Assessment of CMIP6 GCMs for Selecting a Suitable Climate Model for Precipitation Projections in Southern Thailand

The selection of General Circulation Models (GCMs) is critical due to computational limitations and 
underlying uncertainties. This study provides a comprehensive assessment of three bias correction (BC) 
methods, namely the delta change method (DT), quantile mapping (QM), and empirical quantile mapping 
(EQM). Utilizing precipitation data from 30 observation stations across Southern Thailand, the evaluation 
encompasses five CMIP6 GCM models (CAMS-CSM1-0, CanESM5, CNRM-CM6-1, CNRM-ESM2-1, 
IPSL-CM6A-LR). Evaluation metrics, root mean square error (RMSE), mean absolute error (MAE), 
Pearson’s correlation (r), index of agreement (d), and mean bias error (MBE) are employed to assess BC 
methods. Evaluation measures suggest that the DT method outperforms EQM and QM, with higher 
accuracy and lower errors (DT: RMSE = 3.61, MAE = 2.32; EQM: RMSE = 3.82, MAE = 3.70). Taylor 
diagrams show that CNRM-ESM2-1 has the highest correlation across sites (r=0.36), albeit with a wider 
dispersion