A regional peaks-over-threshold model in a nonstationary climate

Water Resources Research

Volumn 48, Issue 11, 2012, Pages

  Roth, M ^a,b   Buishand, T A ^b   Jongbloed, G ^c   Klein Tank, A M G ^b   Van Zanten, J H ^d  

^a EINDHOVEN UNIVERSITY OF TECHNOLOGY   (Netherlands)

^b ROYAL NETHERLANDS METEOROLOGICAL INSTITUTE KNMI   (Netherlands)

^c DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

^d UNIVERSITY OF AMSTERDAM   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

CHANGING CLIMATE; COMPOSITE LIKELIHOOD; ESTIMATION OF DISTRIBUTIONS; GENERALIZED PARETO DISTRIBUTION; MARGINAL DISTRIBUTION; MODEL PARAMETERS; NETHERLANDS; NONSTATIONARY; PRECIPITATION DATA; PRECIPITATION EXTREMES; QUANTILE REGRESSION; REGIONAL FREQUENCY ANALYSIS; SCALE PARAMETER; SPATIAL DEPENDENCE; SPATIAL VARIATIONS; TEMPORAL DEPENDENCE; TEMPORAL TRENDS; WEST COAST; WINTER SEASONS;

PARAMETER ESTIMATION;

CLIMATE MODELS;

CLIMATE CHANGE; DATA SET; FREQUENCY ANALYSIS; NUMERICAL MODEL; PRECIPITATION (CLIMATOLOGY); REGRESSION ANALYSIS; THRESHOLD; UNCERTAINTY ANALYSIS;

NETHERLANDS;

EID: 84870618080     PISSN: 00431397     EISSN: 19447973     Source Type: Journal    
DOI: 10.1029/2012WR012214     Document Type: Article

References (59)

