An increase in heavy rainfall and floods have been observed over South Korea due to recent abnormal weather. In this perspective, the
high-resolution weather forecasts have been widely used to facilitate flood management. However, these models are known to be biased
due to initial conditions and topographical conditions in the process of model building. Theretofore, a bias correction scheme is largely
applied for the practical use of the prediction to flood management. This study introduces a new mean field bias correction (MFBC)
approach for the high-resolution numerical rainfall products, which is based on a Bayesian Kriging model to combine an interpolation
technique and MFBC approach for spatial representation of the error. The results showed that the proposed method can reliably estimate
the bias correction factor over ungauged area with an improvement in the reduction of errors. Moreover, it can be seen that the bias
corrected rainfall forecasts could be used up to 72 hours ahead with a relatively high accuracy.