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    Regional Climate–Weather Research and Forecasting Model

    Source: Bulletin of the American Meteorological Society:;2012:;volume( 093 ):;issue: 009::page 1363
    Author:
    Liang, Xin-Zhong
    ,
    Xu, Min
    ,
    Yuan, Xing
    ,
    Ling, Tiejun
    ,
    Choi, Hyun I.
    ,
    Zhang, Feng
    ,
    Chen, Ligang
    ,
    Liu, Shuyan
    ,
    Su, Shenjian
    ,
    Qiao, Fengxue
    ,
    He, Yuxiang
    ,
    Wang, Julian X. L.
    ,
    Kunkel, Kenneth E.
    ,
    Gao, Wei
    ,
    Joseph, Everette
    ,
    Morris, Vernon
    ,
    Yu, Tsann-Wang
    ,
    Dudhia, Jimy
    ,
    Michalakes, John
    DOI: 10.1175/BAMS-D-11-00180.1
    Publisher: American Meteorological Society
    Abstract: is developed as a climate extension of the Weather Research and Forecasting model (WRF) by incorporating numerous improvements in the representation of physical processes and integration of external (top, surface, lateral) forcings that are crucial to climate scales, including interactions between land, atmosphere, and ocean; convection and microphysics; and cloud, aerosol, and radiation; and system consistency throughout all process modules. This extension inherits all WRF functionalities for numerical weather prediction while enhancing the capability for climate modeling. As such, CWRF can be applied seamlessly to weather forecast and climate prediction. The CWRF is built with a comprehensive ensemble of alternative parameterization schemes for each of the key physical processes, including surface (land, ocean), planetary boundary layer, cumulus (deep, shallow), microphysics, cloud, aerosol, and radiation, and their interactions. This facilitates the use of an optimized physics ensemble approach to improve weather or climate prediction along with a reliable uncertainty estimate. The CWRF also emphasizes the societal service capability to provide impactrelevant information by coupling with detailed models of terrestrial hydrology, coastal ocean, crop growth, air quality, and a recently expanded interactive water quality and ecosystem model. This study provides a general CWRF description and basic skill evaluation based on a continuous integration for the period 1979? 2009 as compared with that of WRF, using a 30-km grid spacing over a domain that includes the contiguous United States plus southern Canada and northern Mexico. In addition to advantages of greater application capability, CWRF improves performance in radiation and terrestrial hydrology over WRF and other regional models. Precipitation simulation, however, remains a challenge for all of the tested models.
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      Regional Climate–Weather Research and Forecasting Model

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    contributor authorLiang, Xin-Zhong
    contributor authorXu, Min
    contributor authorYuan, Xing
    contributor authorLing, Tiejun
    contributor authorChoi, Hyun I.
    contributor authorZhang, Feng
    contributor authorChen, Ligang
    contributor authorLiu, Shuyan
    contributor authorSu, Shenjian
    contributor authorQiao, Fengxue
    contributor authorHe, Yuxiang
    contributor authorWang, Julian X. L.
    contributor authorKunkel, Kenneth E.
    contributor authorGao, Wei
    contributor authorJoseph, Everette
    contributor authorMorris, Vernon
    contributor authorYu, Tsann-Wang
    contributor authorDudhia, Jimy
    contributor authorMichalakes, John
    date accessioned2017-06-09T16:44:07Z
    date available2017-06-09T16:44:07Z
    date copyright2012/09/01
    date issued2012
    identifier issn0003-0007
    identifier otherams-73202.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4215291
    description abstractis developed as a climate extension of the Weather Research and Forecasting model (WRF) by incorporating numerous improvements in the representation of physical processes and integration of external (top, surface, lateral) forcings that are crucial to climate scales, including interactions between land, atmosphere, and ocean; convection and microphysics; and cloud, aerosol, and radiation; and system consistency throughout all process modules. This extension inherits all WRF functionalities for numerical weather prediction while enhancing the capability for climate modeling. As such, CWRF can be applied seamlessly to weather forecast and climate prediction. The CWRF is built with a comprehensive ensemble of alternative parameterization schemes for each of the key physical processes, including surface (land, ocean), planetary boundary layer, cumulus (deep, shallow), microphysics, cloud, aerosol, and radiation, and their interactions. This facilitates the use of an optimized physics ensemble approach to improve weather or climate prediction along with a reliable uncertainty estimate. The CWRF also emphasizes the societal service capability to provide impactrelevant information by coupling with detailed models of terrestrial hydrology, coastal ocean, crop growth, air quality, and a recently expanded interactive water quality and ecosystem model. This study provides a general CWRF description and basic skill evaluation based on a continuous integration for the period 1979? 2009 as compared with that of WRF, using a 30-km grid spacing over a domain that includes the contiguous United States plus southern Canada and northern Mexico. In addition to advantages of greater application capability, CWRF improves performance in radiation and terrestrial hydrology over WRF and other regional models. Precipitation simulation, however, remains a challenge for all of the tested models.
    publisherAmerican Meteorological Society
    titleRegional Climate–Weather Research and Forecasting Model
    typeJournal Paper
    journal volume93
    journal issue9
    journal titleBulletin of the American Meteorological Society
    identifier doi10.1175/BAMS-D-11-00180.1
    journal fristpage1363
    journal lastpage1387
    treeBulletin of the American Meteorological Society:;2012:;volume( 093 ):;issue: 009
    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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