NUMBER OF OBSRVATION PERIOD REQUIRED FOR DEVELOPMENT OF STATISTICAL CORRECTION METHOD FOR JRA-55 PRECIPITATION

Abstract

 In previous studies, reanalysis data has been used instead of observational data for bias correction of GCMs outputs in observational data scarce basin. However, reanalysis data does not match well the real weather characteristics (e.g. precipitation) in a local scale since it is targeted at a global scale. Therefore, this study aims to apply a statistical correction method for re-analysis data based on observational data. And also, we compared accuracy of statistical correction method which is developed in 4 calibration periods (observational datasets for 5 years, 10 years, 15 years and 20 years), to clarify the number of observation period required for development of statistical correction method. As a result, it is revealed that observational datasets at least 15 years should be used as calibration period, to reproduce the statistical characteristics (average, standard deviation, frequency of precipitation, and so on) in observational data.