Statistical Bias Correction of RegCM4 Output Data (Study Area: Indramayu Regency)

Abstract

Climate data that has limitation on spatial and temporal scale becomes an obstacle in perform the climate-related research such us crop simulation, climate risk assessment and many others. Regional climate models such as RegCM4 can produce adequate outcomes of climate data in term of spatial and temporal sides. Output data from RegCM4 can be used for further research once it has been through correction process. On this study, statistical bias correction with three different transfer function (i.e. linear regression, second order polynomials and third order polynomials) were tested. The correction process that has been done on the RegCM4 rainfall data in Indramayu Regency by using third order polynomials-transfer function is able to produce climatology data with value close to observation data. Similarity between observation data and the corrected RegCM4 output data is indicated by similar temporal and spatial distributions. Based on the historical climate and projection of rainfall (1981-2065), it is known that annual rainfall will decrease by 0.84 mm/year.