journal article·2022-02-17Open access

Characterization of Wind Gusts: A Study Based on Meteorological Tower Observations

Bowen Yan, Pakwai Chan, Qiusheng Li, Yuncheng He, Ying Cai, Zhenru Shu, Yao Chen

Applied Sciences· Volume 12· Issue 4

Abstract

Accurate information on wind gusts is of critical importance to various practical problems. In this study, observational wind data from high-frequency response (i.e., at a sampling rate of 10 Hz), ultrasonic anemometers instrumented at four different heights (i.e., 10 m, 40 m, 160 m, 320 m) on a weather tower were collected. The observation site featured a typical suburban condition, with no significant obstacles in the immediate proximity. The data were analyzed to identify a total of twelve descriptors of wind gusts, and to find the parent distributions that estimate these parameters well via regression analysis. The results show that the gust parameters in the context of gust magnitude and amplitude with units are best fit by the Weibull model, while non-dimensional parameters in terms of gust factor and peak factor are reasonably assessed by the log-logistic distribution. The uplift time and gust nonsymmetric factor generally exhibit a lognormal distribution, while the Gamma distribution can describe the gust length scale, uplift magnitude and passage time. It is also shown that gust factors increase linearly along with turbulence intensity. Nevertheless, empirical linear formulas given in previous studies tend to over-predict. For the vertical structure of gust descriptors, it is found that the average wind speed, gust amplitude and gust length scale in 10 min monotonically increase with height, whereas the function relationship of gust amplitude, peak factor, gust factor, turbulence intensity, rise amplitude and falling amplitude tends to decrease with height.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Wind and Air Flow Studies · Aeolian processes and effects · Meteorological Phenomena and Simulations

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Chongqing Key Laboratory of Wind Engineering and Wind Energy Utilization, School of Civil Engineering, Chongqing University, Chongqing 400045, China

Hong Kong Observatory, Kowloon 999077, Hong Kong

Department of Architecture and Civil Engineering, City University of Hong Kong, Kowloon 999077, Hong Kong

Joint Research Centre for Engineering Structure Disaster Prevention and Control, Guangzhou University, Guangzhou 510006, China

School of Civil Engineering, Central South University, Changsha 410075, China

Department of Power Engineering, North China Electric Power University (Baoding), Baoding 071000, China

References (50)

