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Lehmann, Eric A.; Phatak, Aloke; Stephenson, Alec; Lau, Rex

Spatial modelling framework for the characterisation of rainfall extremes at different durations and under climate change. (English) Zbl 1525.62166

Environmetrics 27, No. 4, 239-251 (2016).

Cited in 6 Documents

MSC:

62P12 Applications of statistics to environmental and related topics

Keywords:

Bayesian hierarchical modelling; extreme value theory; Hershfield factor; extremal index; Markov chain Monte Carlo; intensity-frequency-duration curve

Software:

spBayes
Cite Review PDF
Full Text: DOI Link

References:

[1] AtyeoJ, WalshawD. 2012. A region‐based hierarchical model for extreme rainfall over the UK, incorporating spatial dependence and temporal trend. Environmetrics23(6): 509-521.
[2] BanerjeeS, CarlinBP, GelfandAE. 2003. Hierarchical Modeling and Analysis for Spatial Data, Chapman & Hall/CRC Monographs on Statistics & Applied Probability. Taylor & Francis: Boca Raton, Florida.
[3] BrackenC, RajagopalanB, ChengL, KleiberW, GangopadhyayS. 2016. Spatial Bayesian hierarchical modeling of precipitation extremes over a large domain ArXiv e‐prints arXiv:1512.08560v2 [stat.ME].
[4] BrooksSP, RobertsGO. 1998. Convergence assessment techniques for Markov chain Monte Carlo. Statistics and Computing8: 319-335.
[5] ChengL, AghaKouchakA. 2014. Nonstationary precipitation intensity‐duration‐frequency curves for infrastructure design in a changing climate. Scientific Reports4(7093): 1-6.
[6] ColesS. 2001. An Introduction to Statistical Modeling of Extreme Values, Lecture Notes in Control and Information Sciences. Springer: London. · Zbl 0980.62043
[7] CooleyD, NychkaD, NaveauP. 2007. Bayesian spatial modeling of extreme precipitation return levels. Journal of the American Statistical Association102(479): 824-840. · Zbl 1469.62389
[8] CooleyD, SainSR. 2012. Discussion of “Statistical Modeling of Spatial Extremes” by A. C. Davison, S. A. Padoan and M. Ribatet. Statistical Science27(2): 187-188. · Zbl 1330.86020
[9] DavisonAC, PadoanS, RibatetM. 2012. Statistical modelling of spatial extremes. Statistical Science27(2): 161-186. · Zbl 1330.86021
[10] DyrrdalAV, LenkoskiA, ThorarinsdottirTL, StordalFrode. 2015. Bayesian hierarchical modeling of extreme hourly precipitation in Norway. Environmetrics26(2): 89-106. · Zbl 1525.62105
[11] EvansJP, JiF, LeeC, SmithP, ArgüesoD, FitaL. 2014. Design of a regional climate modelling projection ensemble experiment-NARCliM. Geoscientific Model Development7(2): 621-629.
[12] EvansJP, McCabeMF. 2010. Regional climate simulation over Australia’s Murray‐Darling basin: a multitemporal assessment. Journal of Geophysical Research: Atmospheres115(D14): 1-15.
[13] EvansJP, McCabeMF. 2013. Effect of model resolution on a regional climate model simulation over southeast Australia. Climate Research56(2): 131-145.
[14] Garcia‐BartualR, SchneiderM. 2001. Estimating maximum expected short‐duration rainfall intensities from extreme convective storms. Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere26(9): 675-681.
[15] GeirssonÓP, HrafnkelssonB, SimpsonD. 2015. Computationally efficient spatial modeling of annual maximum 24‐h precipitation on a fine grid. Environmetrics26(5): 339-353. · Zbl 1525.62120
[16] GhoshS, MallickBK. 2011. A hierarchical Bayesian spatio‐temporal model for extreme precipitation events. Environmetrics22(2): 192-204.
[17] GreenJ, JohnsonF, XuerebK, TheC, MooreG. 2012. Revised intensity‐frequency‐duration (IFD) design rainfall estimates for Australia ‐ An overview: Sydney, Australia.
