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http://dx.doi.org/10.12989/was.2018.26.3.129

Non-stationary statistical modeling of extreme wind speed series with exposure correction  

Huang, Mingfeng (Institute of Structural Engineering, College of Civil Engineering & Architecture, Zhejiang University)
Li, Qiang (Institute of Structural Engineering, College of Civil Engineering & Architecture, Zhejiang University)
Xu, Haiwei (Institute of Structural Engineering, College of Civil Engineering & Architecture, Zhejiang University)
Lou, Wenjuan (Institute of Structural Engineering, College of Civil Engineering & Architecture, Zhejiang University)
Lin, Ning (Department of Civil and Environmental Engineering, Princeton University)
Publication Information
Wind and Structures / v.26, no.3, 2018 , pp. 129-146 More about this Journal
Abstract
Extreme wind speed analysis has been carried out conventionally by assuming the extreme series data is stationary. However, time-varying trends of the extreme wind speed series could be detected at many surface meteorological stations in China. Two main reasons, exposure change and climate change, were provided to explain the temporal trends of daily maximum wind speed and annual maximum wind speed series data, recorded at Hangzhou (China) meteorological station. After making a correction on wind speed series for time varying exposure, it is necessary to perform non-stationary statistical modeling on the corrected extreme wind speed data series in addition to the classical extreme value analysis. The generalized extreme value (GEV) distribution with time-dependent location and scale parameters was selected as a non-stationary model to describe the corrected extreme wind speed series. The obtained non-stationary extreme value models were then used to estimate the non-stationary extreme wind speed quantiles with various mean recurrence intervals (MRIs) considering changing climate, and compared to the corresponding stationary ones with various MRIs for the Hangzhou area in China. The results indicate that the non-stationary property or dependence of extreme wind speed data should be carefully evaluated and reflected in the determination of design wind speeds.
Keywords
extreme wind speed; exposure adjustment; non-stationary; statistical modeling; generalized maximum likelihood approach;
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1 Chen, K., Jin, X.Y. and Qian, J.H. (2012), "Calculation method on the reference wind pressure accounting for the terrain variations", Acta Sci. Nat. Univ. Pekin., 48(1), 13-19 (in Chinese).
2 Coles, G.S. (2001), An Introduction to Statistical Modeling of Extreme Values, Springer, New York.
3 Cook, N.J. (1985), The Designer's Guide to Wind Loading on Building Structures. Part I: Background, Damage Survey, Wind Data, and Structural Classification. Building Research Establishment, Watford.
4 Cook, N.J. and Harris, R.I. (2004), "Exact and general FT1 penultimate distributions of extreme wind speeds drawn from tail-equivalent Weibull parents", Struct. Saf., 26(4), 391-420.   DOI
5 Chen, L. (2005), Vector time-varying autoregressive (TVAR) models and their application to downburst wind speeds, Ph.D. Dissertation, Texas Tech University.
6 Dyrbye, C. and Hansen, S.O. (1996), Wind Loads on Structures. John Wiley & Sons, New York.
7 El Adlouni, S., Ouarda, T.B.M.J., Zhang, X., Roy, R. and Bobee, B. (2007), "Generalized maximum likelihood estimators for the non-stationary generalized extreme value model", Water Resour. Res., 43(3).
8 GB 50009-2012. Load Code for the Design of Building Structures, Ministry of Housing and Urban-Rural Development of the People's Republic of China. China Architecture & Building Press (in Chinese).
9 Gilbert, R.O. (1987), Statistical Methods for Environmental Pollution Monitoring, Wiley, NY.
10 Aboshosha, H., Bitsuamlak, G. and Damatty, A.E. (2015), "Turbulence characterization of downbursts using LES", J. Wind Eng. Ind. Aerod., 136(136), 44-61.   DOI
11 Aboshosha, H. and Damatty, A.E. (2015), "Engineering method for estimating the reactions of transmission line conductors under downburst winds", Eng. Struct., 99, 272-284.   DOI
12 AIJ-RLB (2004), Recommendations for loads on buildings. Architectural Institute of Japan, Tokyo.
13 Hosking, J.R.M. (1985), "Algorithm AS 215: Maximumlikelihood estimation of the parameters of the generalized extreme-value distribution", J. Roy. Stat. Soc. Series C (Applied Statistics), 34(3), 301-310.
