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

Chen Shenpeng; Duan Yihong; Li Qingqing

doi:10.11898/1001-7313.20220203

Vol.33, NO.2, 2022

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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.

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

DOI: 10.11898/1001-7313.20220203

1.
Shenzhen National Climate Observatory, Shenzhen 518040
2.
Chinese Academy of Meteorological Sciences, Beijing 100081
3.
Nanjing University of Information Science & Technology, Nanjing 210044

Received Date: 2021-11-18
Rev Recd Date: 2022-01-24
Publish Date: 2022-03-31

Abstract

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.
- Shenzhen Meteorological Gradient Observation Tower;
- typhoon;
- boundary layer;
- wind shear index

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References(33)

Figures and Tables

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)

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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

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

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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

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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

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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

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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

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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
拟合高度 (10 m参考层)	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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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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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

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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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References

[1]	He L F, Chen S, Guo Y Q. Observation characteristics and synoptic mechanisms of Typhoon Lekima extreme rainfall in 2019. J Appl Meteor Sci, 2020, 31(5): 513-526. doi: 10.11898/1001-7313.20200501
[2]	Cheng Z Q, Lin L X, Yang G J, et al. Rapid intensification and associated large-scale circulation of super Typhoon Rammasun in 2014. J Appl Meteor Sci, 2017, 28(3): 318-326. doi: 10.11898/1001-7313.20170306
[3]	Okorie M E, Inambao F, Chiguvare Z. Evaluation of wind shear coefficients, surface roughness and energy yields over inland locations in Namibia. Procedia Manufacturing, 2017, 7: 630-638. doi: 10.1016/j.promfg.2016.12.094
[4]	Gong X, Zhu R, Li Z C. Study of near-surface wind shear exponents of different regions in China. Meteor Mon, 2018, 44(9): 1160-1168. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX201809004.htm
[5]	Jin S L, Liu X L, Li H X, et al. A contrast study on vertical wind shear characteristics of different underlying surfaces. Journal of Lanzhou University(Nat Sci), 2019, 55(3): 340-346. https://www.cnki.com.cn/Article/CJFDTOTAL-LDZK201903010.htm
[6]	Liu M, Sun J, Yang H Q, et al. The study on wind speed change with height under different terrain conditions in Hubei Province. Meteor Mon, 2010, 36(4): 63-67. doi: 10.3969/j.issn.1006-009X.2010.04.015
[7]	Jin L L, Li Z J, Miao Q L, et al. Characteristics of the wind shear exponent of the near-surface layer in Urumqi City. Desert Oasis Meteor, 2016, 10(4): 81-86. https://www.cnki.com.cn/Article/CJFDTOTAL-XJQX201604013.htm
[8]	Chen Y, Zhang N. The wind turbulence of the near-surface layer of Jiangsu coastal area and its response to typhoon. J Appl Meteor Sci, 2019, 30(2): 177-190. doi: 10.11898/1001-7313.20190205
[9]	Fu P L, Hu D M, Huang H, et al. Observation of a tornado event in outside-region of Typhoon Mangkhut by X-band polarimetric phased array radar in 2018. J Appl Meteor Sci, 2020, 31(6): 706-718. doi: 10.11898/1001-7313.20200606
[10]	Liu T, Duan Y H, Feng J N, et al. Characteristics and mechanisms of long-lived concentric eyewalls in Typhoon Lekima in 2019. J Appl Meteor Sci, 2021, 32(3): 289-301. doi: 10.11898/1001-7313.20210303
