Future Change in Appearance Frequency of Atmospheric Characteristics Causing Localized Heavy Rainfall during Baiu Season Using AGCM Ensembles

This study investigated future changes of a certain atmospheric characteristic, which can cause localized heavy rainfall events during Baiu season along the Japan islands. In this study, we have utilized Self-organizing map (SOM) to classify atmospheric conditions automatically and to distinguish the specific condition objectively. We have analyzed frequency of the specific atmospheric condition under the future climate as well as the present climate, and evaluated the statistical significance of frequency changes under the future climate based on ensemble experiments output with 60km resolution GCM(MRI-AGCM3.2H). By counting the number of times for the specific atmospheric condition, it is able to estimate possible changes of localized heavy rainfall pattern in the future. Our approach shows one of example that even small scale of localized heavy rainfall can be captured by considering characterized atmospheric conditions in large scale.This study investigated future changes of a certain atmospheric characteristic, which can cause localized heavy rainfall events during Baiu season along the Japan islands. In this study, we have utilized Self-organizing map (SOM) to classify atmospheric conditions automatically and to distinguish the specific condition objectively. We have analyzed frequency of the specific atmospheric condition under the future climate as well as the present climate, and evaluated the statistical significance of frequency changes under the future climate based on ensemble experiments output with 60km resolution GCM(MRI-AGCM3.2H). By counting the number of times for the specific atmospheric condition, it is able to estimate possible changes of localized heavy rainfall pattern in the future. Our approach shows one of example that even small scale of localized heavy rainfall can be captured by considering characterized atmospheric conditions in large scale