Performance of some General Circulation Models on Predicting Temperature and Rainfall in the Sudan-Sahel Region of Nigeria

• Main Authors: M. F. Amodu, C. J. Ejieji
• Format: Article
• Language: English
• Published: University of Maiduguri 2017-04-01
• Series: Arid Zone Journal of Engineering, Technology and Environment
• Online Access: http://azojete.com.ng/index.php/azojete/article/view/10/9
• ISSN: 2545-5818; 2545-5818

Twenty Global Circulation Models (GCMs) were evaluated by comparing their predictions of monthly average air temperature and monthly rainfall amounts of the sudan-sahel region of Nigeria with observed data for the period 1981 to 2000. The GCMs were those in the Program for Climate Model Diagnosis and Intercomparison (PCMDI) of the World Climate Research Program's (WCRP's) Coupled Model Intercomparison Project Phase 3 (CMIP3). The observed data were from four representative stations namely Kano, Katsina, Maiduguri and Sokoto. Coefficient of correlation (r), mean absolute error (MAE) and root mean square error (RMSE) were used as metrics for ranking the GCMs. None of the GCMs was superior in performance across the four representative stations. The trends of observed average monthly air temperature were generally better simulated with positive r-values in contrast with their monthly rainfall predictions which correlated negatively with observed data. The r-values for temperature averaged 0.211, 0.092, 0.373 and 0.212 for Kano, Katsina, Maiduguri and Sokoto respectively. For rainfall, the r-values averaged -0.216, -0.280, -0.115 and -0.351 for Kano, Katsina, Maiduguri and Sokoto respectively. Simulated rainy season commenced 4 to 6 months earlier than observed depending on the particular GCM. The average MAE from the GCMs for the respective stations ranged from 5.23 to 14.31 K for temperature and 81.91 to 91.99 mm for rainfall. For RMSE, the averages from the GCMs ranged from 5.84 to 14.42 K for temperature and 140.21 to 187.99 mm for rainfall. The results of the study have provided the basis for selection of appropriate GCMs for the locations for further downscaling procedures that might be required for the application of a selected GCM to climate change projection.