Extremeweather events, such as unexpected and sudden torrential rains, have received increasing attention by the specialists as well as ordinary people due to the possibility of causing severe material damages and human losses. Computational climate scientists have been working on high-resolution time-varying, multivariate numerical simulations of this kind of short-term event, which is still hard to predict. Local governments of the natural disaster prone countries, like Japan, usually possess disaster management sectors, responsible for storing the disaster related data and analysis results. In this paper, we present a visualization framework for enabling the interactive exploration of the causality, such as of the disasters and the related extreme weather events. The end users will be able to identify the spatio-temporal regions where there is a strong strength of cause-effect relationships. As a case study, we studied the unexpected torrential rain occurred in the city of Kobe, in 2008, where a flash flood, in the urban area, caused some human losses. We utilized high-resolution computational climate simulation results executed on a supercomputer, and the measured river level data obtained from the Civil Engineering Office of Kobe City. We expected that this kind of tool can assist the specialists for better understanding the cause-effect relationships between the extreme weather and the related disasters, as well as, the local government policy makers in the adaptation policies for the disaster risk reductions.