Forecasting performance comparison of daily maximum temperature using ARMA based methods

Abstract

Daily maximum temperature of four different regions in Kerala, India, from 01/01/2019 to 31/12/2020, is recorded and is used for modelling and forecasting. The forecasting methods used are Autoregressive integrated moving average (ARIMA), Seasonal Autoregressive integrated moving average (SARIMA) and Autoregressive fractional integrated moving average (ARFIMA). The comparison of forecasting performance was based on percentage accuracy, mean squared error (MSE) and mean absolute error (MAE). The models used can capture the variations of time series data. All the models exhibit reasonably good performance in predicting the daily maximum temperature. ARFIMA model gives the least forecast errors compared to other models.