Using stochastic methods in modeling of the monthly precipitation and mean temperature (A case study: Shiraz station, Iran)

Stochastic models have been proposed as one technique for generating scenarios of future climate change. In climate study, temperature and precipitation are among the main indicators. The purpose of this study is simulation and modeling of monthly precipitation and mean monthly temperature using stochastic methods. In this study, the 21 years data on the precipitation and mean monthly temperature at shiraz synoptic station are used and based on ARIMA model, the autocorrelation and partial autocorrelation methods, examination of parameters and types of model, the suitable models for forecasting of monthly precipitation: ARIMA (0 0 0) (2 1 0)12 and for forecasting of the mean monthly temperature: ARIMA (2 1 0) (2 1 0)12 were obtained.