The development of bias corrected hourly precipitation dataset for AMeDAS stations based on the projections from d4PDF

Abstract

 A bias correction method that is appropriate for an huge ensemble dataset has been developed. The method was applied to the d4PDF, and validated usting AMeDAS dataset. The result indicates that the developed method has better reproducibility than previous methods. Especially the overestimation by the previous method is sucuesufully removed. The biascorrected dataset in the cathment scale shows it can reproduce historical extremes that is estimated using extreme value theory with small differences.