[11]	Song L L, Mao H Q, Tang H Y, et al. Observation and analysis of Guangdong coastal gales in the near-surface layer. J Trop Meteor, 2004, 20(6): 731-736. doi: 10.3969/j.issn.1004-4965.2004.06.014
[12]	Chen W C, Liu A J, Song L L, et al. Case study of wind characteristics of different strong wind systems. Meteor Mon, 2019, 45(2): 251-262. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX201902010.htm
[13]	Wang X, Huang P, Gu M. Variation of wind profiles near ground during Typhoon Muifa. Journal of Tongji University(Nat Sci), 2013, 41(8): 1165-1171. doi: 10.3969/j.issn.0253-374x.2013.08.008
[14]	Zhang R Y, Zhang X Z, Yang X S, et al. Wind characteristics study in surface layer of Typhoon Morakot(0908). J Appl Meteor Sci, 2012, 23(2): 184-194. doi: 10.3969/j.issn.1001-7313.2012.02.007
[15]	Fang P Z, Zhao B K, Lu X Q, et al. Study on characteristics of wind profiles affected by landed typhoons in Fuzhou area. J Nat Disaster, 2013, 22(2): 91-98. https://www.cnki.com.cn/Article/CJFDTOTAL-ZRZH201302012.htm
[16]	Wang Z C, Zhi S Q. Observational study of strong wind characteristics of Typhoon Kaitak with automotive wind profiler radar. Meteor Sci Technol, 2014, 42(4): 678-681. https://www.cnki.com.cn/Article/CJFDTOTAL-QXKJ201404027.htm
[17]	Xu D H. Wind characteristics in the planetary boundary layer and applications. Acta Aerodyn Sin, 1984, 2(3): 75-87. https://www.cnki.com.cn/Article/CJFDTOTAL-KQDX198403010.htm
[18]	Shen H Y, Wu X, Xie J F, et al. Research on algorithm of wind energy parameters in surface layer with height. Meteor Mon, 2009, 35(7): 54-60. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX200907009.htm
[19]	Wang Z C, Song L L, He Q S, et al. Model analysis of curve fitting of wind speed and its height. J Trop Meteor, 2007, 23(6): 690-692. https://www.cnki.com.cn/Article/CJFDTOTAL-RDQX200706025.htm
[20]	Xu B Q, Wu T T, Li W H, et al. Screening of calculation methods for wind shear exponent. Trans Chin Soc Agric Eng, 2014, 30(16): 188-194. https://www.cnki.com.cn/Article/CJFDTOTAL-NYGU201416025.htm
[21]	Gu X B, Wu H B, Xu L N, et al. Precision analysis of wind speed prediction based on different calculation methods of wind shear exponent. Renew Energ Resour, 2019, 37(9): 1362-1367. https://www.cnki.com.cn/Article/CJFDTOTAL-NCNY201909014.htm
[22]	Zhi S Q, Qian G M, Luo J L. A study of wind velocity varying with altitude on the coastal areas of Guangdong Province. Trop Geogr, 2001, 21(2): 131-134. https://www.cnki.com.cn/Article/CJFDTOTAL-RDDD200102007.htm
[23]	Load Code for the Design of Building Structures. National Standard of the People's Republic of China, GB 50009-2012.2012.
[24]	Hong Kong Building Department. Code of Practice on Wind Effects in Hong Kong. Hong Kong: Building Department, 2004.
[25]	Architectural Institute of Japan. Recommendations for Loads on Buildings: A1J-RLB-2004. Tokyo: Architectural Institute of Japan, 2004.
[26]	American Society of Civil Engineers. Minimum Design Loads for Buildings and Other Structures: ASCE/SEI 7-05. Reston, VA: ASCE, 2006.
[27]	Evaluation Method of Wind Energy Resources in Wind Farm. National Standard of the People's Republic of China, GB/T 18710-2002.2002.
[28]	Wind Turbine Generator Systems-design Requirement. National Standard of the People's Republic of China, GB/T 18451.1-2012.2012.
[29]	Farrugia R N. The wind shear exponent in a Mediterranean island climate. Renewable Energy, 2003, 28: 647-653.
[30]	Bailey B H. Predicting Vertical Wind Profiles as a Function of Time of the Day and Surface Wind Speed. International Colloquium on Wind Energy, 1981.
[31]	Yan J M, Zhao B K, Zhang S, et al. Observation analysis and application evaluation of wind profile radar to diagnosing the boundary layer of landing typhoon. J Appl Meteor Sci, 2021, 32(3): 332-346. doi: 10.11898/1001-7313.20210306
[32]	Liang Z H, Wang D H, Liang Z M. Spatio-temporal characteristics of boundary layer height derived from soundings. J Appl Meteor Sci, 2020, 31(4): 447-459. doi: 10.11898/1001-7313.20200407
[33]	Wang Z C, Zhi S Q, Ding L Y. Observation and analysis on Qiongzhou Strait gales of severe Typhoon Neasat(2011). J Appl Meteor Sci, 2013, 24(5): 595-605. http://qikan.camscma.cn/article/id/20130509