Show source-provided references
1. Characterising the fractal dimension of wind speed time series under different terrain conditions10.1016/j.jweia.2020.104165 ↗
2. On the statistics of wind gusts10.1023/A:1023009722736 ↗
3. Quantitative assessment of offshore wind speed variability using fractal analysis
4. nsights from Super Typhoon Mangkhut (1822) for wind engineering practices10.1016/j.jweia.2020.104238 ↗
5. Wind gust characterization at wind turbine relevant heights in moderately complex terrain10.1175/JAMC-D-18-0040.1 ↗
6. Combination of wind gust models in convective events10.1016/j.jweia.2020.104118 ↗
7. On the vertical structure of wind gusts10.1002/qj.2468 ↗
8. WMO (2012). Measurement of surface wind. Guide to Meteorological Instruments and Methods of Observation, World Meteorological Organization. WMO-No. 8; 2008 Edition Updated in 2010.
9. Wind gust quantification using seismic measurements10.1007/s11069-019-03744-8 ↗
10. A probabilistic analysis of wind gusts using extreme value statistics10.1127/0941-2948/2009/0413 ↗
11. Developing predictive models of wind damage in Austrian forests10.1007/s13595-014-0386-0 ↗
12. Methodology for obtaining wind gusts using Doppler lidar10.1002/qj.3059 ↗
13. Jung, C., Schindler, D., Albrecht, A.T., and Buchholz, A. (2016). The role of highly-resolved gust speed in simulations of storm damage in forests at the landscape scale: A case study from southwest Germany. Atmosphere, 7.10.3390/atmos7010007 ↗
14. Development and application of a physical approach to estimating wind gusts10.1175/1520-0493(2001)129<0005:DAAOAP>2.0.CO;2 ↗
15. Gust characteristics of near-ground typhoon winds10.1016/j.jweia.2019.03.008 ↗
16. Suomi, I., and Vihma, T. (2018). Wind gust measurement techniques—From traditional anemometry to new possibilities. Sensors, 18.10.3390/s18041300 ↗
17. Forecasting wind gusts in complex terrain
18. An analysis of observed daily maximum wind gusts in the UK10.1016/j.jweia.2011.06.004 ↗
19. Gust factors for tropical cyclone, monsoon and thunderstorm winds10.1016/j.jweia.2015.02.003 ↗
20. Reduced gust factor for extreme tropical cyclone winds over ocean10.1016/j.jweia.2020.104445 ↗
21. The dependence of offshore turbulence intensity on wind speed10.1016/j.jweia.2010.02.005 ↗
22. Characterizing wind gusts in complex terrain10.5194/acp-19-3797-2019 ↗
23. Burton, T., Sharpe, D., Jenkins, N., and Bossanyi, E. (2001). Wind Energy Handbook, Wiley.10.1002/0470846062 ↗
24. Wind-gust parametrizations at heights relevant for wind energy: A study based on mast observations10.1002/qj.2039 ↗
25. The influence of sampling and filtering on measured wind gusts10.1175/1520-0426(1987)004<0613:TIOSAF>2.0.CO;2 ↗
26. An analytical approach to wind velocity gust factors10.1016/0167-6105(79)90025-4 ↗
27. International Electrotechnical Commission (2006). Wind Turbines-Part 1: Design Requirements, International Electrotechnical Commission. IEC 614001 Ed. 3.
28. Manwell, J.F., McCowan, J.G., and Rogers, A.L. (2010). Bind Energy Explained: Theory, Design and Application, John Wiley & Sons.10.1002/9781119994367 ↗
29. Stochastic gust model for design calculations of wind turbines10.1016/S0167-6105(02)00255-6 ↗
30. Tower observed vertical distribution of PM2. 5, O3 and NOx in the Pearl River Delta10.1016/j.atmosenv.2019.117083 ↗
31. Observation of Typhoon Hato based on the 356-m high meteorological gradient tower at Shenzhen10.1016/j.jweia.2020.104408 ↗
32. Observational study of wind characteristics, wind speed and turbulence profiles during Super Typhoon Mangkhut10.1016/j.jweia.2020.104362 ↗
33. He, J., Chan, P., Li, Q., Li, L., Lu, C., Zhang, L., and Yang, H. (2020). Characteristics of Wind Structure and Nowcasting of Gust Associated with Subtropical Squall Lines over Hong Kong and Shenzhen, China. Atmosphere, 11.10.3390/atmos11030270 ↗
34. Aubinet, M., Vesala, T., and Papale, D. (2012). Eddy Covariance: A Practical Guide to Measurement and Data Analysis, Springer Science & Business Media.10.1007/978-94-007-2351-1 ↗
35. Toward objective, standardized intensity estimates from surface wind speed observations10.1175/2010BAMS2942.1 ↗
36. A statistical data screening procedure10.1088/0957-0233/4/2/003 ↗
37. Foken, T., and Napo, C.J. (2008). Micrometeorology, Springer.
38. Basic laws of turbulent mixing in the surface layer of the atmosphere
39. Another look at sonic thermometry10.1007/BF00119215 ↗
40. Remarks on the definition and estimation of friction velocity10.1023/A:1002043826623 ↗
41. The effects of atmospheric stability on coastal wind climates10.1017/S1350482799000961 ↗
42. Comparative analysis of methods for modelling the short-term probability distribution of extreme wind turbine loads10.1002/we.1861 ↗
43. Statistical analysis of wind characteristics and wind energy potential in Hong Kong10.1016/j.enconman.2015.05.070 ↗
44. Investigation of offshore wind energy potential in Hong Kong based on Weibull distribution function10.1016/j.apenergy.2015.07.027 ↗
45. Observations of offshore wind characteristics by Doppler-LiDAR for wind energy applications10.1016/j.apenergy.2016.01.135 ↗
46. Distribution of extreme gust loads of wind turbines10.1016/S0167-6105(00)00084-2 ↗
47. Hogg, R.V., McKean, J., and Craig, A.T. (2005). Introduction to Mathematical Statistics, Pearson Education.
48. Wind gust factors in a coastal wind climate10.1016/j.egypro.2016.09.207 ↗
49. Choi, C.C. (1983). Wind Loading in Hong Kong: Commentary on the Code of Practice on Wind Effects Hong Kong, Hong Kong Institution of Engineers.
50. Deaves, D.M., and Harris, R.I. (1978). A Mathematical Model of the Structure of Strong Winds, Construction Industry Research and Information Association. CIRIA Report 76.