Forecasting mean monthly maximum and minimum air temperature of Jalandhar district of Punjab, India using seasonal ARIMA model

Abstract

The long-term air temperature data series from 1971-2019 was analyzed and used for forecasting mean monthly air temperature at the district level. The Augmented Dickey-Fuller test, Kwiatkowski-Phillips-Schmidt-Shin test, and Mann-Kendall test were employed to test the stationarity and trend of the time series. The mean monthly maximum air temperature did not show any significant variation while an increasing trend of 0.04°C per annum was observed in mean monthly minimum air temperature, which was detrended. Box-Jenkins autoregressive integrated moving–averages were used to forecast the forthcoming 5 years (2020-2024) air temperature in the district Jalandhar of Punjab. The goodness of fit was tested against residuals, the autocorrelation function, and the histogram. The fitted model was able to capture dynamics of the time series data and produce a sensible forecast.

Keywords

• Time series
• forecast
• Box-Jenkins
• air temperature
• model