On the bias correction of general circulation model output for Indian summer monsoon

摘要: A general circulation model (GCM) is an alternative way for predicting Indian summer monsoon rainfall (ISMR) over the existing empirical/statistical models in recent time. However, inherent biases present GCM affect its performance. Therefore, there a high requirement bias correction of GCM. Few studies on GCMs are available context ISMR. comparative study reported this paper six different methods by applying hindcast (May start, June–July–August–September) climate forecast system (CFS) from National Centers Environmental Prediction (NCEP) 27 years (1982–2008). Among discussed paper, three did not use any statistical transformation (Mean Bias-remove technique (U), Multiplicative shift (M) and Standardized-reconstruction (Z)) remaining used (Regression (R), Quantile Mapping Method (Q), Principal Component Regression (PCR)). Finally, it was found that (Z) (Q) more skilful than others both equally simulating Bias-corrected four extreme years, out which 1988 1994 characterized excess 1987 2002 deficit, also examined here. Results indicate efficiently capture cases.