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*Corresponding Author Abstract: The forecasting of temperature on a seasonal time scales has been attempted by many researchers by different techniques at different time across the globe. It is a challenging task to forecast temperature on monthly and seasonal time scale. In this paper, an attempt has been made to develop a Seasonal Autoregressive Integrated Moving Average (SARIMA) model to long term temperature data of Dibrugarh, Assam, for the period of fifty (50) years (1966-2015). The analysis revels that the best seasonal models which are satisfactory to describe the data are SARIMA(2,1,1)(0,1,1)12 for monthly maximum and SARIMA(2,1,1)(0,1,1)12 for monthly minimum temperature data respectively.

MONTHLY TEMPERATURE PREDICTION BASED ON ARIMA MODEL: A CASE STUDY IN DIBRUGARH STATION OF ASSAM, INDIA