Abstrait

Evaluation of Cosmo Model Precipitation Forecast for Heavy Rainfall Events Over Nigeria

Chibuzo N Agogbuo, Olubi C Adedamola, Benjamin O Alabi, Mbah Obiageri and Oloruntoba Bamidele

Accurate precipitation forecast from Numerical Weather Prediction models could be a useful tool in the issuance of early warning for extreme weather-related events such as flooding. Analysis of rainfall events over Nigeria is challenged by a lot of factors, ranging from lack of good radar coverage and sparse population of rain gauge stations to inconsistency in the recording of rainfall amounts from the available stations. This article evaluated the precipitation forecast of the COSMO model, which is simulated and used at the Nigerian Meteorological Agency. The evaluation was done in terms of categorical and Quantitative Precipitation Forecast for four heavy rainfall events that caused severe flooding in some cities in Nigeria in the months of August and September 2018. Precipitation forecasts from the COSMO model were compared with observed precipitation at both station and gridded observation points using eyeball verification, categorical statistics, and Taylor diagrams. Categorical Statistics showed that in all four cases studied, the model recorded accuracy and Critical Success Index (CSI) values of over 50%. However, further analysis revealed that location errors and underestimation of heavy rainfall events in some areas were the main sources of forecast uncertainties for most of the days evaluated.