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    Assessing GCM Convergence for India Using the Variable Convergence Score

    Source: Journal of Hydrologic Engineering:;2014:;Volume ( 019 ):;issue: 006
    Author:
    Richa Ojha
    ,
    D. Nagesh Kumar
    ,
    Ashish Sharma
    ,
    Raj Mehrotra
    DOI: 10.1061/(ASCE)HE.1943-5584.0000888
    Publisher: American Society of Civil Engineers
    Abstract: General circulation models (GCMs) use transient climate simulations to predict climate conditions in the future. Coarse-grid resolutions and process uncertainties necessitate the use of downscaling models to simulate precipitation. However, in the downscaling models, with multiple GCMs now available, selecting an atmospheric variable from a particular model which is representative of the ensemble mean becomes an important consideration. The variable convergence score (VCS) provides a simple yet meaningful approach to address this issue, providing a mechanism to evaluate variables against each other with respect to the stability they exhibit in future climate simulations. In this study, VCS methodology is applied to 10 atmospheric variables of particular interest in downscaling precipitation over India and also on a regional basis. The nested bias-correction methodology is used to remove the systematic biases in the GCMs simulations, and a single VCS curve is developed for the entire country. The generated VCS curve is expected to assist in quantifying the variable performance across different GCMs, thus reducing the uncertainty in climate impact–assessment studies. The results indicate higher consistency across GCMs for pressure and temperature, and lower consistency for precipitation and related variables. Regional assessments, while broadly consistent with the overall results, indicate low convergence in atmospheric attributes for the Northeastern parts of India.
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      Assessing GCM Convergence for India Using the Variable Convergence Score

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    http://yetl.yabesh.ir/yetl1/handle/yetl/63774
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    contributor authorRicha Ojha
    contributor authorD. Nagesh Kumar
    contributor authorAshish Sharma
    contributor authorRaj Mehrotra
    date accessioned2017-05-08T21:50:15Z
    date available2017-05-08T21:50:15Z
    date copyrightJune 2014
    date issued2014
    identifier other%28asce%29he%2E1943-5584%2E0000917.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/63774
    description abstractGeneral circulation models (GCMs) use transient climate simulations to predict climate conditions in the future. Coarse-grid resolutions and process uncertainties necessitate the use of downscaling models to simulate precipitation. However, in the downscaling models, with multiple GCMs now available, selecting an atmospheric variable from a particular model which is representative of the ensemble mean becomes an important consideration. The variable convergence score (VCS) provides a simple yet meaningful approach to address this issue, providing a mechanism to evaluate variables against each other with respect to the stability they exhibit in future climate simulations. In this study, VCS methodology is applied to 10 atmospheric variables of particular interest in downscaling precipitation over India and also on a regional basis. The nested bias-correction methodology is used to remove the systematic biases in the GCMs simulations, and a single VCS curve is developed for the entire country. The generated VCS curve is expected to assist in quantifying the variable performance across different GCMs, thus reducing the uncertainty in climate impact–assessment studies. The results indicate higher consistency across GCMs for pressure and temperature, and lower consistency for precipitation and related variables. Regional assessments, while broadly consistent with the overall results, indicate low convergence in atmospheric attributes for the Northeastern parts of India.
    publisherAmerican Society of Civil Engineers
    titleAssessing GCM Convergence for India Using the Variable Convergence Score
    typeJournal Paper
    journal volume19
    journal issue6
    journal titleJournal of Hydrologic Engineering
    identifier doi10.1061/(ASCE)HE.1943-5584.0000888
    treeJournal of Hydrologic Engineering:;2014:;Volume ( 019 ):;issue: 006
    contenttypeFulltext
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