1. Beguería, S., M. Angulo-Martínez, S. M. Vicente-Serrano, J. I. López-Moreno, and A. El-Kenawy (2011), Assessing trends in extreme precipitation events intensity and magnitude using non-stationary peaks-over-threshold analysis: A case study in Northeast Spain from 1930 to 2006, Int. J. Climatol., 31(14), 2102-2114, doi:10.1002/joc.2218.
2. Bengtsson, A., and C. Nilsson (2007), Extreme value modelling of storm damage in Swedish forests, Nat. Hazards Earth Syst. Sci., 7, 515-521. (Pubitemid 47402783)
3. Blanchet, J., and M. Lehning (2010), Mapping snow depth return levels: Smooth spatial modeling versus station interpolation, Hydrol. Earth Syst. Sci., 14(12), 2527-2544, doi:10.5194/hess-14-2527-2010.
4. Brown, S. J., J. Caesar, and C. A. T. Ferro (2008), Global changes in extreme daily temperature since 1950, J. Geophys. Res., 113(D5), D05115, doi :10.1029/2006JD008091.
5. Buishand, T. A. (1984), Zware neerslag in het winterhalfjaar, Cultuurtech. Tijdschrift, 23(5), 263-275, in Dutch.
6. Buishand, T. A. (1989), Statistics of extremes in climatology, Stat. Neerlandica, 43(1), 1-30, doi:10.1111/j.1467-9574.989.b01244.
7. . Buishand, T. A. (1991), Extreme rainfall estimation by combining data from several sites, Hydrol. Sci. J., 36(4), 345-365, doi:10.1080/ 02626669109492519.
8. Buishand, T. A., G. De Martino, H. Spreeuw, and T. Brandsma (2012), Homogeneity of precipitation series in the Netherlands and their trends in the past century, Int. J. Climatol., doi:10.1002/joc.3471, in press.
9. Chandler, R. E., and S. Bate (2007), Inference for clustered data using the independence loglikelihood, Biometrika, 94(1), 167-183, doi:10.1093/ biomet/asm015. (Pubitemid 46410724)
10. Coelho, C. A. S., C. A. T. Ferro, D. B. Stephenson, and D. J. Steinskog (2008), Methods for exploring spatial and temporal variability of extreme events in climate data, J. Clim., 21(10), 2072-2092, doi:10.1175/ 2007JCLI1781. (Pubitemid 351844067)
11. . Coles, S. (1993), Regional modelling of extreme storms via max-stable processes, J. R. Stat. Soc. Ser. B, 55(4), 797-816.
12. Coles, S. (2001), An Introduction to Statistical Modeling of Extreme Values, Springer, London.
13. Cooley, D., D. Nychka, and P. Naveau (2007), Bayesian spatial modeling of extreme precipitation return levels, J. Am. Stat. Assoc., 102(479), 824-840, doi:10.1198/016214506000000780.
14. Cox, D. R., and P. A. W. Lewis (1966), The Statistical Analysis of Series of Events, Methuen, London.
15. Cunnane, C. (1979), A note on the Poisson assumption in partial duration series models, Water Resour. Res., 15(2), 489-494, doi :10.1029/WR015i 002p00489.
16. Cunnane, C. (1988), Methods and merits of regional flood frequency analysis, J. Hydrol., 100(1-3), 269-290, doi:10.1016/0022-1694(88)90188-6.
17. Dales, M. Y., and D. W. Reed (1989), Regional flood and storm hazard assessment, Report No. 102, Institute of Hydrology, Wallingford.
18. Dalrymple, T. (1960), Flood-frequency analyses, manual of hydrology: Part 3, U.S. Geol. Surv. Water Sup. Pap., 1543-A, 86 pp.
19. El Adlouni, S., T. B. M. J. Ouarda, X. Zhang, R. Roy, and B. Bobeé (2007), Generalized maximum likelihood estimators for the nonstationary generalized extreme value model, Water Resour. Res., 43(3), W03410, doi:10.1029/2005WR004545. (Pubitemid 46682780)
20. Embrechts, P., C. Klüppelberg, and T. Mikosch (1997), Modelling Extremal Events, Springer, Berlin.
21. Fowler, H. J., M. Ekström, C. G. Kilsby, and P. D. Jones (2005), New estimates of future changes in extreme rainfall across the UK using regional climate model integrations. 1. Assessment of control climate, J. Hydrol., 300(1-4), 212-233, doi:10.1016/j.jhydrol.2004.6.017 (Pubitemid 39588515)
22. Friederichs, P. (2010), Statistical downscaling of extreme precipitation events using extreme value theory, Extremes, 13, 109-132, doi:10.1007/s10687- 010-0107-5.
23. Hanel, M., T. A. Buishand, and C. A. T. Ferro (2009), A nonstationary index flood model for precipitation extremes in transient regional climate model simulations, J. Geophys. Res., 114(D15), D15107, doi:10.1029/2009JD011712.
24. Haylock, M. R., N. Hofstra, A. M. G. Klein Tank, E. J. Klok, P. D. Jones, and M. New (2008), A European daily high-resolution gridded data set of surface temperature and precipitation for 1950-2006, J. Geophys. Res., 113(D20), D20119, doi:10.1029/2008JD010201.
25. Hosking, J. R. M., and J. R. Wallis (1997), Regional Frequency Analysis, Cambridge University Press, Cambridge, UK.
26. Kharin, V. V. and F. W. Zwiers (2005), Estimating extremes in transient climate change simulations, J. Clim., 18(8), 1156-1173, doi:10.1175/ JCLI3320.1. (Pubitemid 40717074)
27. Klein Tank, A. M. G., and G. P. Können (2003), Trends in indices of daily temperature and precipitation extremes in Europe, 1946-99, J. Clim., 16(22), 3665-3680, doi:10.1175/1520-0442(2003)016 <3665:TIIODT>2.0.CO;2. (Pubitemid 38070232)
28. Koenker, R. (2005), Quantile Regression, Cambridge University Press, Cambridge, UK.
29. Koenker, R., and G. Bassett Jr. (1978), Regression quantiles, Econometrica, 46(1), 33-50.
30. Kyselý, J. (2007), A cautionary note on the use of nonparametric bootstrap for estimating uncertainties in extreme-value models, J. Appl. Meteorol., 47, 3236-3251, doi:10.1175/2008JAMC1763.
