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The performance of the bias correction method applied to both GCM datasets was evaluated by mean, SD, and RMSE with respect to the observed data during 1971–2000 (Table 5). When compared to the raw GCM data, the monthly mean and SDs of all corrected variables were found to be closer to deduced values for field observations. The highest RMSE of PW and RH lies between 4.3 and 2.5 after bias correction. Based on the statistical parameters, both bias corrected GCMs’ data can be used for future rainfall projections in the study area.

Table 5

Performance of quantile mapping bias correction method on monthly data

Raw
Corrected
SeasonStatisticsVariableObservedCSIRO Mk3.6MPI-ESM-MRCSIRO Mk3.6MPI-ESM-MR
FMA season Mean PW (kg/m242.9 46.2 44.2 42.9 42.9 
SLP (mbar) 1,012.9 1,013.2 1,012.5 1,012.9 1,013.0 
SD PW (kg/m25.8 12.6 10.9 5.8 5.8 
SLP (mbar) 1.1 1.3 1.4 1.0 1.0 
RMSE PW (kg/m2 9.0 7.2 4.3 4.0 
SLP (mbar)  1.4 1.5 1.2 1.1 
MJJ season Mean SAT (°C) 21.3 25.0 23.2 21.3 21.3 
SD 2.3 5.4 4.2 2.4 2.4 
RMSE  4.3 4.6 1.2 1.1 
ASO season Mean SLP (mbar) 1,010.1 1,007.4 1,010.5 1,010.1 1,010.1 
RH (%) 77.0 83.5 79.0 77.0 77.0 
SD SLP (mbar) 3.0 4.8 4.2 3.0 3.0 
RH (%) 5.0 4.2 5.8 5.0 4.9 
RMSE SLP (mbar)  3.0 2.8 1.4 1.3 
RH (%)  7.2 3.8 2.5 2.6 
Raw
Corrected
SeasonStatisticsVariableObservedCSIRO Mk3.6MPI-ESM-MRCSIRO Mk3.6MPI-ESM-MR
FMA season Mean PW (kg/m242.9 46.2 44.2 42.9 42.9 
SLP (mbar) 1,012.9 1,013.2 1,012.5 1,012.9 1,013.0 
SD PW (kg/m25.8 12.6 10.9 5.8 5.8 
SLP (mbar) 1.1 1.3 1.4 1.0 1.0 
RMSE PW (kg/m2 9.0 7.2 4.3 4.0 
SLP (mbar)  1.4 1.5 1.2 1.1 
MJJ season Mean SAT (°C) 21.3 25.0 23.2 21.3 21.3 
SD 2.3 5.4 4.2 2.4 2.4 
RMSE  4.3 4.6 1.2 1.1 
ASO season Mean SLP (mbar) 1,010.1 1,007.4 1,010.5 1,010.1 1,010.1 
RH (%) 77.0 83.5 79.0 77.0 77.0 
SD SLP (mbar) 3.0 4.8 4.2 3.0 3.0 
RH (%) 5.0 4.2 5.8 5.0 4.9 
RMSE SLP (mbar)  3.0 2.8 1.4 1.3 
RH (%)  7.2 3.8 2.5 2.6 

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