Numerical Rainfall Prediction for Ghana Using the Weather Research and Forecasting Model

Abstract

Agricultural businesses in Ghana heavily depend on rain-fed farming, but they are facing increasing challenges due to climate change and population growth. Accurate weather forecasts providing useful information on the onset of the rainy season are therefore of utmost importance. Unfortunately, the country still lacks reliable weather information and precise forecasts. This study aims to enhance and expand weather forecasting research in Ghana by running the regional Weather Research and Forecasting (WRF) model over Ghana and verifying its performance in forecasting the local onset of West Africa’s annual rainy season. Three experimental setups were conducted. The first experimental setup tested four different planetary boundary layer (PBL) schemes. Results showed that the schemes performed differently across the various agro-ecological zones of Ghana, highlighting the influence of spatial context on the model’s performance and the choice of PBL scheme. Further analysis within a smaller domain in the Forest zone revealed promising insights into accurately capturing categorized precipitation. In the third and final experiment, the WRF model was compared to the ECMWF’s operational forecast, demonstrating WRF’s capability of detecting local variations in rainfall, including heavier precipitation amounts, which the ECMWF model was not capable of detecting. This comparison underscored the added value of the WRF model over global models. Whether the WRF model can serve as an accurate weather prediction model to forecast the local onset of the rainy season in Ghana depends not only on its performance but also on the chosen definition of the onset. However, the results highlighted its qualities and robustness for multiple definitions, indicating a high potential for this purpose.