Nature's style: Naturally trendy

Geophysical Research Letters

Volumn 32, Issue 23, 2005, Pages 1-5

  Cohn, Timothy A ^a   Lins, Harry F ^a  

^a U S GEOLOGICAL SURVEY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; HYDROGEOLOGY; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; MONTE CARLO METHODS; RANDOM PROCESSES; STATISTICAL METHODS; TIME SERIES ANALYSIS;

HYDROCLIMATOLOGICAL DATA; HYDROCLIMATOLOGICAL TIME SERIES; HYDROCLIMATOLOGY; LONG-TERM PERSISTENCE (LTP);

CLIMATOLOGY;

HYDROLOGICAL REGIME; MONTE CARLO ANALYSIS; TIME SERIES ANALYSIS;

EID: 31544445485     PISSN: 00948276     EISSN: None     Source Type: Journal    
DOI: 10.1029/2005GL024476     Document Type: Article

References (29)

1. Beran, J., and Y. Feng (2002), SEMIFAR models - A semiparametric approach to modelling trends, Comput. Stat. Data Anal., 40(2), 393-419.
2. Box, G. E. P., G. M. Jenkins, and G. C. Reinsel (1994), Time Series Analysis: Forecasting and Control, 3rd ed., Prentice Hall, Upper Saddle River, N. J.
3. Bras, R. L., and L. Rodriguez-Iturbe (1985), Random Functions in Hydrology, 1st ed., Addison-Wesley, Boston, Mass.
4. Craigmile, P. F., P. Guttorp, and D. B. Percival (2004), Trend assessment in a long memory dependence model using the discrete wavelet transform, Environmetrics, 15(4), 35-313.
5. Craigmile, P. F., D. B. Percival, and P. Guttorp (2005), Wavelet based estimation for polynomial contaminated fractionally differenced processes, IEEE Trans. Signal Process., 53(8), 3151-3161.
6. Hosking, J. (1984), Modeling persistence in hydrological time series using fractional differencing, Water Resour. Res., 20(12), 1898-1908.
7. Hurst, H. E. (1951), Long term storage capacities of reservoirs, Trans. Am. Soc. Civ. Eng., 116, 776-808.
8. Jones P. D., M. New, D. E. Parker, S. Martin, and I. G. Rigor (1999), Surface air temperature and its changes over the past 150 years, Rev. Geophys., 37, 173-199. (Data available at http://www.cra.uea.ac.uk/ ftpdata/tavenh2v.dat)
9. Kendall, M., and A. Stuart (1979), The Advanced Theory of Statistics, vol. 2, Inference and Relationship, 4th ed., 748 pp., Oxford Univ. Press, New York.
10. Kendall, M., A. Stuart, and J. K. Ord (1983), The Advanced Theory of Statistics, vol. 3, Design and Analysis, and Time Series, 4th ed., 780 pp., Oxford Univ. Press, New York.
11. Klemeš, V. (1974), The Hurst phenomenon: A puzzle?, Water Resour. Res., 10(4), 675-688.
12. Koutsoyiannis, D. (2000), A generalized mathematical framework for stochastic simulation and forecast of hydrologic time series, Water Resour. Res., 36(6), 1519-1533.
13. Koutsoyiannis, D. (2003), Climate change, the Hurst phenomenon, and hydrologic statistics, Hydrol. Sci, 48(1), 3-24.
14. Lettenmaier, D. P., and S. J. Burges (1978), Climate change: Detection and its impact on hydrologic design, Water Resour. Res., 14(4), 679-687.
15. Loucks, D. P., J. Stedinger, and D. Haith (1981), Water Resource Systems Planning and Analysis, 559 pp., Prentice Hall, Upper Saddle River, N. J.
16. Mandelbrot, B. B., and J. R. Wallis (1968), Noah, Joseph, and operational hydrology, Water Resour. Res., 4(5), 909-918.
17. Mandelbrot B. B., and J. R. Wallis (1969a), Some long-run properties of geophysical records, Water Resour. Res., 5(2), 321-340.
18. Mandelbrot, B. B., and J. R. Wallis (1969b), Computer experiments with fractional Gaussian noises: 1. Averages and variances, Water Resour. Res., 5(1), 228-241.
19. McCloskey, D. (1995), The insignificance of statistical significance, Sci. Am., 272(4), 32-33.
20. Nicholls, N. (2000), The insignificance of significance testing, Bull. Am. Meteorol. Soc., 81(5), 981-986.
21. Potter, K. W. (1976), Evidence of nonstationarity as a physical explanation of the Hurst phenomenon, Water Resour. Res., 12(5), 1047-1052.
22. Potter, K. W., and J. F. Walker (1981), A model of discontinuous measurement error and its effects on the probability distribution of flood discharge measurements, Water Resour. Res., 21, 1505-1509.
23. Slack, J., and J. Landwehr (1992), Hydro-climatic data network (HCDN) - A U.S. Geological Survey streamflow data set for the United States for the study of climate fluctuations, 1874-1988, U.S. Geol. Surv. Open File Rep. 92-129.
24. Smith, R. (1993), Long-range dependence and global warning, in Statistics for the Environment, edited by V. Barnett and F. Turkman, pp. 141-161, John Wiley, Hoboken, N. J.
25. Smith, R., and F.-L. Chen (1996), Regression in long-memory time series, in Athens Conference on Applied Probability and Time Series, vol. 2, Time Series Analysis in Memory of E. J. Hannan, edited by P. Robinson and M. Rosenblatt, Springer Lecture Notes Stat., 115, 378-391.
26. Vogel, R. M., Y. Tsai, and J. F. Limbrunner (1998), The regional persistence and variability of annual streamflow in the United States, Water Resour. Res., 34(12), 3445-3459.
27. von Storch, H., and F. W. Zwiers (1999), Statistical Analysis in Climate Research, 484 pp., Cambridge Univ. Press, New York.
28. Weatherhead, E., et al. (1998), Factors affecting the detection of trends: Statistical considerations and applications to environmental data, J. Geophys. Res., 103(D14), 17,149-17,161.
29. Woodward, W., and H. Gray (1993), Global warming and the problem of testing for trend in time series data, J. Clim., 6(5), 953-962.