Evaluation of General Circulation Models over the Upper Ouémé River Basin in the Republic of Benin

• Published in: Hydrology Vol. 7; no. 1; p. 11
• Main Authors: Attogouinon, André, Lawin, Agnidé E., Deliège, Jean-François
• Format: Journal Article Web Resource
• Language: English
• Published: MDPI Multidisciplinary Digital Publishing Institute 01.03.2020; MDPI AG
• Subjects: Earth sciences & physical geography; Earth-Surface Processes; Global climate models; IPCC; Oceanography; Ouémé river basin; Physical, chemical, mathematical & earth Sciences; Physique, chimie, mathématiques & sciences de la terre; Rainfall; Rainfall indices; Sciences de la terre & géographie physique; Statistical criteria; Waste Management and Disposal; Water Science and Technology
• ISSN: 2306-5338; 2306-5338
• DOI: 10.3390/hydrology7010011

This study assessed the performance of eight general circulation models (GCMs) implemented in the upper Ouémé River basin in Benin Republic (West Africa) during the Fifth Assessment Report on Climate Change. Historical rainfall simulations of the climate model of Rossby Regional Centre (RCA4) driven by eight Coupled Model Intercomparison Project (CMIP5) GCMs over a 55-year period (1951 to 2005) are evaluated using the observational data set. Apart from daily rainfall, other rainfall parameters calculated from observed and simulated rainfall were compared. U-test and other statistical criteria (R2, MBE, MAE, RMSE and standard of standard deviations) were used. According to the results, the simulations correctly reproduce the interannual variability of precipitation in the upper Ouémé River basin. However, the models tend to produce drizzle. Especially, the overestimation of April, May and November rains not only explains the overestimation of seasonal and annual cumulative rainfall but also the early onset of the rainy season and its late withdrawal. However, we noted that this overestimation magnitude varies from one model to another. As for extreme rainfall indices, the models reproduced them poorly. The CanESM2, CNRM-CM5 and EC-EARTH models perform well for daily rainfall. A trade-off is formulated to select the common MPI-ESM-LR, GFDL-ESM2M, NorESM1-M and CanESM2 models for different rainfall parameters for the reliable projection of rainfall in the area. However, the MPI-ESM-LR model is a valuable tool for studying future climate change.