Stochastic models have been proposed as one technique to generate scenarios of future climate change. Temperature and precipitation are among the main indicators in climate study. The goal of this study is the simulation and modeling of monthly precipitation and the mean of monthly temperature using stochastic methods. The 21-year data of precipitation and the mean of monthly temperature at Shiraz Synoptic Station in south of Iran have been used in this study and based on ARIMA model, the autocorrelation and partial autocorrelation methods, assessment of parameters and types of model, the suitable models to forecast monthly precipitation and the mean of monthly temperature were obtained. After models validation and evaluation, the forecasting was made for the crop years 2008 to 2009 and 2009 to 3010. In view of the forecasting made, the precipitation amounts will be improved than recent years. As regards the mean monthly temperature, the findings of the forecasting show an increase in temperature along with a narrowing of the range of variations.
Key words: Precipitation, temperature, time series analysis and Arima.
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