Ahmat, H., and A. S. Yahaya, 2018: The analysis of PM10 concentrations using the generalized extreme value (GEV) and generalized Pareto distribution (GPD) in the Bayesian approach. AIP Conference Proceedings, 1974, 040019, https://doi.org/10.1063/1.5041693.
Altmann, E. G., and H. Kantz, 2005: Recurrence time analysis, long-term correlations, and extreme events. Physical Review E, 71, 056106, https://doi.org/10.1103/PhysRevE.71.056106.
Anastasiades, G., and P. E. McSharry, 2014: Extreme value analysis for estimating 50 year return wind speeds from reanalysis data. Wind Energy, 17, 1231−1245, https://doi.org/10.1002/we.1630.
Badin, G., and D. I. V. Domeisen, 2014: A search for chaotic behavior in stratospheric variability: Comparison between the Northern and Southern Hemispheres. J. Atmos. Sci., 71, 4611−4620, https://doi.org/10.1175/JAS-D-14-0049.1.
Badin, G., and D. I. V. Domeisen, 2016: Nonlinear stratospheric variability: Multifractal de-trended fluctuation analysis and singularity spectra. Proceedings of the Royal Society A, 472, 20150864, https://doi.org/10.1098/rspa.2015.0864.
Beran, J., 1994: Statistics for Long-Memory Processes. Chapman & Hall., 315 pp.
Berman, S. M., 1964: Limit theorems for the maximum term in stationary sequences. The Annals of Mathematical Statistics, 35, 502−516, https://doi.org/10.1214/aoms/1177703551.
Bryce, R. M, and K. B. Sprague, 2012: Revisiting detrended fluctuation analysis. Scientific Reports, 2, 315, https://doi.org/10.1038/srep00315.
Bunde, A., J. F. Eichner, J. W. Kantelhardt, and S. Havlin, 2005: Long-term memory: A natural mechanism for the clustering of extreme events and anomalous residual times in climate records. Physical Review Letters, 94, 048701, https://doi.org/10.1103/PhysRevLett.94.048701.
Boers, N., B. Goswami, A. Rheinwalt, B. Bookhagen, B. Hoskins, and J. Kurth, 2019: Complex networks reveal global pattern of extreme-rainfall teleconnections. Nature, 566, 373−377, https://doi.org/10.1038/s41586-018-0872-x.
Coles, S., 2001: An Introduction to Statistical Modeling of Extreme Values. Springer-Verlag., 208 pp.
Cook, N. J., and R. I. Harris, 2004: Exact and general FT1 penultimate distributions of extreme wind speeds drawn from tail-equivalent Weibull parents. Structural Safety, 26, 391−420, https://doi.org/10.1016/j.strusafe.2004.01.002.
Ding, Y. G., B. Y. Cheng, and Z. H. Jiang, 2008: A newly-discovered GPD-GEV relationship together with comparing their models of extreme precipitation in summer. Adv. Atmos. Sci., 25, 507−516, https://doi.org/10.1007/s00376-008-0507-5.
DuMouchel, W. H., 1983: Estimating the stable index α in order to measure tail thickness: A critique. The Annals of Statistics, 11, 1019−1031, https://doi.org/10.1214/aos/1176346318.
Eichner, J. F., J. W. Kantelhardt, A. Bunde, and S. Havlin, 2006: Extreme value statistics in records with long-term persistence. Physical Review E, 73, 016130, https://doi.org/10.1103/PhysRevE.73.016130.
Gumbel, E., 1958: Statistics of Extremes. Columbia University Press, 375 pp.
Holmes, J. D., 2015: Wind Loading of Structures. 3rd ed., CRC Press, 450 pp.
Holmes, J. D., and W. W. Moriarty, 1999: Application of the generalized Pareto distribution to extreme value analysis in wind engineering. Journal of Wind Engineering and Industrial Aerodynamics, 83, 1−10, https://doi.org/10.1016/S0167-6105(99)00056-2.
Kantelhardt, J. W., E. Koscielny-Bunde, H. H. A. Rego, S. Havlin, and A. Bunde, 2001: Detecting long-range correlations with detrended fluctuation analysis. Physica A: Statistical Mechanics and Its Applications, 295, 441−454, https://doi.org/10.1016/S0378-4371(01)00144-3.
