Modelling radar-rainfall estimation uncertainties using elliptical and Archimedean copulas with different marginal distributions

被引:19
作者
Dai, Qiang [1 ]
Han, Dawei [1 ]
Rico-Ramirez, Miguel A. [1 ]
Islam, Tanvir [2 ]
机构
[1] Univ Bristol, Dept Civil Engn, Water & Environm Management Res Ctr, Bristol BS8 1TR, Avon, England
[2] NOAA, Ctr Satellite Applicat & Res, NESDIS, College Pk, MD USA
来源
HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES | 2014年 / 59卷 / 11期
关键词
ensemble generation; copula; rainfall uncertainties; radar-rainfall estimates; MEAN-FIELD BIAS; PRECIPITATION ESTIMATION; ERROR VARIANCE; RUNOFF; SIMULATIONS; VARIABILITY; SENSITIVITY; CALIBRATION; PARAMETERS; DEPENDENCE;
D O I
10.1080/02626667.2013.865841
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
Given that radar-based rainfall has been broadly applied in hydrological studies, quantitative modelling of its uncertainty is critically important, as the error of input rainfall is the main source of error in hydrological modelling. Using an ensemble of rainfall estimates is an elegant solution to characterize the uncertainty of radar-based rainfall and its spatial and temporal variability. This paper has fully formulated an ensemble generator for radar precipitation estimation based on the copula method. Each ensemble member is a probable realization that represents the unknown true rainfall field based on the distribution of radar rainfall (RR) error and its spatial error structure. An uncertainty model consisting of a deterministic component and a random error factor is presented based on the distribution of gauge rainfall conditioned on the radar rainfall (GR|RR). Two kinds of copulas (elliptical and Archimedean copulas) are introduced to generate random errors, which are imposed by the deterministic component. The elliptical copulas (e.g. Gaussian and t-copula) generate the random errors based on the multivariate distribution, typically of decomposition of the error correlation matrix using the LU decomposition algorithm. The Archimedean copulas (e.g. Clayton and Gumbel) utilize the conditional dependence between different radar pixels to obtain random errors. Based on those, a case application is carried out in the Brue catchment located in southwest England. The results show that the simulated uncertainty bands of rainfall encompass most of the reference raingauge measurements with good agreement between the simulated and observed spatial dependences. This indicates that the proposed scheme is a statistically reliable method in ensemble radar rainfall generation and is a useful tool for describing radar rainfall uncertainty. [GRAPHICS] Editor D. Koutsoyiannis; Associate editor S. Grimaldi
引用
收藏
页码:1992 / 2008
页数:17
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