Journal ArticleDOI
A Poisson-cluster model of rainfall: some high-order moments and extreme values
TLDR
In this paper, a conceptual stochastic model for rainfall, based on a Poisson-cluster process with rectangular pulses representing rain cells, is further developed, and a method for deriving high-order moments is applied to obtain the third-moment function for the model.Abstract:
A conceptual stochastic model for rainfall, based on a Poisson-cluster process with rectangular pulses representing rain cells, is further developed. A method for deriving high-order moments is applied to obtain the third-moment function for the model. This is used with second-order properties to fit the model to January and July time-series taken from a site in Wellington, New Zealand. It is found that the parameter estimates may follow two solution paths converging on an optimum value over a bounded interval. The parameter estimates are used with the model to simulate 200 years of hourly data, and parametric tests used to compare simulated and observed extreme rainfalls. These show good agreement over a range of sampling intervals. The paper concludes with a discussion of the standard errors of the model parameter estimates which are obtained using a non-parametric bootstrap.read more
Citations
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Journal ArticleDOI
Simulation of future climate scenarios with a weather generator
TL;DR: In this article, the authors used a weather generator for downscaling an ensemble of climate model outputs, which can explicitly include climate model uncertainty, which offers valuable information for making probabilistic inferences about climate impacts.
Journal ArticleDOI
RainSim: A spatial-temporal stochastic rainfall modelling system
TL;DR: The ability of the improved model to match observed statistics and extremes is illustrated as an application to the Dommel catchment on the Netherlands/Belgian border illustrates the ability of this robust and well tested stochastic rainfall field generator to match observations and extremes.
Journal ArticleDOI
A comparison of different regional climate models and statistical downscaling methods for extreme rainfall estimation under climate change
TL;DR: In this article, the authors compare five statistical downscaling methods based on a common change factor methodology using results from four different RCMs driven by different GCMs, showing that three of the four RCMs predicted an increase in the extreme precipitation events in the future.
Journal ArticleDOI
Spatial-temporal rainfall modelling for flood risk estimation
Howard Wheater,Richard E. Chandler,Christian Onof,Valerie Isham,E. Bellone,E. Bellone,C. Yang,Demetris F. Lekkas,G. Lourmas,M.-L. Segond +9 more
TL;DR: In this article, a simple methodology is described, in which a single site Poisson process model provides hourly sequences, conditioned on the observed or generalized linear models (GLM)simulated daily data.
Journal ArticleDOI
Comparison of different ANN techniques in river flow prediction
Ozgur Kisi,H. Kerem Cigizoglu +1 more
TL;DR: In general, the forecasting performance of RBF is found to be superior to the other two ANN techniques and a time series model in terms of the selected performance criteria.
References
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L-Moments: Analysis and Estimation of Distributions Using Linear Combinations of Order Statistics
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Models for exceedances over high thresholds
Anthony C. Davison,Richard Smith +1 more
TL;DR: In this article, the authors discuss the analysis of the extremes of data by modelling the sizes and occurrence of exceedances over high thresholds, and the natural distribution for such exceedances, the generalized Pareto distribution, is described and its properties elucidated.
Journal ArticleDOI
Some Models for Rainfall Based on Stochastic Point Processes
TL;DR: In this paper, the variation of rainfall intensity at a fixed point in space is discussed for the variation in rainfall intensity over a fixed period of time and the main properties of these models are determined analytically.