A nonstationary index flood model for precipitation extremes in transient regional climate model simulations

被引:82
作者
Hanel, Martin [1 ]
Buishand, T. Adri [1 ]
Ferro, Christopher A. T. [2 ]
机构
[1] Royal Netherlands Meteorol Inst, Climate Serv, NL-3730 AE De Bilt, Netherlands
[2] Univ Exeter, Sch Engn Comp & Math, Exeter EX4 4QF, Devon, England
关键词
FUTURE CHANGES; ANNUAL MAXIMA; RAINFALL; EVENTS; TEMPERATURE; TRENDS; INTEGRATIONS; VARIABILITY; ROBUSTNESS; REGRESSION;
D O I
10.1029/2009JD011712
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The generalized extreme value (GEV) distribution has often been used to describe the distribution of daily maximum precipitation in observed and climate model data. The model developed in this paper allows the GEV location parameter to vary over the region, while the dispersion coefficient (the ratio of the GEV scale and location parameters) and the GEV shape parameter are assumed to be constant over the region. This corresponds with the index flood assumption in hydrology. It is further assumed that all three GEV parameters vary with time, such that the relative change in a quantile of the distribution is constant over the region. This nonstationary model is fitted to the 1-day summer and 5-day winter precipitation maxima in the Rhine basin in a simulation of the Regional Atmospheric Climate Model (RACMO) for the period 1950-2099, and the results are compared with gridded observations. Except for an underestimation of the dispersion coefficient of the 5-day winter maxima by about 35%, the GEV parameters obtained from the observations are reasonably well reproduced by RACMO. A positive trend in the dispersion coefficient is found in the summer season, which implies that the relative increase of a quantile increases with increasing return period. In the winter season there is a positive trend in the location parameter and a negative trend in the shape parameter. For large quantiles the latter counterbalances the effect of the increase of the location parameter. It is shown that the standard errors of the parameter estimates are significantly reduced in the regional approach compared to those of the estimated parameters from individual grid box values, especially for the summer maxima.
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页数:16
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共 56 条
[11]   ROBUST LOCALLY WEIGHTED REGRESSION AND SMOOTHING SCATTERPLOTS [J].
CLEVELAND, WS .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1979, 74 (368) :829-836
[12]   Methods for exploring spatial and temporal variability of extreme events in climate data [J].
Coelho, C. A. S. ;
Ferro, C. A. T. ;
Stephenson, D. B. ;
Steinskog, D. J. .
JOURNAL OF CLIMATE, 2008, 21 (10) :2072-2092
[13]  
Coles S., 2001, An Introduction to Statistical Modelling of Extreme Values
[14]   Regional flood-duration-frequency modeling in the changing environment [J].
Cunderlik, JM ;
Ouarda, TBMJ .
JOURNAL OF HYDROLOGY, 2006, 318 (1-4) :276-291
[15]   Non-stationary pooled flood frequency analysis [J].
Cunderlik, JM ;
Burn, DH .
JOURNAL OF HYDROLOGY, 2003, 276 (1-4) :210-223
[16]   A comparison of extreme European daily precipitation simulated by a global and a regional climate model for present and future climates [J].
Durman, CF ;
Gregory, JM ;
Hassell, DC ;
Jones, RG ;
Murphy, JM .
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2001, 127 (573) :1005-1015
[17]   New estimates of future changes in extreme rainfall across the UK using regional climate model integrations.: 2.: Future estimates and use in impact studies [J].
Ekström, M ;
Fowler, HJ ;
Kilsby, CG ;
Jones, PD .
JOURNAL OF HYDROLOGY, 2005, 300 (1-4) :234-251
[18]   Generalized maximum likelihood estimators for the nonstationary generalized extreme value model [J].
El Adlouni, S. ;
Ouarda, T. B. M. J. ;
Zhang, X. ;
Roy, R. ;
Bobee, B. .
WATER RESOURCES RESEARCH, 2007, 43 (03)
[19]   The FORGEX method of rainfall growth estimation - III: Examples and confidence intervals [J].
Faulkner, DS ;
Jones, DA .
HYDROLOGY AND EARTH SYSTEM SCIENCES, 1999, 3 (02) :205-212
[20]   New estimates of future changes in extreme rainfall across the UK using regional climate model integrations.: 1.: Assessment of control climate [J].
Fowler, HJ ;
Ekström, M ;
Kilsby, CG ;
Jones, PD .
JOURNAL OF HYDROLOGY, 2005, 300 (1-4) :212-233