate ways for mitigating these large biases. Specifically, the study demonstrates the impact of the LSM soil moisture climatology in the magnitude of TB biases. After cumulative distribution function matching the SM climatology of the LSM to SMOS retrievals, the average bias decreases from 30 K to less than 5 K. Further improvements can be made through calibration of RTM parameters related to the modeling of surface roughness and vegetation. Consequently, it can be concluded that SM rescaling and RTM optimization are efficient means for mitigating biases and form a necessary preparatory step for data assimilation.
    publisherAmerican Meteorological Society
    titleOptimization of a Radiative Transfer Forward Operator for Simulating SMOS Brightness Temperatures over the Upper Mississippi Basin
    typeJournal Paper
    journal volume16
    journal issue3
    journal titleJournal of Hydrometeorology
    identifier doi10.1175/JHM-D-14-0052.1
    journal fristpage1109
    journal lastpage1134
    treeJournal of Hydrometeorology:;2015:;Volume( 016 ):;issue: 003
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian