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    Reply to “Comment on ‘Bias Correction, Quantile Mapping, and Downscaling: Revisiting the Inflation Issue’”

    Source: Journal of Climate:;2013:;volume( 027 ):;issue: 004::page 1821
    Author:
    Maraun, Douglas
    DOI: 10.1175/JCLI-D-13-00307.1
    Publisher: American Meteorological Society
    Abstract: n his comment, G. Bürger criticizes the conclusion that inflation of trends by quantile mapping is an adverse effect. He assumes that the argument would be ?based on the belief that long-term trends and along with them future climate signals are to be large scale.? His line of argument reverts to the so-called inflated regression. Here it is shown, by referring to previous critiques of inflation and standard literature in statistical modeling as well as weather forecasting, that inflation is built upon a wrong understanding of explained versus unexplained variability and prediction versus simulation. It is argued that a sound regression-based downscaling can in principle introduce systematic local variability in long-term trends, but inflation systematically deteriorates the representation of trends. Furthermore, it is demonstrated that inflation by construction deteriorates weather forecasts and is not able to correctly simulate small-scale spatiotemporal structure.
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      Reply to “Comment on ‘Bias Correction, Quantile Mapping, and Downscaling: Revisiting the Inflation Issue’”

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4222953
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    contributor authorMaraun, Douglas
    date accessioned2017-06-09T17:08:46Z
    date available2017-06-09T17:08:46Z
    date copyright2014/02/01
    date issued2013
    identifier issn0894-8755
    identifier otherams-80099.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4222953
    description abstractn his comment, G. Bürger criticizes the conclusion that inflation of trends by quantile mapping is an adverse effect. He assumes that the argument would be ?based on the belief that long-term trends and along with them future climate signals are to be large scale.? His line of argument reverts to the so-called inflated regression. Here it is shown, by referring to previous critiques of inflation and standard literature in statistical modeling as well as weather forecasting, that inflation is built upon a wrong understanding of explained versus unexplained variability and prediction versus simulation. It is argued that a sound regression-based downscaling can in principle introduce systematic local variability in long-term trends, but inflation systematically deteriorates the representation of trends. Furthermore, it is demonstrated that inflation by construction deteriorates weather forecasts and is not able to correctly simulate small-scale spatiotemporal structure.
    publisherAmerican Meteorological Society
    titleReply to “Comment on ‘Bias Correction, Quantile Mapping, and Downscaling: Revisiting the Inflation Issue’”
    typeJournal Paper
    journal volume27
    journal issue4
    journal titleJournal of Climate
    identifier doi10.1175/JCLI-D-13-00307.1
    journal fristpage1821
    journal lastpage1825
    treeJournal of Climate:;2013:;volume( 027 ):;issue: 004
    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
    yabeshDSpacePersian