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    An Improved Algorithm for Low-Level Turbulence Forecasting

    Source: Journal of Applied Meteorology and Climatology:;2018:;volume 057:;issue 006::page 1249
    Author:
    Muñoz-Esparza, Domingo
    ,
    Sharman, Robert
    DOI: 10.1175/JAMC-D-17-0337.1
    Publisher: American Meteorological Society
    Abstract: AbstractA low-level turbulence (LLT) forecasting algorithm is proposed and implemented within the Graphical Turbulence Guidance (GTG) turbulence forecasting system. The LLT algorithm provides predictions of energy dissipation rate (EDR; turbulence dissipation to the one-third power), which is the standard turbulence metric used by the aviation community. The algorithm is based upon the use of distinct log-Weibull and lognormal probability distributions in a statistical remapping technique to represent accurately the behavior of turbulence in the atmospheric boundary layer for daytime and nighttime conditions, respectively, thus accounting for atmospheric stability. A 1-yr-long GTG LLT calibration was performed using the High-Resolution Rapid Refresh operational model, and optimum GTG ensembles of turbulence indices for clear-air and mountain-wave turbulence that minimize the mean absolute percentage error (MAPE) were determined. Evaluation of the proposed algorithm with in situ EDR data from the Boulder Atmospheric Observatory tower covering a range of altitudes up to 300 m above the surface demonstrates a reduction in the error by a factor of approximately 2.0 (MAPE = 55%) relative to the current operational GTG system (version 3). In addition, the probability of detection of typical small and large EDR values at low levels is increased by approximately 15%?20%. The improved LLT algorithm is expected to benefit several nonconventional turbulence-prediction sectors such as unmanned aerial systems and wind energy.
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      An Improved Algorithm for Low-Level Turbulence Forecasting

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    contributor authorMuñoz-Esparza, Domingo
    contributor authorSharman, Robert
    date accessioned2019-09-19T10:06:50Z
    date available2019-09-19T10:06:50Z
    date copyright4/2/2018 12:00:00 AM
    date issued2018
    identifier otherjamc-d-17-0337.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4261673
    description abstractAbstractA low-level turbulence (LLT) forecasting algorithm is proposed and implemented within the Graphical Turbulence Guidance (GTG) turbulence forecasting system. The LLT algorithm provides predictions of energy dissipation rate (EDR; turbulence dissipation to the one-third power), which is the standard turbulence metric used by the aviation community. The algorithm is based upon the use of distinct log-Weibull and lognormal probability distributions in a statistical remapping technique to represent accurately the behavior of turbulence in the atmospheric boundary layer for daytime and nighttime conditions, respectively, thus accounting for atmospheric stability. A 1-yr-long GTG LLT calibration was performed using the High-Resolution Rapid Refresh operational model, and optimum GTG ensembles of turbulence indices for clear-air and mountain-wave turbulence that minimize the mean absolute percentage error (MAPE) were determined. Evaluation of the proposed algorithm with in situ EDR data from the Boulder Atmospheric Observatory tower covering a range of altitudes up to 300 m above the surface demonstrates a reduction in the error by a factor of approximately 2.0 (MAPE = 55%) relative to the current operational GTG system (version 3). In addition, the probability of detection of typical small and large EDR values at low levels is increased by approximately 15%?20%. The improved LLT algorithm is expected to benefit several nonconventional turbulence-prediction sectors such as unmanned aerial systems and wind energy.
    publisherAmerican Meteorological Society
    titleAn Improved Algorithm for Low-Level Turbulence Forecasting
    typeJournal Paper
    journal volume57
    journal issue6
    journal titleJournal of Applied Meteorology and Climatology
    identifier doi10.1175/JAMC-D-17-0337.1
    journal fristpage1249
    journal lastpage1263
    treeJournal of Applied Meteorology and Climatology:;2018:;volume 057:;issue 006
    contenttypeFulltext
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    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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