Eniola Olaniyan, Ernest Afiesimama, Feyi Oni and Kamoru A. Lawal
Understanding the dynamics and variability of the West African Monsoon (WAM) at daily time scales will improve skillful prediction of the onset and evolution of the monsoon and thus would contribute toward food security of Nigeria. This study, therefore, uses high resolution regional COSMO-model, a weather-mode model from the German Weather Service adopted by the Nigerian Meteorological Agency, to study the daily evolution of WAM as well as the ability of the model to predict the daily characteristics of monsoon, for the first half of 2015, over Nigeria. Results show that, qualitatively, the model has the ability to predict the daily evolution of WAM, daily variability of rainfall, which includes the onset of the raining season as well as dry-spells, over Nigeria. The spatial correlations between the observation and the forecast are generally greater than 0.64, implying that the model, though, underestimates the rainfall amount as much as half of the actual amount, it nevertheless proved to have a good representation of the spatial characteristics of the rain over Nigeria. The model shows that the Inter-Tropical Discontinuity (ITD) advances northward, from the Gulf of Guinea (GOG) to the Sahelian region, by about 0.42° per week; and that for the onset of monsoon in Nigeria, the average position of the ITD should be at least 6.7°N and must not retreat south of it in the subsequent average weekly position. In agreement with earlier findings, the model also shows that the African Easterly Jet (AEJ), together with its associated core, is not only a boreal summer element but can also exist during the boreal winter with the same strength in the wind speed. The atmospheric thermodynamic properties, predicted by the model, show that for an onset of the rains, a threshold value of at least 1500 J/Kg of convective available potential energy (CAPE) may be required. The results suggest that COSMO-Model has proved to be a good tool for operational daily weather forecast; therefore, the model could also have potential for seasonal rainfall predictions over Nigeria when run in climate mode.