Kong, X. H., A. H. Wang, X. Q. Bi, and D. Wang, 2019: Assessment of temperature extremes in China using RegCM4 and WRF. Adv. Atmos. Sci., 36(4), 363−377, https://doi.org/10.1007/s00376-018-8144-0.
Larsén, X. G., J. Mann, O. Rathmann, and H. E. Jørgensen, 2015: Uncertainties of the 50-year wind from short time series using generalized extreme value distribution and generalized Pareto distribution. Wind Energy, 18, 59−74, https://doi.org/10.1002/we.1683.
Leadbetter, M. R., G. Lindgren, and H. Rootzén, 1983: Extremes and Related Properties of Random Sequences and Processes. Springer-Verlag, 336 pp.
Liu, L., and F. Hu, 2013: Cascade-like and scaling behavior of wind velocity increments in the atmospheric surface layer. Physica A: Statistical Mechanics and its Applications, 392, 5808−5816, https://doi.org/10.1016/j.physa.2013.07.054.
Liu, L., F. Hu, and X. L. Cheng, 2014: Extreme fluctuations of vertical velocity in the unstable atmospheric surface layer. Nonlinear Processes in Geophysics, 21, 463−475, https://doi.org/10.5194/npg-21-463-2014.
Moloney, N. R., and J. Davidsen, 2009: Extreme value statistics and return intervals in long-range correlated uniform deviates. Physical Review E, 79, 041131, https://doi.org/10.1103/PhysRevE.79.041131.
Palutikof, J. P., B. B. Brabson, D. H. Lister, and S. T. Adcock, 1999: A review of methods to calculate extreme wind speeds. Meteorological Applications, 6, 119−132, https://doi.org/10.1017/S1350482799001103.
Peng, C. K., S. V. Buldyrev, A. L. Goldberger, S. Havlin, F. Sciortino, M. Simons, and H. E. Stanley, 1992: Long-range correlations in nucleotide sequences. Nature, 356, 168−170, https://doi.org/10.1038/356168a0.
Peng, C. K., S. V. Buldyrev, S. Havlin, M. Simons, H. E. Stanley, and A. L. Goldberger, 1994: Mosaic organization of DNA nucleotides. Physical Review E, 49, 1685−1689, https://doi.org/10.1103/PhysRevE.49.1685.
Peterka, J. A., and S. Shahid, 1998: Design gust wind speeds in the United States. Journal of Structural Engineering, 124, 207−214, https://doi.org/10.1061/(ASCE)0733-9445(1998)124:2(207).
Ross, S. M., 1996: Stochastic Processes. 2nd ed., John Wiley & Sons, Inc., 528 pp.
Santhanam, M., and H. Kantz, 2005: Long-range correlations and rare events in boundary layer wind fields. Physica A: Statistical Mechanics and its Applications, 345, 713−721, https://doi.org/10.1016/j.physa.2004.07.012.
Scarrott, C., and A. MacDonald, 2012: A review of extreme value threshold estimation and uncertainty quantification. Revstat-Statistical Journal, 10, 33−60.
Schumann, A. Y., N. R. Moloney, and J. Davidsen, 2012: Extreme value and record statistics in heavy-tailed processes with long-range memory. Extreme Events and Natural Hazards: The Complexity Perspective, A. S. Sharma et al., Eds., American Geophysical Union, 315−334.
Wever, N., and G. Groen, 2009: Improving potential wind for extreme wind statistics. KNMI Scientific Report, WR2009-02.
Yan, Z. W., C. Yang, and P. Jones, 2001: Influence of inhomogeneity on the estimation of mean and extreme temperature trends in Beijing and Shanghai. Adv. Atmos. Sci., 18, 309−322, https://doi.org/10.1007/BF02919312.
Zhang, H., and P. M. Zhai, 2011: Temporal and spatial characteristics of extreme hourly precipitation over eastern China in the warm season. Adv. Atmos. Sci., 28, 1177−1183, https://doi.org/10.1007/s00376-011-0020-0.