14 Harris, R.I. (2009), "XIMIS, a penultimate extreme value method suitable for all types of wind climate", J. Wind Eng. Ind. Aerod., 97(5-6), 271-286.   DOI
15 Harris, R.I. and Cook, R.J. (2014), "The parent wind speed distribution: Why Weibull?", J. Wind Eng. Ind. Aerod., 131, 72-87.   DOI
16 Holmes, J.D. and Moriarty, W.W. (1999), "Application of the generalized Pareto distribution to extreme value analysis in wind engineering", J. Wind Eng. Ind. Aerod., 83(1), 1-10.   DOI
17 Hosking, J.R.M., Wallis, J.R. and Wood, E.F. (1985), "Estimation of the generalized extreme-value distribution by the method of probability-weighted moments", Technometrics, 27(3), 251-261.   DOI
18 Hundecha, Y., St-Hilaire, A., Ouarda, T.B.M.J., El Adlouni, S. and Gachon, P. (2008), "A nonstationary extreme value analysis for the assessment of changes in extreme annual wind speed over the Gulf of St. Lawrence", Can. J. Appl. Meteorol. Clim., 47(11), 2745-2759.   DOI
19 Huang, G. and Chen, X. (2009), "Wavelets-based estimation of multivariate evolutionary spectra and its application to nonstationary downburst winds", Eng. Struct., 31(4), 976-989.   DOI
20 Huang, G., Zheng, H., Xu, Y.L. and Li, Y. (2015), "Spectrum models for nonstationary extreme winds", J. Struct. Eng., 141(10), 04015010.   DOI
21 Jiang, Y., Luo, Y., Zhao, Z. and Tao, S. (2010), "Changes in wind speed over China during 1956-2004", Theor. Appl. Climatol., 99(3-4), 421-430.   DOI
22 Kharin, V.V. and Zwiers, F.W. (2005), "Estimating extremes in transient climate change simulations", J. Climate, 18(8), 1156-1173.   DOI
23 Ashcroft, J. (1994), "The relationship between the gust ratio, terrain roughness, gust duration and the hourly mean wind speed", J. Wind Eng. Ind. Aerod., 53(3), 331-355.   DOI
24 BS EN 1991-1-4 (2005), Eurocode 1: Actions on Structures - Part 1-4: General actions - Wind Actions, European Committee for Standardization, British Standards Institution, London.
25 Kasperski, M. (2009), "Specification of the design wind load-A critical review of code concepts", J. Wind Eng. Ind. Aerod., 97(7-8), 335-357.   DOI
26 Katz, R.W., Parlange, M.B. and Naveau, P. (2002), "Statistics of extremes in hydrology", Adv. Water Resour., 25(8), 1287-1304.   DOI
27 Kendall, M.G. (1975), Rank Correlation Methods, 4th Ed., Charles Griffin, London.
28 Li, Z.X., He, Y., Wang, P., Theakstone, W. H., An, W., Wang, X. and, Cao, W. (2012), "Changes of daily climate extremes in southwestern China during 1961-2008", Global and Planetary Change, 80, 255-272.
29 Lombardo, F.T., Main, J.A. and Simiu, E. (2009), "Automated extraction and classification of thunderstorm and nonthunderstorm wind data for extreme-value analysis", J. Wind Eng. Ind. Aerod., 97(3), 120-131.   DOI
30 Lombardo, F.T. (2012), Improved extreme wind speed estimation for wind engineering applications. J. Wind Eng. Ind. Aerod., 104-106, 278-284.   DOI
31 Lombardo, F.T. (2014), "Extreme wind speeds from multiple wind hazards excluding tropical cyclones", Wind Struct., 19(5), 467-480.   DOI
32 Lombardo, F.T. and Ayyub, B.M. (2015), "Analysis of Washington, DC, wind and temperature extremes with examination of climate change for engineering applications. ASCE-ASME", J. Risk Uncertainty in Eng. Syst., Part A: Civil Eng., 1(1), 04014005.
33 Lombardo, F.T. and Krupar III, R.J. (2016), "A comparison of aerodynamic roughness length estimation methods for use in characterizing surface terrain conditions", submitted to J. Struct. Eng.
34 Masters, F.J., Tieleman, H.W. and Balderrama, J.A. (2010a), "Surface wind measurements in three gulf coast hurricanes of 2005", J. Wind Eng. Ind. Aerod., 98(10-11), 533-547.   DOI
35 Macleod, A.J. (1989), "A remark on algorithm AS 215: Maximumlikelihood estimation of the parameters of the generalized extreme-value distribution", Appl. Statist., 38(1), 198-199.   DOI
