Time Series Analysis of Monthly Average Temperature and Rainfall Using Seasonal ARIMA Model (in Case of Ambo Area, Ethiopia)

Abstract

Forecasting mean temperature and rainfall is an important for planning and formulating agricultural strategies.Thus, this paper, try to analyze and forecast monthly mean temperature and rainfall in Ambo area on the data from January 2012 to March 2019. From graphical analysis on time plot and ACF, the series seems to have a seasonal component. For that purpose, a Seasonal Autoregressive Integrated Moving Average (SARIMA) models were used to estimate and forecast the average monthly temperature and rainfall in the Ambo area, Ethiopia. Among the competitive tentative model, SARIMA (2, 0, 1) (2, 0, 1) 12 and SARIMA (1, 0, 1) (1, 0, 1) 12 model are the best time series model for fitting and forecasting mean temperature and rainfall, respectively. Moreover, the model diagnostic test on the residuals of SARIMA (2, 0, 1) (2, 0, 1) 12 and SARIMA (1, 0, 1) (1, 0, 1) 12 on mean temperature and rainfall satisfies the randomness, independency, normality and constant variance (homoscedasticity) assumptions. Finally, SARIMA (2, 0, 1) (2, 0, 1) 12 and SARIMA (1, 0, 1) (1, 0, 1) 12 were used to forecast mean of monthly temperature and rainfall from the period April 2019 to March 2023.

Exploring Temperature Trends and Evapotranspiration Modelling for Effective Water Management: A Comprehensive Analysis Using Mann-Kendall Test and Seasonal ARIMA Model

“…In the early 1970s, Box and Jenkins popularized Autoregressive Integrated Moving Average (ARIMA) models, a versatile linear method for analysing both stationary and non-stationary time series, relying on autocorrelation patterns without assuming specific historical patterns, and frequently applied in weather variability research. (Abebe, 2020) conducted a study on monthly mean temperature and rainfall in the Ambo area, Ethiopia, using Seasonal Autoregressive Integrated Moving Average SARIMA (Chaudhuri & Dutta, 2014) models. SARIMA (2, 0, 1) (2, 0, 1) 12 and SARIMA (1, 0, 1) (1, 0, 1) 12 were identified as the best models for temperature and rainfall respectively, while meeting diagnostic test assumptions, and these models were utilized to predict data from April 2019 to March 2023.…”