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Fitting of Wind Shear Index in the Boundary Layer of Landfalling Typhoons Based on High Tower Observation
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摘要: 利用深圳气象梯度观测塔观测数据, 以2017年以来进入深圳150 km范围的7个台风个例为研究对象, 基于幂指数律拟合讨论台风边界层风切变指数的变化规律。结果表明:幂指数能较好地拟合台风影响下350 m高度以下风廓线, 随着拟合高度范围增加, 风切变指数增大, 拟合精度基本维持;用深圳气象梯度观测塔等差层数据拟合台风风速效果好于全层次数据和等比层数据拟合;7个台风影响期间拟合风切变指数平均值为0.268, 明显高于以往研究(0.1~0.177), 主要原因是拟合的高度范围较以往研究明显增大, 此外还与强风样本较少以及下垫面更粗糙有关。利用幂函数拟合台风不同风速段最大风切变指数, 可在台风过程中预估不同高度极端大风风险。研究还表明:台风眼经过铁塔前后风切变指数明显升高, 在抗风设计以及台风防御过程中应充分考虑这一变化。Abstract: 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.
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图 1 台风个例路径示意图
(红色圆点为深圳梯度观测塔位置)
Fig. 1 Tracks of typhoons
(the red dot denotes the location of Shenzhen Meteorological Gradient Observation Tower)
图 2 风速拟合决定系数(R2)平均值随拟合高度范围变化
(a)台风影响前，(b)台风影响期间，(c)台风影响后
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
图 4 各风速段最大风切变指数α随风速变化拟合
(a)幂函数拟合，(b)对数函数拟合
Fig. 4 Fitting of the maximum wind shear index and the wind speed
(a)power function fitting,(b)logarithmic function fitting
图 5 2017年7月23日台风洛克(1707)经过深圳气象梯度观测塔的50 m高度10 min平均气压变化
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
图 6 2017年7月23日台风洛克(1707)经过深圳气象梯度观测塔的风切变指数时间序列(a)和10 m，100 m高度2 min平均风速时间序列(b)
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
图 7 2017年8月23日09:00—24日02:00台风天鸽(1713)影响期间深圳气象梯度观测塔10 m高度10 min平均风速及风切变指数α(a)和拟合决定系数R2(b)随时间变化
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
表 1 台风影响前、影响期间和影响后不同高度范围风速拟合风切变指数对比
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 
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表 2 不同高度层选取方案拟合风切变指数对比
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
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表 4 幂指数律拟合台风边界层风速拟合决定系数R2跃升情况
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
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