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    Predicting the Inland Penetration of Long-Lake-Axis-Parallel Snowbands

    Source: Weather and Forecasting:;2018:;volume 033:;issue 005::page 1435
    Author:
    Eipper, Daniel T.
    ,
    Young, George S.
    ,
    Greybush, Steven J.
    ,
    Saslo, Seth
    ,
    Sikora, Todd D.
    ,
    Clark, Richard D.
    DOI: 10.1175/WAF-D-18-0033.1
    Publisher: American Meteorological Society
    Abstract: AbstractPredicting the inland penetration of lake-effect long-lake-axis-parallel (LLAP) snowbands is crucial to public safety because LLAP bands can produce hazardous weather well downwind of the parent lake. Accordingly, hypotheses for the variation in inland penetration of LLAP-band radar echoes (InPen) are formulated and tested. The hypothesis testing includes an examination of statistical relationships between environmental variables and InPen for 34 snapshots of LLAP bands observed during the Ontario Winter Lake-effect Systems (OWLeS) field campaign. Several previously proposed predictors of LLAP-band formation or InPen demonstrate weak correlations with InPen during OWLeS. A notable exception is convective boundary layer (CBL) depth, which is strongly correlated with InPen. In addition to CBL depth, InPen is strongly correlated with cold-air advection in the upper portion of the CBL, suggesting that boundary layer destabilization produced by vertically differential cold-air advection may be an important inland power source for preexisting LLAP bands. This power production is quantified through atmospheric energetics and the resulting variable, differential thermal advection power (DTAP), yields reasonably skillful predictions of InPen. Nevertheless, an InPen model developed using DTAP is outperformed by an empirical model combining CBL depth and potential temperature advection in the upper portion of the CBL. This two-variable model explains 76% of the observed InPen variance when tested on independent data. Finally, implications for operational forecasting of InPen are discussed.
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      Predicting the Inland Penetration of Long-Lake-Axis-Parallel Snowbands

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    contributor authorEipper, Daniel T.
    contributor authorYoung, George S.
    contributor authorGreybush, Steven J.
    contributor authorSaslo, Seth
    contributor authorSikora, Todd D.
    contributor authorClark, Richard D.
    date accessioned2019-09-19T10:05:32Z
    date available2019-09-19T10:05:32Z
    date copyright8/8/2018 12:00:00 AM
    date issued2018
    identifier otherwaf-d-18-0033.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4261429
    description abstractAbstractPredicting the inland penetration of lake-effect long-lake-axis-parallel (LLAP) snowbands is crucial to public safety because LLAP bands can produce hazardous weather well downwind of the parent lake. Accordingly, hypotheses for the variation in inland penetration of LLAP-band radar echoes (InPen) are formulated and tested. The hypothesis testing includes an examination of statistical relationships between environmental variables and InPen for 34 snapshots of LLAP bands observed during the Ontario Winter Lake-effect Systems (OWLeS) field campaign. Several previously proposed predictors of LLAP-band formation or InPen demonstrate weak correlations with InPen during OWLeS. A notable exception is convective boundary layer (CBL) depth, which is strongly correlated with InPen. In addition to CBL depth, InPen is strongly correlated with cold-air advection in the upper portion of the CBL, suggesting that boundary layer destabilization produced by vertically differential cold-air advection may be an important inland power source for preexisting LLAP bands. This power production is quantified through atmospheric energetics and the resulting variable, differential thermal advection power (DTAP), yields reasonably skillful predictions of InPen. Nevertheless, an InPen model developed using DTAP is outperformed by an empirical model combining CBL depth and potential temperature advection in the upper portion of the CBL. This two-variable model explains 76% of the observed InPen variance when tested on independent data. Finally, implications for operational forecasting of InPen are discussed.
    publisherAmerican Meteorological Society
    titlePredicting the Inland Penetration of Long-Lake-Axis-Parallel Snowbands
    typeJournal Paper
    journal volume33
    journal issue5
    journal titleWeather and Forecasting
    identifier doi10.1175/WAF-D-18-0033.1
    journal fristpage1435
    journal lastpage1451
    treeWeather and Forecasting:;2018:;volume 033:;issue 005
    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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