Stochastic simulation of precipitation using Markov chain-mixed exponential model

Abstract

The stochastic precipitation simulation is used to produce time series of precipitation that have similar statistical properties as that of observed data. The Markov chain-mixed exponential model is developed based on the combination of the precipitation occurrence (described using Markov chain process) and the distribution of precipitation intensities on wet days (represented by the mixed exponential probability distribution). The model parameters are estimated using the maximum likelihood method. The model is assessed using a 21-years historical records. The results indicate that Markov chain-mixed exponential model is suitable for the simulation of precipitation process.