[18] HershfieldDM. 1961. Rainfall frequency atlas of the United States for durations from 30 minutes to 24 hours and return periods from 1 to 100 years. Weather Bureau Technical Paper 40, U.S. Department of Commerce. Washington, D.C.
[19] HershfieldDM, WilsonWT. 1958. Generalizing of rainfall intensity‐frequency data. IUGG/IAHS Publication43: 499-506.
[20] HoskingJrm, WallisJR. 2005. Regional Frequency Analysis: An Approach Based on L‐Moments. Cambridge University Press: New York.
[21] IPCC. 2013. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press: Cambridge, United Kingdom and New York, NY, USA. pp. 1535.
[22] KoutsoyiannisD, KozonisD, ManetasA. 1998. A mathematical framework for studying rainfall intensity‐duration‐frequency relationships. Journal of Hydrology206(1): 118-135.
[23] LehmannEA, PhatakA, SoltykS, ChiaJ, LauR, PalmerM. 2013. Bayesian hierarchical modelling of rainfall extremes: Adelaide, Australia.
[24] MullerA, BacroJ‐N, LangM. 2008. Bayesian comparison of different rainfall depth‐duration‐frequency relationships. Stochastic Environmental Research and Risk Assessment22(1): 33-46. · Zbl 1169.62397
[25] NadarajahS, AndersonCW, TawnJA. 1998. Ordered multivariate extremes. Journal of the Royal Statistical Society: Series B (Statistical Methodology)60(2): 473-496. · Zbl 0910.62054
[26] PeckA, ProdanovicP, SimonovicSPP. 2012. Rainfall intensity duration frequency curves under climate change: City of London, Ontario, Canada. Canadian Water Resources Journal / Revue canadienne des ressources hydriques37(3): 177-189.
[27] PilgrimDH. 1997. Australian Rainfall and Runoff: A Guide to Flood Estimation. Institution of Engineers, Australia: Barton, ACT, Australia.
[28] RobertCR, CasellaG. 2010. Introducing Monte Carlo Methods with R. Springer: New York, NY. · Zbl 1196.65025
[29] RobinsonM, TawnJ. 2000. Extremal analysis of processes sampled at different frequencies. Journal of the Royal Statistical Society: Series B (Statistical Methodology)62(1): 117-135. · Zbl 0976.62093
[30] SangH, GelfandAE. 2010. Continuous spatial process models for spatial extreme values. Journal of Agricultural, Biological, and Environmental Statistics15(1): 49-65. · Zbl 1306.62334
[31] SrivastavRK, SchardongA, SimonovicSP. 2014. Equidistance quantile matching method for updating IDF curves under climate change. Water Resources Management28(9): 2539-2562.
[32] StephensonAG. 2016. Bayesian inference for extreme value modelling. Chapman & Hall/CRC: Boca Raton, Florida.
[33] StephensonAG, LehmannEA, PhatakA. 2016. A max‐stable process model for rainfall extremes at different accumulation durations. Submitted to Weather and Climate Extremes (under revision).
[34] Van de VyverH. 2012. Spatial regression models for extreme precipitation in Belgium. Water Resources Research48(9): 1-17.
[35] Van de VyverH. 2015. Bayesian estimation of rainfall intensity‐duration‐frequency relationships. Journal of Hydrology529(3): 1451-1463.
[36] vanMontfortMAJ. 1997. Concomitants of the Hershfield factor. Journal of Hydrology194: 357-365.
[37] WangY, SoM. 2016. A Bayesian hierarchical model for spatial extremes with multiple durations. Computational Statistics and Data Analysis95: 39-56. · Zbl 1468.62207
[38] YilmazAG, HossainI, PereraBJC. 2014. Effect of climate change and variability on extreme rainfall intensity‐frequency‐duration relationships: a case study of Melbourne. Hydrology and Earth System Sciences18(10): 4065-4076.
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