STATISTICAL DOWNSCALED LOCAL CLIMATE MODEL FOR FUTURE RAINFALL CHANGES ANALYSIS: A CASE STUDY OF HYOGO PREFECTURE, JAPAN

<p>For decades, climate models have been used to understand the present and historical climates, especially global (GCMs). They are interaction between system processes forecast future climates. However, issue of low resolution accuracy often lead inadequacy in capturing variations variables related impact assessment. In order capture local changes Hyogo Prefecture Western Japan, a modelling based on Second Generation Canadian Earth System Model (CanESM2) was applied using statistical downscaling technique. Representative Concentration Pathway (RCP) 4.5 8.5 scenario were generating models. The reliability tested with Linear Regression, Pearson correlation, Cronbach Alpha. Moderate relationship rainfall data both RCP scenarios found all chosen stations. Spatial analysis outcome showed that there is possibility increase annual prefecture, where significant Northern region. There maximum minimum temperature four selected stations due greenhouse gas emissions.</p>