36 Mann, H.B. (1945), "Non-parametric tests against trend", Econometrica, 13,163-171.
37 Martins, E.S. and Stedinger, J.R. (2000), "Generalized maximumlikelihood generalized extreme-value quantile estimators for hydrologic data", Water Resour. Res., 36(3), 737-744.   DOI
38 Masters, F.J., Vickery, P.J., Bacon, P. and Rappaport, E.N. (2010b), "Toward objective, standardized intensity estimates from surface wind speed observations", Bull. Am. Meteorol. Soc., 91(12), 1665-1681.   DOI
39 Miller, C., Balderrama, J.A. and Masters, F. (2015), "Aspects of observed gust factors in landfalling tropical cyclones: gust components, terrain, and upstream fetch effects", Bound.- Lay. Meteorol., 155(1), 1-27.   DOI
40 Mo, H.M., Hong, H.P. and Fan, F. (2015), "Estimating the extreme wind speed for regions in China using surface wind observations and reanalysis data", J. Wind Eng. Ind. Aerod., 143, 19-33.   DOI
41 Pagnini, L.C. and Solari, G. (2015), "Joint modeling of the parent population and extreme value distributions of the mean wind velocity", J. Struct. Eng., 142(2), 04015138
42 Palutikof, J.P., Brabson, B.B., Lister, D.H. and Adcock, S.T. (1999), "A review of methods to calculate extreme wind speeds", Meteorol. Appl., 6(2), 119-132.   DOI
43 Simiu, E. and Heckert, N.A. (1996), "Extreme wind distribution tails: a "peaks over threshold" approach", J. Struct. Eng., 122(5), 539-547.   DOI
44 Pavia, E.G. and O'Brien, J.J. (1986), "Weibull statistics of wind speed over the ocean", J. Clim. Appl. Meteorol., 25(10), 1324-1332.   DOI
45 Ruest, B., Neumeier, U., Dumont, D., Bismuth, E., Senneville, S. and Caveen, J. (2016), "Recent wave climate and expected future changes in the seasonally ice-infested waters of the Gulf of St. Lawrence", Can. Clim. Dynam., 46(1-2), 449-466.   DOI
46 Sacre, C., Moisselin, J.M., Sabre, M., Flori, J.P. and Dubuisson, B. (2007), "A new statistical approach to extreme wind speeds in france", J. Wind Eng. Ind. Aerod., 95(9-11), 1415-1423.   DOI
47 Smith, R.L. (1985), "Maximum likelihood estimation in a class of non-regular cases", Biometrika, 72(1), 67-90.   DOI
48 Solari, G., Repetto, M. P., Burlando, M., De Gaetano, P., Pizzo, M., Tizzi, M. and Parodi, M. (2012), "The wind forecast for safety management of port areas", J. Wind Eng. Ind. Aerod., 104, 266-277.
49 Su, Y., Huang, G. and Xu Y. (2015), "Derivation of time-varying mean for non-stationary downburst winds", J. Wind Eng. Ind. Aerod., 141, 39-48.   DOI
50 Tuller, S.E. and Brett, A.C. (1984), "The characteristics of wind velocity that favor the fitting of a Weibull distribution in wind speed analysis", J. Clim. Appl. Meteorol., 23(1), 124-134.   DOI
51 World meteorological organization (2012), Guide to Meteorological Instruments and Methods of Observation. Secretariat of the World Meteorological Organization.
52 Yang, X., Li, Z., Feng, Q., He, Y., An, W., Zhang, W. et al. (2012), "The decreasing wind speed in southwestern china during 1969-2009, and possible causes", Quaternary Int., 263(3), 71-84.   DOI
53 Xu, M., Chang, C.P., Fu, C., Qi, Y., Robock, A., Robinson, D. and Zhang, H.M. (2006), "Steady decline of east Asian monsoon winds, 1969-2000: Evidence from direct ground measurements of wind speed", J. Geophys. Res: Atmos., 111(D24).
54 Xu, Y.L., Hu, L. and Kareem, A. (2014), "Conditional simulation of nonstationary fluctuating wind speeds for long-span bridges", J. Eng. Mech., 140(1), 61-73.   DOI
55 Yan, Z., Bate, S., Chandler, R.E., Isham, V. and Wheater, H. (2006), "Changes in extreme wind speeds in NW Europe simulated by generalized linear models", Theor. Appl. Climatol., 83(1-4), 121-137.   DOI
56 Zwiers, F.W. and Kharin, V.V. (1998), "Changes in the extremes of the climate simulated by CCC GCM2 under CO2 doubling", J. Climate, 11(9), 2200-2222.   DOI
57 Ying, M., Zhang, W., Yu, H., Lu, X., Feng, J., Fan, Y. et al. (2014), "An overview of the China Meteorological Administration tropical cyclone database", J. Atmos. Oceanic Technol., 31(2), 287-301.   DOI
58 You, Q., Kang, S., Aguilar, E., Pepin, N., Flugel, W. A., Yan, Y. and Huang, J. (2011), "Changes in daily climate extremes in China and their connection to the large scale atmospheric circulation during 1961-2003", Clim. Dynam., 36(11-12), 2399-2417.   DOI
59 Zhang, X., Zwiers, F.W. and Li, G. (2004), "Monte Carlo experiments on the detection of trends in extreme values", J. Climate, 17(10), 1945-1952.   DOI