ひまわり8号などのマルチセンサー観測の データ同化によるゲリラ豪雨予測

Abstract

As the growing process of a cumulonimbus cloud is very short, guerrilla-heavy rainfall is difficult to accurately predict in advance. In this study, we aim to improve the accuracy of early prediction by using assimilation of observation data from multi-sensors including Himawari-8. Multi-sensors observation is considered to be effective for prediction as they provide more information earlier than weather radars. But the capability of multi-sensors observation assimilation is still not clarified because not much literature is available at present. Therefore, we examine it by using ideal experiments in Observing System Simulation Experiments (OSSE). The result shows the data with Himawari-8 assimilation can predict the precipitation, which cannot be predicted by the one without assimilation. In order to further improve prediction accuracy, our next step would be to conduct real case studies to find out relationships among assimilation parameters and developing stages of a cloud