Analyzing of changes and Modeling on Temperature of The Caspian southern coasts

In this paper, modeling of temperature of the Caspian southern coasts has been done by sARIMA or seasonal Autoregressive integrated moving average. Therefore monthly mean temperature related to Anzali, Ramsar and babolsar synoptic stations with long term dataset has been studied through (1955 – 2008). Statistical surveys of climate change usually analyze three phenomena as homogeneity, trend and jump in the climatic series. Hence in order to study the climate change process in the region, three phenomena; homogeneity, trend and discontinuity of the series were analyzed. Then temperature time series have prepared for performance of seasonal ARIMA model. In preparation of the time series to use the ARIMA model, at first the time series have transformed to normal and stationary series using differencing method. Then, after selection of some suitable models and estimation of parameters by maximum likelihood method, independence and normality of model residuals (t a) were considered. At the end, Akaike information criterion (AIC) was used to select one among the various alternative models. So, sARIMA (1,0,0) (0,1,1) 12 was selected for Anzali and Babolsar and sARIMA (0,0,2) (0,1,1) 12 was selected for Ramsar mean monthly temperature. Performance of seasonal ARIMA model for each time series has well suited, in comparison with the actual data in four years 2005 to 2008 as the gauge by sARIMA model. Correlation coefficient between the actual and fitted data was nearly 0.97 and the absolute and relative errors were very small.