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.
Highlights
Climate change has become a critical issue for policy makers, climate researchers, politicians and the public around the world
They concluded that Seasonal Autoregressive Integrated Moving Average (SARIMA) model was a proper method for modeling and predicting the monthly rainfall
The monthly data used in this study covers from January 1, 2012 to March 1, 2019, which were collected from Ambo University Meteorological Agency
Summary
Climate change has become a critical issue for policy makers, climate researchers, politicians and the public around the world. Rainfall in Ethiopia is highly erratic, and International Journal of Theoretical and Applied Mathematics 2020; 6(5): 76-87 most rain falls in convective storms, with very high rainfall intensity and extreme spatial and temporal variability [6]. In this regard, several studies have been conducted to the analysis the pattern and trend of climate variation in various regions of the world using different time series methods. This paper addresses the shortcomings in analytical literature about climate change using seasonal ARIMA model to analyze the pattern and trend, to fit an appropriate model, and forecast the future value of of climate data (mean temperature and rainfall) in Ambo area, Ethiopia
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
