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A spatial‐temporal model of rainfall, based on a Neyman‐Scott stochastic point process, is fitted to hourly data taken from nine sites in the Arno Basin, Italy. The stochastic model is an extension of the temporal Neyman‐Scott rectangular pulses model into two‐dimensional space and introduces a further parameter into the model. In the model, storms arrive in a Poisson process, where each storm consists of discs representing rain cells, with centers distributed over an area according to a spatial Poisson process. The cells have a random radius, lifetime, and intensity, with the intensity remaining constant over the area of the disc and cell lifetime. A fitting procedure is proposed which couples the results obtained in two preceding papers: the second‐order properties of the spatial‐temporal model and the third moment function of the single site model Cowpertwait , 1995 , 1998 . The model is validated by comparing extreme historical hourly data and equivalent data simulated using the fitted spatial‐temporal model. These comparisons are made using a regional frequency analysis, based on L moments, and log‐log plots of the upper distribution tail. The results indicate that the model is able to preserve regional extremes and support the use of the model in hydrological applications.
Cowpertwait et al. (Thu,) studied this question.
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