A hybrid model for point rainfall modeling

Abstract

A hybrid point rainfall model, a product of two random processes, is presented. The model uses a jitter model, a general technique for improving the fit of any point process based model. We use the nonrandomized Bartlett‐Lewis rectangular pulse and an autoregressive model as a jitter. First, the five parameters of the Bartlett‐Lewis model are estimated by the method of moments using the mean of one aggregation level and the dry probabilities of all aggregation levels considered. Second, the parameters of the autoregressive model are derived from the moments of the historical data and those given by the Bartlett‐Lewis model, without additional cost in terms of parameter calibration. Using 15‐min point rainfall data of Capella, central Queensland, Australia, as a test case, the results of the hybrid model were better than the best results given by the randomized Bartlett‐Lewis model. On its own the nonrandomized Bartlett‐Lewis model produced very poor results.