Modeling and Forecasting Selected Meteorological Parameters for the Environmental Awareness in Sub-Sahel West Africa Stations

Francis Olatunbosun Aweda; Jacob Adebayo Akinpelu; Timothy Kayode Samson; Mohammed Sanni; Bukunmi Sunday Olatinwo

doi:10.46481/jnsps.2022.820

Authors

F. O. Aweda
[email protected]

Bowen University, Iwo
J. A. Akinpelu
Physics and Solar Energy Programme, College of Agriculture, Engineering and Science, Bowen University, PMB 284 Iwo, Osun State, Nigeria
T. K. Samson
Statistics Programme, College of Agriculture, Engineering and Science, Bowen University
M. Sanni
Department of Science Technology, Federal Polytechnic, Offa, Kwara State
B. S. Olatinwo
Physics and Solar Energy Programme, College of Agriculture, Engineering and Science, Bowen University, PMB 284 Iwo, Osun State, Nigeria

Keywords:

Meteorological Parameters, ARIMA models, ACF, PACF, Forecast

Abstract

The monthly air temperature, rainfall, air pressure, and wind speed direction for the environmental time series recorded between January 1, 1980 and December 31, 2020 in six African stations from different climatic zones were modeled and forecasted. In the forecasting, Augmented Dickey Fuller test, ARIMA models, Auto correlation Function (ACF) and Partial Autocorrelation Function (PACF) were used. Result showed that in most of the fitted models, the Moving Average terms both seasonal and non- seasonal were also significant (p<0.05) indicating that the previous day value of the stochastic term also had a significant effect on the present value of meteorological parameters in the environment. It was observed that in all the fitted models except for wind direction in Conakry and rainfall in Abidjan have all their Autoregressive term of order 1 significant (p<0.05) which implies that previous day value of these meteorological parameter had a significant effect on the present day value of the parameters. Therefore, the forecast model indicates that maximum temperature are expected in February, March, April, and June while minimum temperatures in January, August, December. Although, the selected models cannot forecast the precise air temperature, this can also provide information that can be of help to create tactics for appropriate preparation of farming which can be used as tools for effective environmental preparation and policymaking.

Dimensions

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