Abstract:
Rainfall is one of the most crucial climatic elements to examine and investigate the effects of the
changing climate. Simulations of Global Climate Models (GCMs) have become the most useful
and commonly used tools for examining changing in climate systems and simulating future
climate. This study evaluated the performance of Coupled Model Inter-comparison Project Phase
6 Global climate models (CMIP6 GCMs) for simulations of rainfall climatology over Ethiopia.
The study evaluated the rainfall simulation performance of eight CMIP6 GCMs at daily,
monthly, and annual temporal scale over five Argo Ecology Zones (AEZs) of Ethiopia for the
period 1995-2014 using station data as reference. The performance evaluation was carried out
using continuous statistical metrics like Root mean square error (RMSE), Percent bias (PBIAS),
and Pearson Correlation Coefficient (r) and line graphs. The performance of each GCM over
different AEZs was ranked based on Critical Rating Index (CRI). The result revealed that;
models have different simulation performance of daily to annual rainfall total over AEZs of
Ethiopia. In addition, they have both overestimation and underestimation problem. For better
simulation of daily rainfall total, Ec-Earth3-veg (over tropical, sub-tropical, and temperate AEZ
s),MRI-CSM2-0 (over desert AEZ),and MPI-ESM-1-2-LR (over alpine AEZ) is high ranked and p
referable.BCC-CSM-2-MR performed well over tropical, sub-tropical, temperate, and alpine
AEZs,butMRI-ESM2-0 has better performance over desert AEZ. For simulation of annual
rainfall total, MRI-ESM2-0 (over desert and tropical AEZs), BCC-CSM-2-MR (over temperate
and alpine AEZs), and Ec-Earth3-veg (over sub-tropical AEZ) is preferable and acceptable. EcEarth3
is the worst climate model to reproduce mean monthly rainfall of Ethiopia. The
performance of models is not consistent in reproducing rainfall distributions at different
statistical metrics and timeframes. Since the performance of CMIP6 GCMs different from place
to place and time to time, I recommend to evaluate the performance of models to use for specific
place and application and apply appropriate bias correction. The author also further recommen
ds, evaluating the performance of CMIP6 GCMs rainfall simulation capability over rainfall
regimes of Ethiopia.