Even though several reports over the past few decades indicate an increasing aridity over West Africa, attempts to establish the controlling factor(s) have not been successful. The traditional belief of the position of the Inter-tropical Convergence Zone (ITCZ) as the predominant factor over the region has been refuted by recent findings. Changes in major atmospheric circulations such as African Easterly Jet (AEJ) and Tropical Easterly Jet (TEJ) are being cited as major precipitation driving forces over the region. Thus, any attempt to predict long term precipitation events over the region using Global Circulation or Local Circulation Models could be flawed as the controlling factors are not fully elucidated yet. Successful prediction effort will require models which depend on past events as their inputs as in the case of time series models such as Autoregressive Integrated Moving Average (ARIMA) model. In this study, the researcher used historical precipitation data to build appropriate Seasonal Multiplicative Autoregressive Integrated Moving Average model, ARIMA (p,d,q)*(P,D,Q) in an R programming language. The model was then used to predict long term precipitation events over the Ghanaian segment of the Volta Basin which could be used in planning and implementation of development policies.
Keywords: Modelling; West Africa; Total Precipitation Depth; Statistical Approach
Biography: Simon Sovoe has a B.Sc Degree in Zoology, M.Phill in Oceanography, and has completed his Ph.D Degree in Environmental Science (University of Ghana), thesis submitted for examination. He has worked with the Environmental Protection Agency, Ghana as an Environmental Quality Officer, Collecting and analysing data, developing base line information for noise pollution monitoring, water and air quality parameters. His work focused on spatial and hydrologic modelling and simulations using Spatial Decision Support Systems (SDSS), Geographic Information Systems (GIS) and Geo-statistical analysis tools in an R programming language. His work also involves time series data modelling and development of forecasting models using Box-Jenkings' (Autoregressive Integrated Moving Average) approach.