Modeling of Climate Change Prediction and its Impact on the Tea Production in Sylhet District, Bangladesh

Abstract

Climate change, one of the most pressing issues, poses the greatest threat to human existence on our planet ever understanding the underlying structure, function and forecasting the future behavior has become considerable apparatus in numerous applications like metrological phenomena and production pattern of any observations. This study was conducted to model and forecast micro climatic variables in Sylhet district. The weather data for humidity, maximum temperature, minimum temperature, light duration, wind speed and monthly rainfall for the period 2005 to 2017 in Moulvibazar and Sylhet was collected for this study. Using Box-Jekins methodology, seasonal ARIMA model has been applied and models have also been verified. The best models were selected mainly based on AIC criterion. The best fitted SARIMA models for in Moulvibazar for humidity, maximum temperature, minimum temperature, light duration, wind speed and rainfall are ARIMA(1,0,1)(2,1,0)[12], ARIMA(1,0,0)(2,0,0)[12], ARIMA(2,0,1)(2,1,0)[12], ARIMA(1,1,1)(1,0,0)[12], ARIMA(4,0,1)(2,1,0)[12] and ARIMA(2,0,3)(1,1,2)[12] and in Sylhet ARIMA(0,0,1)(1,1,0)[12], ARIMA(0,0,0)(2,0,0)[12], ARIMA(0,0,0)(2,0,0)[12], ARIMA(0,1,2(2,0,0)[12], ARIMA(3,0,1)(1,0,0)[12] and ARIMA(1,0,0)(2,1,1) [12], respectively. This model can help to predict the climatic condition earlier, which could enhance the estimation of tea production in the next preceding years.

Keywords

• AIC criterion, ADF, ARIMA, KPSS and SARIMA