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    An Algorithm for Detecting the Chesapeake Bay Breeze from Mesoscale NWP Model Output

    Source: Journal of Applied Meteorology and Climatology:;2022:;volume( 061 ):;issue: 001
    DOI: 10.1175/JAMC-D-21-0097.1
    Abstract: A novel algorithm is developed for detecting and classifying the Chesapeake Bay breeze and similar water-body breezes in output from mesoscale numerical weather prediction (NWP) models. To assess the generality of the new model-based detection algorithm (MBDA), it is tested on simulations from the Weather Research and Forecasting (WRF) Model and on analyses and forecasts from the High-Resolution Rapid Refresh (HRRR) model. The MBDA outperforms three observation-based detection algorithms (OBDAs) when applied to the same model output. In addition, by defining the onshore wind directions on the basis of model land-use data and not on the actual geography of the region of interest, performance of the OBDAs with model output can be improved. Although simulations by the WRF Model were used to develop the new MBDA, it performed best when applied to HRRR analyses. The generality of the MBDA is promising, and additional tuning of its parameters might improve it further.
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      An Algorithm for Detecting the Chesapeake Bay Breeze from Mesoscale NWP Model Output

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4286084
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    date accessioned2022-05-09T01:00:38Z
    date available2022-05-09T01:00:38Z
    date copyright27 Jan 2022
    date issued2022
    identifier otherJAMC-D-21-0097.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4286084
    description abstractA novel algorithm is developed for detecting and classifying the Chesapeake Bay breeze and similar water-body breezes in output from mesoscale numerical weather prediction (NWP) models. To assess the generality of the new model-based detection algorithm (MBDA), it is tested on simulations from the Weather Research and Forecasting (WRF) Model and on analyses and forecasts from the High-Resolution Rapid Refresh (HRRR) model. The MBDA outperforms three observation-based detection algorithms (OBDAs) when applied to the same model output. In addition, by defining the onshore wind directions on the basis of model land-use data and not on the actual geography of the region of interest, performance of the OBDAs with model output can be improved. Although simulations by the WRF Model were used to develop the new MBDA, it performed best when applied to HRRR analyses. The generality of the MBDA is promising, and additional tuning of its parameters might improve it further.
    titleAn Algorithm for Detecting the Chesapeake Bay Breeze from Mesoscale NWP Model Output
    typeJournal Paper
    journal volume61
    journal issue1
    journal titleJournal of Applied Meteorology and Climatology
    identifier doi10.1175/JAMC-D-21-0097.1
    page61–75
    treeJournal of Applied Meteorology and Climatology:;2022:;volume( 061 ):;issue: 001
    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