Abstract
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.
Highlights
Climate change resulting from anthropogenic greenhouse gas (GHG) emissions has adverse impacts on human lives, properties and the environment
The mean bias (MBE) between simulated and observed precipitation is positive for all models at all stations where rains appear to be overestimated, except for the CanESM2 model which underestimates them at Bembèrèkè (−0.764), Ina (−0.615) and Tchaourou (−0.170) and the model CNRM-CM5 at Bembèrèkè (−0.026)
Considering the mean value of this parameter for all studied stations, the simulation results are from the most satisfactory to the least satisfactory according to the following order of the models: CanESM2, CNRM-CM5, EC-EARTH, NorESM1-M, GFDL-ESM2M, MIROC5, MPI-ESM-LR and HadGEM2-ES
Summary
Climate change resulting from anthropogenic greenhouse gas (GHG) emissions has adverse impacts on human lives, properties and the environment. Humans can only protect themselves from the inherent damage and manage the consequences of climate change by thinking about the development of projections of future changes. General circulation models (GCMs) are the most reliable means of estimating future climate change in an atmosphere where the concentration of greenhouse gases continues to increase significantly [1,2,3]. Because of the large number of processes and interactions between the atmosphere, ocean and biosphere, the climate model is extremely complex. This sophisticated tool is limited by the computing power and time available today [5].
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