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    A Comparative Study of Atmospheric Moisture Recycling Rate between Observations and Models

    Source: Journal of Climate:;2018:;volume 031:;issue 006::page 2389
    Author:
    Kao, Angela
    ,
    Jiang, Xun
    ,
    Li, Liming
    ,
    Trammell, James H.
    ,
    Zhang, Guang J.
    ,
    Su, Hui
    ,
    Jiang, Jonathan H.
    ,
    Yung, Yuk L.
    DOI: 10.1175/JCLI-D-17-0421.1
    Publisher: American Meteorological Society
    Abstract: AbstractPrecipitation and column water vapor data from 13 CMIP5 models and observational datasets are used to analyze atmospheric moisture recycling rate from 1988 to 2008. The comparisons between observations and model simulations suggest that most CMIP5 models capture two main characteristics of the recycling rate: 1) long-term decreasing trend of the global-average maritime recycling rate (atmospheric recycling rate over ocean within 60°S?60°N) and 2) dominant spatial patterns of the temporal variations of the recycling rate (i.e., increasing in the intertropical convergence zone and decreasing in subtropical regions). All models, except one, successfully simulate not only the long-term trend but also the interannual variability of column water vapor. The simulations of precipitation are relatively poor, especially over the relatively short time scales, which lead to the discrepancy of the recycling rate between observations and the CMIP5 models. Comparisons of spatial patterns also suggest that the CMIP5 models simulate column water vapor better than precipitation. The comparative studies indicate the scope of improvement in the simulations of precipitation, especially for the relatively short-time-scale variations, to better simulate the recycling rate of atmospheric moisture, an important indicator of climate change.
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      A Comparative Study of Atmospheric Moisture Recycling Rate between Observations and Models

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    contributor authorKao, Angela
    contributor authorJiang, Xun
    contributor authorLi, Liming
    contributor authorTrammell, James H.
    contributor authorZhang, Guang J.
    contributor authorSu, Hui
    contributor authorJiang, Jonathan H.
    contributor authorYung, Yuk L.
    date accessioned2019-09-19T10:09:19Z
    date available2019-09-19T10:09:19Z
    date copyright1/2/2018 12:00:00 AM
    date issued2018
    identifier otherjcli-d-17-0421.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4262156
    description abstractAbstractPrecipitation and column water vapor data from 13 CMIP5 models and observational datasets are used to analyze atmospheric moisture recycling rate from 1988 to 2008. The comparisons between observations and model simulations suggest that most CMIP5 models capture two main characteristics of the recycling rate: 1) long-term decreasing trend of the global-average maritime recycling rate (atmospheric recycling rate over ocean within 60°S?60°N) and 2) dominant spatial patterns of the temporal variations of the recycling rate (i.e., increasing in the intertropical convergence zone and decreasing in subtropical regions). All models, except one, successfully simulate not only the long-term trend but also the interannual variability of column water vapor. The simulations of precipitation are relatively poor, especially over the relatively short time scales, which lead to the discrepancy of the recycling rate between observations and the CMIP5 models. Comparisons of spatial patterns also suggest that the CMIP5 models simulate column water vapor better than precipitation. The comparative studies indicate the scope of improvement in the simulations of precipitation, especially for the relatively short-time-scale variations, to better simulate the recycling rate of atmospheric moisture, an important indicator of climate change.
    publisherAmerican Meteorological Society
    titleA Comparative Study of Atmospheric Moisture Recycling Rate between Observations and Models
    typeJournal Paper
    journal volume31
    journal issue6
    journal titleJournal of Climate
    identifier doi10.1175/JCLI-D-17-0421.1
    journal fristpage2389
    journal lastpage2398
    treeJournal of Climate:;2018:;volume 031:;issue 006
    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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