Chen Shenpeng, Duan Yihong, Li Qingqing. Fitting of wind shear index in the boundary layer of landfalling typhoons based on high tower observation. J Appl Meteor Sci, 2022, 33(2): 155-166. DOI:  10.11898/1001-7313.20220203.
Citation: Chen Shenpeng, Duan Yihong, Li Qingqing. Fitting of wind shear index in the boundary layer of landfalling typhoons based on high tower observation. J Appl Meteor Sci, 2022, 33(2): 155-166. DOI:  10.11898/1001-7313.20220203.

Fitting of Wind Shear Index in the Boundary Layer of Landfalling Typhoons Based on High Tower Observation

DOI: 10.11898/1001-7313.20220203
  • Received Date: 2021-11-18
  • Rev Recd Date: 2022-01-24
  • Publish Date: 2022-03-31
  • The characteristics of wind speed variations with height in the boundary layer (especially in the near-ground layer) are crucial for the design of wind resistance coefficients of high buildings. The coast of South China is frequently impacted by typhoons, but the study of wind variation characteristics above 100 m within the typhoon boundary layer is insufficient due to the lack of direct observations. The 356 m Meteorological Gradient Observation Tower of Shenzhen can make up for data shortage, and 7 typhoons that affected Shenzhen since 2017(Typhoons Merbok, Roke, Hato, Pakhar, Mangkhut, Higos, and Lupit) are analyzed to study the variation of wind shear index based on the power exponential law. It shows the power index can well fit the wind profile below 350 m under the influence of typhoons, the wind shear index α increases with height, and the fitting accuracy is basically stable. The wind profile of the typhoon boundary layer is fitted with the wind speed data from the tower, the fitting accuracy differs for different combinations of levels, and the equal difference scheme leads to the best fitting results. For 7 typhoon cases, the mean value of 350 m wind shear index α during the impact period is 0.268, which is significantly higher than that of 0.1-0.177. The main cause is that the fitted height range is significantly larger than that of previous studies, and it is also related to the smaller sample of strong winds and rougher underlying surface. The maximum wind shear indices of different wind speed sections of the typhoons can be well fitted with power functions, which can predict the risk of extreme winds at different heights.The wind shear index before and after landing of Typhoon Roke is also analyzed. It shows that after the typhoon eye passes, α increases sharply, because the wind speed above 100 m may have increased significantly before the surface wind re-increase. Therefore, this result should be specially considered in the design of engineering wind resistance and typhoon prevention.
  • Fig. 1  Tracks of typhoons

    (the red dot denotes the location of Shenzhen Meteorological Gradient Observation Tower)

    Fig. 2  Variations of average determination coefficient(R2) in the wind speed fitting with different height ranges

    (a)before typhoons,(b)during typhoons, (c)after typhoons

    Fig. 3  Scatter diagram of the wind shear index α and wind speed

    Fig. 4  Fitting of the maximum wind shear index and the wind speed

    (a)power function fitting,(b)logarithmic function fitting

    Fig. 5  Time series of 10 min average pressure at 50 m height of Shenzhen Gradient Observation Tower during the passing of Typhoon Roke(1707) on 23 Jul 2017

    Fig. 6  The wind shear index(a) and 2 min average wind speed at 10 m and 100 m height(b) of Shenzhen Gradient Observation Tower during the passing of Typhoon Roke(1707) on 23 Jul 2017

    Fig. 7  Time series of 10 min average wind speed at 10 m with the wind shear index α(a) and fitting determination coefficient(R2)(b) of Shenzhen Gradient Observation Tower during Typhoon Hato(1713) from 0900 BT 23 Aug to 0200 BT 24 Aug in 2017

    Table  1  Comparison of wind shear indices based on the observed wind with different height ranges before,during and after impacts of typhoons

    拟合高度
    (10 m参考层)
    影响前 影响期间 影响后
    α平均值 α变异系数 α平均值 α变异系数 α平均值 α变异系数
    40 m以下(3层) 0.083 4.427 0.197 1.053 0.276 1.209
    50 m以下(4层) 0.112 2.846 0.204 0.907 0.279 1.153
    80 m以下(5层) 0.132 2.222 0.212 0.841 0.278 1.104
    100 m以下(6层) 0.148 1.876 0.216 0.828 0.281 1.032
    150 m以下(7层) 0.168 1.557 0.228 0.750 0.285 0.947
    160 m以下(8层) 0.177 1.460 0.234 0.721 0.287 0.904
    200 m以下(9层) 0.183 1.387 0.240 0.692 0.290 0.856
    250 m以下(10层) 0.189 1.304 0.247 0.661 0.293 0.816
    300 m以下(11层) 0.196 1.228 0.253 0.637 0.297 0.782
    320 m以下(12层) 0.199 1.200 0.257 0.625 0.301 0.760
    350 m以下(13层) 0.206 1.135 0.264 0.598 0.306 0.733
    DownLoad: Download CSV

    Table  2  Comparison of wind shear indices from different layer-combinations

    数据层选取 α平均值 α变异系数 R2平均值 R2变异系数
    全层次 0.264 0.600 0.813 0.353
    等差层 0.268 0.594 0.823 0.336
    等比层 0.254 0.623 0.764 0.480
    DownLoad: Download CSV

    Table  3  Comparison of wind shear indices and the related norms

    文献来源 数据来源 最高观测层高度/m 台风数量 样本选取 α
    本文 深圳气象梯度观测塔 350
    80
    7
    7
    10 min平均风速
    10 min平均风速
    0.268
    0.212
    文献[11] 炮台角(徐闻)
    东海角(湛江)
    甲东(汕尾)
    65
    40
    40
    5
    5
    5
    10 m高度10 min平均风速
    不低于17.2 m·s-1
    0.1
    0.11
    0.14
    文献[12] 沙田塔(东莞) 80 1 60 m高度10 min平均风速
    不低于20.8 m·s-1
    0.177
    文献[23] B类下垫面
    C类下垫面
    0.15
    0.22
    DownLoad: Download CSV

    Table  4  Sudden rise of the fitting determination coefficient(R2) of wind speed in the typhoon boundary layer based on the power exponential law

    统计项目 台风苗柏 台风洛克 台风天鸽 台风帕卡 台风山竹 台风海高斯
    R2跃升前值 0.660 0.225 0.637 0.582 0.833 0.679
    R2跃升后值 0.919 0.973 0.867 0.976 0.964 0.911
    R2跃升时平均风速/(m·s-1) 7.0 3.2 5.9 1.2 10.5 1.6
    R2跃升时间点 00:20 11:30 10:00 01:50 12:00 01:50
    平均风速峰值时间 00:00 13:00 12:10 08:10 15:00 05:40
    R2跃升前观测塔所处台风象限 第二 第二 第二 第二 第二 第二
    R2跃升后观测塔所处台风象限 第三 第四 第一 第二 第一 第一
    DownLoad: Download CSV
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    • Received : 2021-11-18
    • Accepted : 2022-01-24
    • Published : 2022-03-31

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