31. . Kyselý, J. (2009), Coverage probability of bootstrap confidence intervals in heavy-tailed frequency models, with application to precipitation data, Theor. Appl. Climatol., 101, 345-361, doi:10.1007/s00704-009-0190-1.
32. Kyselý, J., and R. Beranová (2009), Climate-change effects on extreme precipitation in central Europe: Uncertainties of scenarios based on regional climate models, Theor. Appl. Climatol., 95, 361-374, doi:10.1007/s00704-008-0014-8.
33. Kyselý, J., J. Picek, and R. Beranová (2010) Estimating extremes in climate change simulations using the peaks-over-threshold method with a nonstationary threshold, Global Planet. Change, 72(1-2), 55-68, doi:10.1002/joc.1874.
34. Lang,M., T. B. M. J. Ouarda, andB. Bobée (1999), Towards operational guidelines for over-threshold modeling, J. Hydrol., 95, 361-374, doi:10.1007/s00704-008-0014-8.
35. Madsen, H., and D. Rosbjerg (1997), The partial duration series method in regional index-flood modeling, Water Resour. Res., 33(4), 737-746, doi:10.1029/96WR03847.
36. Madsen, H., P. F. Rasmussen, and D. Rosbjerg (1997a), Comparison of annual maximum series and partial duration series methods for modeling extreme hydrologic events: 1. At-site modeling, Water Resour. Res., 33(4), 747-757, doi:10.1029/96WR03848.
37. Madsen, H., C. P. Pearson, and D. Rosbjerg (1997b), Comparison of annual maximum series and partial duration series methods for modeling extreme hydrologic events: 2. Regional modeling, Water Resour. Res., 33(4), 759-769, doi:10.1029/96WR03849.
38. Milly, P. C. D., J. Betancourt, M. Falkenmark, R. M. Hirsch, Z. W. Kundzewicz, D. P. Lettenmaier, and R. J. Stouffer (2008), Stationarity is dead: Whither water management?, Science, 319(5863), 573-574, doi:10.1126/ science.1151915. (Pubitemid 351197047)
39. Moore, R. J. (1987), Combined regional flood frequency analysis and regression on catchment characteristics by maximum likelihood estimation, in Regional Flood Frequency Analysis, edited by V. P. Singh, pp. 119-131, Reidel, Dordrecht.
40. Nelsen, R. B. (2006), An Introduction to Copulas, Springer, New York.
41. Overeem, A., T. A. Buishand, and I. Holleman (2008), Rainfall depth-duration- frequency curves and their uncertainties, J. Hydrol., 348, 124-134, doi:10.1016/j.jhydrol.2007.9.044. (Pubitemid 351483862)
42. R Development Core Team (2011), R: A language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria.
43. Reed, D. W., and E. J. Stewart (1994), Inter-site and inter-duration dependence of rainfall extremes, in Statistics for the Environment 2, edited by V. Barnett and K. F. Turkman, pp. 125-143, Wiley, Chichester.
44. Reiss, R. D., and M. Thomas (2007), Statistical Analysis of Extreme Values: With Applications to Insurance, Finance, Hydrology and Other Fields, 3rd ed., Birkhäuser, Basel, Switzerland.
45. Robinson, J. S., and M. Sivapalan (1997), An investigation into the physical causes of scaling and heterogeneity of regional flood frequency, Water Resour. Res., 33(5), 1045-1059, doi:10.1029/97WR00044.
46. Smith, J. A. (1989), Regional flood frequency analysis using extreme order statistics of the annual peak record, Water Resour. Res., 25(2), 311-317, doi:10.1029/WR025i002p00311. (Pubitemid 19303577)
47. Smith, R. L. (1986), Extreme value theory based on the r largest annual events, J. Hydrol., 86(1-2), 27-43, doi:10.1016/0022-1694(86)90004-1.
48. Smith, R. L. (1989), Extreme value analysis of environmental time series: An application to trend detection in ground-level ozone, Stat. Sci., 4(4), 367-377.
49. Svensson, C., and D. A. Jones (2010), Review of rainfall frequency estimation methods, J. Flood Risk Manage., 3(4), 296-313, doi:10.1111/j.1753- 318X.2010.1079.
50. . Turco, M., and M. C. Llasat (2011), Trends in indices of daily precipitation extremes in Catalonia (NE Spain), 1951-2003, Nat. Hazards Earth Syst. Sci., 11(12), 3213-3226, doi:10.5194/nhess-11-3213-2011.
51. Van den Brink, H. W., and G. P. Können (2011), Estimating 10000-year return values from short time series, Int. J. Climatol., 31(1), 115-126, doi:10.1002/joc.2047.
52. Van de Vyver, H. (2012), Spatial regression models for extreme precipitation in Belgium, Water Resour. Res., 48,W09549, doi:10.1029/ 2011WR011707.
53. Varin, C., N. Reid, and D. Firth (2011), An overview of composite likelihood methods, Stat. Sinica, 21, 5-42.
54. Wang, Q. J. (1991), The POT model described by the generalized Pareto distribution with Poisson arrival rate, J. Hydrol., 129(1-4), 263-280, doi:10.1016/0022-1694(91)90054-L.
55. Westra, S., and S. Sisson (2011), Detection of non-stationarity in precipitation extremes using a max-stable process model, J. Hydrol., 406, 119-128, doi:10.1016/j.jhydrol.2011.6.014.
56. Wigley, T. (2009), The effect of changing climate on the frequency of absolute extreme events. Clim. Change, 97, 67-76, doi:10.1007/s10584-009- 9654-7.
57. Yee, T. W., and A. G. Stephenson (2007), Vector generalized linear and additive extreme value models, Extremes, 10, 1-19, doi:10.1007/s10687-007-0032- 4.
58. Yiou, P., P. Ribereau, P. Naveau, M. Nogaj, and R. Brázdil (2006), Statistical analysis of floods in Bohemia (Czech Republic) since 1825, Hydrol. Sci. J., 51(5), 930-945, doi:10.1623/hysj.51.5.930. (Pubitemid 44501653)
59. Zhang, X., F. W. Zwiers, and G. Li (2004), Monte Carlo experiments on the detection of trends in extreme values, J. Clim., 17(10), 1945-1952, doi:10.1175/1520-0442(2004)017<1945:MCEOTD>2.0.CO;2. (Pubitemid 38673140)