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    Estimating Maximum Surface Winds from Hurricane Reconnaissance Measurements

    Source: Weather and Forecasting:;2009:;volume( 024 ):;issue: 003::page 868
    Author:
    Powell, Mark D.
    ,
    Uhlhorn, Eric W.
    ,
    Kepert, Jeffrey D.
    DOI: 10.1175/2008WAF2007087.1
    Publisher: American Meteorological Society
    Abstract: Radial profiles of surface winds measured by the Stepped Frequency Microwave Radiometer (SFMR) are compared to radial profiles of flight-level winds to determine the slant ratio of the maximum surface wind speed to the maximum flight-level wind speed, for flight altitude ranges of 2?4 km. The radius of maximum surface wind is found on average to be 0.875 of the radius of the maximum flight-level wind, and very few cases have a surface wind maximum at greater radius than the flight-level maximum. The mean slant reduction factor is 0.84 with a standard deviation of 0.09 and varies with storm-relative azimuth from a maximum of 0.89 on the left side of the storm to a minimum of 0.79 on the right side. Larger slant reduction factors are found in small storms with large values of inertial stability and small values of relative angular momentum at the flight-level radius of maximum wind, which is consistent with Kepert?s recent boundary layer theories. The global positioning system (GPS) dropwindsonde-based reduction factors that are assessed using this new dataset have a high bias and substantially larger RMS errors than the new technique. A new regression model for the slant reduction factor based upon SFMR data is presented, and used to make retrospective estimates of maximum surface wind speeds for significant Atlantic basin storms, including Hurricanes Allen (1980), Gilbert (1988), Hugo (1989), Andrew (1992), and Mitch (1998).
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      Estimating Maximum Surface Winds from Hurricane Reconnaissance Measurements

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4209565
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    contributor authorPowell, Mark D.
    contributor authorUhlhorn, Eric W.
    contributor authorKepert, Jeffrey D.
    date accessioned2017-06-09T16:26:55Z
    date available2017-06-09T16:26:55Z
    date copyright2009/06/01
    date issued2009
    identifier issn0882-8156
    identifier otherams-68050.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4209565
    description abstractRadial profiles of surface winds measured by the Stepped Frequency Microwave Radiometer (SFMR) are compared to radial profiles of flight-level winds to determine the slant ratio of the maximum surface wind speed to the maximum flight-level wind speed, for flight altitude ranges of 2?4 km. The radius of maximum surface wind is found on average to be 0.875 of the radius of the maximum flight-level wind, and very few cases have a surface wind maximum at greater radius than the flight-level maximum. The mean slant reduction factor is 0.84 with a standard deviation of 0.09 and varies with storm-relative azimuth from a maximum of 0.89 on the left side of the storm to a minimum of 0.79 on the right side. Larger slant reduction factors are found in small storms with large values of inertial stability and small values of relative angular momentum at the flight-level radius of maximum wind, which is consistent with Kepert?s recent boundary layer theories. The global positioning system (GPS) dropwindsonde-based reduction factors that are assessed using this new dataset have a high bias and substantially larger RMS errors than the new technique. A new regression model for the slant reduction factor based upon SFMR data is presented, and used to make retrospective estimates of maximum surface wind speeds for significant Atlantic basin storms, including Hurricanes Allen (1980), Gilbert (1988), Hugo (1989), Andrew (1992), and Mitch (1998).
    publisherAmerican Meteorological Society
    titleEstimating Maximum Surface Winds from Hurricane Reconnaissance Measurements
    typeJournal Paper
    journal volume24
    journal issue3
    journal titleWeather and Forecasting
    identifier doi10.1175/2008WAF2007087.1
    journal fristpage868
    journal lastpage883
    treeWeather and Forecasting:;2009:;volume( 024 ):;issue: 003
    contenttypeFulltext
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